Opinion

Editor’s note: This article is adapted from an explanatory statement that Dr. Feldman wrote for the Coalition of State Rheumatology Organizations (CSRO).

According to the Guinness Book of World records, the longest time someone has held their breath underwater voluntarily is 24 minutes and 37.36 seconds. While certainly an amazing feat, UnitedHealthcare, many of the Blues, and other national “payers” are expecting rheumatologists and other specialists to live “underwater” in order to take care of their patients. In other words, these insurance companies are mandating that specialists use certain provider-administered biosimilars whose acquisition cost is higher than what the insurance company is willing to reimburse them. Essentially, the insurance companies expect the rheumatologists to pay them to take care of their patients. Because of the substantial and destabilizing financial losses incurred, many practices and free-standing infusion centers have been forced to cease offering these biosimilars. Most rheumatologists will provide patients with appropriate alternatives when available and permitted by the insurer; otherwise, they must refer patients to hospital-based infusion centers. That results in delayed care and increased costs for patients and the system, because hospital-based infusion typically costs more than twice what office-based infusion costs.

Quantifying the Problem

To help quantify the magnitude of this issue, the Coalition of State Rheumatology Organizations (CSRO) recently conducted a survey of its membership. A shocking 97% of respondents reported that their practice had been affected by reimbursement rates for some biosimilars being lower than acquisition costs, with 91% of respondents stating that this issue is more pronounced for certain biosimilars than others. Across the board, respondents most frequently identified Inflectra (infliximab-dyyb) and Avsola (infliximab-axxq) as being especially affected: Over 88% and over 85% of respondents identified these two products, respectively, as being underwater. These results support the ongoing anecdotal reports CSRO continues to receive from rheumatology practices.

However, the survey results indicated that this issue is by no means confined to those two biosimilars. Truxima (rituximab-abbs) — a biosimilar for Rituxan — was frequently mentioned as well. Notably, respondents almost uniformly identified biosimilars in the infliximab and rituximab families, which illustrates that this issue is no longer confined to one or two early-to-market biosimilars but has almost become a hallmark of this particular biosimilars market. Remarkably, one respondent commented that the brand products are now cheaper to acquire than the biosimilars. Furthermore, the survey included respondents from across the country, indicating that this issue is not confined to a particular region.
 

How Did This Happen?

Biosimilars held promise for increasing availability and decreasing biologic costs for patients but, thus far, no patients have seen their cost go down. It appears that the only biosimilars that have made it to “preferred” status on the formulary are the ones that have made more money for the middlemen in the drug supply chain, particularly those that construct formularies. Now, we have provider-administered biosimilars whose acquisition cost exceeds the reimbursement for these drugs. This disparity was ultimately created by biosimilar manufacturers “over-rebating” their drugs to health insurance companies to gain “fail-first” status on the formulary.

For example, the manufacturer of Inflectra offered substantial rebates to health insurers for preferred formulary placement. These rebates are factored into the sales price of the medication, which then results in a rapidly declining average sales price (ASP) for the biosimilar. Unfortunately, the acquisition cost for the drug does not experience commensurate reductions, resulting in physicians being reimbursed far less for the drug than it costs to acquire. The financial losses for physicians put them underwater as a result of the acquisition costs for the preferred drugs far surpassing the reimbursement from the health insurance company that constructed the formulary.

While various factors affect ASPs and acquisition costs, this particular consequence of formulary placement based on price concessions is a major driver of the underwater situation in which physicians have found themselves with many biosimilars. Not only does that lead to a lower uptake of biosimilars, but it also results in patients being referred to the hospital outpatient infusion sites to receive this care, as freestanding infusion centers cannot treat these patients either. Hospitals incur higher costs because of facility fees and elevated rates, and this makes private rheumatology in-office infusion centers a much lower-cost option. Similarly, home infusion services, while convenient, are marginally more expensive than private practices and, in cases of biologic infusions, it is important to note that physicians’ offices have a greater safety profile than home infusion of biologics. The overall result of these “fail-first underwater drugs” is delayed and more costly care for the patient and the “system,” particularly self-insured employers.
 

What Is Being Done to Correct This?

Since ASPs are updated quarterly, it is possible that acquisition costs and reimbursements might stabilize over time, making the drugs affordable again to practices. However, that does not appear to be happening in the near future, so that possibility does not offer immediate relief to struggling practices. It doesn’t promise a favorable outlook for future biosimilar entries of provider-administered medications if formularies continue to prefer the highest-rebated medication.

This dynamic between ASP and acquisition cost does not happen on the pharmacy side because the price concessions on specific drug rebates and fees are proprietary. There appears to be no equivalent to a publicly known ASP on the pharmacy side, which has led to myriad pricing definitions and manipulation on the pharmacy benefit side of medications. In any event, the savings from rebates and other manufacturer price concessions on pharmacy drugs do not influence ASPs of medical benefit drugs.

The Inflation Reduction Act provided a temporary increase in the add-on payment for biosimilars from ASP+6% to ASP+8%, but as long as the biosimilar’s ASP is lower than the reference brand’s ASP, that temporary increase does not appear to make up for the large differential between ASP and acquisition cost. It should be noted that any federal attempt to artificially lower the ASP of a provider-administered drug without a pathway assuring that the acquisition cost for the provider is less than the reimbursement is going to result in loss of access for patients to those medications and/or higher hospital site of care costs.
 

A Few Partial Fixes, But Most Complaints Go Ignored

Considering the higher costs of hospital-based infusion, insurers should be motivated to keep patients within private practices. Perhaps through insurers’ recognition of that fact, some practices have successfully negotiated exceptions for specific patients by discussing this situation with insurers. From the feedback that CSRO has received from rheumatology practices, it appears that most insurers have been ignoring the complaints from physicians. The few who have responded have resulted in only partial fixes, with some of the biosimilars still left underwater.

Ultimate Solution?

This issue is a direct result of the “rebate game,” whereby price concessions from drug manufacturers drive formulary placement. For provider-administered medications, this results in an artificially lowered ASP, not as a consequence of free-market incentives that benefit the patient, but as a result of misaligned incentives created by Safe Harbor–protected “kickbacks,” distorting the free market and paradoxically reducing access to these medications, delaying care, and increasing prices for patients and the healthcare system.

While federal and state governments are not likely to address this particular situation in the biosimilars market, CSRO is highlighting this issue as a prime example of why the current formulary construction system urgently requires federal reform. At this time, the biosimilars most affected are Inflectra and Avsola, but if nothing changes, more and more biosimilars will fall victim to the short-sighted pricing strategy of aggressive rebating to gain formulary position, with physician purchasers and patients left to navigate the aftermath. The existing system, which necessitates drug companies purchasing formulary access from pharmacy benefit managers, has led to delayed and even denied patient access to certain provider-administered drugs. Moreover, it now appears to be hindering the adoption of biosimilars.

To address this, a multifaceted approach is required. It not only involves reevaluating the rebate system and its impact on formulary construction and ASP, but also ensuring that acquisition costs for providers are aligned with reimbursement rates. Insurers must recognize the economic and clinical value of maintaining infusions within private practices and immediately update their policies to ensure that physician in-office infusion is financially feasible for these “fail-first” biosimilars.

Ultimately, the goal should be to create a sustainable model that promotes the use of affordable biosimilars, enhances patient access to affordable care, and supports the financial viability of medical practices. Concerted efforts to reform the current formulary construction system are required to achieve a healthcare environment that is both cost effective and patient centric.

Dr. Feldman is a rheumatologist in private practice with The Rheumatology Group in New Orleans. She is the CSRO’s vice president of advocacy and government affairs and its immediate past president, as well as past chair of the Alliance for Safe Biologic Medicines and a past member of the American College of Rheumatology insurance subcommittee. You can reach her at [email protected].

Editor’s note: This article is adapted from an explanatory statement that Dr. Feldman wrote for the Coalition of State Rheumatology Organizations (CSRO).

According to the Guinness Book of World records, the longest time someone has held their breath underwater voluntarily is 24 minutes and 37.36 seconds. While certainly an amazing feat, UnitedHealthcare, many of the Blues, and other national “payers” are expecting rheumatologists and other specialists to live “underwater” in order to take care of their patients. In other words, these insurance companies are mandating that specialists use certain provider-administered biosimilars whose acquisition cost is higher than what the insurance company is willing to reimburse them. Essentially, the insurance companies expect the rheumatologists to pay them to take care of their patients. Because of the substantial and destabilizing financial losses incurred, many practices and free-standing infusion centers have been forced to cease offering these biosimilars. Most rheumatologists will provide patients with appropriate alternatives when available and permitted by the insurer; otherwise, they must refer patients to hospital-based infusion centers. That results in delayed care and increased costs for patients and the system, because hospital-based infusion typically costs more than twice what office-based infusion costs.

Quantifying the Problem

To help quantify the magnitude of this issue, the Coalition of State Rheumatology Organizations (CSRO) recently conducted a survey of its membership. A shocking 97% of respondents reported that their practice had been affected by reimbursement rates for some biosimilars being lower than acquisition costs, with 91% of respondents stating that this issue is more pronounced for certain biosimilars than others. Across the board, respondents most frequently identified Inflectra (infliximab-dyyb) and Avsola (infliximab-axxq) as being especially affected: Over 88% and over 85% of respondents identified these two products, respectively, as being underwater. These results support the ongoing anecdotal reports CSRO continues to receive from rheumatology practices.

