User login
Considering the true costs of clinical trials
This transcript has been edited for clarity.
We need to think about the ways that participating in clinical trials results in increased out-of-pocket costs to our patients and how that limits the ability of marginalized groups to participate. That should be a problem for us.
There are many subtle and some egregious ways that participating in clinical trials can result in increased costs. We may ask patients to come to the clinic more frequently. That may mean costs for transportation, wear and tear on your car, and gas prices. It may also mean that if you work in a job where you don’t have time off, and if you’re not at work, you don’t get paid. That’s a major hit to your take-home pay.
We also need to take a close and more honest look at our study budgets and what we consider standard of care. Now, this becomes a slippery slope because there are clear recommendations that we would all agree, but there are also differences of practice and differences of opinion.
How often should patients with advanced disease, who clinically are doing well, have scans to evaluate their disease status and look for subtle evidence of progression? Are laboratory studies part of the follow-up in patients in the adjuvant setting? Did you really need a urinalysis in somebody who’s going to be starting chemotherapy? Do you need an EKG if you’re going to be giving them a drug that doesn’t have potential cardiac toxicity, for which QTc prolongation is not a problem?
Those are often included in our clinical trials. In some cases, they might be paid for by the trial. In other cases, they’re billed to the insurance provider, which means they’ll contribute to deductibles and copays will apply. It is very likely that they will cost your patient something out of pocket.
Now, this becomes important because many of our consent forms would specifically say that things that are only done for the study are paid for by the study. How we define standard of care becomes vitally important. These issues have not been linked in this way frequently.
Clinical trials are how we make progress. The more patients who are able to participate in clinical trials, the better it is for all of us and all our future patients.
Kathy D. Miller, MD, is associate director of clinical research and codirector of the breast cancer program at the Melvin and Bren Simon Cancer Center at Indiana University, Indianapolis. She disclosed no relevant conflicts of interest.
A version of this article first appeared on Medscape.com.
This transcript has been edited for clarity.
We need to think about the ways that participating in clinical trials results in increased out-of-pocket costs to our patients and how that limits the ability of marginalized groups to participate. That should be a problem for us.
There are many subtle and some egregious ways that participating in clinical trials can result in increased costs. We may ask patients to come to the clinic more frequently. That may mean costs for transportation, wear and tear on your car, and gas prices. It may also mean that if you work in a job where you don’t have time off, and if you’re not at work, you don’t get paid. That’s a major hit to your take-home pay.
We also need to take a close and more honest look at our study budgets and what we consider standard of care. Now, this becomes a slippery slope because there are clear recommendations that we would all agree, but there are also differences of practice and differences of opinion.
How often should patients with advanced disease, who clinically are doing well, have scans to evaluate their disease status and look for subtle evidence of progression? Are laboratory studies part of the follow-up in patients in the adjuvant setting? Did you really need a urinalysis in somebody who’s going to be starting chemotherapy? Do you need an EKG if you’re going to be giving them a drug that doesn’t have potential cardiac toxicity, for which QTc prolongation is not a problem?
Those are often included in our clinical trials. In some cases, they might be paid for by the trial. In other cases, they’re billed to the insurance provider, which means they’ll contribute to deductibles and copays will apply. It is very likely that they will cost your patient something out of pocket.
Now, this becomes important because many of our consent forms would specifically say that things that are only done for the study are paid for by the study. How we define standard of care becomes vitally important. These issues have not been linked in this way frequently.
Clinical trials are how we make progress. The more patients who are able to participate in clinical trials, the better it is for all of us and all our future patients.
Kathy D. Miller, MD, is associate director of clinical research and codirector of the breast cancer program at the Melvin and Bren Simon Cancer Center at Indiana University, Indianapolis. She disclosed no relevant conflicts of interest.
A version of this article first appeared on Medscape.com.
This transcript has been edited for clarity.
We need to think about the ways that participating in clinical trials results in increased out-of-pocket costs to our patients and how that limits the ability of marginalized groups to participate. That should be a problem for us.
There are many subtle and some egregious ways that participating in clinical trials can result in increased costs. We may ask patients to come to the clinic more frequently. That may mean costs for transportation, wear and tear on your car, and gas prices. It may also mean that if you work in a job where you don’t have time off, and if you’re not at work, you don’t get paid. That’s a major hit to your take-home pay.
We also need to take a close and more honest look at our study budgets and what we consider standard of care. Now, this becomes a slippery slope because there are clear recommendations that we would all agree, but there are also differences of practice and differences of opinion.
How often should patients with advanced disease, who clinically are doing well, have scans to evaluate their disease status and look for subtle evidence of progression? Are laboratory studies part of the follow-up in patients in the adjuvant setting? Did you really need a urinalysis in somebody who’s going to be starting chemotherapy? Do you need an EKG if you’re going to be giving them a drug that doesn’t have potential cardiac toxicity, for which QTc prolongation is not a problem?
Those are often included in our clinical trials. In some cases, they might be paid for by the trial. In other cases, they’re billed to the insurance provider, which means they’ll contribute to deductibles and copays will apply. It is very likely that they will cost your patient something out of pocket.
Now, this becomes important because many of our consent forms would specifically say that things that are only done for the study are paid for by the study. How we define standard of care becomes vitally important. These issues have not been linked in this way frequently.
Clinical trials are how we make progress. The more patients who are able to participate in clinical trials, the better it is for all of us and all our future patients.
Kathy D. Miller, MD, is associate director of clinical research and codirector of the breast cancer program at the Melvin and Bren Simon Cancer Center at Indiana University, Indianapolis. She disclosed no relevant conflicts of interest.
A version of this article first appeared on Medscape.com.
The bloated medical record
Until the 19th century there was nothing even resembling our current conception of the medical record. A few physicians may have kept personal notes, observations, and some sketches of their patients primarily to be used in teaching medical students or as part of their own curiosity-driven research. However, around 1800 the Governor Council of the State of New York adopted a proposition that all home doctors should register their medical cases again to be used as an educational tool. By 1830 these registries became annual reporting requirements that included admissions and discharges, treatment results, and expenditures. It shouldn’t surprise you learn that a review of these entries could be linked to a doctor’s prospects for promotion.
In 1919 the American College of Surgeons attempted to standardize its members’ “treatment diaries” to look something more like our current medical records with a history, lab tests, diagnosis, treatment plan, and something akin to daily progress notes. However, as late as the 1970s, when I began primary care practice, there were very few dictates on what our office notes should contain. A few (not including myself) had been trained to use a S.O.A.P. format (Subjective, Objective, Assessment, and Plan) to organize their observations. Back then I viewed my office records as primarily a mnemonic device and only because I had a partner did I make any passing attempt at legibility.
With AI staring us in the face and threatening to expand what has become an already bloated medical record,
Although there was a time when a doctor’s notes simply functioned as a mnemonic, few physicians today practice in isolation and their records must now serve as a vehicle to communicate with covering physicians and consultants.
How detailed do those notes need to be? Do we need more than the hard data – the numbers, the prescriptions, the biometrics, the chronology of the patient’s procedures? As a covering physician or consultant, I’m not really that interested in your subjective observations. It’s not that I don’t trust you, but like any good physician I’m going to take my own history directly from the patient and do my own physical exam. You may have missed something and I owe the patient a fresh look and listen before I render an opinion or prescribe a management plan.
The medical record has become a detailed invoice to be attached to your bill to third-party payers. You need to prove to them that your service has some value. It’s not that the third-party payers don’t trust you ... well maybe that’s the issue. They don’t. So you have to prove to them that you really did something. Since they weren’t in the exam room, you must document that you asked the patient questions, did a thorough exam, and spent a specified amount of time at it. Of course that assumes that there is a direct correlation between the amount of time you spent with the patient and the quality of care. Which isn’t always the case. One sentence merely stating that you are a well-trained professional and did a thorough job doesn’t seem to be good enough. It works for the plumber and the electrician. But again, it’s that trust thing.
Of course there are the licensing and certification organizations that have a legitimate interest in the quality of your work. Because having an observer following you around for a day or two is impractical (which I still think is a good idea), you need to include evidence in your chart that you practice the standard of care by following accepted screening measures and treating according to standard guidelines.
And finally, while we are talking about trust, there is the whole risk management thing – maybe the most potent inflater of medical records. The lawyer-promoted myth “if you didn’t document it, it didn’t happen” encourages doctors to use voluminous verbiage merely to give your lawyer ammunition when you find yourself in a he-said/she-said situation.
Of course all of this needs to be carefully worded because the patient now has and deserves the right to review his or her medical records. And this might be the only good news. AI can be taught to create a medical record that is complete and more easily read and digested by the patient. This could make the records even more voluminous and as more patients become familiar with their own health records they may begin to demand that they become more concise and actually reflect what went on in the visit.
Dr. Wilkoff practiced primary care pediatrics in Brunswick, Maine, for nearly 40 years. He has authored several books on behavioral pediatrics, including “How to Say No to Your Toddler.” Other than a Littman stethoscope he accepted as a first-year medical student in 1966, Dr. Wilkoff reports having nothing to disclose. Email him at [email protected].
Until the 19th century there was nothing even resembling our current conception of the medical record. A few physicians may have kept personal notes, observations, and some sketches of their patients primarily to be used in teaching medical students or as part of their own curiosity-driven research. However, around 1800 the Governor Council of the State of New York adopted a proposition that all home doctors should register their medical cases again to be used as an educational tool. By 1830 these registries became annual reporting requirements that included admissions and discharges, treatment results, and expenditures. It shouldn’t surprise you learn that a review of these entries could be linked to a doctor’s prospects for promotion.
In 1919 the American College of Surgeons attempted to standardize its members’ “treatment diaries” to look something more like our current medical records with a history, lab tests, diagnosis, treatment plan, and something akin to daily progress notes. However, as late as the 1970s, when I began primary care practice, there were very few dictates on what our office notes should contain. A few (not including myself) had been trained to use a S.O.A.P. format (Subjective, Objective, Assessment, and Plan) to organize their observations. Back then I viewed my office records as primarily a mnemonic device and only because I had a partner did I make any passing attempt at legibility.
With AI staring us in the face and threatening to expand what has become an already bloated medical record,
Although there was a time when a doctor’s notes simply functioned as a mnemonic, few physicians today practice in isolation and their records must now serve as a vehicle to communicate with covering physicians and consultants.
How detailed do those notes need to be? Do we need more than the hard data – the numbers, the prescriptions, the biometrics, the chronology of the patient’s procedures? As a covering physician or consultant, I’m not really that interested in your subjective observations. It’s not that I don’t trust you, but like any good physician I’m going to take my own history directly from the patient and do my own physical exam. You may have missed something and I owe the patient a fresh look and listen before I render an opinion or prescribe a management plan.
The medical record has become a detailed invoice to be attached to your bill to third-party payers. You need to prove to them that your service has some value. It’s not that the third-party payers don’t trust you ... well maybe that’s the issue. They don’t. So you have to prove to them that you really did something. Since they weren’t in the exam room, you must document that you asked the patient questions, did a thorough exam, and spent a specified amount of time at it. Of course that assumes that there is a direct correlation between the amount of time you spent with the patient and the quality of care. Which isn’t always the case. One sentence merely stating that you are a well-trained professional and did a thorough job doesn’t seem to be good enough. It works for the plumber and the electrician. But again, it’s that trust thing.
Of course there are the licensing and certification organizations that have a legitimate interest in the quality of your work. Because having an observer following you around for a day or two is impractical (which I still think is a good idea), you need to include evidence in your chart that you practice the standard of care by following accepted screening measures and treating according to standard guidelines.
And finally, while we are talking about trust, there is the whole risk management thing – maybe the most potent inflater of medical records. The lawyer-promoted myth “if you didn’t document it, it didn’t happen” encourages doctors to use voluminous verbiage merely to give your lawyer ammunition when you find yourself in a he-said/she-said situation.
Of course all of this needs to be carefully worded because the patient now has and deserves the right to review his or her medical records. And this might be the only good news. AI can be taught to create a medical record that is complete and more easily read and digested by the patient. This could make the records even more voluminous and as more patients become familiar with their own health records they may begin to demand that they become more concise and actually reflect what went on in the visit.
Dr. Wilkoff practiced primary care pediatrics in Brunswick, Maine, for nearly 40 years. He has authored several books on behavioral pediatrics, including “How to Say No to Your Toddler.” Other than a Littman stethoscope he accepted as a first-year medical student in 1966, Dr. Wilkoff reports having nothing to disclose. Email him at [email protected].
Until the 19th century there was nothing even resembling our current conception of the medical record. A few physicians may have kept personal notes, observations, and some sketches of their patients primarily to be used in teaching medical students or as part of their own curiosity-driven research. However, around 1800 the Governor Council of the State of New York adopted a proposition that all home doctors should register their medical cases again to be used as an educational tool. By 1830 these registries became annual reporting requirements that included admissions and discharges, treatment results, and expenditures. It shouldn’t surprise you learn that a review of these entries could be linked to a doctor’s prospects for promotion.
In 1919 the American College of Surgeons attempted to standardize its members’ “treatment diaries” to look something more like our current medical records with a history, lab tests, diagnosis, treatment plan, and something akin to daily progress notes. However, as late as the 1970s, when I began primary care practice, there were very few dictates on what our office notes should contain. A few (not including myself) had been trained to use a S.O.A.P. format (Subjective, Objective, Assessment, and Plan) to organize their observations. Back then I viewed my office records as primarily a mnemonic device and only because I had a partner did I make any passing attempt at legibility.
With AI staring us in the face and threatening to expand what has become an already bloated medical record,
Although there was a time when a doctor’s notes simply functioned as a mnemonic, few physicians today practice in isolation and their records must now serve as a vehicle to communicate with covering physicians and consultants.
How detailed do those notes need to be? Do we need more than the hard data – the numbers, the prescriptions, the biometrics, the chronology of the patient’s procedures? As a covering physician or consultant, I’m not really that interested in your subjective observations. It’s not that I don’t trust you, but like any good physician I’m going to take my own history directly from the patient and do my own physical exam. You may have missed something and I owe the patient a fresh look and listen before I render an opinion or prescribe a management plan.
The medical record has become a detailed invoice to be attached to your bill to third-party payers. You need to prove to them that your service has some value. It’s not that the third-party payers don’t trust you ... well maybe that’s the issue. They don’t. So you have to prove to them that you really did something. Since they weren’t in the exam room, you must document that you asked the patient questions, did a thorough exam, and spent a specified amount of time at it. Of course that assumes that there is a direct correlation between the amount of time you spent with the patient and the quality of care. Which isn’t always the case. One sentence merely stating that you are a well-trained professional and did a thorough job doesn’t seem to be good enough. It works for the plumber and the electrician. But again, it’s that trust thing.
Of course there are the licensing and certification organizations that have a legitimate interest in the quality of your work. Because having an observer following you around for a day or two is impractical (which I still think is a good idea), you need to include evidence in your chart that you practice the standard of care by following accepted screening measures and treating according to standard guidelines.
And finally, while we are talking about trust, there is the whole risk management thing – maybe the most potent inflater of medical records. The lawyer-promoted myth “if you didn’t document it, it didn’t happen” encourages doctors to use voluminous verbiage merely to give your lawyer ammunition when you find yourself in a he-said/she-said situation.
Of course all of this needs to be carefully worded because the patient now has and deserves the right to review his or her medical records. And this might be the only good news. AI can be taught to create a medical record that is complete and more easily read and digested by the patient. This could make the records even more voluminous and as more patients become familiar with their own health records they may begin to demand that they become more concise and actually reflect what went on in the visit.
Dr. Wilkoff practiced primary care pediatrics in Brunswick, Maine, for nearly 40 years. He has authored several books on behavioral pediatrics, including “How to Say No to Your Toddler.” Other than a Littman stethoscope he accepted as a first-year medical student in 1966, Dr. Wilkoff reports having nothing to disclose. Email him at [email protected].
The best CRC screening test is still this one
I’m Dr. Kenny Lin. I am a family physician and associate director of the Lancaster General Hospital Family Medicine Residency, and I blog at Common Sense Family Doctor.
I’m 47 years old. Two years ago, when the U.S. Preventive Services Task Force (USPSTF) followed the American Cancer Society and lowered the starting age for colorectal cancer (CRC) screening from 50 to 45, my family physician brought up screening options at a health maintenance visit. Although I had expressed some skepticism about this change when the ACS updated its screening guideline in 2018, I generally follow the USPSTF recommendations in my own clinical practice, so I dutifully selected a test that, fortunately, came out negative.
Not everyone in the primary care community, however, is on board with screening average-risk adults in their late 40s for colorectal cancer. The American Academy of Family Physicians (AAFP) published a notable dissent, arguing that the evidence from modeling studies cited by the USPSTF to support lowering the starting age was insufficient. The AAFP also expressed concern that devoting screening resources to younger adults could come at the expense of improving screening rates in older adults who are at higher risk for CRC and increase health care costs without corresponding benefit.
Now, the American College of Physicians has joined the AAFP by releasing an updated guidance statement for CRC screening that discourages screening asymptomatic, average-risk adults between the ages of 45 and 49. In addition to the uncertainty surrounding benefits of screening adults in this age range, the ACP pointed out that starting screening at age 45, compared with age 50, would increase the number of colonoscopies and colonoscopy complications. My colleagues and I recently published a systematic review estimating that for every 10,000 screening colonoscopies performed, 8 people suffer a bowel perforation and 16 to 36 have severe bleeding requiring hospitalization. One in 3 patients undergoing colonoscopies report minor adverse events such as abdominal pain, bloating, and abdominal discomfort in the first 2 weeks following the procedure.