However, the survey results indicated that this issue is by no means confined to those two biosimilars. Truxima (rituximab-abbs) — a biosimilar for Rituxan — was frequently mentioned as well. Notably, respondents almost uniformly identified biosimilars in the infliximab and rituximab families, which illustrates that this issue is no longer confined to one or two early-to-market biosimilars but has almost become a hallmark of this particular biosimilars market. Remarkably, one respondent commented that the brand products are now cheaper to acquire than the biosimilars. Furthermore, the survey included respondents from across the country, indicating that this issue is not confined to a particular region.
 

How Did This Happen?

Biosimilars held promise for increasing availability and decreasing biologic costs for patients but, thus far, no patients have seen their cost go down. It appears that the only biosimilars that have made it to “preferred” status on the formulary are the ones that have made more money for the middlemen in the drug supply chain, particularly those that construct formularies. Now, we have provider-administered biosimilars whose acquisition cost exceeds the reimbursement for these drugs. This disparity was ultimately created by biosimilar manufacturers “over-rebating” their drugs to health insurance companies to gain “fail-first” status on the formulary.

For example, the manufacturer of Inflectra offered substantial rebates to health insurers for preferred formulary placement. These rebates are factored into the sales price of the medication, which then results in a rapidly declining average sales price (ASP) for the biosimilar. Unfortunately, the acquisition cost for the drug does not experience commensurate reductions, resulting in physicians being reimbursed far less for the drug than it costs to acquire. The financial losses for physicians put them underwater as a result of the acquisition costs for the preferred drugs far surpassing the reimbursement from the health insurance company that constructed the formulary.

While various factors affect ASPs and acquisition costs, this particular consequence of formulary placement based on price concessions is a major driver of the underwater situation in which physicians have found themselves with many biosimilars. Not only does that lead to a lower uptake of biosimilars, but it also results in patients being referred to the hospital outpatient infusion sites to receive this care, as freestanding infusion centers cannot treat these patients either. Hospitals incur higher costs because of facility fees and elevated rates, and this makes private rheumatology in-office infusion centers a much lower-cost option. Similarly, home infusion services, while convenient, are marginally more expensive than private practices and, in cases of biologic infusions, it is important to note that physicians’ offices have a greater safety profile than home infusion of biologics. The overall result of these “fail-first underwater drugs” is delayed and more costly care for the patient and the “system,” particularly self-insured employers.
 

What Is Being Done to Correct This?

Since ASPs are updated quarterly, it is possible that acquisition costs and reimbursements might stabilize over time, making the drugs affordable again to practices. However, that does not appear to be happening in the near future, so that possibility does not offer immediate relief to struggling practices. It doesn’t promise a favorable outlook for future biosimilar entries of provider-administered medications if formularies continue to prefer the highest-rebated medication.

This dynamic between ASP and acquisition cost does not happen on the pharmacy side because the price concessions on specific drug rebates and fees are proprietary. There appears to be no equivalent to a publicly known ASP on the pharmacy side, which has led to myriad pricing definitions and manipulation on the pharmacy benefit side of medications. In any event, the savings from rebates and other manufacturer price concessions on pharmacy drugs do not influence ASPs of medical benefit drugs.

The Inflation Reduction Act provided a temporary increase in the add-on payment for biosimilars from ASP+6% to ASP+8%, but as long as the biosimilar’s ASP is lower than the reference brand’s ASP, that temporary increase does not appear to make up for the large differential between ASP and acquisition cost. It should be noted that any federal attempt to artificially lower the ASP of a provider-administered drug without a pathway assuring that the acquisition cost for the provider is less than the reimbursement is going to result in loss of access for patients to those medications and/or higher hospital site of care costs.
 

A Few Partial Fixes, But Most Complaints Go Ignored

Considering the higher costs of hospital-based infusion, insurers should be motivated to keep patients within private practices. Perhaps through insurers’ recognition of that fact, some practices have successfully negotiated exceptions for specific patients by discussing this situation with insurers. From the feedback that CSRO has received from rheumatology practices, it appears that most insurers have been ignoring the complaints from physicians. The few who have responded have resulted in only partial fixes, with some of the biosimilars still left underwater.

Ultimate Solution?

This issue is a direct result of the “rebate game,” whereby price concessions from drug manufacturers drive formulary placement. For provider-administered medications, this results in an artificially lowered ASP, not as a consequence of free-market incentives that benefit the patient, but as a result of misaligned incentives created by Safe Harbor–protected “kickbacks,” distorting the free market and paradoxically reducing access to these medications, delaying care, and increasing prices for patients and the healthcare system.

While federal and state governments are not likely to address this particular situation in the biosimilars market, CSRO is highlighting this issue as a prime example of why the current formulary construction system urgently requires federal reform. At this time, the biosimilars most affected are Inflectra and Avsola, but if nothing changes, more and more biosimilars will fall victim to the short-sighted pricing strategy of aggressive rebating to gain formulary position, with physician purchasers and patients left to navigate the aftermath. The existing system, which necessitates drug companies purchasing formulary access from pharmacy benefit managers, has led to delayed and even denied patient access to certain provider-administered drugs. Moreover, it now appears to be hindering the adoption of biosimilars.

To address this, a multifaceted approach is required. It not only involves reevaluating the rebate system and its impact on formulary construction and ASP, but also ensuring that acquisition costs for providers are aligned with reimbursement rates. Insurers must recognize the economic and clinical value of maintaining infusions within private practices and immediately update their policies to ensure that physician in-office infusion is financially feasible for these “fail-first” biosimilars.

Ultimately, the goal should be to create a sustainable model that promotes the use of affordable biosimilars, enhances patient access to affordable care, and supports the financial viability of medical practices. Concerted efforts to reform the current formulary construction system are required to achieve a healthcare environment that is both cost effective and patient centric.

Dr. Feldman is a rheumatologist in private practice with The Rheumatology Group in New Orleans. She is the CSRO’s vice president of advocacy and government affairs and its immediate past president, as well as past chair of the Alliance for Safe Biologic Medicines and a past member of the American College of Rheumatology insurance subcommittee. You can reach her at [email protected].

Editor’s note: This article is adapted from an explanatory statement that Dr. Feldman wrote for the Coalition of State Rheumatology Organizations (CSRO).

According to the Guinness Book of World records, the longest time someone has held their breath underwater voluntarily is 24 minutes and 37.36 seconds. While certainly an amazing feat, UnitedHealthcare, many of the Blues, and other national “payers” are expecting rheumatologists and other specialists to live “underwater” in order to take care of their patients. In other words, these insurance companies are mandating that specialists use certain provider-administered biosimilars whose acquisition cost is higher than what the insurance company is willing to reimburse them. Essentially, the insurance companies expect the rheumatologists to pay them to take care of their patients. Because of the substantial and destabilizing financial losses incurred, many practices and free-standing infusion centers have been forced to cease offering these biosimilars. Most rheumatologists will provide patients with appropriate alternatives when available and permitted by the insurer; otherwise, they must refer patients to hospital-based infusion centers. That results in delayed care and increased costs for patients and the system, because hospital-based infusion typically costs more than twice what office-based infusion costs.

Quantifying the Problem

To help quantify the magnitude of this issue, the Coalition of State Rheumatology Organizations (CSRO) recently conducted a survey of its membership. A shocking 97% of respondents reported that their practice had been affected by reimbursement rates for some biosimilars being lower than acquisition costs, with 91% of respondents stating that this issue is more pronounced for certain biosimilars than others. Across the board, respondents most frequently identified Inflectra (infliximab-dyyb) and Avsola (infliximab-axxq) as being especially affected: Over 88% and over 85% of respondents identified these two products, respectively, as being underwater. These results support the ongoing anecdotal reports CSRO continues to receive from rheumatology practices.

However, the survey results indicated that this issue is by no means confined to those two biosimilars. Truxima (rituximab-abbs) — a biosimilar for Rituxan — was frequently mentioned as well. Notably, respondents almost uniformly identified biosimilars in the infliximab and rituximab families, which illustrates that this issue is no longer confined to one or two early-to-market biosimilars but has almost become a hallmark of this particular biosimilars market. Remarkably, one respondent commented that the brand products are now cheaper to acquire than the biosimilars. Furthermore, the survey included respondents from across the country, indicating that this issue is not confined to a particular region.
 

How Did This Happen?

Biosimilars held promise for increasing availability and decreasing biologic costs for patients but, thus far, no patients have seen their cost go down. It appears that the only biosimilars that have made it to “preferred” status on the formulary are the ones that have made more money for the middlemen in the drug supply chain, particularly those that construct formularies. Now, we have provider-administered biosimilars whose acquisition cost exceeds the reimbursement for these drugs. This disparity was ultimately created by biosimilar manufacturers “over-rebating” their drugs to health insurance companies to gain “fail-first” status on the formulary.

For example, the manufacturer of Inflectra offered substantial rebates to health insurers for preferred formulary placement. These rebates are factored into the sales price of the medication, which then results in a rapidly declining average sales price (ASP) for the biosimilar. Unfortunately, the acquisition cost for the drug does not experience commensurate reductions, resulting in physicians being reimbursed far less for the drug than it costs to acquire. The financial losses for physicians put them underwater as a result of the acquisition costs for the preferred drugs far surpassing the reimbursement from the health insurance company that constructed the formulary.

While various factors affect ASPs and acquisition costs, this particular consequence of formulary placement based on price concessions is a major driver of the underwater situation in which physicians have found themselves with many biosimilars. Not only does that lead to a lower uptake of biosimilars, but it also results in patients being referred to the hospital outpatient infusion sites to receive this care, as freestanding infusion centers cannot treat these patients either. Hospitals incur higher costs because of facility fees and elevated rates, and this makes private rheumatology in-office infusion centers a much lower-cost option. Similarly, home infusion services, while convenient, are marginally more expensive than private practices and, in cases of biologic infusions, it is important to note that physicians’ offices have a greater safety profile than home infusion of biologics. The overall result of these “fail-first underwater drugs” is delayed and more costly care for the patient and the “system,” particularly self-insured employers.
 

What Is Being Done to Correct This?

Since ASPs are updated quarterly, it is possible that acquisition costs and reimbursements might stabilize over time, making the drugs affordable again to practices. However, that does not appear to be happening in the near future, so that possibility does not offer immediate relief to struggling practices. It doesn’t promise a favorable outlook for future biosimilar entries of provider-administered medications if formularies continue to prefer the highest-rebated medication.

This dynamic between ASP and acquisition cost does not happen on the pharmacy side because the price concessions on specific drug rebates and fees are proprietary. There appears to be no equivalent to a publicly known ASP on the pharmacy side, which has led to myriad pricing definitions and manipulation on the pharmacy benefit side of medications. In any event, the savings from rebates and other manufacturer price concessions on pharmacy drugs do not influence ASPs of medical benefit drugs.

The Inflation Reduction Act provided a temporary increase in the add-on payment for biosimilars from ASP+6% to ASP+8%, but as long as the biosimilar’s ASP is lower than the reference brand’s ASP, that temporary increase does not appear to make up for the large differential between ASP and acquisition cost. It should be noted that any federal attempt to artificially lower the ASP of a provider-administered drug without a pathway assuring that the acquisition cost for the provider is less than the reimbursement is going to result in loss of access for patients to those medications and/or higher hospital site of care costs.
 

A Few Partial Fixes, But Most Complaints Go Ignored

Considering the higher costs of hospital-based infusion, insurers should be motivated to keep patients within private practices. Perhaps through insurers’ recognition of that fact, some practices have successfully negotiated exceptions for specific patients by discussing this situation with insurers. From the feedback that CSRO has received from rheumatology practices, it appears that most insurers have been ignoring the complaints from physicians. The few who have responded have resulted in only partial fixes, with some of the biosimilars still left underwater.

Ultimate Solution?

This issue is a direct result of the “rebate game,” whereby price concessions from drug manufacturers drive formulary placement. For provider-administered medications, this results in an artificially lowered ASP, not as a consequence of free-market incentives that benefit the patient, but as a result of misaligned incentives created by Safe Harbor–protected “kickbacks,” distorting the free market and paradoxically reducing access to these medications, delaying care, and increasing prices for patients and the healthcare system.

While federal and state governments are not likely to address this particular situation in the biosimilars market, CSRO is highlighting this issue as a prime example of why the current formulary construction system urgently requires federal reform. At this time, the biosimilars most affected are Inflectra and Avsola, but if nothing changes, more and more biosimilars will fall victim to the short-sighted pricing strategy of aggressive rebating to gain formulary position, with physician purchasers and patients left to navigate the aftermath. The existing system, which necessitates drug companies purchasing formulary access from pharmacy benefit managers, has led to delayed and even denied patient access to certain provider-administered drugs. Moreover, it now appears to be hindering the adoption of biosimilars.

To address this, a multifaceted approach is required. It not only involves reevaluating the rebate system and its impact on formulary construction and ASP, but also ensuring that acquisition costs for providers are aligned with reimbursement rates. Insurers must recognize the economic and clinical value of maintaining infusions within private practices and immediately update their policies to ensure that physician in-office infusion is financially feasible for these “fail-first” biosimilars.

Ultimately, the goal should be to create a sustainable model that promotes the use of affordable biosimilars, enhances patient access to affordable care, and supports the financial viability of medical practices. Concerted efforts to reform the current formulary construction system are required to achieve a healthcare environment that is both cost effective and patient centric.

Dr. Feldman is a rheumatologist in private practice with The Rheumatology Group in New Orleans. She is the CSRO’s vice president of advocacy and government affairs and its immediate past president, as well as past chair of the Alliance for Safe Biologic Medicines and a past member of the American College of Rheumatology insurance subcommittee. You can reach her at [email protected].

Claudia* was a charming 27-year-old newlywed. She and her husband wanted to start a family — with one small catch. She had recently gained 30 pounds. During COVID, she and her husband spent 18 months camped out in her parents’ guest room in upstate New York and had eaten their emotions with abandon. They ate when they were happy and ate more when they were sad. They ate when they felt isolated and again when they felt anxious. It didn’t help that her mother was a Culinary Institute–trained amateur chef. They both worked from home and logged long hours on Zoom calls. Because there was no home gym, they replaced their usual fitness club workouts in the city with leisurely strolls around the local lake. When I met her, Claudia categorically refused to entertain the notion of pregnancy until she reached her pre-COVID weight.

At the time, this all seemed quite reasonable to me. We outlined a plan including semaglutide (Wegovy) until she reached her target weight and then a minimum of 2 months off Wegovy prior to conception. We also lined up sessions with a dietitian and trainer and renewed her birth control pill. There was one detail I failed to mention to her: Birth control pills are less effective while on incretin hormones like semaglutide. The reason for my omission is that the medical community at large wasn’t yet aware of this issue. 

About 12 weeks into treatment, Claudia had lost 20 of the 30 pounds. She had canceled several appointments with the trainer and dietitian due to work conflicts. She messaged me over the weekend in a panic. Her period was late, and her pregnancy test was positive.

She had three pressing questions for me:

Q: How had this happened while she had taken the birth control pills faithfully?

A: I answered that the scientific reasons for the decrease in efficacy of birth control pills while on semaglutide medications are threefold: 

• Weight loss can improve menstrual cycle irregularities and improve fertility. In fact, I have been using semaglutide-like medications to treat polycystic ovary syndrome for decades, well before these medications became mainstream.
• The delayed gastric emptying inherent to incretins leads to decreased absorption of birth control pills.
• Finally, while this did not apply to Claudia, no medicine is particularly efficacious if vomited up shortly after taking. Wegovy is known to cause nausea and vomiting in a sizable percentage of patients.

Q: Would she have a healthy pregnancy given the lingering effects of Wegovy?

A: The short answer is: most likely yes. A review of the package insert revealed something fascinating. It was not strictly contraindicated. It advised doctors to weigh the risks and benefits of the medication during pregnancy. Animal studies have shown that semaglutide increases the risk for fetal death, birth defects, and growth issues, but this is probably due to restrictive eating patterns rather than a direct effect of the medication. A recent study of health records of more than 50,000 women with diabetes who had been inadvertently taking these medications in early pregnancy showed no increase in birth defects when compared with women who took insulin.

Q: What would happen to her weight loss efforts?

A: To address her third concern, I tried to offset the risk for rebound weight gain by stopping Wegovy and giving her metformin in the second and third trimesters. Considered a safe medication in pregnancy, metformin is thought to support weight loss, but it proved to be ineffective against the rebound weight gain from stopping Wegovy. Claudia had not resumed regular exercise and quickly fell into the age-old eating-for-two trap. She gained nearly 50 pounds over the course of her pregnancy. 

After a short and unfulfilling attempt at nursing, Claudia restarted Wegovy, this time in conjunction with a Mediterranean meal plan and regular sessions at a fitness club. After losing the pregnancy weight, she has been able to successfully maintain her ideal body weight for the past year, and her baby is perfectly healthy and beautiful. 

*Patient’s name changed. 

A version of this article appeared on Medscape.com.

Claudia* was a charming 27-year-old newlywed. She and her husband wanted to start a family — with one small catch. She had recently gained 30 pounds. During COVID, she and her husband spent 18 months camped out in her parents’ guest room in upstate New York and had eaten their emotions with abandon. They ate when they were happy and ate more when they were sad. They ate when they felt isolated and again when they felt anxious. It didn’t help that her mother was a Culinary Institute–trained amateur chef. They both worked from home and logged long hours on Zoom calls. Because there was no home gym, they replaced their usual fitness club workouts in the city with leisurely strolls around the local lake. When I met her, Claudia categorically refused to entertain the notion of pregnancy until she reached her pre-COVID weight.

At the time, this all seemed quite reasonable to me. We outlined a plan including semaglutide (Wegovy) until she reached her target weight and then a minimum of 2 months off Wegovy prior to conception. We also lined up sessions with a dietitian and trainer and renewed her birth control pill. There was one detail I failed to mention to her: Birth control pills are less effective while on incretin hormones like semaglutide. The reason for my omission is that the medical community at large wasn’t yet aware of this issue. 

About 12 weeks into treatment, Claudia had lost 20 of the 30 pounds. She had canceled several appointments with the trainer and dietitian due to work conflicts. She messaged me over the weekend in a panic. Her period was late, and her pregnancy test was positive.

She had three pressing questions for me:

Q: How had this happened while she had taken the birth control pills faithfully?

A: I answered that the scientific reasons for the decrease in efficacy of birth control pills while on semaglutide medications are threefold: 

• Weight loss can improve menstrual cycle irregularities and improve fertility. In fact, I have been using semaglutide-like medications to treat polycystic ovary syndrome for decades, well before these medications became mainstream.
• The delayed gastric emptying inherent to incretins leads to decreased absorption of birth control pills.
• Finally, while this did not apply to Claudia, no medicine is particularly efficacious if vomited up shortly after taking. Wegovy is known to cause nausea and vomiting in a sizable percentage of patients.