Other aspects of the ACP guidance differ from other colorectal cancer screening guidelines. Unlike the USPSTF, which made no distinctions between various recommended screening tests, the ACP preferentially endorsed fecal immunochemical or high-sensitivity fecal occult blood testing every 2 years, colonoscopy every 10 years, or flexible sigmoidoscopy every 10 years plus a fecal immunochemical test every 2 years. That leaves out stool DNA testing, which my patients increasingly request because they have seen television or online advertisements, and newer blood tests that detect methylation sequences in circulating tumor DNA.
Perhaps most controversial is the ACP’s suggestion that it is probably reasonable for some adults to start screening later than age 50 or undergo screening at longer intervals than currently recommended (for example, colonoscopy every 15 years). Recent data support extending the interval to repeat screening colonoscopy in selected populations; a large cross-sectional study found a low prevalence of advanced adenomas and colorectal cancers in colonoscopies performed 10 or more years after an initial negative colonoscopy, particularly in women and younger patients without gastrointestinal symptoms. A prominent BMJ guideline suggests that patients need not be screened until their estimated 15-year CRC risk is greater than 3% (which most people do not reach until their 60s) and then only need a single sigmoidoscopy or colonoscopy.
Despite some departures from other guidelines, it’s worth emphasizing that the ACP guideline agrees that screening for CRC is generally worthwhile between the ages of 50 and 75 years. On that front, we in primary care have more work to do; the Centers for Disease Control and Prevention estimates that 28% of American adults older than 50 are not up-to-date on CRC screening. And despite some recent debate about the relative benefits and harms of screening colonoscopy, compared with less invasive fecal tests, gastroenterologists and family physicians can agree that the best screening test is the test that gets done.
A version of this article first appeared on Medscape.com.
I’m Dr. Kenny Lin. I am a family physician and associate director of the Lancaster General Hospital Family Medicine Residency, and I blog at Common Sense Family Doctor.
I’m 47 years old. Two years ago, when the U.S. Preventive Services Task Force (USPSTF) followed the American Cancer Society and lowered the starting age for colorectal cancer (CRC) screening from 50 to 45, my family physician brought up screening options at a health maintenance visit. Although I had expressed some skepticism about this change when the ACS updated its screening guideline in 2018, I generally follow the USPSTF recommendations in my own clinical practice, so I dutifully selected a test that, fortunately, came out negative.
Not everyone in the primary care community, however, is on board with screening average-risk adults in their late 40s for colorectal cancer. The American Academy of Family Physicians (AAFP) published a notable dissent, arguing that the evidence from modeling studies cited by the USPSTF to support lowering the starting age was insufficient. The AAFP also expressed concern that devoting screening resources to younger adults could come at the expense of improving screening rates in older adults who are at higher risk for CRC and increase health care costs without corresponding benefit.
Now, the American College of Physicians has joined the AAFP by releasing an updated guidance statement for CRC screening that discourages screening asymptomatic, average-risk adults between the ages of 45 and 49. In addition to the uncertainty surrounding benefits of screening adults in this age range, the ACP pointed out that starting screening at age 45, compared with age 50, would increase the number of colonoscopies and colonoscopy complications. My colleagues and I recently published a systematic review estimating that for every 10,000 screening colonoscopies performed, 8 people suffer a bowel perforation and 16 to 36 have severe bleeding requiring hospitalization. One in 3 patients undergoing colonoscopies report minor adverse events such as abdominal pain, bloating, and abdominal discomfort in the first 2 weeks following the procedure.
Other aspects of the ACP guidance differ from other colorectal cancer screening guidelines. Unlike the USPSTF, which made no distinctions between various recommended screening tests, the ACP preferentially endorsed fecal immunochemical or high-sensitivity fecal occult blood testing every 2 years, colonoscopy every 10 years, or flexible sigmoidoscopy every 10 years plus a fecal immunochemical test every 2 years. That leaves out stool DNA testing, which my patients increasingly request because they have seen television or online advertisements, and newer blood tests that detect methylation sequences in circulating tumor DNA.
Perhaps most controversial is the ACP’s suggestion that it is probably reasonable for some adults to start screening later than age 50 or undergo screening at longer intervals than currently recommended (for example, colonoscopy every 15 years). Recent data support extending the interval to repeat screening colonoscopy in selected populations; a large cross-sectional study found a low prevalence of advanced adenomas and colorectal cancers in colonoscopies performed 10 or more years after an initial negative colonoscopy, particularly in women and younger patients without gastrointestinal symptoms. A prominent BMJ guideline suggests that patients need not be screened until their estimated 15-year CRC risk is greater than 3% (which most people do not reach until their 60s) and then only need a single sigmoidoscopy or colonoscopy.
Despite some departures from other guidelines, it’s worth emphasizing that the ACP guideline agrees that screening for CRC is generally worthwhile between the ages of 50 and 75 years. On that front, we in primary care have more work to do; the Centers for Disease Control and Prevention estimates that 28% of American adults older than 50 are not up-to-date on CRC screening. And despite some recent debate about the relative benefits and harms of screening colonoscopy, compared with less invasive fecal tests, gastroenterologists and family physicians can agree that the best screening test is the test that gets done.
A version of this article first appeared on Medscape.com.
I’m Dr. Kenny Lin. I am a family physician and associate director of the Lancaster General Hospital Family Medicine Residency, and I blog at Common Sense Family Doctor.
I’m 47 years old. Two years ago, when the U.S. Preventive Services Task Force (USPSTF) followed the American Cancer Society and lowered the starting age for colorectal cancer (CRC) screening from 50 to 45, my family physician brought up screening options at a health maintenance visit. Although I had expressed some skepticism about this change when the ACS updated its screening guideline in 2018, I generally follow the USPSTF recommendations in my own clinical practice, so I dutifully selected a test that, fortunately, came out negative.
Not everyone in the primary care community, however, is on board with screening average-risk adults in their late 40s for colorectal cancer. The American Academy of Family Physicians (AAFP) published a notable dissent, arguing that the evidence from modeling studies cited by the USPSTF to support lowering the starting age was insufficient. The AAFP also expressed concern that devoting screening resources to younger adults could come at the expense of improving screening rates in older adults who are at higher risk for CRC and increase health care costs without corresponding benefit.
Now, the American College of Physicians has joined the AAFP by releasing an updated guidance statement for CRC screening that discourages screening asymptomatic, average-risk adults between the ages of 45 and 49. In addition to the uncertainty surrounding benefits of screening adults in this age range, the ACP pointed out that starting screening at age 45, compared with age 50, would increase the number of colonoscopies and colonoscopy complications. My colleagues and I recently published a systematic review estimating that for every 10,000 screening colonoscopies performed, 8 people suffer a bowel perforation and 16 to 36 have severe bleeding requiring hospitalization. One in 3 patients undergoing colonoscopies report minor adverse events such as abdominal pain, bloating, and abdominal discomfort in the first 2 weeks following the procedure.
Other aspects of the ACP guidance differ from other colorectal cancer screening guidelines. Unlike the USPSTF, which made no distinctions between various recommended screening tests, the ACP preferentially endorsed fecal immunochemical or high-sensitivity fecal occult blood testing every 2 years, colonoscopy every 10 years, or flexible sigmoidoscopy every 10 years plus a fecal immunochemical test every 2 years. That leaves out stool DNA testing, which my patients increasingly request because they have seen television or online advertisements, and newer blood tests that detect methylation sequences in circulating tumor DNA.
Perhaps most controversial is the ACP’s suggestion that it is probably reasonable for some adults to start screening later than age 50 or undergo screening at longer intervals than currently recommended (for example, colonoscopy every 15 years). Recent data support extending the interval to repeat screening colonoscopy in selected populations; a large cross-sectional study found a low prevalence of advanced adenomas and colorectal cancers in colonoscopies performed 10 or more years after an initial negative colonoscopy, particularly in women and younger patients without gastrointestinal symptoms. A prominent BMJ guideline suggests that patients need not be screened until their estimated 15-year CRC risk is greater than 3% (which most people do not reach until their 60s) and then only need a single sigmoidoscopy or colonoscopy.
Despite some departures from other guidelines, it’s worth emphasizing that the ACP guideline agrees that screening for CRC is generally worthwhile between the ages of 50 and 75 years. On that front, we in primary care have more work to do; the Centers for Disease Control and Prevention estimates that 28% of American adults older than 50 are not up-to-date on CRC screening. And despite some recent debate about the relative benefits and harms of screening colonoscopy, compared with less invasive fecal tests, gastroenterologists and family physicians can agree that the best screening test is the test that gets done.
A version of this article first appeared on Medscape.com.
Unveiling the potential of prediction models in obstetrics
In the dawn of artificial intelligence’s potential to inform clinical practice, the importance of understanding the intent and interpretation of prediction tools is vital. In medicine, informed decision-making promotes patient autonomy and can lead to improved patient satisfaction and engagement in their own care.
This shared understanding enables patients to make informed choices about their care, reducing anxiety and increasing confidence in medical decision-making.
In obstetric clinical practice, prediction tools have been created to assess risk of primary cesarean delivery in gestational diabetes,1 cesarean delivery in hypertensive disorders of pregnancy,2 and failed induction of labor in nulliparous patients with an unfavorable cervix.3 By assessing a patient’s risk profile, clinicians can identify high-risk individuals who may require closer monitoring, early interventions, or specialized care. This allows for more timely interventions to optimize maternal and fetal health outcomes.
Other prediction tools are created to better elucidate to patients their individual risk of an outcome that may be modifiable, aiding physician counseling on mitigating factors to improve overall results. A relevant example is the American Diabetes Association’s risk of type 2 diabetes calculator used for counseling patients on risk reduction. This model includes both preexisting (ethnicity, family history, age, sex assigned at birth) and modifiable risk factors (body mass index, hypertension, physical activity) to predict risk of type 2 diabetes and is widely used in clinical practice to encourage integration of lifestyle changes to decrease risk.4 This model highlights the utility of prediction tools in counseling, providing quantitative data to clinicians to discuss a patient’s individual risk and how to mitigate that risk.
While predictive models clearly have many advantages and potential to improve personalized medicine, concerns have been raised that their interpretation and application can sometimes have unintended consequences as the complexity of these models can lead to variation in understanding among clinicians that impact decision-making. Different clinicians may assign different levels of importance to the predicted risks, resulting in differences in treatment plans and interventions. This variability can lead to disparities in care and outcomes, as patients with similar risk profiles may receive different management approaches based on the interpreting clinician.
Providers may either overly rely on prediction models or completely disregard them, depending on their level of trust or skepticism. Overreliance on prediction models may lead to the neglect of important clinical information or intuition, while disregarding the models may result in missed opportunities for early intervention or appropriate risk stratification. Achieving a balance between clinical judgment and the use of prediction models is crucial for optimal decision-making.
An example of how misinterpretation of the role of prediction tools in patient counseling can have far reaching consequences is the vaginal birth after cesarean (VBAC) calculator where race and ethnicity naturalized racial differences and likely contributed to cesarean overuse in Black pregnant people as non-White race was associated with a decreased chance of successful VBAC. Although the authors of the study that created the VBAC calculator intended it to be used as an adjunct to counseling, institutions and providers used low calculator scores to discourage or prohibit pregnant people from attempting a trial of labor after cesarean (TOLAC). This highlighted the importance of contextualizing the intent of prediction models within the broader clinical setting and individual patient circumstances and preferences.
This gap between intent and interpretation and subsequent application is influenced by individual clinician experience, training, personal biases, and subjective judgment. These subjective elements can introduce inconsistencies and variability in the utilization of prediction tools, leading to potential discrepancies in patient care. Inadequate understanding of prediction models and their statistical concepts can contribute to misinterpretation. It is this bias that prevents prediction models from serving their true purpose: to inform clinical decision-making, improve patient outcomes, and optimize resource allocation.
Clinicians may struggle with concepts such as predictive accuracy, overfitting, calibration, and external validation. Educational initiatives and enhanced training in statistical literacy can empower clinicians to better comprehend and apply prediction models in their practice. Researchers should make it clear that models should not be used in isolation, but rather integrated with clinical expertise and patient preferences. Understanding the limitations of prediction models and incorporating additional clinical information is essential.
Prediction models in obstetrics should undergo continuous evaluation and improvement to enhance their reliability and applicability. Regular updates, external validation, and recalibration are necessary to account for evolving clinical practices, changes in patient populations, and emerging evidence. Engaging clinicians in the evaluation process can foster ownership and promote a sense of trust in the models.
As machine learning and artificial intelligence improve the accuracy of prediction models, there is potential to revolutionize obstetric care by enabling more accurate individualized risk assessment and decision-making. Machine learning has the potential to significantly enhance prediction models in obstetrics by leveraging complex algorithms and advanced computational techniques. However, the unpredictable nature of clinician interpretation poses challenges to the effective utilization of these models.
By emphasizing communication, collaboration, education, and continuous evaluation, we can bridge the gap between prediction models and clinician interpretation that optimizes their use. This concerted effort will ultimately lead to improved patient care, enhanced clinical outcomes, and a more harmonious integration of these tools into obstetric practice.
Dr. Ramos is assistant professor of maternal fetal medicine and associate principal investigator at the Mother Infant Research Institute, Tufts University and Tufts Medical Center, Boston.
References
1. Ramos SZ et al. Predicting primary cesarean delivery in pregnancies complicated by gestational diabetes mellitus. Am J Obstet Gynecol. 2023 Jun 7;S0002-9378(23)00371-X. doi: 10.1016/j.ajog.2023.06.002.
2. Beninati MJ et al. Prediction model for vaginal birth after induction of labor in women with hypertensive disorders of pregnancy. Obstet Gynecol. 2020 Aug;136(2):402-410. doi: 10.1097/AOG.0000000000003938.
3. Levine LD et al. A validated calculator to estimate risk of cesarean after an induction of labor with an unfavorable cervix. Am J Obstet Gynecol. 2018 Feb;218(2):254.e1-254.e7. doi: 10.1016/j.ajog.2017.11.603.
4. American Diabetes Association. Our 60-Second Type 2 Diabetes Risk Test.
In the dawn of artificial intelligence’s potential to inform clinical practice, the importance of understanding the intent and interpretation of prediction tools is vital. In medicine, informed decision-making promotes patient autonomy and can lead to improved patient satisfaction and engagement in their own care.
This shared understanding enables patients to make informed choices about their care, reducing anxiety and increasing confidence in medical decision-making.
In obstetric clinical practice, prediction tools have been created to assess risk of primary cesarean delivery in gestational diabetes,1 cesarean delivery in hypertensive disorders of pregnancy,2 and failed induction of labor in nulliparous patients with an unfavorable cervix.3 By assessing a patient’s risk profile, clinicians can identify high-risk individuals who may require closer monitoring, early interventions, or specialized care. This allows for more timely interventions to optimize maternal and fetal health outcomes.
Other prediction tools are created to better elucidate to patients their individual risk of an outcome that may be modifiable, aiding physician counseling on mitigating factors to improve overall results. A relevant example is the American Diabetes Association’s risk of type 2 diabetes calculator used for counseling patients on risk reduction. This model includes both preexisting (ethnicity, family history, age, sex assigned at birth) and modifiable risk factors (body mass index, hypertension, physical activity) to predict risk of type 2 diabetes and is widely used in clinical practice to encourage integration of lifestyle changes to decrease risk.4 This model highlights the utility of prediction tools in counseling, providing quantitative data to clinicians to discuss a patient’s individual risk and how to mitigate that risk.
While predictive models clearly have many advantages and potential to improve personalized medicine, concerns have been raised that their interpretation and application can sometimes have unintended consequences as the complexity of these models can lead to variation in understanding among clinicians that impact decision-making. Different clinicians may assign different levels of importance to the predicted risks, resulting in differences in treatment plans and interventions. This variability can lead to disparities in care and outcomes, as patients with similar risk profiles may receive different management approaches based on the interpreting clinician.
Providers may either overly rely on prediction models or completely disregard them, depending on their level of trust or skepticism. Overreliance on prediction models may lead to the neglect of important clinical information or intuition, while disregarding the models may result in missed opportunities for early intervention or appropriate risk stratification. Achieving a balance between clinical judgment and the use of prediction models is crucial for optimal decision-making.
An example of how misinterpretation of the role of prediction tools in patient counseling can have far reaching consequences is the vaginal birth after cesarean (VBAC) calculator where race and ethnicity naturalized racial differences and likely contributed to cesarean overuse in Black pregnant people as non-White race was associated with a decreased chance of successful VBAC. Although the authors of the study that created the VBAC calculator intended it to be used as an adjunct to counseling, institutions and providers used low calculator scores to discourage or prohibit pregnant people from attempting a trial of labor after cesarean (TOLAC). This highlighted the importance of contextualizing the intent of prediction models within the broader clinical setting and individual patient circumstances and preferences.
This gap between intent and interpretation and subsequent application is influenced by individual clinician experience, training, personal biases, and subjective judgment. These subjective elements can introduce inconsistencies and variability in the utilization of prediction tools, leading to potential discrepancies in patient care. Inadequate understanding of prediction models and their statistical concepts can contribute to misinterpretation. It is this bias that prevents prediction models from serving their true purpose: to inform clinical decision-making, improve patient outcomes, and optimize resource allocation.
Clinicians may struggle with concepts such as predictive accuracy, overfitting, calibration, and external validation. Educational initiatives and enhanced training in statistical literacy can empower clinicians to better comprehend and apply prediction models in their practice. Researchers should make it clear that models should not be used in isolation, but rather integrated with clinical expertise and patient preferences. Understanding the limitations of prediction models and incorporating additional clinical information is essential.
Prediction models in obstetrics should undergo continuous evaluation and improvement to enhance their reliability and applicability. Regular updates, external validation, and recalibration are necessary to account for evolving clinical practices, changes in patient populations, and emerging evidence. Engaging clinicians in the evaluation process can foster ownership and promote a sense of trust in the models.
As machine learning and artificial intelligence improve the accuracy of prediction models, there is potential to revolutionize obstetric care by enabling more accurate individualized risk assessment and decision-making. Machine learning has the potential to significantly enhance prediction models in obstetrics by leveraging complex algorithms and advanced computational techniques. However, the unpredictable nature of clinician interpretation poses challenges to the effective utilization of these models.
By emphasizing communication, collaboration, education, and continuous evaluation, we can bridge the gap between prediction models and clinician interpretation that optimizes their use. This concerted effort will ultimately lead to improved patient care, enhanced clinical outcomes, and a more harmonious integration of these tools into obstetric practice.
Dr. Ramos is assistant professor of maternal fetal medicine and associate principal investigator at the Mother Infant Research Institute, Tufts University and Tufts Medical Center, Boston.
References
1. Ramos SZ et al. Predicting primary cesarean delivery in pregnancies complicated by gestational diabetes mellitus. Am J Obstet Gynecol. 2023 Jun 7;S0002-9378(23)00371-X. doi: 10.1016/j.ajog.2023.06.002.
2. Beninati MJ et al. Prediction model for vaginal birth after induction of labor in women with hypertensive disorders of pregnancy. Obstet Gynecol. 2020 Aug;136(2):402-410. doi: 10.1097/AOG.0000000000003938.
3. Levine LD et al. A validated calculator to estimate risk of cesarean after an induction of labor with an unfavorable cervix. Am J Obstet Gynecol. 2018 Feb;218(2):254.e1-254.e7. doi: 10.1016/j.ajog.2017.11.603.
4. American Diabetes Association. Our 60-Second Type 2 Diabetes Risk Test.
In the dawn of artificial intelligence’s potential to inform clinical practice, the importance of understanding the intent and interpretation of prediction tools is vital. In medicine, informed decision-making promotes patient autonomy and can lead to improved patient satisfaction and engagement in their own care.
This shared understanding enables patients to make informed choices about their care, reducing anxiety and increasing confidence in medical decision-making.
In obstetric clinical practice, prediction tools have been created to assess risk of primary cesarean delivery in gestational diabetes,1 cesarean delivery in hypertensive disorders of pregnancy,2 and failed induction of labor in nulliparous patients with an unfavorable cervix.3 By assessing a patient’s risk profile, clinicians can identify high-risk individuals who may require closer monitoring, early interventions, or specialized care. This allows for more timely interventions to optimize maternal and fetal health outcomes.
Other prediction tools are created to better elucidate to patients their individual risk of an outcome that may be modifiable, aiding physician counseling on mitigating factors to improve overall results. A relevant example is the American Diabetes Association’s risk of type 2 diabetes calculator used for counseling patients on risk reduction. This model includes both preexisting (ethnicity, family history, age, sex assigned at birth) and modifiable risk factors (body mass index, hypertension, physical activity) to predict risk of type 2 diabetes and is widely used in clinical practice to encourage integration of lifestyle changes to decrease risk.4 This model highlights the utility of prediction tools in counseling, providing quantitative data to clinicians to discuss a patient’s individual risk and how to mitigate that risk.
While predictive models clearly have many advantages and potential to improve personalized medicine, concerns have been raised that their interpretation and application can sometimes have unintended consequences as the complexity of these models can lead to variation in understanding among clinicians that impact decision-making. Different clinicians may assign different levels of importance to the predicted risks, resulting in differences in treatment plans and interventions. This variability can lead to disparities in care and outcomes, as patients with similar risk profiles may receive different management approaches based on the interpreting clinician.
Providers may either overly rely on prediction models or completely disregard them, depending on their level of trust or skepticism. Overreliance on prediction models may lead to the neglect of important clinical information or intuition, while disregarding the models may result in missed opportunities for early intervention or appropriate risk stratification. Achieving a balance between clinical judgment and the use of prediction models is crucial for optimal decision-making.
An example of how misinterpretation of the role of prediction tools in patient counseling can have far reaching consequences is the vaginal birth after cesarean (VBAC) calculator where race and ethnicity naturalized racial differences and likely contributed to cesarean overuse in Black pregnant people as non-White race was associated with a decreased chance of successful VBAC. Although the authors of the study that created the VBAC calculator intended it to be used as an adjunct to counseling, institutions and providers used low calculator scores to discourage or prohibit pregnant people from attempting a trial of labor after cesarean (TOLAC). This highlighted the importance of contextualizing the intent of prediction models within the broader clinical setting and individual patient circumstances and preferences.
This gap between intent and interpretation and subsequent application is influenced by individual clinician experience, training, personal biases, and subjective judgment. These subjective elements can introduce inconsistencies and variability in the utilization of prediction tools, leading to potential discrepancies in patient care. Inadequate understanding of prediction models and their statistical concepts can contribute to misinterpretation. It is this bias that prevents prediction models from serving their true purpose: to inform clinical decision-making, improve patient outcomes, and optimize resource allocation.
Clinicians may struggle with concepts such as predictive accuracy, overfitting, calibration, and external validation. Educational initiatives and enhanced training in statistical literacy can empower clinicians to better comprehend and apply prediction models in their practice. Researchers should make it clear that models should not be used in isolation, but rather integrated with clinical expertise and patient preferences. Understanding the limitations of prediction models and incorporating additional clinical information is essential.
Prediction models in obstetrics should undergo continuous evaluation and improvement to enhance their reliability and applicability. Regular updates, external validation, and recalibration are necessary to account for evolving clinical practices, changes in patient populations, and emerging evidence. Engaging clinicians in the evaluation process can foster ownership and promote a sense of trust in the models.
As machine learning and artificial intelligence improve the accuracy of prediction models, there is potential to revolutionize obstetric care by enabling more accurate individualized risk assessment and decision-making. Machine learning has the potential to significantly enhance prediction models in obstetrics by leveraging complex algorithms and advanced computational techniques. However, the unpredictable nature of clinician interpretation poses challenges to the effective utilization of these models.
By emphasizing communication, collaboration, education, and continuous evaluation, we can bridge the gap between prediction models and clinician interpretation that optimizes their use. This concerted effort will ultimately lead to improved patient care, enhanced clinical outcomes, and a more harmonious integration of these tools into obstetric practice.
Dr. Ramos is assistant professor of maternal fetal medicine and associate principal investigator at the Mother Infant Research Institute, Tufts University and Tufts Medical Center, Boston.
References
1. Ramos SZ et al. Predicting primary cesarean delivery in pregnancies complicated by gestational diabetes mellitus. Am J Obstet Gynecol. 2023 Jun 7;S0002-9378(23)00371-X. doi: 10.1016/j.ajog.2023.06.002.
2. Beninati MJ et al. Prediction model for vaginal birth after induction of labor in women with hypertensive disorders of pregnancy. Obstet Gynecol. 2020 Aug;136(2):402-410. doi: 10.1097/AOG.0000000000003938.
3. Levine LD et al. A validated calculator to estimate risk of cesarean after an induction of labor with an unfavorable cervix. Am J Obstet Gynecol. 2018 Feb;218(2):254.e1-254.e7. doi: 10.1016/j.ajog.2017.11.603.
4. American Diabetes Association. Our 60-Second Type 2 Diabetes Risk Test.
For NSCLC, neoadjuvant, adjuvant, or both?
This transcript has been edited for clarity.
Dr. West: Here at ASCO 2023 [American Society of Clinical Oncology] in Chicago, we’ve seen some blockbuster presentations in thoracic oncology. Many of these have brought up some important questions about the clinical implications that we need to discuss further.
At ASCO, as well as in the couple or 3 months preceding ASCO, we’ve gotten more and more data on perioperative approaches. Of course, over the past couple of years, we’ve had some new options of postoperative immunotherapy for a year, say, after chemotherapy or possibly after chemotherapy.
We have also had very influential data, such as the CheckMate 816 trial that gave three cycles of chemotherapy with nivolumab vs. chemotherapy alone to patients with stage IB to IIIA disease, but largely, nearly two thirds, with IIIA disease. That showed a very clear improvement in the pathologic complete response (pCR) rate with nivolumab added to chemotherapy and also a highly significant improvement in event-free survival and a strong trend toward improved overall survival. This is FDA approved and has been increasingly adopted, I would say, maybe with some variability by geography and center, but really a good amount of enthusiasm.
Now, we have a bunch of trials that give chemotherapy with immunotherapy. We’ve got the AEGEAN trial with durvalumab. We have Neotorch with chemotherapy and toripalimab. At ASCO 2023, we had a highly prominent presentation of KEYNOTE-671, giving four cycles of chemotherapy with pembrolizumab vs. chemotherapy and placebo.
Then there’s the built-in postoperative component of a year of immunotherapy as well, in all these trials. The data for KEYNOTE-671 look quite good. Of course, the other trials also were significant. I would say the comparator now is not nothing or chemotherapy alone anymore; it’s really against what is the best current standard of care.
It certainly adds some cost, it adds some risk for toxicity, and it adds a year of a patient coming into the clinic and getting IV infusions all this time to get a treatment that the patient has already had for four cycles in most of these trials.
If your cancer is resistant, is there going to be an incremental benefit to giving more of it? What are your thoughts about the risk and benefit? Going to a patient in your own clinic, how are you going to counsel your patients? Will anything change after the presentation of all these data and how you approach preoperatively?
Dr. Rotow: I agree. In some sense, it’s an embarrassment of riches, right?
Dr. West: Yes.
Dr. Rotow: We have so many positive studies looking at perioperative immunotherapy for our patients. They all show improved outcomes, but of course, they all compare with the old control arm of chemotherapy alone in some form, and this is no longer a useful control in this space. The open question is, do you use neoadjuvant, do you use adjuvant, or do you use both?
My high-level takeaway from these data is that the neoadjuvant component appears to be important. I think the overall trend, comparing across studies, of course, is that outcomes seem to be better with the neoadjuvant component. You also get the advantage of potential downstaging and potential greater ease of surgical resection. We know they have lower morbidity resection and shorter surgeries. You can comment on that. You also get your pathologic response data.
Dr. West: You get the feedback.
Dr. Rotow: Exactly.
Dr. West: The deliverability is also a big issue. You know you can much more reliably deliver your intended treatment by doing neoadjuvant followed by surgery.
Dr. Rotow: Exactly.
Dr. West: We know there’s major drop-off if patients have surgery, and in the recovery room they hear you got it all, and then they need to come back and maybe get chemotherapy and immunotherapy for a year. They’d ask, “What for? I can’t see anything.”
Dr. Rotow: Exactly. I think there are many advantages to that neoadjuvant component. I think all or many of us now have integrated this into our routine practice. Now the question is, do you need the adjuvant element or not on top? That is challenging because no trial has compared adjuvant to nonadjuvant. I think we all advocate for the need for this trial to answer this in a more randomized, prospective fashion. Of course, that doesn’t help our clinic practice tomorrow when we see a patient.
Dr. West: Or for the next 4 years.
Dr. Rotow: Or for the next 4 years – exactly. There’s going to be the open question of who really needs this? In some sense, we may be guided by the path response during the surgery itself. I think there may be those who claim that if you have a pCR, do you really need additional therapy? We don’t know the answer, but it’s tempting to say we know the outcomes in event-free survival are extremely good with a pCR.
Dr. West: Which is only 20% or 25% of patients, so it’s not most.
Dr. Rotow: It’s not most, but it’s better than the 2% or so with chemotherapy alone. That’s real progress, and it’s nice to have that readout. For that 80% without a pCR, what to do? I suspect there will be variation from provider to provider and from patient to patient, depending on tolerability to prior therapy, the patient’s wishes around the goals of care, and the patient’s risk for autoimmune toxicities.
Maybe there’s a patient with underlying autoimmune disease who’s gotten their neoadjuvant therapy and done well. You don’t want to risk that ongoing risk of exposure. Perhaps a patient with no risk factors who desires very aggressive treatment might be interested in more treatment.
In KEYNOTE-671, I was interested in the PD-L1 subgroups. These did trend the way you expect, with better responses in PD-L1 high, but there were also good outcomes and benefit to immunotherapy with the perioperative strategy in PD-L1–negative patients.
Dr. West: That didn’t really exclude anybody.
Dr. Rotow: It didn’t exclude anybody. In CheckMate 816, everyone benefited, but the benefit was less with those PD-L1–negative patients.
Dr. West: True.
Dr. Rotow: Absent further data to guide me or any prospective data here comparing these strategies, I might lean toward a longer course of immunotherapy in that population in hopes of triggering a response. I suspect that there will be variation from clinician to clinician in that space.
Dr. West: This is a setting where I feel like I have equipoise. I really feel that the incremental benefit is pretty small.
Dr. Rotow: Small. I agree.
Dr. West: It’s, frankly, somewhat dubious. On the other hand, you’re in a situation where if you know that three of four patients will experience a relapse and less-than-amazing outcomes, it’s hard to leave something that’s FDA approved and studied and a well-sanctioned option on the table if this patient may have relapse later.
In the end, I feel like I’d like to offer this and discuss it with all my patients. I think it’s a great place for shared decision-making because if a patient hears about that and decides they’re not interested, I’ll be fine with that. I think that’s a very sensible approach, but I don’t want to make it unilaterally. Other patients may say they want every opportunity, and if it comes back, at least I’ll know I did everything we could.
Dr. Rotow: Exactly. I agree with your statement about equipoise. I truly think that this is present here in the situation, and that there’s room for discussion in both directions with patients.
Now, one caveat I’d like to add to all these data is that the data should not apply to patients with some of our classic nonsmoking-associated driver mutations. This is another piece to the neoadjuvant data that I think is worth commenting on – the need to get appropriate testing before initiation of therapy and the pitfalls of starting this kind of treatment without knowing full biomarker testing. I think that’s something we have to watch for in our clinical practice as well.
Dr. West: Perhaps especially if we’re talking about doing a year of postoperative and someone has an ALK rearrangement or an EGFR mutation and we didn’t know it. That is a group where we’re worried about a rapid transition and potentially prohibitive, even life-threatening, toxicities from not planning in advance for this. This is something you don’t want to give concurrently or one right on top of the other. You don’t want to give immunotherapy and then transition right to targeted therapy. It’s dangerous.
Dr. Rotow: Exactly. The stakes were already high with neoadjuvant alone, but at least you had that gap of the presurgical period, surgical recovery, and then initiation of adjuvant therapy, if needed, or at relapse. With a postoperative long adjuvant period, those stakes are elevated because the immunotherapy exposure continues, so it’s something to be mindful of.
Dr. West: We have a general sense that many, but not all, of the targets that we’re talking about are associated with low benefit from immunotherapy. It’s not that well studied. I think this is another place for individualized discussion of the pros and cons. They were included in the trial, but they probably benefit less.
Dr. Rotow: Exactly. I think with the best established, EGFR and ALK probably are not benefiting much. They were actually included in the trial. Many of the neoadjuvant studies do not allow them to enroll if they’re known. On the other end of that spectrum, I think KRAS is just fine to treat with immunotherapy.
Dr. West: Sure.
Dr. Rotow: It’s an actionable driver. It’s not a traditional nonsmoking-associated driver, and those do just fine.
Dr. West: The studies show that these patients benefit just as much, at least, as the other patients.
Dr. Rotow: Exactly. I would never withhold this form of therapy for a KRAS driver mutation. The others, I think, are still in a gray zone. Depending on the patient demographics and tobacco use, I may elicit more or less caution in that space.
Dr. West: Well, I think we’re going to have much to still tease apart, with room for judgment here without a strong sense of the data telling us exactly what to do.
Dr. Rotow: Exactly.
Dr. West: There’s a large amount of excitement and interest in these new data, but there are still many open questions. I hope we continue to mull it over as we get more data and more insight to shape our plans.
Dr. West is an associate professor at City of Hope Comprehensive Cancer Center in Duarte, Calif., and vice president of network strategy at AccessHope in Los Angeles. Dr. Rotow is the clinical director of the Lowe Center for Thoracic Oncology at the Dana-Farber Cancer Institute in Boston. Dr. West reported conflicts of interest with Ariad/Takeda, Bristol Myers Squibb, Boehringer Ingelheim, Spectrum, AstraZeneca, Celgene, Genentech/Roche, Pfizer, Merck, and Eli Lilly. Dr. Rotow reported conflicts of interest with Genentech, AstraZeneca,Guardant, and Janssen.
A version of this article first appeared on Medscape.com.
This transcript has been edited for clarity.
Dr. West: Here at ASCO 2023 [American Society of Clinical Oncology] in Chicago, we’ve seen some blockbuster presentations in thoracic oncology. Many of these have brought up some important questions about the clinical implications that we need to discuss further.
At ASCO, as well as in the couple or 3 months preceding ASCO, we’ve gotten more and more data on perioperative approaches. Of course, over the past couple of years, we’ve had some new options of postoperative immunotherapy for a year, say, after chemotherapy or possibly after chemotherapy.