Q: Would she have a healthy pregnancy given the lingering effects of Wegovy?

A: The short answer is: most likely yes. A review of the package insert revealed something fascinating. It was not strictly contraindicated. It advised doctors to weigh the risks and benefits of the medication during pregnancy. Animal studies have shown that semaglutide increases the risk for fetal death, birth defects, and growth issues, but this is probably due to restrictive eating patterns rather than a direct effect of the medication. A recent study of health records of more than 50,000 women with diabetes who had been inadvertently taking these medications in early pregnancy showed no increase in birth defects when compared with women who took insulin.

Q: What would happen to her weight loss efforts?

A: To address her third concern, I tried to offset the risk for rebound weight gain by stopping Wegovy and giving her metformin in the second and third trimesters. Considered a safe medication in pregnancy, metformin is thought to support weight loss, but it proved to be ineffective against the rebound weight gain from stopping Wegovy. Claudia had not resumed regular exercise and quickly fell into the age-old eating-for-two trap. She gained nearly 50 pounds over the course of her pregnancy. 

After a short and unfulfilling attempt at nursing, Claudia restarted Wegovy, this time in conjunction with a Mediterranean meal plan and regular sessions at a fitness club. After losing the pregnancy weight, she has been able to successfully maintain her ideal body weight for the past year, and her baby is perfectly healthy and beautiful. 

*Patient’s name changed. 

A version of this article appeared on Medscape.com.

Claudia* was a charming 27-year-old newlywed. She and her husband wanted to start a family — with one small catch. She had recently gained 30 pounds. During COVID, she and her husband spent 18 months camped out in her parents’ guest room in upstate New York and had eaten their emotions with abandon. They ate when they were happy and ate more when they were sad. They ate when they felt isolated and again when they felt anxious. It didn’t help that her mother was a Culinary Institute–trained amateur chef. They both worked from home and logged long hours on Zoom calls. Because there was no home gym, they replaced their usual fitness club workouts in the city with leisurely strolls around the local lake. When I met her, Claudia categorically refused to entertain the notion of pregnancy until she reached her pre-COVID weight.

At the time, this all seemed quite reasonable to me. We outlined a plan including semaglutide (Wegovy) until she reached her target weight and then a minimum of 2 months off Wegovy prior to conception. We also lined up sessions with a dietitian and trainer and renewed her birth control pill. There was one detail I failed to mention to her: Birth control pills are less effective while on incretin hormones like semaglutide. The reason for my omission is that the medical community at large wasn’t yet aware of this issue. 

About 12 weeks into treatment, Claudia had lost 20 of the 30 pounds. She had canceled several appointments with the trainer and dietitian due to work conflicts. She messaged me over the weekend in a panic. Her period was late, and her pregnancy test was positive.

She had three pressing questions for me:

Q: How had this happened while she had taken the birth control pills faithfully?

A: I answered that the scientific reasons for the decrease in efficacy of birth control pills while on semaglutide medications are threefold: 

• Weight loss can improve menstrual cycle irregularities and improve fertility. In fact, I have been using semaglutide-like medications to treat polycystic ovary syndrome for decades, well before these medications became mainstream.
• The delayed gastric emptying inherent to incretins leads to decreased absorption of birth control pills.
• Finally, while this did not apply to Claudia, no medicine is particularly efficacious if vomited up shortly after taking. Wegovy is known to cause nausea and vomiting in a sizable percentage of patients.

Q: Would she have a healthy pregnancy given the lingering effects of Wegovy?

A: The short answer is: most likely yes. A review of the package insert revealed something fascinating. It was not strictly contraindicated. It advised doctors to weigh the risks and benefits of the medication during pregnancy. Animal studies have shown that semaglutide increases the risk for fetal death, birth defects, and growth issues, but this is probably due to restrictive eating patterns rather than a direct effect of the medication. A recent study of health records of more than 50,000 women with diabetes who had been inadvertently taking these medications in early pregnancy showed no increase in birth defects when compared with women who took insulin.

Q: What would happen to her weight loss efforts?

A: To address her third concern, I tried to offset the risk for rebound weight gain by stopping Wegovy and giving her metformin in the second and third trimesters. Considered a safe medication in pregnancy, metformin is thought to support weight loss, but it proved to be ineffective against the rebound weight gain from stopping Wegovy. Claudia had not resumed regular exercise and quickly fell into the age-old eating-for-two trap. She gained nearly 50 pounds over the course of her pregnancy. 

After a short and unfulfilling attempt at nursing, Claudia restarted Wegovy, this time in conjunction with a Mediterranean meal plan and regular sessions at a fitness club. After losing the pregnancy weight, she has been able to successfully maintain her ideal body weight for the past year, and her baby is perfectly healthy and beautiful. 

*Patient’s name changed. 

A version of this article appeared on Medscape.com.

A distant friend and I were recently chatting by email. After years of trying, she’s become a successful author, and decided to leave medicine to focus on the new career.

She’s excited about this, as it’s really what she’s always dreamed of doing, but at the same time feels guilty about it. Leaving medicine for a new career isn’t quite the same as quitting your job as a waitress or insurance salesman. You’ve put a lot of time, and effort, and money, into becoming an attending physician.

Dr. Block has a solo neurology practice in Scottsdale, Arizona.

A distant friend and I were recently chatting by email. After years of trying, she’s become a successful author, and decided to leave medicine to focus on the new career.

She’s excited about this, as it’s really what she’s always dreamed of doing, but at the same time feels guilty about it. Leaving medicine for a new career isn’t quite the same as quitting your job as a waitress or insurance salesman. You’ve put a lot of time, and effort, and money, into becoming an attending physician.

Dr. Block has a solo neurology practice in Scottsdale, Arizona.

A distant friend and I were recently chatting by email. After years of trying, she’s become a successful author, and decided to leave medicine to focus on the new career.

She’s excited about this, as it’s really what she’s always dreamed of doing, but at the same time feels guilty about it. Leaving medicine for a new career isn’t quite the same as quitting your job as a waitress or insurance salesman. You’ve put a lot of time, and effort, and money, into becoming an attending physician.

Dr. Block has a solo neurology practice in Scottsdale, Arizona.

I have already shared with you that healthcare systems value panel size and productivity when they are considering primary care physician compensation. Your employers also know that the market won’t bear a substantial price increase for the procedure-poor practice style typical of primary care. You know that the relative value unit (RVU) system for calculating complexity of service is time consuming and discourages the inclusion of customer-friendly short visits that could allow an efficient provider to see more patients. Unfortunately, there is little hope that RVUs will become more PCP-friendly in the near future.

However, before leaving the topic of value and moving on to a consideration of quality, I can’t resist sharing some thoughts about efficiency and time management.

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].

I have already shared with you that healthcare systems value panel size and productivity when they are considering primary care physician compensation. Your employers also know that the market won’t bear a substantial price increase for the procedure-poor practice style typical of primary care. You know that the relative value unit (RVU) system for calculating complexity of service is time consuming and discourages the inclusion of customer-friendly short visits that could allow an efficient provider to see more patients. Unfortunately, there is little hope that RVUs will become more PCP-friendly in the near future.

However, before leaving the topic of value and moving on to a consideration of quality, I can’t resist sharing some thoughts about efficiency and time management.

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].

I have already shared with you that healthcare systems value panel size and productivity when they are considering primary care physician compensation. Your employers also know that the market won’t bear a substantial price increase for the procedure-poor practice style typical of primary care. You know that the relative value unit (RVU) system for calculating complexity of service is time consuming and discourages the inclusion of customer-friendly short visits that could allow an efficient provider to see more patients. Unfortunately, there is little hope that RVUs will become more PCP-friendly in the near future.

However, before leaving the topic of value and moving on to a consideration of quality, I can’t resist sharing some thoughts about efficiency and time management.

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].

In a recent article in the American Journal of Obstetrics & Gynecology, Rebecca C. Thurston, PhD, and Pauline Maki, PhD, leading scientists in the area of menopause’s impact on brain function, presented data from their assessment of 248 late perimenopausal and postmenopausal women who reported hot flashes, also known as vasomotor symptoms (VMS).

Hot flashes are known to be associated with changes in brain white matter, carotid atherosclerosis, brain function, and memory. Dr. Thurston and colleagues objectively measured VMS over 24 hours, using skin conductance monitoring. Plasma concentrations of Alzheimer’s disease biomarkers, including the amyloid beta 42–to–amyloid beta 40 ratio, were assessed. The mean age of study participants was 59 years, and they experienced a mean of five objective VMS daily.

A key finding was that VMS, particularly those occurring during sleep, were associated with a significantly lower amyloid beta 42–to–beta 40 ratio. This finding suggests that nighttime VMS may be a marker of risk for Alzheimer’s disease.

Previous research has found that menopausal hormone therapy is associated with favorable changes in Alzheimer’s disease biomarkers. Likewise, large observational studies have shown a lower incidence of Alzheimer’s disease among women who initiate hormone therapy in their late perimenopausal or early postmenopausal years and continue such therapy long term.

The findings of this important study by Thurston and colleagues provide further evidence to support the tantalizing possibility that agents that reduce nighttime hot flashes (including hormone therapy) may lower the subsequent incidence of Alzheimer’s disease in high-risk women.
 

Dr. Kaunitz is a tenured professor and associate chair in the department of obstetrics and gynecology at the University of Florida College of Medicine–Jacksonville, and medical director and director of menopause and gynecologic ultrasound services at the University of Florida Southside Women’s Health, Jacksonville. He disclosed ties to Sumitomo Pharma America, Mithra, Viatris, Bayer, Merck, Mylan (Viatris), and UpToDate.