We have also had very influential data, such as the CheckMate 816 trial that gave three cycles of chemotherapy with nivolumab vs. chemotherapy alone to patients with stage IB to IIIA disease, but largely, nearly two thirds, with IIIA disease. That showed a very clear improvement in the pathologic complete response (pCR) rate with nivolumab added to chemotherapy and also a highly significant improvement in event-free survival and a strong trend toward improved overall survival. This is FDA approved and has been increasingly adopted, I would say, maybe with some variability by geography and center, but really a good amount of enthusiasm.
Now, we have a bunch of trials that give chemotherapy with immunotherapy. We’ve got the AEGEAN trial with durvalumab. We have Neotorch with chemotherapy and toripalimab. At ASCO 2023, we had a highly prominent presentation of KEYNOTE-671, giving four cycles of chemotherapy with pembrolizumab vs. chemotherapy and placebo.
Then there’s the built-in postoperative component of a year of immunotherapy as well, in all these trials. The data for KEYNOTE-671 look quite good. Of course, the other trials also were significant. I would say the comparator now is not nothing or chemotherapy alone anymore; it’s really against what is the best current standard of care.
It certainly adds some cost, it adds some risk for toxicity, and it adds a year of a patient coming into the clinic and getting IV infusions all this time to get a treatment that the patient has already had for four cycles in most of these trials.
If your cancer is resistant, is there going to be an incremental benefit to giving more of it? What are your thoughts about the risk and benefit? Going to a patient in your own clinic, how are you going to counsel your patients? Will anything change after the presentation of all these data and how you approach preoperatively?
Dr. Rotow: I agree. In some sense, it’s an embarrassment of riches, right?
Dr. West: Yes.
Dr. Rotow: We have so many positive studies looking at perioperative immunotherapy for our patients. They all show improved outcomes, but of course, they all compare with the old control arm of chemotherapy alone in some form, and this is no longer a useful control in this space. The open question is, do you use neoadjuvant, do you use adjuvant, or do you use both?
My high-level takeaway from these data is that the neoadjuvant component appears to be important. I think the overall trend, comparing across studies, of course, is that outcomes seem to be better with the neoadjuvant component. You also get the advantage of potential downstaging and potential greater ease of surgical resection. We know they have lower morbidity resection and shorter surgeries. You can comment on that. You also get your pathologic response data.
Dr. West: You get the feedback.
Dr. Rotow: Exactly.
Dr. West: The deliverability is also a big issue. You know you can much more reliably deliver your intended treatment by doing neoadjuvant followed by surgery.
Dr. Rotow: Exactly.
Dr. West: We know there’s major drop-off if patients have surgery, and in the recovery room they hear you got it all, and then they need to come back and maybe get chemotherapy and immunotherapy for a year. They’d ask, “What for? I can’t see anything.”
Dr. Rotow: Exactly. I think there are many advantages to that neoadjuvant component. I think all or many of us now have integrated this into our routine practice. Now the question is, do you need the adjuvant element or not on top? That is challenging because no trial has compared adjuvant to nonadjuvant. I think we all advocate for the need for this trial to answer this in a more randomized, prospective fashion. Of course, that doesn’t help our clinic practice tomorrow when we see a patient.
Dr. West: Or for the next 4 years.
Dr. Rotow: Or for the next 4 years – exactly. There’s going to be the open question of who really needs this? In some sense, we may be guided by the path response during the surgery itself. I think there may be those who claim that if you have a pCR, do you really need additional therapy? We don’t know the answer, but it’s tempting to say we know the outcomes in event-free survival are extremely good with a pCR.
Dr. West: Which is only 20% or 25% of patients, so it’s not most.
Dr. Rotow: It’s not most, but it’s better than the 2% or so with chemotherapy alone. That’s real progress, and it’s nice to have that readout. For that 80% without a pCR, what to do? I suspect there will be variation from provider to provider and from patient to patient, depending on tolerability to prior therapy, the patient’s wishes around the goals of care, and the patient’s risk for autoimmune toxicities.
Maybe there’s a patient with underlying autoimmune disease who’s gotten their neoadjuvant therapy and done well. You don’t want to risk that ongoing risk of exposure. Perhaps a patient with no risk factors who desires very aggressive treatment might be interested in more treatment.
In KEYNOTE-671, I was interested in the PD-L1 subgroups. These did trend the way you expect, with better responses in PD-L1 high, but there were also good outcomes and benefit to immunotherapy with the perioperative strategy in PD-L1–negative patients.
Dr. West: That didn’t really exclude anybody.
Dr. Rotow: It didn’t exclude anybody. In CheckMate 816, everyone benefited, but the benefit was less with those PD-L1–negative patients.
Dr. West: True.
Dr. Rotow: Absent further data to guide me or any prospective data here comparing these strategies, I might lean toward a longer course of immunotherapy in that population in hopes of triggering a response. I suspect that there will be variation from clinician to clinician in that space.
Dr. West: This is a setting where I feel like I have equipoise. I really feel that the incremental benefit is pretty small.
Dr. Rotow: Small. I agree.
Dr. West: It’s, frankly, somewhat dubious. On the other hand, you’re in a situation where if you know that three of four patients will experience a relapse and less-than-amazing outcomes, it’s hard to leave something that’s FDA approved and studied and a well-sanctioned option on the table if this patient may have relapse later.
In the end, I feel like I’d like to offer this and discuss it with all my patients. I think it’s a great place for shared decision-making because if a patient hears about that and decides they’re not interested, I’ll be fine with that. I think that’s a very sensible approach, but I don’t want to make it unilaterally. Other patients may say they want every opportunity, and if it comes back, at least I’ll know I did everything we could.
Dr. Rotow: Exactly. I agree with your statement about equipoise. I truly think that this is present here in the situation, and that there’s room for discussion in both directions with patients.
Now, one caveat I’d like to add to all these data is that the data should not apply to patients with some of our classic nonsmoking-associated driver mutations. This is another piece to the neoadjuvant data that I think is worth commenting on – the need to get appropriate testing before initiation of therapy and the pitfalls of starting this kind of treatment without knowing full biomarker testing. I think that’s something we have to watch for in our clinical practice as well.
Dr. West: Perhaps especially if we’re talking about doing a year of postoperative and someone has an ALK rearrangement or an EGFR mutation and we didn’t know it. That is a group where we’re worried about a rapid transition and potentially prohibitive, even life-threatening, toxicities from not planning in advance for this. This is something you don’t want to give concurrently or one right on top of the other. You don’t want to give immunotherapy and then transition right to targeted therapy. It’s dangerous.
Dr. Rotow: Exactly. The stakes were already high with neoadjuvant alone, but at least you had that gap of the presurgical period, surgical recovery, and then initiation of adjuvant therapy, if needed, or at relapse. With a postoperative long adjuvant period, those stakes are elevated because the immunotherapy exposure continues, so it’s something to be mindful of.
Dr. West: We have a general sense that many, but not all, of the targets that we’re talking about are associated with low benefit from immunotherapy. It’s not that well studied. I think this is another place for individualized discussion of the pros and cons. They were included in the trial, but they probably benefit less.
Dr. Rotow: Exactly. I think with the best established, EGFR and ALK probably are not benefiting much. They were actually included in the trial. Many of the neoadjuvant studies do not allow them to enroll if they’re known. On the other end of that spectrum, I think KRAS is just fine to treat with immunotherapy.
Dr. West: Sure.
Dr. Rotow: It’s an actionable driver. It’s not a traditional nonsmoking-associated driver, and those do just fine.
Dr. West: The studies show that these patients benefit just as much, at least, as the other patients.
Dr. Rotow: Exactly. I would never withhold this form of therapy for a KRAS driver mutation. The others, I think, are still in a gray zone. Depending on the patient demographics and tobacco use, I may elicit more or less caution in that space.
Dr. West: Well, I think we’re going to have much to still tease apart, with room for judgment here without a strong sense of the data telling us exactly what to do.
Dr. Rotow: Exactly.
Dr. West: There’s a large amount of excitement and interest in these new data, but there are still many open questions. I hope we continue to mull it over as we get more data and more insight to shape our plans.
Dr. West is an associate professor at City of Hope Comprehensive Cancer Center in Duarte, Calif., and vice president of network strategy at AccessHope in Los Angeles. Dr. Rotow is the clinical director of the Lowe Center for Thoracic Oncology at the Dana-Farber Cancer Institute in Boston. Dr. West reported conflicts of interest with Ariad/Takeda, Bristol Myers Squibb, Boehringer Ingelheim, Spectrum, AstraZeneca, Celgene, Genentech/Roche, Pfizer, Merck, and Eli Lilly. Dr. Rotow reported conflicts of interest with Genentech, AstraZeneca,Guardant, and Janssen.
A version of this article first appeared on Medscape.com.
This transcript has been edited for clarity.
Dr. West: Here at ASCO 2023 [American Society of Clinical Oncology] in Chicago, we’ve seen some blockbuster presentations in thoracic oncology. Many of these have brought up some important questions about the clinical implications that we need to discuss further.
At ASCO, as well as in the couple or 3 months preceding ASCO, we’ve gotten more and more data on perioperative approaches. Of course, over the past couple of years, we’ve had some new options of postoperative immunotherapy for a year, say, after chemotherapy or possibly after chemotherapy.
We have also had very influential data, such as the CheckMate 816 trial that gave three cycles of chemotherapy with nivolumab vs. chemotherapy alone to patients with stage IB to IIIA disease, but largely, nearly two thirds, with IIIA disease. That showed a very clear improvement in the pathologic complete response (pCR) rate with nivolumab added to chemotherapy and also a highly significant improvement in event-free survival and a strong trend toward improved overall survival. This is FDA approved and has been increasingly adopted, I would say, maybe with some variability by geography and center, but really a good amount of enthusiasm.
Now, we have a bunch of trials that give chemotherapy with immunotherapy. We’ve got the AEGEAN trial with durvalumab. We have Neotorch with chemotherapy and toripalimab. At ASCO 2023, we had a highly prominent presentation of KEYNOTE-671, giving four cycles of chemotherapy with pembrolizumab vs. chemotherapy and placebo.
Then there’s the built-in postoperative component of a year of immunotherapy as well, in all these trials. The data for KEYNOTE-671 look quite good. Of course, the other trials also were significant. I would say the comparator now is not nothing or chemotherapy alone anymore; it’s really against what is the best current standard of care.
It certainly adds some cost, it adds some risk for toxicity, and it adds a year of a patient coming into the clinic and getting IV infusions all this time to get a treatment that the patient has already had for four cycles in most of these trials.
If your cancer is resistant, is there going to be an incremental benefit to giving more of it? What are your thoughts about the risk and benefit? Going to a patient in your own clinic, how are you going to counsel your patients? Will anything change after the presentation of all these data and how you approach preoperatively?
Dr. Rotow: I agree. In some sense, it’s an embarrassment of riches, right?
Dr. West: Yes.
Dr. Rotow: We have so many positive studies looking at perioperative immunotherapy for our patients. They all show improved outcomes, but of course, they all compare with the old control arm of chemotherapy alone in some form, and this is no longer a useful control in this space. The open question is, do you use neoadjuvant, do you use adjuvant, or do you use both?
My high-level takeaway from these data is that the neoadjuvant component appears to be important. I think the overall trend, comparing across studies, of course, is that outcomes seem to be better with the neoadjuvant component. You also get the advantage of potential downstaging and potential greater ease of surgical resection. We know they have lower morbidity resection and shorter surgeries. You can comment on that. You also get your pathologic response data.
Dr. West: You get the feedback.
Dr. Rotow: Exactly.
Dr. West: The deliverability is also a big issue. You know you can much more reliably deliver your intended treatment by doing neoadjuvant followed by surgery.
Dr. Rotow: Exactly.
Dr. West: We know there’s major drop-off if patients have surgery, and in the recovery room they hear you got it all, and then they need to come back and maybe get chemotherapy and immunotherapy for a year. They’d ask, “What for? I can’t see anything.”
Dr. Rotow: Exactly. I think there are many advantages to that neoadjuvant component. I think all or many of us now have integrated this into our routine practice. Now the question is, do you need the adjuvant element or not on top? That is challenging because no trial has compared adjuvant to nonadjuvant. I think we all advocate for the need for this trial to answer this in a more randomized, prospective fashion. Of course, that doesn’t help our clinic practice tomorrow when we see a patient.
Dr. West: Or for the next 4 years.
Dr. Rotow: Or for the next 4 years – exactly. There’s going to be the open question of who really needs this? In some sense, we may be guided by the path response during the surgery itself. I think there may be those who claim that if you have a pCR, do you really need additional therapy? We don’t know the answer, but it’s tempting to say we know the outcomes in event-free survival are extremely good with a pCR.
Dr. West: Which is only 20% or 25% of patients, so it’s not most.
Dr. Rotow: It’s not most, but it’s better than the 2% or so with chemotherapy alone. That’s real progress, and it’s nice to have that readout. For that 80% without a pCR, what to do? I suspect there will be variation from provider to provider and from patient to patient, depending on tolerability to prior therapy, the patient’s wishes around the goals of care, and the patient’s risk for autoimmune toxicities.
Maybe there’s a patient with underlying autoimmune disease who’s gotten their neoadjuvant therapy and done well. You don’t want to risk that ongoing risk of exposure. Perhaps a patient with no risk factors who desires very aggressive treatment might be interested in more treatment.
In KEYNOTE-671, I was interested in the PD-L1 subgroups. These did trend the way you expect, with better responses in PD-L1 high, but there were also good outcomes and benefit to immunotherapy with the perioperative strategy in PD-L1–negative patients.
Dr. West: That didn’t really exclude anybody.
Dr. Rotow: It didn’t exclude anybody. In CheckMate 816, everyone benefited, but the benefit was less with those PD-L1–negative patients.
Dr. West: True.
Dr. Rotow: Absent further data to guide me or any prospective data here comparing these strategies, I might lean toward a longer course of immunotherapy in that population in hopes of triggering a response. I suspect that there will be variation from clinician to clinician in that space.
Dr. West: This is a setting where I feel like I have equipoise. I really feel that the incremental benefit is pretty small.
Dr. Rotow: Small. I agree.
Dr. West: It’s, frankly, somewhat dubious. On the other hand, you’re in a situation where if you know that three of four patients will experience a relapse and less-than-amazing outcomes, it’s hard to leave something that’s FDA approved and studied and a well-sanctioned option on the table if this patient may have relapse later.
In the end, I feel like I’d like to offer this and discuss it with all my patients. I think it’s a great place for shared decision-making because if a patient hears about that and decides they’re not interested, I’ll be fine with that. I think that’s a very sensible approach, but I don’t want to make it unilaterally. Other patients may say they want every opportunity, and if it comes back, at least I’ll know I did everything we could.
Dr. Rotow: Exactly. I agree with your statement about equipoise. I truly think that this is present here in the situation, and that there’s room for discussion in both directions with patients.
Now, one caveat I’d like to add to all these data is that the data should not apply to patients with some of our classic nonsmoking-associated driver mutations. This is another piece to the neoadjuvant data that I think is worth commenting on – the need to get appropriate testing before initiation of therapy and the pitfalls of starting this kind of treatment without knowing full biomarker testing. I think that’s something we have to watch for in our clinical practice as well.
Dr. West: Perhaps especially if we’re talking about doing a year of postoperative and someone has an ALK rearrangement or an EGFR mutation and we didn’t know it. That is a group where we’re worried about a rapid transition and potentially prohibitive, even life-threatening, toxicities from not planning in advance for this. This is something you don’t want to give concurrently or one right on top of the other. You don’t want to give immunotherapy and then transition right to targeted therapy. It’s dangerous.
Dr. Rotow: Exactly. The stakes were already high with neoadjuvant alone, but at least you had that gap of the presurgical period, surgical recovery, and then initiation of adjuvant therapy, if needed, or at relapse. With a postoperative long adjuvant period, those stakes are elevated because the immunotherapy exposure continues, so it’s something to be mindful of.
Dr. West: We have a general sense that many, but not all, of the targets that we’re talking about are associated with low benefit from immunotherapy. It’s not that well studied. I think this is another place for individualized discussion of the pros and cons. They were included in the trial, but they probably benefit less.
Dr. Rotow: Exactly. I think with the best established, EGFR and ALK probably are not benefiting much. They were actually included in the trial. Many of the neoadjuvant studies do not allow them to enroll if they’re known. On the other end of that spectrum, I think KRAS is just fine to treat with immunotherapy.
Dr. West: Sure.
Dr. Rotow: It’s an actionable driver. It’s not a traditional nonsmoking-associated driver, and those do just fine.
Dr. West: The studies show that these patients benefit just as much, at least, as the other patients.
Dr. Rotow: Exactly. I would never withhold this form of therapy for a KRAS driver mutation. The others, I think, are still in a gray zone. Depending on the patient demographics and tobacco use, I may elicit more or less caution in that space.
Dr. West: Well, I think we’re going to have much to still tease apart, with room for judgment here without a strong sense of the data telling us exactly what to do.
Dr. Rotow: Exactly.
Dr. West: There’s a large amount of excitement and interest in these new data, but there are still many open questions. I hope we continue to mull it over as we get more data and more insight to shape our plans.
Dr. West is an associate professor at City of Hope Comprehensive Cancer Center in Duarte, Calif., and vice president of network strategy at AccessHope in Los Angeles. Dr. Rotow is the clinical director of the Lowe Center for Thoracic Oncology at the Dana-Farber Cancer Institute in Boston. Dr. West reported conflicts of interest with Ariad/Takeda, Bristol Myers Squibb, Boehringer Ingelheim, Spectrum, AstraZeneca, Celgene, Genentech/Roche, Pfizer, Merck, and Eli Lilly. Dr. Rotow reported conflicts of interest with Genentech, AstraZeneca,Guardant, and Janssen.
A version of this article first appeared on Medscape.com.
FROM ASCO 2023
PRISm and nonspecific pattern: New insights in lung testing interpretation
The recent statement on interpretive strategies for lung testing uses the acronym PRISm for preserved ratio impaired spirometry. PRISm identifies patients with a normal forced expiratory volume in 1 second/forced vital capacity ratio but abnormal FEV1 and/or FVC (usually both). Most medical students are taught to call this a “restrictive pattern,” and every first-year pulmonary fellow orders full lung volumes when they see it. If total lung capacity (TLC) is normal, PRISm becomes the nonspecific pattern. If TLC is low, then the patient has “true” restriction, and if it’s elevated, then hyperinflation may be present.
The traditional classification scheme for basic spirometry interpretation (normal, restricted, obstructed, or mixed) is simple and conceptually clear. It turns out that many with this pattern won’t have an abnormal TLC, so the name is, in some ways, a misnomer and can be misleading. Enter PRISm, a more descriptive and inclusive term. The phrase also lends itself to a phonetic acronym that is fun to say, easy to remember, and likely to catch on with learners.
Information on occurrence and clinical behavior comes from large cohorts with basic spirometry, but without full lung volumes because PRISm no longer applies once TLC is determined. As may be expected, prevalence varies by the population studied. Estimates for general populations have been in the 7%-12% range; however, one study examining a database of patients with clinical spirometry referrals found a prevalence of 22.3%. Rates may be far higher in low- and middle-income countries. Identified risk factors include sex, tobacco use, and body mass index; the presence of PRISm is associated with respiratory symptoms and mortality. Thus, PRISm is common and it matters.
Along with PRISm, the nonspecific pattern is a new addition, if not a new concept, to the 2022 interpretative strategies statement. As with PRISm, the title is necessarily broad, though far less imaginative. Defined by reductions in FEV1 and FVC and a normal TLC, the nonspecific pattern has classically been considered a marker of early airway disease. The idea is that early, heterogeneous closure of distal segments of the bronchial tree can reduce total volume during a forced expiration before affecting the FEV1/FVC. The fact that the TLC is not a forced maneuver means there is proportionately less effect from more collapsible/susceptible smaller units. More recent data suggest that there are additional causes.
Because the nonspecific pattern requires full lung volumes, we have less population-level data than for PRISm. Estimated prevalence is approximately 9.5% in patients with complete test results. The two most common causes are obesity and airway obstruction, and the pattern is relatively stable over time. Notably, an increase in specific airway resistance or TLC minus alveolar volume difference predicts progression to frank obstruction on spirometry.
The physiologic changes that obesity inflicts on the lung have been well described. Patients with obesity breathe at lower lung volumes and are therefore susceptible to small airway closure at rest and during forced expiration. There is no doubt that the increased recognition of PRISm and the nonspecific pattern is in part related to the worldwide rise in obesity rates.
Key takeaways
In summary, PRISm and the nonspecific pattern are now part of the classification scheme we use for spirometry and full lung volumes, respectively. They should be included in interpretations given their diagnostic and predictive value. Airway disease and obesity are common causes and often coexist with either pattern. Many will not have a true, restrictive lung deficit, and a reductionist approach to interpretation is likely to lead to erroneous diagnoses. There were many important updates included in the 2022 iteration on lung testing interpretation that should not fly under the radar.
Dr. Holley is professor of medicine at Uniformed Services University in Bethesda, Md., and a pulmonary/sleep and critical care medicine physician at MedStar Washington Hospital Center in Washington. He disclosed ties with CHEST College, Metapharm, and WebMD.
A version of this article appeared on Medscape.com.
The recent statement on interpretive strategies for lung testing uses the acronym PRISm for preserved ratio impaired spirometry. PRISm identifies patients with a normal forced expiratory volume in 1 second/forced vital capacity ratio but abnormal FEV1 and/or FVC (usually both). Most medical students are taught to call this a “restrictive pattern,” and every first-year pulmonary fellow orders full lung volumes when they see it. If total lung capacity (TLC) is normal, PRISm becomes the nonspecific pattern. If TLC is low, then the patient has “true” restriction, and if it’s elevated, then hyperinflation may be present.
The traditional classification scheme for basic spirometry interpretation (normal, restricted, obstructed, or mixed) is simple and conceptually clear. It turns out that many with this pattern won’t have an abnormal TLC, so the name is, in some ways, a misnomer and can be misleading. Enter PRISm, a more descriptive and inclusive term. The phrase also lends itself to a phonetic acronym that is fun to say, easy to remember, and likely to catch on with learners.
Information on occurrence and clinical behavior comes from large cohorts with basic spirometry, but without full lung volumes because PRISm no longer applies once TLC is determined. As may be expected, prevalence varies by the population studied. Estimates for general populations have been in the 7%-12% range; however, one study examining a database of patients with clinical spirometry referrals found a prevalence of 22.3%. Rates may be far higher in low- and middle-income countries. Identified risk factors include sex, tobacco use, and body mass index; the presence of PRISm is associated with respiratory symptoms and mortality. Thus, PRISm is common and it matters.
Along with PRISm, the nonspecific pattern is a new addition, if not a new concept, to the 2022 interpretative strategies statement. As with PRISm, the title is necessarily broad, though far less imaginative. Defined by reductions in FEV1 and FVC and a normal TLC, the nonspecific pattern has classically been considered a marker of early airway disease. The idea is that early, heterogeneous closure of distal segments of the bronchial tree can reduce total volume during a forced expiration before affecting the FEV1/FVC. The fact that the TLC is not a forced maneuver means there is proportionately less effect from more collapsible/susceptible smaller units. More recent data suggest that there are additional causes.
Because the nonspecific pattern requires full lung volumes, we have less population-level data than for PRISm. Estimated prevalence is approximately 9.5% in patients with complete test results. The two most common causes are obesity and airway obstruction, and the pattern is relatively stable over time. Notably, an increase in specific airway resistance or TLC minus alveolar volume difference predicts progression to frank obstruction on spirometry.
The physiologic changes that obesity inflicts on the lung have been well described. Patients with obesity breathe at lower lung volumes and are therefore susceptible to small airway closure at rest and during forced expiration. There is no doubt that the increased recognition of PRISm and the nonspecific pattern is in part related to the worldwide rise in obesity rates.
Key takeaways
In summary, PRISm and the nonspecific pattern are now part of the classification scheme we use for spirometry and full lung volumes, respectively. They should be included in interpretations given their diagnostic and predictive value. Airway disease and obesity are common causes and often coexist with either pattern. Many will not have a true, restrictive lung deficit, and a reductionist approach to interpretation is likely to lead to erroneous diagnoses. There were many important updates included in the 2022 iteration on lung testing interpretation that should not fly under the radar.
Dr. Holley is professor of medicine at Uniformed Services University in Bethesda, Md., and a pulmonary/sleep and critical care medicine physician at MedStar Washington Hospital Center in Washington. He disclosed ties with CHEST College, Metapharm, and WebMD.
A version of this article appeared on Medscape.com.
The recent statement on interpretive strategies for lung testing uses the acronym PRISm for preserved ratio impaired spirometry. PRISm identifies patients with a normal forced expiratory volume in 1 second/forced vital capacity ratio but abnormal FEV1 and/or FVC (usually both). Most medical students are taught to call this a “restrictive pattern,” and every first-year pulmonary fellow orders full lung volumes when they see it. If total lung capacity (TLC) is normal, PRISm becomes the nonspecific pattern. If TLC is low, then the patient has “true” restriction, and if it’s elevated, then hyperinflation may be present.
The traditional classification scheme for basic spirometry interpretation (normal, restricted, obstructed, or mixed) is simple and conceptually clear. It turns out that many with this pattern won’t have an abnormal TLC, so the name is, in some ways, a misnomer and can be misleading. Enter PRISm, a more descriptive and inclusive term. The phrase also lends itself to a phonetic acronym that is fun to say, easy to remember, and likely to catch on with learners.
Information on occurrence and clinical behavior comes from large cohorts with basic spirometry, but without full lung volumes because PRISm no longer applies once TLC is determined. As may be expected, prevalence varies by the population studied. Estimates for general populations have been in the 7%-12% range; however, one study examining a database of patients with clinical spirometry referrals found a prevalence of 22.3%. Rates may be far higher in low- and middle-income countries. Identified risk factors include sex, tobacco use, and body mass index; the presence of PRISm is associated with respiratory symptoms and mortality. Thus, PRISm is common and it matters.
Along with PRISm, the nonspecific pattern is a new addition, if not a new concept, to the 2022 interpretative strategies statement. As with PRISm, the title is necessarily broad, though far less imaginative. Defined by reductions in FEV1 and FVC and a normal TLC, the nonspecific pattern has classically been considered a marker of early airway disease. The idea is that early, heterogeneous closure of distal segments of the bronchial tree can reduce total volume during a forced expiration before affecting the FEV1/FVC. The fact that the TLC is not a forced maneuver means there is proportionately less effect from more collapsible/susceptible smaller units. More recent data suggest that there are additional causes.
Because the nonspecific pattern requires full lung volumes, we have less population-level data than for PRISm. Estimated prevalence is approximately 9.5% in patients with complete test results. The two most common causes are obesity and airway obstruction, and the pattern is relatively stable over time. Notably, an increase in specific airway resistance or TLC minus alveolar volume difference predicts progression to frank obstruction on spirometry.
The physiologic changes that obesity inflicts on the lung have been well described. Patients with obesity breathe at lower lung volumes and are therefore susceptible to small airway closure at rest and during forced expiration. There is no doubt that the increased recognition of PRISm and the nonspecific pattern is in part related to the worldwide rise in obesity rates.
Key takeaways
In summary, PRISm and the nonspecific pattern are now part of the classification scheme we use for spirometry and full lung volumes, respectively. They should be included in interpretations given their diagnostic and predictive value. Airway disease and obesity are common causes and often coexist with either pattern. Many will not have a true, restrictive lung deficit, and a reductionist approach to interpretation is likely to lead to erroneous diagnoses. There were many important updates included in the 2022 iteration on lung testing interpretation that should not fly under the radar.
Dr. Holley is professor of medicine at Uniformed Services University in Bethesda, Md., and a pulmonary/sleep and critical care medicine physician at MedStar Washington Hospital Center in Washington. He disclosed ties with CHEST College, Metapharm, and WebMD.
A version of this article appeared on Medscape.com.
A new and completely different pain medicine
This transcript has been edited for clarity.
When you stub your toe or get a paper cut on your finger, you feel the pain in that part of your body. It feels like the pain is coming from that place. But, of course, that’s not really what is happening. Pain doesn’t really happen in your toe or your finger. It happens in your brain.
It’s a game of telephone, really. The afferent nerve fiber detects the noxious stimulus, passing that signal to the second-order neuron in the dorsal root ganglia of the spinal cord, which runs it up to the thalamus to be passed to the third-order neuron which brings it to the cortex for localization and conscious perception. It’s not even a very good game of telephone. It takes about 100 ms for a pain signal to get from the hand to the brain – longer from the feet, given the greater distance. You see your foot hit the corner of the coffee table and have just enough time to think: “Oh no!” before the pain hits.
Given the Rube Goldberg nature of the process, it would seem like there are any number of places we could stop pain sensation. And sure, local anesthetics at the site of injury, or even spinal anesthetics, are powerful – if temporary and hard to administer – solutions to acute pain.
But in our everyday armamentarium, let’s be honest – we essentially have three options: opiates and opioids, which activate the mu-receptors in the brain to dull pain (and cause a host of other nasty side effects); NSAIDs, which block prostaglandin synthesis and thus limit the ability for pain-conducting neurons to get excited; and acetaminophen, which, despite being used for a century, is poorly understood.
But
If you were to zoom in on the connection between that first afferent pain fiber and the secondary nerve in the spinal cord dorsal root ganglion, you would see a receptor called Nav1.8, a voltage-gated sodium channel.
This receptor is a key part of the apparatus that passes information from nerve 1 to nerve 2, but only for fibers that transmit pain signals. In fact, humans with mutations in this receptor that leave it always in the “open” state have a severe pain syndrome. Blocking the receptor, therefore, might reduce pain.
In preclinical work, researchers identified VX-548, which doesn’t have a brand name yet, as a potent blocker of that channel even in nanomolar concentrations. Importantly, the compound was highly selective for that particular channel – about 30,000 times more selective than it was for the other sodium channels in that family.
Of course, a highly selective and specific drug does not a blockbuster analgesic make. To determine how this drug would work on humans in pain, they turned to two populations: 303 individuals undergoing abdominoplasty and 274 undergoing bunionectomy, as reported in a new paper in the New England Journal of Medicine.
I know this seems a bit random, but abdominoplasty is quite painful and a good model for soft-tissue pain. Bunionectomy is also quite a painful procedure and a useful model of bone pain. After the surgeries, patients were randomized to several different doses of VX-548, hydrocodone plus acetaminophen, or placebo for 48 hours.
At 19 time points over that 48-hour period, participants were asked to rate their pain on a scale from 0 to 10. The primary outcome was the cumulative pain experienced over the 48 hours. So, higher pain would be worse here, but longer duration of pain would also be worse.
The story of the study is really told in this chart.
Yes, those assigned to the highest dose of VX-548 had a statistically significant lower cumulative amount of pain in the 48 hours after surgery. But the picture is really worth more than the stats here. You can see that the onset of pain relief was fairly quick, and that pain relief was sustained over time. You can also see that this is not a miracle drug. Pain scores were a bit better 48 hours out, but only by about a point and a half.
Placebo isn’t really the fair comparison here; few of us treat our postabdominoplasty patients with placebo, after all. The authors do not formally compare the effect of VX-548 with that of the opioid hydrocodone, for instance. But that doesn’t stop us.
This graph, which I put together from data in the paper, shows pain control across the four randomization categories, with higher numbers indicating more (cumulative) control. While all the active agents do a bit better than placebo, VX-548 at the higher dose appears to do the best. But I should note that 5 mg of hydrocodone may not be an adequate dose for most people.
Yes, I would really have killed for an NSAID arm in this trial. Its absence, given that NSAIDs are a staple of postoperative care, is ... well, let’s just say, notable.
Although not a pain-destroying machine, VX-548 has some other things to recommend it. The receptor is really not found in the brain at all, which suggests that the drug should not carry much risk for dependency, though that has not been formally studied.
The side effects were generally mild – headache was the most common – and less prevalent than what you see even in the placebo arm.
Perhaps most notable is the fact that the rate of discontinuation of the study drug was lowest in the VX-548 arm. Patients could stop taking the pill they were assigned for any reason, ranging from perceived lack of efficacy to side effects. A low discontinuation rate indicates to me a sort of “voting with your feet” that suggests this might be a well-tolerated and reasonably effective drug.
VX-548 isn’t on the market yet; phase 3 trials are ongoing. But whether it is this particular drug or another in this class, I’m happy to see researchers trying to find new ways to target that most primeval form of suffering: pain.
Dr. Wilson is an associate professor of medicine and public health and director of Yale’s Clinical and Translational Research Accelerator, New Haven, Conn. He disclosed no relevant financial relationships.
A version of this article appeared on Medscape.com.
This transcript has been edited for clarity.
When you stub your toe or get a paper cut on your finger, you feel the pain in that part of your body. It feels like the pain is coming from that place. But, of course, that’s not really what is happening. Pain doesn’t really happen in your toe or your finger. It happens in your brain.
It’s a game of telephone, really. The afferent nerve fiber detects the noxious stimulus, passing that signal to the second-order neuron in the dorsal root ganglia of the spinal cord, which runs it up to the thalamus to be passed to the third-order neuron which brings it to the cortex for localization and conscious perception. It’s not even a very good game of telephone. It takes about 100 ms for a pain signal to get from the hand to the brain – longer from the feet, given the greater distance. You see your foot hit the corner of the coffee table and have just enough time to think: “Oh no!” before the pain hits.
Given the Rube Goldberg nature of the process, it would seem like there are any number of places we could stop pain sensation. And sure, local anesthetics at the site of injury, or even spinal anesthetics, are powerful – if temporary and hard to administer – solutions to acute pain.
But in our everyday armamentarium, let’s be honest – we essentially have three options: opiates and opioids, which activate the mu-receptors in the brain to dull pain (and cause a host of other nasty side effects); NSAIDs, which block prostaglandin synthesis and thus limit the ability for pain-conducting neurons to get excited; and acetaminophen, which, despite being used for a century, is poorly understood.
But
If you were to zoom in on the connection between that first afferent pain fiber and the secondary nerve in the spinal cord dorsal root ganglion, you would see a receptor called Nav1.8, a voltage-gated sodium channel.
This receptor is a key part of the apparatus that passes information from nerve 1 to nerve 2, but only for fibers that transmit pain signals. In fact, humans with mutations in this receptor that leave it always in the “open” state have a severe pain syndrome. Blocking the receptor, therefore, might reduce pain.
In preclinical work, researchers identified VX-548, which doesn’t have a brand name yet, as a potent blocker of that channel even in nanomolar concentrations. Importantly, the compound was highly selective for that particular channel – about 30,000 times more selective than it was for the other sodium channels in that family.
Of course, a highly selective and specific drug does not a blockbuster analgesic make. To determine how this drug would work on humans in pain, they turned to two populations: 303 individuals undergoing abdominoplasty and 274 undergoing bunionectomy, as reported in a new paper in the New England Journal of Medicine.