A version of this article appeared on Medscape.com.

In a recent article in the American Journal of Obstetrics & Gynecology, Rebecca C. Thurston, PhD, and Pauline Maki, PhD, leading scientists in the area of menopause’s impact on brain function, presented data from their assessment of 248 late perimenopausal and postmenopausal women who reported hot flashes, also known as vasomotor symptoms (VMS).

Hot flashes are known to be associated with changes in brain white matter, carotid atherosclerosis, brain function, and memory. Dr. Thurston and colleagues objectively measured VMS over 24 hours, using skin conductance monitoring. Plasma concentrations of Alzheimer’s disease biomarkers, including the amyloid beta 42–to–amyloid beta 40 ratio, were assessed. The mean age of study participants was 59 years, and they experienced a mean of five objective VMS daily.

A key finding was that VMS, particularly those occurring during sleep, were associated with a significantly lower amyloid beta 42–to–beta 40 ratio. This finding suggests that nighttime VMS may be a marker of risk for Alzheimer’s disease.

Previous research has found that menopausal hormone therapy is associated with favorable changes in Alzheimer’s disease biomarkers. Likewise, large observational studies have shown a lower incidence of Alzheimer’s disease among women who initiate hormone therapy in their late perimenopausal or early postmenopausal years and continue such therapy long term.

The findings of this important study by Thurston and colleagues provide further evidence to support the tantalizing possibility that agents that reduce nighttime hot flashes (including hormone therapy) may lower the subsequent incidence of Alzheimer’s disease in high-risk women.
 

Dr. Kaunitz is a tenured professor and associate chair in the department of obstetrics and gynecology at the University of Florida College of Medicine–Jacksonville, and medical director and director of menopause and gynecologic ultrasound services at the University of Florida Southside Women’s Health, Jacksonville. He disclosed ties to Sumitomo Pharma America, Mithra, Viatris, Bayer, Merck, Mylan (Viatris), and UpToDate.

A version of this article appeared on Medscape.com.

In a recent article in the American Journal of Obstetrics & Gynecology, Rebecca C. Thurston, PhD, and Pauline Maki, PhD, leading scientists in the area of menopause’s impact on brain function, presented data from their assessment of 248 late perimenopausal and postmenopausal women who reported hot flashes, also known as vasomotor symptoms (VMS).

Hot flashes are known to be associated with changes in brain white matter, carotid atherosclerosis, brain function, and memory. Dr. Thurston and colleagues objectively measured VMS over 24 hours, using skin conductance monitoring. Plasma concentrations of Alzheimer’s disease biomarkers, including the amyloid beta 42–to–amyloid beta 40 ratio, were assessed. The mean age of study participants was 59 years, and they experienced a mean of five objective VMS daily.

A key finding was that VMS, particularly those occurring during sleep, were associated with a significantly lower amyloid beta 42–to–beta 40 ratio. This finding suggests that nighttime VMS may be a marker of risk for Alzheimer’s disease.

Previous research has found that menopausal hormone therapy is associated with favorable changes in Alzheimer’s disease biomarkers. Likewise, large observational studies have shown a lower incidence of Alzheimer’s disease among women who initiate hormone therapy in their late perimenopausal or early postmenopausal years and continue such therapy long term.

The findings of this important study by Thurston and colleagues provide further evidence to support the tantalizing possibility that agents that reduce nighttime hot flashes (including hormone therapy) may lower the subsequent incidence of Alzheimer’s disease in high-risk women.
 

Dr. Kaunitz is a tenured professor and associate chair in the department of obstetrics and gynecology at the University of Florida College of Medicine–Jacksonville, and medical director and director of menopause and gynecologic ultrasound services at the University of Florida Southside Women’s Health, Jacksonville. He disclosed ties to Sumitomo Pharma America, Mithra, Viatris, Bayer, Merck, Mylan (Viatris), and UpToDate.

A version of this article appeared on Medscape.com.

Historically, endometrial cancer has been classified as type I or type II. Type I endometrial cancers are typically estrogen driven, low grade, with endometrioid histology, and have a more favorable prognosis. In contrast, type II endometrial cancers are typically high grade, have more aggressive histologies (eg, serous or clear cell), and have a poorer prognosis.¹

While this system provides a helpful schema for understanding endometrial cancers, it fails to represent the immense variation of biologic behavior and outcomes in endometrial cancers and oversimplifies what has come to be understood as a complex and molecularly diverse disease.

UNC Chapel Hill

Dr. Haag is a gynecologic oncology fellow in the Department of Obstetrics and Gynecology, University of North Carolina Hospitals, Chapel Hill. Dr. Tucker is assistant professor of gynecologic oncology at the University of North Carolina at Chapel Hill. They have no conflicts of interest.

References

1. Bokhman JV. Two pathogenetic types of endometrial carcinoma. Gynecologic Oncology. 1983;15(1):10-17.

2. Kandoth C et al. Integrated genomic characterization of endometrial carcinoma. Nature. 2013;497(7447):67-73.

3. León-Castillo A et al. Molecular classification of the PORTEC-3 trial for high-risk endometrial cancer: Impact on prognosis and benefit from adjuvant therapy. J Clin Oncology. 2020;38(29):3388-3397.

4. Mirza MR et al. Dostarlimab for primary advanced or recurrent endometrial cancer. N Engl J Med. 2023;388(23):2145-2158.

5. Eskander RN et al. Pembrolizumab plus chemotherapy in advanced endometrial cancer. N Engl J Med. 2023;388(23):2159-2170.

6. Talia KL et al. The role of HER2 as a therapeutic biomarker in gynaecological malignancy: Potential for use beyond uterine serous carcinoma. Pathology. 2023;55(1):8-18.

7. Kommoss S et al. Final validation of the ProMisE molecular classifier for endometrial carcinoma in a large population-based case series. Annals Oncology. 2018;29(5):1180-1188.

8. Berek JS et al. FIGO staging of endometrial cancer: 2023. Int J Gynaecol Obstet. 2023;162(2):383-394.

Historically, endometrial cancer has been classified as type I or type II. Type I endometrial cancers are typically estrogen driven, low grade, with endometrioid histology, and have a more favorable prognosis. In contrast, type II endometrial cancers are typically high grade, have more aggressive histologies (eg, serous or clear cell), and have a poorer prognosis.¹

While this system provides a helpful schema for understanding endometrial cancers, it fails to represent the immense variation of biologic behavior and outcomes in endometrial cancers and oversimplifies what has come to be understood as a complex and molecularly diverse disease.

UNC Chapel Hill

Dr. Haag is a gynecologic oncology fellow in the Department of Obstetrics and Gynecology, University of North Carolina Hospitals, Chapel Hill. Dr. Tucker is assistant professor of gynecologic oncology at the University of North Carolina at Chapel Hill. They have no conflicts of interest.

References

1. Bokhman JV. Two pathogenetic types of endometrial carcinoma. Gynecologic Oncology. 1983;15(1):10-17.

2. Kandoth C et al. Integrated genomic characterization of endometrial carcinoma. Nature. 2013;497(7447):67-73.

3. León-Castillo A et al. Molecular classification of the PORTEC-3 trial for high-risk endometrial cancer: Impact on prognosis and benefit from adjuvant therapy. J Clin Oncology. 2020;38(29):3388-3397.

4. Mirza MR et al. Dostarlimab for primary advanced or recurrent endometrial cancer. N Engl J Med. 2023;388(23):2145-2158.

5. Eskander RN et al. Pembrolizumab plus chemotherapy in advanced endometrial cancer. N Engl J Med. 2023;388(23):2159-2170.

6. Talia KL et al. The role of HER2 as a therapeutic biomarker in gynaecological malignancy: Potential for use beyond uterine serous carcinoma. Pathology. 2023;55(1):8-18.

7. Kommoss S et al. Final validation of the ProMisE molecular classifier for endometrial carcinoma in a large population-based case series. Annals Oncology. 2018;29(5):1180-1188.

8. Berek JS et al. FIGO staging of endometrial cancer: 2023. Int J Gynaecol Obstet. 2023;162(2):383-394.

Historically, endometrial cancer has been classified as type I or type II. Type I endometrial cancers are typically estrogen driven, low grade, with endometrioid histology, and have a more favorable prognosis. In contrast, type II endometrial cancers are typically high grade, have more aggressive histologies (eg, serous or clear cell), and have a poorer prognosis.¹

While this system provides a helpful schema for understanding endometrial cancers, it fails to represent the immense variation of biologic behavior and outcomes in endometrial cancers and oversimplifies what has come to be understood as a complex and molecularly diverse disease.

UNC Chapel Hill

Dr. Haag is a gynecologic oncology fellow in the Department of Obstetrics and Gynecology, University of North Carolina Hospitals, Chapel Hill. Dr. Tucker is assistant professor of gynecologic oncology at the University of North Carolina at Chapel Hill. They have no conflicts of interest.

References

1. Bokhman JV. Two pathogenetic types of endometrial carcinoma. Gynecologic Oncology. 1983;15(1):10-17.

2. Kandoth C et al. Integrated genomic characterization of endometrial carcinoma. Nature. 2013;497(7447):67-73.

3. León-Castillo A et al. Molecular classification of the PORTEC-3 trial for high-risk endometrial cancer: Impact on prognosis and benefit from adjuvant therapy. J Clin Oncology. 2020;38(29):3388-3397.