I know this seems a bit random, but abdominoplasty is quite painful and a good model for soft-tissue pain. Bunionectomy is also quite a painful procedure and a useful model of bone pain. After the surgeries, patients were randomized to several different doses of VX-548, hydrocodone plus acetaminophen, or placebo for 48 hours.
At 19 time points over that 48-hour period, participants were asked to rate their pain on a scale from 0 to 10. The primary outcome was the cumulative pain experienced over the 48 hours. So, higher pain would be worse here, but longer duration of pain would also be worse.
The story of the study is really told in this chart.
Yes, those assigned to the highest dose of VX-548 had a statistically significant lower cumulative amount of pain in the 48 hours after surgery. But the picture is really worth more than the stats here. You can see that the onset of pain relief was fairly quick, and that pain relief was sustained over time. You can also see that this is not a miracle drug. Pain scores were a bit better 48 hours out, but only by about a point and a half.
Placebo isn’t really the fair comparison here; few of us treat our postabdominoplasty patients with placebo, after all. The authors do not formally compare the effect of VX-548 with that of the opioid hydrocodone, for instance. But that doesn’t stop us.
This graph, which I put together from data in the paper, shows pain control across the four randomization categories, with higher numbers indicating more (cumulative) control. While all the active agents do a bit better than placebo, VX-548 at the higher dose appears to do the best. But I should note that 5 mg of hydrocodone may not be an adequate dose for most people.
Yes, I would really have killed for an NSAID arm in this trial. Its absence, given that NSAIDs are a staple of postoperative care, is ... well, let’s just say, notable.
Although not a pain-destroying machine, VX-548 has some other things to recommend it. The receptor is really not found in the brain at all, which suggests that the drug should not carry much risk for dependency, though that has not been formally studied.
The side effects were generally mild – headache was the most common – and less prevalent than what you see even in the placebo arm.
Perhaps most notable is the fact that the rate of discontinuation of the study drug was lowest in the VX-548 arm. Patients could stop taking the pill they were assigned for any reason, ranging from perceived lack of efficacy to side effects. A low discontinuation rate indicates to me a sort of “voting with your feet” that suggests this might be a well-tolerated and reasonably effective drug.
VX-548 isn’t on the market yet; phase 3 trials are ongoing. But whether it is this particular drug or another in this class, I’m happy to see researchers trying to find new ways to target that most primeval form of suffering: pain.
Dr. Wilson is an associate professor of medicine and public health and director of Yale’s Clinical and Translational Research Accelerator, New Haven, Conn. He disclosed no relevant financial relationships.
A version of this article appeared on Medscape.com.
This transcript has been edited for clarity.
When you stub your toe or get a paper cut on your finger, you feel the pain in that part of your body. It feels like the pain is coming from that place. But, of course, that’s not really what is happening. Pain doesn’t really happen in your toe or your finger. It happens in your brain.
It’s a game of telephone, really. The afferent nerve fiber detects the noxious stimulus, passing that signal to the second-order neuron in the dorsal root ganglia of the spinal cord, which runs it up to the thalamus to be passed to the third-order neuron which brings it to the cortex for localization and conscious perception. It’s not even a very good game of telephone. It takes about 100 ms for a pain signal to get from the hand to the brain – longer from the feet, given the greater distance. You see your foot hit the corner of the coffee table and have just enough time to think: “Oh no!” before the pain hits.
Given the Rube Goldberg nature of the process, it would seem like there are any number of places we could stop pain sensation. And sure, local anesthetics at the site of injury, or even spinal anesthetics, are powerful – if temporary and hard to administer – solutions to acute pain.
But in our everyday armamentarium, let’s be honest – we essentially have three options: opiates and opioids, which activate the mu-receptors in the brain to dull pain (and cause a host of other nasty side effects); NSAIDs, which block prostaglandin synthesis and thus limit the ability for pain-conducting neurons to get excited; and acetaminophen, which, despite being used for a century, is poorly understood.
But
If you were to zoom in on the connection between that first afferent pain fiber and the secondary nerve in the spinal cord dorsal root ganglion, you would see a receptor called Nav1.8, a voltage-gated sodium channel.
This receptor is a key part of the apparatus that passes information from nerve 1 to nerve 2, but only for fibers that transmit pain signals. In fact, humans with mutations in this receptor that leave it always in the “open” state have a severe pain syndrome. Blocking the receptor, therefore, might reduce pain.
In preclinical work, researchers identified VX-548, which doesn’t have a brand name yet, as a potent blocker of that channel even in nanomolar concentrations. Importantly, the compound was highly selective for that particular channel – about 30,000 times more selective than it was for the other sodium channels in that family.
Of course, a highly selective and specific drug does not a blockbuster analgesic make. To determine how this drug would work on humans in pain, they turned to two populations: 303 individuals undergoing abdominoplasty and 274 undergoing bunionectomy, as reported in a new paper in the New England Journal of Medicine.
I know this seems a bit random, but abdominoplasty is quite painful and a good model for soft-tissue pain. Bunionectomy is also quite a painful procedure and a useful model of bone pain. After the surgeries, patients were randomized to several different doses of VX-548, hydrocodone plus acetaminophen, or placebo for 48 hours.
At 19 time points over that 48-hour period, participants were asked to rate their pain on a scale from 0 to 10. The primary outcome was the cumulative pain experienced over the 48 hours. So, higher pain would be worse here, but longer duration of pain would also be worse.
The story of the study is really told in this chart.
Yes, those assigned to the highest dose of VX-548 had a statistically significant lower cumulative amount of pain in the 48 hours after surgery. But the picture is really worth more than the stats here. You can see that the onset of pain relief was fairly quick, and that pain relief was sustained over time. You can also see that this is not a miracle drug. Pain scores were a bit better 48 hours out, but only by about a point and a half.
Placebo isn’t really the fair comparison here; few of us treat our postabdominoplasty patients with placebo, after all. The authors do not formally compare the effect of VX-548 with that of the opioid hydrocodone, for instance. But that doesn’t stop us.
This graph, which I put together from data in the paper, shows pain control across the four randomization categories, with higher numbers indicating more (cumulative) control. While all the active agents do a bit better than placebo, VX-548 at the higher dose appears to do the best. But I should note that 5 mg of hydrocodone may not be an adequate dose for most people.
Yes, I would really have killed for an NSAID arm in this trial. Its absence, given that NSAIDs are a staple of postoperative care, is ... well, let’s just say, notable.
Although not a pain-destroying machine, VX-548 has some other things to recommend it. The receptor is really not found in the brain at all, which suggests that the drug should not carry much risk for dependency, though that has not been formally studied.
The side effects were generally mild – headache was the most common – and less prevalent than what you see even in the placebo arm.
Perhaps most notable is the fact that the rate of discontinuation of the study drug was lowest in the VX-548 arm. Patients could stop taking the pill they were assigned for any reason, ranging from perceived lack of efficacy to side effects. A low discontinuation rate indicates to me a sort of “voting with your feet” that suggests this might be a well-tolerated and reasonably effective drug.
VX-548 isn’t on the market yet; phase 3 trials are ongoing. But whether it is this particular drug or another in this class, I’m happy to see researchers trying to find new ways to target that most primeval form of suffering: pain.
Dr. Wilson is an associate professor of medicine and public health and director of Yale’s Clinical and Translational Research Accelerator, New Haven, Conn. He disclosed no relevant financial relationships.
A version of this article appeared on Medscape.com.
Prescribing lifestyle changes: When medicine isn’t enough
In psychiatry, patients come to us with their list of symptoms, often a diagnosis they’ve made themselves, and the expectation that they will be given medication to fix their problem. Their diagnoses are often right on target – people often know if they are depressed or anxious, and Doctor Google may provide useful information.
Sometimes they want a specific medication, one they saw in a TV ad, or one that helped them in the past or has helped someone they know. As psychiatrists have focused more on their strengths as psychopharmacologists and less on psychotherapy, it gets easy for both the patient and the doctor to look to medication, cocktails, and titration as the only thing we do.
“My medicine stopped working,” is a line I commonly hear. Often the patient is on a complicated regimen that has been serving them well, and it seems unlikely that the five psychotropic medications they are taking have suddenly “stopped working.” An obvious exception is the SSRI “poop out” that can occur 6-12 months or more after beginning treatment. In addition, it’s important to make sure patients are taking their medications as prescribed, and that the generic formulations have not changed.
But as rates of mental illness increase, some of it spurred on by difficult times,
This is not to devalue our medications, but to help the patient see symptoms as having multiple factors and give them some means to intervene, in addition to medications. At the beginning of therapy, it is important to “prescribe” lifestyle changes that will facilitate the best possible outcomes.
Nonpharmaceutical prescriptions
Early in my career, people with alcohol use problems were told they needed to be substance free before they were candidates for antidepressants. While we no longer do that, it is still important to emphasize abstinence from addictive substances, and to recommend specific treatment when necessary.
Patients are often reluctant to see their use of alcohol, marijuana (it’s medical! It’s part of wellness!), or their pain medications as part of the problem, and this can be difficult. There have been times, after multiple medications have failed to help their symptoms, when I have said, “If you don’t get treatment for this problem, I am not going to be able to help you feel better” and that has been motivating for the patient.
There are other “prescriptions” to write. Regular sleep is essential for people with mood disorders, and this can be difficult for many patients, especially those who do shift work, or who have regular disruptions to their sleep from noise, pets, and children. Exercise is wonderful for the cardiovascular system, calms anxiety, and maintains strength, endurance, mobility, and quality of life as people age. But it can be a hard sell to people in a mental health crisis.
Nature is healing, and sunshine helps with maintaining circadian rhythms. For those who don’t exercise, I often “prescribe” 20 to 30 minutes a day of walking, preferably outside, during daylight hours, in a park or natural setting. For people with anxiety, it is important to check their caffeine consumption and to suggest ways to moderate it – moving to decaffeinated beverages or titrating down by mixing decaf with caffeinated.
Meditation is something that many people find helpful. For anxious people, it can be very difficult, and I will prescribe a specific instructional video course that I like on the well-being app InsightTimer – Sarah Blondin’s Learn How to Meditate in Seven Days. The sessions are approximately 10 minutes long, and that seems like the right amount of time for a beginner.
When people are very ill and don’t want to go into the hospital, I talk with them about things that happen in the hospital that are helpful, things they can try to mimic at home. In the hospital, patients don’t go to work, they don’t spend hours a day on the computer, and they are given a pass from dealing with the routine stresses of daily life.
I ask them to take time off work, to avoid as much stress as possible, to spend time with loved ones who give them comfort, and to avoid the people who leave them feeling drained or distressed. I ask them to engage in activities they find healing, to eat well, exercise, and avoid social media. In the hospital, I emphasize, they wake patients up in the morning, ask them to get out of bed and engage in therapeutic activities. They are fed and kept from intoxicants.
When it comes to nutrition, we know so little about how food affects mental health. I feel like it can’t hurt to ask people to avoid fast foods, soft drinks, and processed foods, and so I do.
And what about compliance? Of course, not everyone complies; not everyone is interested in making changes and these can be hard changes. I’ve recently started to recommend the book Atomic Habits by James Clear. Sometimes a bit of motivational interviewing can also be helpful in getting people to look at slowly moving toward making changes.
In prescribing lifestyle changes, it is important to offer most of these changes as suggestions, not as things we insist on, or that will leave the patient feeling ashamed if he doesn’t follow through. They should be discussed early in treatment so that patients don’t feel blamed for their illness or relapses. As with all the things we prescribe, some of these behavior changes help some of the people some of the time. Suggesting them, however, makes the strong statement that treating psychiatric disorders can be about more than passively swallowing a pill.
Dr. Miller is a coauthor of “Committed: The Battle Over Involuntary Psychiatric Care” (Baltimore: Johns Hopkins University Press, 2016). She has a private practice and is an assistant professor of psychiatry and behavioral sciences at Johns Hopkins University, Baltimore. She disclosed no relevant conflicts of interest.
In psychiatry, patients come to us with their list of symptoms, often a diagnosis they’ve made themselves, and the expectation that they will be given medication to fix their problem. Their diagnoses are often right on target – people often know if they are depressed or anxious, and Doctor Google may provide useful information.
Sometimes they want a specific medication, one they saw in a TV ad, or one that helped them in the past or has helped someone they know. As psychiatrists have focused more on their strengths as psychopharmacologists and less on psychotherapy, it gets easy for both the patient and the doctor to look to medication, cocktails, and titration as the only thing we do.
“My medicine stopped working,” is a line I commonly hear. Often the patient is on a complicated regimen that has been serving them well, and it seems unlikely that the five psychotropic medications they are taking have suddenly “stopped working.” An obvious exception is the SSRI “poop out” that can occur 6-12 months or more after beginning treatment. In addition, it’s important to make sure patients are taking their medications as prescribed, and that the generic formulations have not changed.
But as rates of mental illness increase, some of it spurred on by difficult times,
This is not to devalue our medications, but to help the patient see symptoms as having multiple factors and give them some means to intervene, in addition to medications. At the beginning of therapy, it is important to “prescribe” lifestyle changes that will facilitate the best possible outcomes.
Nonpharmaceutical prescriptions
Early in my career, people with alcohol use problems were told they needed to be substance free before they were candidates for antidepressants. While we no longer do that, it is still important to emphasize abstinence from addictive substances, and to recommend specific treatment when necessary.
Patients are often reluctant to see their use of alcohol, marijuana (it’s medical! It’s part of wellness!), or their pain medications as part of the problem, and this can be difficult. There have been times, after multiple medications have failed to help their symptoms, when I have said, “If you don’t get treatment for this problem, I am not going to be able to help you feel better” and that has been motivating for the patient.
There are other “prescriptions” to write. Regular sleep is essential for people with mood disorders, and this can be difficult for many patients, especially those who do shift work, or who have regular disruptions to their sleep from noise, pets, and children. Exercise is wonderful for the cardiovascular system, calms anxiety, and maintains strength, endurance, mobility, and quality of life as people age. But it can be a hard sell to people in a mental health crisis.
Nature is healing, and sunshine helps with maintaining circadian rhythms. For those who don’t exercise, I often “prescribe” 20 to 30 minutes a day of walking, preferably outside, during daylight hours, in a park or natural setting. For people with anxiety, it is important to check their caffeine consumption and to suggest ways to moderate it – moving to decaffeinated beverages or titrating down by mixing decaf with caffeinated.
Meditation is something that many people find helpful. For anxious people, it can be very difficult, and I will prescribe a specific instructional video course that I like on the well-being app InsightTimer – Sarah Blondin’s Learn How to Meditate in Seven Days. The sessions are approximately 10 minutes long, and that seems like the right amount of time for a beginner.
When people are very ill and don’t want to go into the hospital, I talk with them about things that happen in the hospital that are helpful, things they can try to mimic at home. In the hospital, patients don’t go to work, they don’t spend hours a day on the computer, and they are given a pass from dealing with the routine stresses of daily life.
I ask them to take time off work, to avoid as much stress as possible, to spend time with loved ones who give them comfort, and to avoid the people who leave them feeling drained or distressed. I ask them to engage in activities they find healing, to eat well, exercise, and avoid social media. In the hospital, I emphasize, they wake patients up in the morning, ask them to get out of bed and engage in therapeutic activities. They are fed and kept from intoxicants.
When it comes to nutrition, we know so little about how food affects mental health. I feel like it can’t hurt to ask people to avoid fast foods, soft drinks, and processed foods, and so I do.
And what about compliance? Of course, not everyone complies; not everyone is interested in making changes and these can be hard changes. I’ve recently started to recommend the book Atomic Habits by James Clear. Sometimes a bit of motivational interviewing can also be helpful in getting people to look at slowly moving toward making changes.
In prescribing lifestyle changes, it is important to offer most of these changes as suggestions, not as things we insist on, or that will leave the patient feeling ashamed if he doesn’t follow through. They should be discussed early in treatment so that patients don’t feel blamed for their illness or relapses. As with all the things we prescribe, some of these behavior changes help some of the people some of the time. Suggesting them, however, makes the strong statement that treating psychiatric disorders can be about more than passively swallowing a pill.
Dr. Miller is a coauthor of “Committed: The Battle Over Involuntary Psychiatric Care” (Baltimore: Johns Hopkins University Press, 2016). She has a private practice and is an assistant professor of psychiatry and behavioral sciences at Johns Hopkins University, Baltimore. She disclosed no relevant conflicts of interest.
In psychiatry, patients come to us with their list of symptoms, often a diagnosis they’ve made themselves, and the expectation that they will be given medication to fix their problem. Their diagnoses are often right on target – people often know if they are depressed or anxious, and Doctor Google may provide useful information.
Sometimes they want a specific medication, one they saw in a TV ad, or one that helped them in the past or has helped someone they know. As psychiatrists have focused more on their strengths as psychopharmacologists and less on psychotherapy, it gets easy for both the patient and the doctor to look to medication, cocktails, and titration as the only thing we do.
“My medicine stopped working,” is a line I commonly hear. Often the patient is on a complicated regimen that has been serving them well, and it seems unlikely that the five psychotropic medications they are taking have suddenly “stopped working.” An obvious exception is the SSRI “poop out” that can occur 6-12 months or more after beginning treatment. In addition, it’s important to make sure patients are taking their medications as prescribed, and that the generic formulations have not changed.
But as rates of mental illness increase, some of it spurred on by difficult times,
This is not to devalue our medications, but to help the patient see symptoms as having multiple factors and give them some means to intervene, in addition to medications. At the beginning of therapy, it is important to “prescribe” lifestyle changes that will facilitate the best possible outcomes.
Nonpharmaceutical prescriptions
Early in my career, people with alcohol use problems were told they needed to be substance free before they were candidates for antidepressants. While we no longer do that, it is still important to emphasize abstinence from addictive substances, and to recommend specific treatment when necessary.
Patients are often reluctant to see their use of alcohol, marijuana (it’s medical! It’s part of wellness!), or their pain medications as part of the problem, and this can be difficult. There have been times, after multiple medications have failed to help their symptoms, when I have said, “If you don’t get treatment for this problem, I am not going to be able to help you feel better” and that has been motivating for the patient.
There are other “prescriptions” to write. Regular sleep is essential for people with mood disorders, and this can be difficult for many patients, especially those who do shift work, or who have regular disruptions to their sleep from noise, pets, and children. Exercise is wonderful for the cardiovascular system, calms anxiety, and maintains strength, endurance, mobility, and quality of life as people age. But it can be a hard sell to people in a mental health crisis.
Nature is healing, and sunshine helps with maintaining circadian rhythms. For those who don’t exercise, I often “prescribe” 20 to 30 minutes a day of walking, preferably outside, during daylight hours, in a park or natural setting. For people with anxiety, it is important to check their caffeine consumption and to suggest ways to moderate it – moving to decaffeinated beverages or titrating down by mixing decaf with caffeinated.
Meditation is something that many people find helpful. For anxious people, it can be very difficult, and I will prescribe a specific instructional video course that I like on the well-being app InsightTimer – Sarah Blondin’s Learn How to Meditate in Seven Days. The sessions are approximately 10 minutes long, and that seems like the right amount of time for a beginner.
When people are very ill and don’t want to go into the hospital, I talk with them about things that happen in the hospital that are helpful, things they can try to mimic at home. In the hospital, patients don’t go to work, they don’t spend hours a day on the computer, and they are given a pass from dealing with the routine stresses of daily life.
I ask them to take time off work, to avoid as much stress as possible, to spend time with loved ones who give them comfort, and to avoid the people who leave them feeling drained or distressed. I ask them to engage in activities they find healing, to eat well, exercise, and avoid social media. In the hospital, I emphasize, they wake patients up in the morning, ask them to get out of bed and engage in therapeutic activities. They are fed and kept from intoxicants.
When it comes to nutrition, we know so little about how food affects mental health. I feel like it can’t hurt to ask people to avoid fast foods, soft drinks, and processed foods, and so I do.
And what about compliance? Of course, not everyone complies; not everyone is interested in making changes and these can be hard changes. I’ve recently started to recommend the book Atomic Habits by James Clear. Sometimes a bit of motivational interviewing can also be helpful in getting people to look at slowly moving toward making changes.
In prescribing lifestyle changes, it is important to offer most of these changes as suggestions, not as things we insist on, or that will leave the patient feeling ashamed if he doesn’t follow through. They should be discussed early in treatment so that patients don’t feel blamed for their illness or relapses. As with all the things we prescribe, some of these behavior changes help some of the people some of the time. Suggesting them, however, makes the strong statement that treating psychiatric disorders can be about more than passively swallowing a pill.
Dr. Miller is a coauthor of “Committed: The Battle Over Involuntary Psychiatric Care” (Baltimore: Johns Hopkins University Press, 2016). She has a private practice and is an assistant professor of psychiatry and behavioral sciences at Johns Hopkins University, Baltimore. She disclosed no relevant conflicts of interest.
Will this trial help solve chronic back pain?
Chronic pain, and back pain in particular, is among the most frequent concerns for patients in the primary care setting. Roughly 8% of adults in the United States say they suffer from chronic low back pain, and many of them say the pain is significant enough to impair their ability to move, work, and otherwise enjoy life. All this, despite decades of research and countless millions in funding to find the optimal approach to treating chronic pain.
As the United States crawls out of the opioid epidemic, a group of pain specialists is hoping to identify effective, personalized approaches to managing back pain. Daniel Clauw, MD, professor of anesthesiology, internal medicine, and psychiatry at the University of Michigan, Ann Arbor, is helping lead the BEST trial. With projected enrollment of nearly 800 patients, BEST will be the largest federally funded clinical trial of interventions to treat chronic low back pain.
In an interview, The interview has been edited for length and clarity.
What are your thoughts on the current state of primary care physicians’ understanding and management of pain?
Primary care physicians need a lot of help in demystifying the diagnosis and treatment of any kind of pain, but back pain is a really good place to start. When it comes to back pain, most primary care physicians are not any more knowledgeable than a layperson.
What has the opioid debacle-cum-tragedy taught you about pain management, particular as regards people with chronic pain?
I don’t feel opioids should ever be used to treat chronic low back pain. The few long-term studies that have been performed using opioids for longer than 3 months suggest that they often make pain worse rather than just failing to make pain better – and we know they are associated with a significantly increased all-cause mortality with increased deaths from myocardial infarction, accidents, and suicides, in addition to overdose.
Given how many patients experience back pain, how did we come to the point at which primary care physicians are so ill equipped?
We’ve had terrible pain curricula in medical schools. To give you an example: I’m one of the leading pain experts in the world and I’m not allowed to teach our medical students their pain curriculum. The students learn about neurophysiology and the anatomy of the nerves, not what’s relevant in pain.
This is notorious in medical school: Curricula are almost impossible to modify and change. So it starts with poor training in medical school. And then, regardless of what education they do or don’t get in medical school, a lot of their education about pain management is through our residencies – mainly in inpatient settings, where you’re really seeing the management of acute pain and not the management of chronic pain.
People get more accustomed to managing acute pain, where opioids are a reasonable option. It’s just that when you start managing subacute or chronic pain, opioids don’t work as well.
The other big problem is that historically, most people trained in medicine think that if you have pain in your elbow, there’s got to be something wrong in your elbow. This third mechanism of pain, central sensitization – or nociplastic pain – the kind of pain that we see in fibromyalgia, headache, and low back pain, where the pain is coming from the brain – that’s confusing to people. People can have pain without any damage or inflammation to that region of the body.
Physicians are trained that if there’s pain, there’s something wrong and we have to do surgery or there’s been some trauma. Most chronic pain is none of that. There’s a big disconnect between how people are trained, and then when they go out and are seeing a tremendous number of people with chronic pain.
What are the different types of pain, and how should they inform clinicians’ understanding about what approaches might work for managing their patients in pain?
The way the central nervous system responds to pain is analogous to the loudness of an electric guitar. You can make an electric guitar louder either by strumming the strings harder or by turning up the amplifier. For many people with fibromyalgia, low back pain, and endometriosis, for example, the problem is really more that the amplifier is turned up too high rather than its being that the guitar is strummed too strongly. That kind of pain where the pain is not due to anatomic damage or inflammation is particularly flummoxing for providers.
Can you explain the design of the new study?
It’s a 13-site study looking at four treatments: enhanced self-care, cognitive-behavioral therapy, physical therapy, and duloxetine. It’s a big precision medicine trial, trying to take everything we’ve learned and putting it all into one big study.
We’re using a SMART design, which randomizes people to two of those treatments, unless they are very much improved from the first treatment. To be eligible for the trial, you have to be able to be randomized to three of the four treatments, and people can’t choose which of the four they get.
We give them one of those treatments for 12 weeks, and at the end of 12 weeks we make the call – “Did you respond or not respond?” – and then we go back to the phenotypic data we collected at the beginning of that trial and say, “What information at baseline that we collected predicts that someone is going to respond better to duloxetine or worse to duloxetine?” And then we create the phenotype that responds best to each of those four treatments.
None of our treatments works so well that someone doesn’t end up getting randomized to a second treatment. About 85% of people so far need a second treatment because they still have enough pain that they want more relief. But the nice thing about that is we’ve already done all the functional brain imaging and all these really expensive and time-consuming things.
We’re hoping to have around 700-800 people total in this trial, which means that around 170 people will get randomized to each of the four initial treatments. No one’s ever done a study that has functional brain imaging and all these other things in it with more than 80 or 100 people. The scale of this is totally unprecedented.
Given that the individual therapies don’t appear to be all that successful on their own, what is your goal?
The primary aim is to match the phenotypic characteristics of a patient with chronic low back pain with treatment response to each of these four treatments. So at the end, we can give clinicians information on which of the patients is going to respond to physical therapy, for instance.
Right now, about one out of three people respond to most treatments for pain. We think by doing a trial like this, we can take treatments that work in one out of three people and make them work in one out of two or two out of three people just by using them in the right people.
How do you differentiate between these types of pain in your study?
We phenotype people by asking them a number of questions. We also do brain imaging, look at their back with MRI, test biomechanics, and then give them four different treatments that we know work in groups of people with low back pain.
We think one of the first parts of the phenotype is, do they have pain just in their back? Or do they have pain in their back plus a lot of other body regions? Because the more body regions that people have pain in, the more likely it is that this is an amplifier problem rather than a guitar problem.
Treatments like physical therapy, surgery, and injections are going to work better for people in whom the pain is a guitar problem rather than an amplifier problem. And drugs like duloxetine, which works in the brain, and cognitive-behavioral therapy are going to work a lot better in the people with pain in multiple sites besides the back.
To pick up on your metaphor, do any symptoms help clinicians differentiate between the guitar and the amplifier?
Sleep problems, fatigue, memory problems, and mood problems are common in patients with chronic pain and are more common with amplifier pain. Because again, those are all central nervous system problems. And so we see that the people that have anxiety, depression, and a lot of distress are more likely to have this kind of pain.
Does medical imaging help?
There’s a terrible relationship between what you see on an MRI of the back and whether someone has pain or how severe the pain is going to be. There’s always going to be individuals that have a lot of anatomic damage who don’t have any pain because they happen to be on the other end of the continuum from fibromyalgia; they’re actually pain-insensitive people.
What are your thoughts about ketamine as a possible treatment for chronic pain?
I have a mentee who’s doing a ketamine trial. We’re doing psilocybin trials in patients with fibromyalgia. Ketamine is such a dirty drug; it has so many different mechanisms of action. It does have some psychedelic effects, but it also is an NMDA blocker. It really has so many different effects.
I think it’s being thrown around like water in settings where we don’t yet know it to be efficacious. Even the data in treatment-refractory depression are pretty weak, but we’re so desperate to do something for those patients. If you’re trying to harness the psychedelic properties of ketamine, I think there’s other psychedelics that are a lot more interesting, which is why we’re using psilocybin for a subset of patients. Most of us in the pain field think that the psychedelics will work best for the people with chronic pain who have a lot of comorbid psychiatric illness, especially the ones with a lot of trauma. These drugs will allow us therapeutically to get at a lot of these patients with the side-by-side psychotherapy that’s being done as people are getting care in the medicalized setting.
Dr. Clauw reported conflicts of interest with Pfizer, Tonix, Theravance, Zynerba, Samumed, Aptinyx, Daiichi Sankyo, Intec, Regeneron, Teva, Lundbeck, Virios, and Cerephex.
A version of this article first appeared on Medscape.com.
Chronic pain, and back pain in particular, is among the most frequent concerns for patients in the primary care setting. Roughly 8% of adults in the United States say they suffer from chronic low back pain, and many of them say the pain is significant enough to impair their ability to move, work, and otherwise enjoy life. All this, despite decades of research and countless millions in funding to find the optimal approach to treating chronic pain.
As the United States crawls out of the opioid epidemic, a group of pain specialists is hoping to identify effective, personalized approaches to managing back pain. Daniel Clauw, MD, professor of anesthesiology, internal medicine, and psychiatry at the University of Michigan, Ann Arbor, is helping lead the BEST trial. With projected enrollment of nearly 800 patients, BEST will be the largest federally funded clinical trial of interventions to treat chronic low back pain.
In an interview, The interview has been edited for length and clarity.
What are your thoughts on the current state of primary care physicians’ understanding and management of pain?
Primary care physicians need a lot of help in demystifying the diagnosis and treatment of any kind of pain, but back pain is a really good place to start. When it comes to back pain, most primary care physicians are not any more knowledgeable than a layperson.
What has the opioid debacle-cum-tragedy taught you about pain management, particular as regards people with chronic pain?
I don’t feel opioids should ever be used to treat chronic low back pain. The few long-term studies that have been performed using opioids for longer than 3 months suggest that they often make pain worse rather than just failing to make pain better – and we know they are associated with a significantly increased all-cause mortality with increased deaths from myocardial infarction, accidents, and suicides, in addition to overdose.
Given how many patients experience back pain, how did we come to the point at which primary care physicians are so ill equipped?
We’ve had terrible pain curricula in medical schools. To give you an example: I’m one of the leading pain experts in the world and I’m not allowed to teach our medical students their pain curriculum. The students learn about neurophysiology and the anatomy of the nerves, not what’s relevant in pain.
This is notorious in medical school: Curricula are almost impossible to modify and change. So it starts with poor training in medical school. And then, regardless of what education they do or don’t get in medical school, a lot of their education about pain management is through our residencies – mainly in inpatient settings, where you’re really seeing the management of acute pain and not the management of chronic pain.
People get more accustomed to managing acute pain, where opioids are a reasonable option. It’s just that when you start managing subacute or chronic pain, opioids don’t work as well.
The other big problem is that historically, most people trained in medicine think that if you have pain in your elbow, there’s got to be something wrong in your elbow. This third mechanism of pain, central sensitization – or nociplastic pain – the kind of pain that we see in fibromyalgia, headache, and low back pain, where the pain is coming from the brain – that’s confusing to people. People can have pain without any damage or inflammation to that region of the body.
Physicians are trained that if there’s pain, there’s something wrong and we have to do surgery or there’s been some trauma. Most chronic pain is none of that. There’s a big disconnect between how people are trained, and then when they go out and are seeing a tremendous number of people with chronic pain.
What are the different types of pain, and how should they inform clinicians’ understanding about what approaches might work for managing their patients in pain?
The way the central nervous system responds to pain is analogous to the loudness of an electric guitar. You can make an electric guitar louder either by strumming the strings harder or by turning up the amplifier. For many people with fibromyalgia, low back pain, and endometriosis, for example, the problem is really more that the amplifier is turned up too high rather than its being that the guitar is strummed too strongly. That kind of pain where the pain is not due to anatomic damage or inflammation is particularly flummoxing for providers.
Can you explain the design of the new study?
It’s a 13-site study looking at four treatments: enhanced self-care, cognitive-behavioral therapy, physical therapy, and duloxetine. It’s a big precision medicine trial, trying to take everything we’ve learned and putting it all into one big study.
We’re using a SMART design, which randomizes people to two of those treatments, unless they are very much improved from the first treatment. To be eligible for the trial, you have to be able to be randomized to three of the four treatments, and people can’t choose which of the four they get.
We give them one of those treatments for 12 weeks, and at the end of 12 weeks we make the call – “Did you respond or not respond?” – and then we go back to the phenotypic data we collected at the beginning of that trial and say, “What information at baseline that we collected predicts that someone is going to respond better to duloxetine or worse to duloxetine?” And then we create the phenotype that responds best to each of those four treatments.
None of our treatments works so well that someone doesn’t end up getting randomized to a second treatment. About 85% of people so far need a second treatment because they still have enough pain that they want more relief. But the nice thing about that is we’ve already done all the functional brain imaging and all these really expensive and time-consuming things.
We’re hoping to have around 700-800 people total in this trial, which means that around 170 people will get randomized to each of the four initial treatments. No one’s ever done a study that has functional brain imaging and all these other things in it with more than 80 or 100 people. The scale of this is totally unprecedented.
Given that the individual therapies don’t appear to be all that successful on their own, what is your goal?
The primary aim is to match the phenotypic characteristics of a patient with chronic low back pain with treatment response to each of these four treatments. So at the end, we can give clinicians information on which of the patients is going to respond to physical therapy, for instance.
Right now, about one out of three people respond to most treatments for pain. We think by doing a trial like this, we can take treatments that work in one out of three people and make them work in one out of two or two out of three people just by using them in the right people.
How do you differentiate between these types of pain in your study?
We phenotype people by asking them a number of questions. We also do brain imaging, look at their back with MRI, test biomechanics, and then give them four different treatments that we know work in groups of people with low back pain.
We think one of the first parts of the phenotype is, do they have pain just in their back? Or do they have pain in their back plus a lot of other body regions? Because the more body regions that people have pain in, the more likely it is that this is an amplifier problem rather than a guitar problem.
Treatments like physical therapy, surgery, and injections are going to work better for people in whom the pain is a guitar problem rather than an amplifier problem. And drugs like duloxetine, which works in the brain, and cognitive-behavioral therapy are going to work a lot better in the people with pain in multiple sites besides the back.
To pick up on your metaphor, do any symptoms help clinicians differentiate between the guitar and the amplifier?
Sleep problems, fatigue, memory problems, and mood problems are common in patients with chronic pain and are more common with amplifier pain. Because again, those are all central nervous system problems. And so we see that the people that have anxiety, depression, and a lot of distress are more likely to have this kind of pain.
Does medical imaging help?
There’s a terrible relationship between what you see on an MRI of the back and whether someone has pain or how severe the pain is going to be. There’s always going to be individuals that have a lot of anatomic damage who don’t have any pain because they happen to be on the other end of the continuum from fibromyalgia; they’re actually pain-insensitive people.
What are your thoughts about ketamine as a possible treatment for chronic pain?