4. Mirza MR et al. Dostarlimab for primary advanced or recurrent endometrial cancer. N Engl J Med. 2023;388(23):2145-2158.

5. Eskander RN et al. Pembrolizumab plus chemotherapy in advanced endometrial cancer. N Engl J Med. 2023;388(23):2159-2170.

6. Talia KL et al. The role of HER2 as a therapeutic biomarker in gynaecological malignancy: Potential for use beyond uterine serous carcinoma. Pathology. 2023;55(1):8-18.

7. Kommoss S et al. Final validation of the ProMisE molecular classifier for endometrial carcinoma in a large population-based case series. Annals Oncology. 2018;29(5):1180-1188.

8. Berek JS et al. FIGO staging of endometrial cancer: 2023. Int J Gynaecol Obstet. 2023;162(2):383-394.

As we settle back into our daily routines following another fantastic DDW, I’d like to take a moment to congratulate this year’s AGA’s Recognition Award recipients, who have made outstanding contributions to the organization and to our field, including through excellence in clinical practice, research, mentorship, and DEI.

This month’s Member Spotlight column highlights one of these remarkable individuals, Dr. Scott Ketover, president and CEO of MNGI Digestive Health, who is the recipient of this year’s AGA Distinguished Clinician Award in Private Practice. We hope you enjoy learning more about Scott, as well as the other award recipients who were recognized at a special ceremony in DC last month.

University of Michigan

Also highlighted in our June issue is the FDA’s recent approval of subcutaneous vedolizumab for Crohn’s maintenance therapy, an exciting development that will provide us with more flexible treatment options for our patients. We also report on the 2024 AGA Tech Summit (Chicago, IL), and introduce the winners (survivors?) of its annual Shark Tank competition, Dr. Renu Dhanasekaran and Dr. Venthan Elango. Their company, Arithmedics, which developed technology that harnesses generative AI and data intelligence to streamline medical billing, was identified as the most promising among a robust field of entrants.

We also present some of the best clinically oriented content from our GI journals, including an observational study from Gastroenterology evaluating the effect of longitudinal alcohol use on risk of cirrhosis among patients with steatotic liver disease, and summarize recently released AGA Clinical Practice Updates on performance of high-quality upper endoscopy and treatment of cannabinoid hyperemesis syndrome. We hope you enjoy all the exciting content featured in this issue and take some well-deserved time to rest and recharge this summer!

Megan A. Adams, MD, JD, MSc

Editor-in-Chief

As we settle back into our daily routines following another fantastic DDW, I’d like to take a moment to congratulate this year’s AGA’s Recognition Award recipients, who have made outstanding contributions to the organization and to our field, including through excellence in clinical practice, research, mentorship, and DEI.

This month’s Member Spotlight column highlights one of these remarkable individuals, Dr. Scott Ketover, president and CEO of MNGI Digestive Health, who is the recipient of this year’s AGA Distinguished Clinician Award in Private Practice. We hope you enjoy learning more about Scott, as well as the other award recipients who were recognized at a special ceremony in DC last month.

University of Michigan

Also highlighted in our June issue is the FDA’s recent approval of subcutaneous vedolizumab for Crohn’s maintenance therapy, an exciting development that will provide us with more flexible treatment options for our patients. We also report on the 2024 AGA Tech Summit (Chicago, IL), and introduce the winners (survivors?) of its annual Shark Tank competition, Dr. Renu Dhanasekaran and Dr. Venthan Elango. Their company, Arithmedics, which developed technology that harnesses generative AI and data intelligence to streamline medical billing, was identified as the most promising among a robust field of entrants.

We also present some of the best clinically oriented content from our GI journals, including an observational study from Gastroenterology evaluating the effect of longitudinal alcohol use on risk of cirrhosis among patients with steatotic liver disease, and summarize recently released AGA Clinical Practice Updates on performance of high-quality upper endoscopy and treatment of cannabinoid hyperemesis syndrome. We hope you enjoy all the exciting content featured in this issue and take some well-deserved time to rest and recharge this summer!

Megan A. Adams, MD, JD, MSc

Editor-in-Chief

As we settle back into our daily routines following another fantastic DDW, I’d like to take a moment to congratulate this year’s AGA’s Recognition Award recipients, who have made outstanding contributions to the organization and to our field, including through excellence in clinical practice, research, mentorship, and DEI.

This month’s Member Spotlight column highlights one of these remarkable individuals, Dr. Scott Ketover, president and CEO of MNGI Digestive Health, who is the recipient of this year’s AGA Distinguished Clinician Award in Private Practice. We hope you enjoy learning more about Scott, as well as the other award recipients who were recognized at a special ceremony in DC last month.

University of Michigan

Also highlighted in our June issue is the FDA’s recent approval of subcutaneous vedolizumab for Crohn’s maintenance therapy, an exciting development that will provide us with more flexible treatment options for our patients. We also report on the 2024 AGA Tech Summit (Chicago, IL), and introduce the winners (survivors?) of its annual Shark Tank competition, Dr. Renu Dhanasekaran and Dr. Venthan Elango. Their company, Arithmedics, which developed technology that harnesses generative AI and data intelligence to streamline medical billing, was identified as the most promising among a robust field of entrants.

We also present some of the best clinically oriented content from our GI journals, including an observational study from Gastroenterology evaluating the effect of longitudinal alcohol use on risk of cirrhosis among patients with steatotic liver disease, and summarize recently released AGA Clinical Practice Updates on performance of high-quality upper endoscopy and treatment of cannabinoid hyperemesis syndrome. We hope you enjoy all the exciting content featured in this issue and take some well-deserved time to rest and recharge this summer!

Megan A. Adams, MD, JD, MSc

Editor-in-Chief

In Part 2 of this series on PCP Compensation, I concluded by saying that it is possible, maybe even likely, that growing your panel size will further endanger your health. When you share this concern with your boss, based purely on economic principles, he or she should answer, “How about charging more per visit?” However, your boss knows that third-party payers are going to look askance at that simple strategy. He or she may then suggest that you make each visit worth more to justify the increased charge.

Here is where the topic of Relative Value Units (RVUs) raises its ugly head.

Before the invention of “health insurance,” when the patient paid for his or her own office visits, it was an unspoken negotiation between patient and physician that decided the value of the care.

When third-party payers first came on the scene, the value of the visit was based roughly on the time spent with the patient. Coupling time spent with value gave no credit to more experienced or skilled physicians who were more efficient at managing their patients. If, on average, it took me 10 minutes to effectively manage an ear infection and my younger associate 20 minutes, should he or she be paid twice as much as I’m paid?

But, value spent on a crude estimate of time spent was a system ripe for abuse.

I have no way of knowing what other physicians were doing, but I suspect I was not alone in factoring my own assessment of “complexity” into the calculation when deciding what to bill for a visit, giving only a passing glance at the recommended time-based definitions of short, standard, and complex visits. The payers then began demanding a more definable method of determining complexity. The result was the RVU, the labor-intensive, but no more accurate, system in which the provider must build a case to defend his or her charges.

Unfortunately, the institution of the RVU system was a major contributor to the death of the short visit. The extra work required to submit and defend the coding of any visit meant that, from a strictly clerical point of view, the short visit became as costly to the business to process as a more complex visit. The result was that every astute business consultant worth his or her salt would begin with the recommendation to “Code up!” Do whatever it takes to build your case for a more complex visit even though it may be a stretch. (It would certainly mean a lot more time-gobbling documenting.) Stop doing short visits. They are your loss leaders.

Before there were RVUs, there was a way physicians could be profitable and include short visits in their schedule. But it meant the provider had to be efficient. But patients generally don’t like going to follow-up visits they see as needless. And, more often than not, the patients are correct. However, patients love the same-day availability that an abundance of short visits in a primary care provider’s schedule can offer. The patient who knows that he or she won’t have to wait weeks or months to see the provider is far less likely to show up at a visit with a laundry list as long as their arm of problems and questions they have saved up while they were waiting to get an appointment. It used to be possible to provide efficient and profitable care by including short visits in a PCP’s schedule. Whether it can still be done under the current RVU system is unclear and probably doubtful.

In the last and final Letter in this series, we will begin with a brief look at efficiency and a PCP’s contribution to overhead before exploring the more difficult subject of defining the quality of a provider’s care and how this could relate to compensation.
 

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].

In Part 2 of this series on PCP Compensation, I concluded by saying that it is possible, maybe even likely, that growing your panel size will further endanger your health. When you share this concern with your boss, based purely on economic principles, he or she should answer, “How about charging more per visit?” However, your boss knows that third-party payers are going to look askance at that simple strategy. He or she may then suggest that you make each visit worth more to justify the increased charge.

Here is where the topic of Relative Value Units (RVUs) raises its ugly head.

Before the invention of “health insurance,” when the patient paid for his or her own office visits, it was an unspoken negotiation between patient and physician that decided the value of the care.

When third-party payers first came on the scene, the value of the visit was based roughly on the time spent with the patient. Coupling time spent with value gave no credit to more experienced or skilled physicians who were more efficient at managing their patients. If, on average, it took me 10 minutes to effectively manage an ear infection and my younger associate 20 minutes, should he or she be paid twice as much as I’m paid?

But, value spent on a crude estimate of time spent was a system ripe for abuse.

I have no way of knowing what other physicians were doing, but I suspect I was not alone in factoring my own assessment of “complexity” into the calculation when deciding what to bill for a visit, giving only a passing glance at the recommended time-based definitions of short, standard, and complex visits. The payers then began demanding a more definable method of determining complexity. The result was the RVU, the labor-intensive, but no more accurate, system in which the provider must build a case to defend his or her charges.

Unfortunately, the institution of the RVU system was a major contributor to the death of the short visit. The extra work required to submit and defend the coding of any visit meant that, from a strictly clerical point of view, the short visit became as costly to the business to process as a more complex visit. The result was that every astute business consultant worth his or her salt would begin with the recommendation to “Code up!” Do whatever it takes to build your case for a more complex visit even though it may be a stretch. (It would certainly mean a lot more time-gobbling documenting.) Stop doing short visits. They are your loss leaders.

Before there were RVUs, there was a way physicians could be profitable and include short visits in their schedule. But it meant the provider had to be efficient. But patients generally don’t like going to follow-up visits they see as needless. And, more often than not, the patients are correct. However, patients love the same-day availability that an abundance of short visits in a primary care provider’s schedule can offer. The patient who knows that he or she won’t have to wait weeks or months to see the provider is far less likely to show up at a visit with a laundry list as long as their arm of problems and questions they have saved up while they were waiting to get an appointment. It used to be possible to provide efficient and profitable care by including short visits in a PCP’s schedule. Whether it can still be done under the current RVU system is unclear and probably doubtful.

In the last and final Letter in this series, we will begin with a brief look at efficiency and a PCP’s contribution to overhead before exploring the more difficult subject of defining the quality of a provider’s care and how this could relate to compensation.
 

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].

In Part 2 of this series on PCP Compensation, I concluded by saying that it is possible, maybe even likely, that growing your panel size will further endanger your health. When you share this concern with your boss, based purely on economic principles, he or she should answer, “How about charging more per visit?” However, your boss knows that third-party payers are going to look askance at that simple strategy. He or she may then suggest that you make each visit worth more to justify the increased charge.

Here is where the topic of Relative Value Units (RVUs) raises its ugly head.

Before the invention of “health insurance,” when the patient paid for his or her own office visits, it was an unspoken negotiation between patient and physician that decided the value of the care.

When third-party payers first came on the scene, the value of the visit was based roughly on the time spent with the patient. Coupling time spent with value gave no credit to more experienced or skilled physicians who were more efficient at managing their patients. If, on average, it took me 10 minutes to effectively manage an ear infection and my younger associate 20 minutes, should he or she be paid twice as much as I’m paid?

But, value spent on a crude estimate of time spent was a system ripe for abuse.

I have no way of knowing what other physicians were doing, but I suspect I was not alone in factoring my own assessment of “complexity” into the calculation when deciding what to bill for a visit, giving only a passing glance at the recommended time-based definitions of short, standard, and complex visits. The payers then began demanding a more definable method of determining complexity. The result was the RVU, the labor-intensive, but no more accurate, system in which the provider must build a case to defend his or her charges.

Unfortunately, the institution of the RVU system was a major contributor to the death of the short visit. The extra work required to submit and defend the coding of any visit meant that, from a strictly clerical point of view, the short visit became as costly to the business to process as a more complex visit. The result was that every astute business consultant worth his or her salt would begin with the recommendation to “Code up!” Do whatever it takes to build your case for a more complex visit even though it may be a stretch. (It would certainly mean a lot more time-gobbling documenting.) Stop doing short visits. They are your loss leaders.

Before there were RVUs, there was a way physicians could be profitable and include short visits in their schedule. But it meant the provider had to be efficient. But patients generally don’t like going to follow-up visits they see as needless. And, more often than not, the patients are correct. However, patients love the same-day availability that an abundance of short visits in a primary care provider’s schedule can offer. The patient who knows that he or she won’t have to wait weeks or months to see the provider is far less likely to show up at a visit with a laundry list as long as their arm of problems and questions they have saved up while they were waiting to get an appointment. It used to be possible to provide efficient and profitable care by including short visits in a PCP’s schedule. Whether it can still be done under the current RVU system is unclear and probably doubtful.

In the last and final Letter in this series, we will begin with a brief look at efficiency and a PCP’s contribution to overhead before exploring the more difficult subject of defining the quality of a provider’s care and how this could relate to compensation.
 

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].

This transcript has been edited for clarity.

As you all know by now, I’m always looking out for lifestyle changes that are both pleasurable and healthy. They are hard to find, especially when it comes to diet. My kids complain about this all the time: “When you say ‘healthy food,’ you just mean yucky food.” And yes, French fries are amazing, and no, we can’t have them three times a day.

So, when I saw an article claiming that olive oil reduces the risk for dementia, I was interested. I love olive oil; I cook with it all the time. But as is always the case in the world of nutritional epidemiology, we need to be careful. There are a lot of reasons to doubt the results of this study — and one reason to believe it’s true.

The study I’m talking about is “Consumption of Olive Oil and Diet Quality and Risk of Dementia-Related Death,” appearing in JAMA Network Open and following a well-trod formula in the nutritional epidemiology space.

Nearly 100,000 participants, all healthcare workers, filled out a food frequency questionnaire every 4 years with 130 questions touching on all aspects of diet: How often do you eat bananas, bacon, olive oil? Participants were followed for more than 20 years, and if they died, the cause of death was flagged as being dementia-related or not. Over that time frame there were around 38,000 deaths, of which 4751 were due to dementia.

The rest is just statistics. The authors show that those who reported consuming more olive oil were less likely to die from dementia — about 50% less likely, if you compare those who reported eating more than 7 grams of olive oil a day with those who reported eating none.
 

Is It What You Eat, or What You Don’t Eat?

And we could stop there if we wanted to; I’m sure big olive oil would be happy with that. Is there such a thing as “big olive oil”? But no, we need to dig deeper here because this study has the same problems as all nutritional epidemiology studies. Number one, no one is sitting around drinking small cups of olive oil. They consume it with other foods. And it was clear from the food frequency questionnaire that people who consumed more olive oil also consumed less red meat, more fruits and vegetables, more whole grains, more butter, and less margarine. And those are just the findings reported in the paper. I suspect that people who eat more olive oil also eat more tomatoes, for example, though data this granular aren’t shown. So, it can be really hard, in studies like this, to know for sure that it’s actually the olive oil that is helpful rather than some other constituent in the diet.

The flip side of that coin presents another issue. The food you eat is also a marker of the food you don’t eat. People who ate olive oil consumed less margarine, for example. At the time of this study, margarine was still adulterated with trans-fats, which a pretty solid evidence base suggests are really bad for your vascular system. So perhaps it’s not that olive oil is particularly good for you but that something else is bad for you. In other words, simply adding olive oil to your diet without changing anything else may not do anything.

The other major problem with studies of this sort is that people don’t consume food at random. The type of person who eats a lot of olive oil is simply different from the type of person who doesn›t. For one thing, olive oil is expensive. A 25-ounce bottle of olive oil is on sale at my local supermarket right now for $11.00. A similar-sized bottle of vegetable oil goes for $4.00.

Isn’t it interesting that food that costs more money tends to be associated with better health outcomes? (I’m looking at you, red wine.) Perhaps it’s not the food; perhaps it’s the money. We aren’t provided data on household income in this study, but we can see that the heavy olive oil users were less likely to be current smokers and they got more physical activity.

Now, the authors are aware of these limitations and do their best to account for them. In multivariable models, they adjust for other stuff in the diet, and even for income (sort of; they use census tract as a proxy for income, which is really a broad brush), and still find a significant though weakened association showing a protective effect of olive oil on dementia-related death. But still — adjustment is never perfect, and the small effect size here could definitely be due to residual confounding.
 

Evidence More Convincing

Now, I did tell you that there is one reason to believe that this study is true, but it’s not really from this study.

It’s from the PREDIMED randomized trial.

This is nutritional epidemiology I can get behind. Published in 2018, investigators in Spain randomized around 7500 participants to receive a liter of olive oil once a week vs mixed nuts, vs small nonfood gifts, the idea here being that if you have olive oil around, you’ll use it more. And people who were randomly assigned to get the olive oil had a 30% lower rate of cardiovascular events. A secondary analysis of that study found that the rate of development of mild cognitive impairment was 65% lower in those who were randomly assigned to olive oil. That’s an impressive result.

So, there might be something to this olive oil thing, but I’m not quite ready to add it to my “pleasurable things that are still good for you” list just yet. Though it does make me wonder: Can we make French fries in the stuff?
 

Dr. Wilson is associate professor of medicine and public health and director of the Clinical and Translational Research Accelerator at Yale University, New Haven, Conn. He has disclosed no relevant financial relationships.

A version of this article appeared on Medscape.com.

This transcript has been edited for clarity.

As you all know by now, I’m always looking out for lifestyle changes that are both pleasurable and healthy. They are hard to find, especially when it comes to diet. My kids complain about this all the time: “When you say ‘healthy food,’ you just mean yucky food.” And yes, French fries are amazing, and no, we can’t have them three times a day.

So, when I saw an article claiming that olive oil reduces the risk for dementia, I was interested. I love olive oil; I cook with it all the time. But as is always the case in the world of nutritional epidemiology, we need to be careful. There are a lot of reasons to doubt the results of this study — and one reason to believe it’s true.

The study I’m talking about is “Consumption of Olive Oil and Diet Quality and Risk of Dementia-Related Death,” appearing in JAMA Network Open and following a well-trod formula in the nutritional epidemiology space.