I have a mentee who’s doing a ketamine trial. We’re doing psilocybin trials in patients with fibromyalgia. Ketamine is such a dirty drug; it has so many different mechanisms of action. It does have some psychedelic effects, but it also is an NMDA blocker. It really has so many different effects.
I think it’s being thrown around like water in settings where we don’t yet know it to be efficacious. Even the data in treatment-refractory depression are pretty weak, but we’re so desperate to do something for those patients. If you’re trying to harness the psychedelic properties of ketamine, I think there’s other psychedelics that are a lot more interesting, which is why we’re using psilocybin for a subset of patients. Most of us in the pain field think that the psychedelics will work best for the people with chronic pain who have a lot of comorbid psychiatric illness, especially the ones with a lot of trauma. These drugs will allow us therapeutically to get at a lot of these patients with the side-by-side psychotherapy that’s being done as people are getting care in the medicalized setting.
Dr. Clauw reported conflicts of interest with Pfizer, Tonix, Theravance, Zynerba, Samumed, Aptinyx, Daiichi Sankyo, Intec, Regeneron, Teva, Lundbeck, Virios, and Cerephex.
A version of this article first appeared on Medscape.com.
Chronic pain, and back pain in particular, is among the most frequent concerns for patients in the primary care setting. Roughly 8% of adults in the United States say they suffer from chronic low back pain, and many of them say the pain is significant enough to impair their ability to move, work, and otherwise enjoy life. All this, despite decades of research and countless millions in funding to find the optimal approach to treating chronic pain.
As the United States crawls out of the opioid epidemic, a group of pain specialists is hoping to identify effective, personalized approaches to managing back pain. Daniel Clauw, MD, professor of anesthesiology, internal medicine, and psychiatry at the University of Michigan, Ann Arbor, is helping lead the BEST trial. With projected enrollment of nearly 800 patients, BEST will be the largest federally funded clinical trial of interventions to treat chronic low back pain.
In an interview, The interview has been edited for length and clarity.
What are your thoughts on the current state of primary care physicians’ understanding and management of pain?
Primary care physicians need a lot of help in demystifying the diagnosis and treatment of any kind of pain, but back pain is a really good place to start. When it comes to back pain, most primary care physicians are not any more knowledgeable than a layperson.
What has the opioid debacle-cum-tragedy taught you about pain management, particular as regards people with chronic pain?
I don’t feel opioids should ever be used to treat chronic low back pain. The few long-term studies that have been performed using opioids for longer than 3 months suggest that they often make pain worse rather than just failing to make pain better – and we know they are associated with a significantly increased all-cause mortality with increased deaths from myocardial infarction, accidents, and suicides, in addition to overdose.
Given how many patients experience back pain, how did we come to the point at which primary care physicians are so ill equipped?
We’ve had terrible pain curricula in medical schools. To give you an example: I’m one of the leading pain experts in the world and I’m not allowed to teach our medical students their pain curriculum. The students learn about neurophysiology and the anatomy of the nerves, not what’s relevant in pain.
This is notorious in medical school: Curricula are almost impossible to modify and change. So it starts with poor training in medical school. And then, regardless of what education they do or don’t get in medical school, a lot of their education about pain management is through our residencies – mainly in inpatient settings, where you’re really seeing the management of acute pain and not the management of chronic pain.
People get more accustomed to managing acute pain, where opioids are a reasonable option. It’s just that when you start managing subacute or chronic pain, opioids don’t work as well.
The other big problem is that historically, most people trained in medicine think that if you have pain in your elbow, there’s got to be something wrong in your elbow. This third mechanism of pain, central sensitization – or nociplastic pain – the kind of pain that we see in fibromyalgia, headache, and low back pain, where the pain is coming from the brain – that’s confusing to people. People can have pain without any damage or inflammation to that region of the body.
Physicians are trained that if there’s pain, there’s something wrong and we have to do surgery or there’s been some trauma. Most chronic pain is none of that. There’s a big disconnect between how people are trained, and then when they go out and are seeing a tremendous number of people with chronic pain.
What are the different types of pain, and how should they inform clinicians’ understanding about what approaches might work for managing their patients in pain?
The way the central nervous system responds to pain is analogous to the loudness of an electric guitar. You can make an electric guitar louder either by strumming the strings harder or by turning up the amplifier. For many people with fibromyalgia, low back pain, and endometriosis, for example, the problem is really more that the amplifier is turned up too high rather than its being that the guitar is strummed too strongly. That kind of pain where the pain is not due to anatomic damage or inflammation is particularly flummoxing for providers.
Can you explain the design of the new study?
It’s a 13-site study looking at four treatments: enhanced self-care, cognitive-behavioral therapy, physical therapy, and duloxetine. It’s a big precision medicine trial, trying to take everything we’ve learned and putting it all into one big study.
We’re using a SMART design, which randomizes people to two of those treatments, unless they are very much improved from the first treatment. To be eligible for the trial, you have to be able to be randomized to three of the four treatments, and people can’t choose which of the four they get.
We give them one of those treatments for 12 weeks, and at the end of 12 weeks we make the call – “Did you respond or not respond?” – and then we go back to the phenotypic data we collected at the beginning of that trial and say, “What information at baseline that we collected predicts that someone is going to respond better to duloxetine or worse to duloxetine?” And then we create the phenotype that responds best to each of those four treatments.
None of our treatments works so well that someone doesn’t end up getting randomized to a second treatment. About 85% of people so far need a second treatment because they still have enough pain that they want more relief. But the nice thing about that is we’ve already done all the functional brain imaging and all these really expensive and time-consuming things.
We’re hoping to have around 700-800 people total in this trial, which means that around 170 people will get randomized to each of the four initial treatments. No one’s ever done a study that has functional brain imaging and all these other things in it with more than 80 or 100 people. The scale of this is totally unprecedented.
Given that the individual therapies don’t appear to be all that successful on their own, what is your goal?
The primary aim is to match the phenotypic characteristics of a patient with chronic low back pain with treatment response to each of these four treatments. So at the end, we can give clinicians information on which of the patients is going to respond to physical therapy, for instance.
Right now, about one out of three people respond to most treatments for pain. We think by doing a trial like this, we can take treatments that work in one out of three people and make them work in one out of two or two out of three people just by using them in the right people.
How do you differentiate between these types of pain in your study?
We phenotype people by asking them a number of questions. We also do brain imaging, look at their back with MRI, test biomechanics, and then give them four different treatments that we know work in groups of people with low back pain.
We think one of the first parts of the phenotype is, do they have pain just in their back? Or do they have pain in their back plus a lot of other body regions? Because the more body regions that people have pain in, the more likely it is that this is an amplifier problem rather than a guitar problem.
Treatments like physical therapy, surgery, and injections are going to work better for people in whom the pain is a guitar problem rather than an amplifier problem. And drugs like duloxetine, which works in the brain, and cognitive-behavioral therapy are going to work a lot better in the people with pain in multiple sites besides the back.
To pick up on your metaphor, do any symptoms help clinicians differentiate between the guitar and the amplifier?
Sleep problems, fatigue, memory problems, and mood problems are common in patients with chronic pain and are more common with amplifier pain. Because again, those are all central nervous system problems. And so we see that the people that have anxiety, depression, and a lot of distress are more likely to have this kind of pain.
Does medical imaging help?
There’s a terrible relationship between what you see on an MRI of the back and whether someone has pain or how severe the pain is going to be. There’s always going to be individuals that have a lot of anatomic damage who don’t have any pain because they happen to be on the other end of the continuum from fibromyalgia; they’re actually pain-insensitive people.
What are your thoughts about ketamine as a possible treatment for chronic pain?
I have a mentee who’s doing a ketamine trial. We’re doing psilocybin trials in patients with fibromyalgia. Ketamine is such a dirty drug; it has so many different mechanisms of action. It does have some psychedelic effects, but it also is an NMDA blocker. It really has so many different effects.
I think it’s being thrown around like water in settings where we don’t yet know it to be efficacious. Even the data in treatment-refractory depression are pretty weak, but we’re so desperate to do something for those patients. If you’re trying to harness the psychedelic properties of ketamine, I think there’s other psychedelics that are a lot more interesting, which is why we’re using psilocybin for a subset of patients. Most of us in the pain field think that the psychedelics will work best for the people with chronic pain who have a lot of comorbid psychiatric illness, especially the ones with a lot of trauma. These drugs will allow us therapeutically to get at a lot of these patients with the side-by-side psychotherapy that’s being done as people are getting care in the medicalized setting.
Dr. Clauw reported conflicts of interest with Pfizer, Tonix, Theravance, Zynerba, Samumed, Aptinyx, Daiichi Sankyo, Intec, Regeneron, Teva, Lundbeck, Virios, and Cerephex.
A version of this article first appeared on Medscape.com.
Who owns your genes?
Who owns your genes? The assumption of any sane person would be that he or she owns his or her own genes. I mean, how dumb a question is that?
Yet, in 2007, Dov Michaeli, MD, PhD, described how an American company had claimed ownership of genetic materials and believed that it had the right to commercialize those naturally occurring bits of DNA. Myriad Genetics began by patenting mutations of BRCA. Dr. Michaeli issued a call for action to support early efforts to pass legislation to restore and preserve individual ownership of one’s own genes. This is a historically important quick read/watch/listen. Give it a click.
In related legislation, the Genetic Information Nondiscrimination Act (GINA), originally introduced by New York Rep. Louise Slaughter in 1995, was ultimately spearheaded by California Rep. Xavier Becerra (now Secretary of Health & Human Services) to passage by the House of Representatives on April 25, 2007, by a vote of 420-9-3. Led by Sen. Edward Kennedy of Massachusetts, it was passed by the Senate on April 24, 2008, by a vote of 95-0. President George W. Bush signed the bill into law on May 21, 2008.
GINA is a landmark piece of legislation that protects Americans. It prohibits employers and health insurers from discriminating against people on the basis of their genetic information, and it also prohibits the use of genetic information in life insurance and long-term care insurance.
Its impact has been immense. GINA has been indispensable in promoting progress in the field of human genetics. By safeguarding individuals against discrimination based on genetic information, it has encouraged broader participation in research, built public trust, and stimulated advancements in genetic testing and personalized medicine. GINA’s impact extends beyond borders and has influenced much of the rest of the world.
As important as GINA was to the field, more was needed. National legislation to protect ownership of genetic materials has, despite many attempts, still not become law in the United States. However, in our system of divided government and balance of power, we also have independent courts.
June 13, 2023, was the 10th anniversary of another landmark event. The legal case is that of the Association for Molecular Pathology v. Myriad Genetics, a Salt Lake City–based biotech company that held patents on isolated DNA sequences associated with breast and ovarian cancer. The AMP, joined by several other organizations and researchers, challenged Myriad’s gene patents, arguing that human genes are naturally occurring and, therefore, should not be subject to patenting. In a unanimous decision, the Supreme Court held that naturally occurring DNA segments are products of nature and therefore are not eligible for patent protection.
This was a pivotal decision in the field of human genetics and had a broad impact on genetic research. The decision clarified that naturally occurring DNA sequences cannot be patented, which means that researchers are free to use these sequences in their research without fear of patent infringement. This has led to a vast increase in the amount of genetic research being conducted, and it has also led to the development of new genetic tests and treatments.
The numbers of genetic research papers published in scientific journals and of genetic tests available to consumers have increased significantly, while the cost of genetic testing has decreased significantly. The AMP v. Myriad decision is likely to continue to have an impact for many years to come.
Thank you, common sense, activist American molecular pathologists, Congress, the President, and the Supreme Court for siding with the people.Dr. Lundbert is editor in chief of Cancer Commons. He has disclosed no relevant financial relationships.
A version of this article first appeared on Medscape.com.
Who owns your genes? The assumption of any sane person would be that he or she owns his or her own genes. I mean, how dumb a question is that?
Yet, in 2007, Dov Michaeli, MD, PhD, described how an American company had claimed ownership of genetic materials and believed that it had the right to commercialize those naturally occurring bits of DNA. Myriad Genetics began by patenting mutations of BRCA. Dr. Michaeli issued a call for action to support early efforts to pass legislation to restore and preserve individual ownership of one’s own genes. This is a historically important quick read/watch/listen. Give it a click.
In related legislation, the Genetic Information Nondiscrimination Act (GINA), originally introduced by New York Rep. Louise Slaughter in 1995, was ultimately spearheaded by California Rep. Xavier Becerra (now Secretary of Health & Human Services) to passage by the House of Representatives on April 25, 2007, by a vote of 420-9-3. Led by Sen. Edward Kennedy of Massachusetts, it was passed by the Senate on April 24, 2008, by a vote of 95-0. President George W. Bush signed the bill into law on May 21, 2008.
GINA is a landmark piece of legislation that protects Americans. It prohibits employers and health insurers from discriminating against people on the basis of their genetic information, and it also prohibits the use of genetic information in life insurance and long-term care insurance.
Its impact has been immense. GINA has been indispensable in promoting progress in the field of human genetics. By safeguarding individuals against discrimination based on genetic information, it has encouraged broader participation in research, built public trust, and stimulated advancements in genetic testing and personalized medicine. GINA’s impact extends beyond borders and has influenced much of the rest of the world.
As important as GINA was to the field, more was needed. National legislation to protect ownership of genetic materials has, despite many attempts, still not become law in the United States. However, in our system of divided government and balance of power, we also have independent courts.
June 13, 2023, was the 10th anniversary of another landmark event. The legal case is that of the Association for Molecular Pathology v. Myriad Genetics, a Salt Lake City–based biotech company that held patents on isolated DNA sequences associated with breast and ovarian cancer. The AMP, joined by several other organizations and researchers, challenged Myriad’s gene patents, arguing that human genes are naturally occurring and, therefore, should not be subject to patenting. In a unanimous decision, the Supreme Court held that naturally occurring DNA segments are products of nature and therefore are not eligible for patent protection.
This was a pivotal decision in the field of human genetics and had a broad impact on genetic research. The decision clarified that naturally occurring DNA sequences cannot be patented, which means that researchers are free to use these sequences in their research without fear of patent infringement. This has led to a vast increase in the amount of genetic research being conducted, and it has also led to the development of new genetic tests and treatments.
The numbers of genetic research papers published in scientific journals and of genetic tests available to consumers have increased significantly, while the cost of genetic testing has decreased significantly. The AMP v. Myriad decision is likely to continue to have an impact for many years to come.
Thank you, common sense, activist American molecular pathologists, Congress, the President, and the Supreme Court for siding with the people.Dr. Lundbert is editor in chief of Cancer Commons. He has disclosed no relevant financial relationships.
A version of this article first appeared on Medscape.com.
Who owns your genes? The assumption of any sane person would be that he or she owns his or her own genes. I mean, how dumb a question is that?
Yet, in 2007, Dov Michaeli, MD, PhD, described how an American company had claimed ownership of genetic materials and believed that it had the right to commercialize those naturally occurring bits of DNA. Myriad Genetics began by patenting mutations of BRCA. Dr. Michaeli issued a call for action to support early efforts to pass legislation to restore and preserve individual ownership of one’s own genes. This is a historically important quick read/watch/listen. Give it a click.
In related legislation, the Genetic Information Nondiscrimination Act (GINA), originally introduced by New York Rep. Louise Slaughter in 1995, was ultimately spearheaded by California Rep. Xavier Becerra (now Secretary of Health & Human Services) to passage by the House of Representatives on April 25, 2007, by a vote of 420-9-3. Led by Sen. Edward Kennedy of Massachusetts, it was passed by the Senate on April 24, 2008, by a vote of 95-0. President George W. Bush signed the bill into law on May 21, 2008.
GINA is a landmark piece of legislation that protects Americans. It prohibits employers and health insurers from discriminating against people on the basis of their genetic information, and it also prohibits the use of genetic information in life insurance and long-term care insurance.
Its impact has been immense. GINA has been indispensable in promoting progress in the field of human genetics. By safeguarding individuals against discrimination based on genetic information, it has encouraged broader participation in research, built public trust, and stimulated advancements in genetic testing and personalized medicine. GINA’s impact extends beyond borders and has influenced much of the rest of the world.
As important as GINA was to the field, more was needed. National legislation to protect ownership of genetic materials has, despite many attempts, still not become law in the United States. However, in our system of divided government and balance of power, we also have independent courts.
June 13, 2023, was the 10th anniversary of another landmark event. The legal case is that of the Association for Molecular Pathology v. Myriad Genetics, a Salt Lake City–based biotech company that held patents on isolated DNA sequences associated with breast and ovarian cancer. The AMP, joined by several other organizations and researchers, challenged Myriad’s gene patents, arguing that human genes are naturally occurring and, therefore, should not be subject to patenting. In a unanimous decision, the Supreme Court held that naturally occurring DNA segments are products of nature and therefore are not eligible for patent protection.
This was a pivotal decision in the field of human genetics and had a broad impact on genetic research. The decision clarified that naturally occurring DNA sequences cannot be patented, which means that researchers are free to use these sequences in their research without fear of patent infringement. This has led to a vast increase in the amount of genetic research being conducted, and it has also led to the development of new genetic tests and treatments.
The numbers of genetic research papers published in scientific journals and of genetic tests available to consumers have increased significantly, while the cost of genetic testing has decreased significantly. The AMP v. Myriad decision is likely to continue to have an impact for many years to come.
Thank you, common sense, activist American molecular pathologists, Congress, the President, and the Supreme Court for siding with the people.Dr. Lundbert is editor in chief of Cancer Commons. He has disclosed no relevant financial relationships.
A version of this article first appeared on Medscape.com.