Nearly 100,000 participants, all healthcare workers, filled out a food frequency questionnaire every 4 years with 130 questions touching on all aspects of diet: How often do you eat bananas, bacon, olive oil? Participants were followed for more than 20 years, and if they died, the cause of death was flagged as being dementia-related or not. Over that time frame there were around 38,000 deaths, of which 4751 were due to dementia.

The rest is just statistics. The authors show that those who reported consuming more olive oil were less likely to die from dementia — about 50% less likely, if you compare those who reported eating more than 7 grams of olive oil a day with those who reported eating none.
 

Is It What You Eat, or What You Don’t Eat?

And we could stop there if we wanted to; I’m sure big olive oil would be happy with that. Is there such a thing as “big olive oil”? But no, we need to dig deeper here because this study has the same problems as all nutritional epidemiology studies. Number one, no one is sitting around drinking small cups of olive oil. They consume it with other foods. And it was clear from the food frequency questionnaire that people who consumed more olive oil also consumed less red meat, more fruits and vegetables, more whole grains, more butter, and less margarine. And those are just the findings reported in the paper. I suspect that people who eat more olive oil also eat more tomatoes, for example, though data this granular aren’t shown. So, it can be really hard, in studies like this, to know for sure that it’s actually the olive oil that is helpful rather than some other constituent in the diet.

The flip side of that coin presents another issue. The food you eat is also a marker of the food you don’t eat. People who ate olive oil consumed less margarine, for example. At the time of this study, margarine was still adulterated with trans-fats, which a pretty solid evidence base suggests are really bad for your vascular system. So perhaps it’s not that olive oil is particularly good for you but that something else is bad for you. In other words, simply adding olive oil to your diet without changing anything else may not do anything.

The other major problem with studies of this sort is that people don’t consume food at random. The type of person who eats a lot of olive oil is simply different from the type of person who doesn›t. For one thing, olive oil is expensive. A 25-ounce bottle of olive oil is on sale at my local supermarket right now for $11.00. A similar-sized bottle of vegetable oil goes for $4.00.

Isn’t it interesting that food that costs more money tends to be associated with better health outcomes? (I’m looking at you, red wine.) Perhaps it’s not the food; perhaps it’s the money. We aren’t provided data on household income in this study, but we can see that the heavy olive oil users were less likely to be current smokers and they got more physical activity.

Now, the authors are aware of these limitations and do their best to account for them. In multivariable models, they adjust for other stuff in the diet, and even for income (sort of; they use census tract as a proxy for income, which is really a broad brush), and still find a significant though weakened association showing a protective effect of olive oil on dementia-related death. But still — adjustment is never perfect, and the small effect size here could definitely be due to residual confounding.
 

Evidence More Convincing

Now, I did tell you that there is one reason to believe that this study is true, but it’s not really from this study.

It’s from the PREDIMED randomized trial.

This is nutritional epidemiology I can get behind. Published in 2018, investigators in Spain randomized around 7500 participants to receive a liter of olive oil once a week vs mixed nuts, vs small nonfood gifts, the idea here being that if you have olive oil around, you’ll use it more. And people who were randomly assigned to get the olive oil had a 30% lower rate of cardiovascular events. A secondary analysis of that study found that the rate of development of mild cognitive impairment was 65% lower in those who were randomly assigned to olive oil. That’s an impressive result.

So, there might be something to this olive oil thing, but I’m not quite ready to add it to my “pleasurable things that are still good for you” list just yet. Though it does make me wonder: Can we make French fries in the stuff?
 

Dr. Wilson is associate professor of medicine and public health and director of the Clinical and Translational Research Accelerator at Yale University, New Haven, Conn. He has disclosed no relevant financial relationships.

A version of this article appeared on Medscape.com.

This transcript has been edited for clarity.

As you all know by now, I’m always looking out for lifestyle changes that are both pleasurable and healthy. They are hard to find, especially when it comes to diet. My kids complain about this all the time: “When you say ‘healthy food,’ you just mean yucky food.” And yes, French fries are amazing, and no, we can’t have them three times a day.

So, when I saw an article claiming that olive oil reduces the risk for dementia, I was interested. I love olive oil; I cook with it all the time. But as is always the case in the world of nutritional epidemiology, we need to be careful. There are a lot of reasons to doubt the results of this study — and one reason to believe it’s true.

The study I’m talking about is “Consumption of Olive Oil and Diet Quality and Risk of Dementia-Related Death,” appearing in JAMA Network Open and following a well-trod formula in the nutritional epidemiology space.

Nearly 100,000 participants, all healthcare workers, filled out a food frequency questionnaire every 4 years with 130 questions touching on all aspects of diet: How often do you eat bananas, bacon, olive oil? Participants were followed for more than 20 years, and if they died, the cause of death was flagged as being dementia-related or not. Over that time frame there were around 38,000 deaths, of which 4751 were due to dementia.

The rest is just statistics. The authors show that those who reported consuming more olive oil were less likely to die from dementia — about 50% less likely, if you compare those who reported eating more than 7 grams of olive oil a day with those who reported eating none.
 

Is It What You Eat, or What You Don’t Eat?

And we could stop there if we wanted to; I’m sure big olive oil would be happy with that. Is there such a thing as “big olive oil”? But no, we need to dig deeper here because this study has the same problems as all nutritional epidemiology studies. Number one, no one is sitting around drinking small cups of olive oil. They consume it with other foods. And it was clear from the food frequency questionnaire that people who consumed more olive oil also consumed less red meat, more fruits and vegetables, more whole grains, more butter, and less margarine. And those are just the findings reported in the paper. I suspect that people who eat more olive oil also eat more tomatoes, for example, though data this granular aren’t shown. So, it can be really hard, in studies like this, to know for sure that it’s actually the olive oil that is helpful rather than some other constituent in the diet.

The flip side of that coin presents another issue. The food you eat is also a marker of the food you don’t eat. People who ate olive oil consumed less margarine, for example. At the time of this study, margarine was still adulterated with trans-fats, which a pretty solid evidence base suggests are really bad for your vascular system. So perhaps it’s not that olive oil is particularly good for you but that something else is bad for you. In other words, simply adding olive oil to your diet without changing anything else may not do anything.

The other major problem with studies of this sort is that people don’t consume food at random. The type of person who eats a lot of olive oil is simply different from the type of person who doesn›t. For one thing, olive oil is expensive. A 25-ounce bottle of olive oil is on sale at my local supermarket right now for $11.00. A similar-sized bottle of vegetable oil goes for $4.00.

Isn’t it interesting that food that costs more money tends to be associated with better health outcomes? (I’m looking at you, red wine.) Perhaps it’s not the food; perhaps it’s the money. We aren’t provided data on household income in this study, but we can see that the heavy olive oil users were less likely to be current smokers and they got more physical activity.

Now, the authors are aware of these limitations and do their best to account for them. In multivariable models, they adjust for other stuff in the diet, and even for income (sort of; they use census tract as a proxy for income, which is really a broad brush), and still find a significant though weakened association showing a protective effect of olive oil on dementia-related death. But still — adjustment is never perfect, and the small effect size here could definitely be due to residual confounding.
 

Evidence More Convincing

Now, I did tell you that there is one reason to believe that this study is true, but it’s not really from this study.

It’s from the PREDIMED randomized trial.

This is nutritional epidemiology I can get behind. Published in 2018, investigators in Spain randomized around 7500 participants to receive a liter of olive oil once a week vs mixed nuts, vs small nonfood gifts, the idea here being that if you have olive oil around, you’ll use it more. And people who were randomly assigned to get the olive oil had a 30% lower rate of cardiovascular events. A secondary analysis of that study found that the rate of development of mild cognitive impairment was 65% lower in those who were randomly assigned to olive oil. That’s an impressive result.

So, there might be something to this olive oil thing, but I’m not quite ready to add it to my “pleasurable things that are still good for you” list just yet. Though it does make me wonder: Can we make French fries in the stuff?
 

Dr. Wilson is associate professor of medicine and public health and director of the Clinical and Translational Research Accelerator at Yale University, New Haven, Conn. He has disclosed no relevant financial relationships.

A version of this article appeared on Medscape.com.

Observational studies on red meat consumption and lifespan are prime examples of attempts to find signal in a sea of noise. 

Randomized controlled trials are the best way to sort cause from mere correlation. But these are not possible in most matters of food consumption. So, we look back and observe groups with different exposures.

My most frequent complaint about these nonrandom comparison studies has been the chance that the two groups differ in important ways, and it’s these differences — not the food in question — that account for the disparate outcomes.

But selection biases are only one issue. There is also the matter of analytic flexibility. Observational studies are born from large databases. Researchers have many choices in how to analyze all these data.

A few years ago, Brian Nosek, PhD, and colleagues elegantly showed that analytic choices can affect results. His Many Analysts, One Data Set study had little uptake in the medical community, perhaps because he studied a social science question.
 

Multiple Ways to Slice the Data

Recently, a group from McMaster University, led by Dena Zeraatkar, PhD, has confirmed the analytic choices problem, using the question of red meat consumption and mortality. 

Their idea was simple: Because there are many plausible and defensible ways to analyze a dataset, we should not choose one method; rather, we should choose thousands, combine the results, and see where the truth lies. 

You might wonder how there could be thousands of ways to analyze a dataset. I surely did. 

The answer stems from the choices that researchers face. For instance, there is the selection of eligible participants, the choice of analytic model (logistic, Poisson, etc.), and covariates for which to adjust. Think exponents when combining possible choices.

Dr. Zeraatkar and colleagues are research methodologists, so, sadly, they are comfortable with the clunky name of this approach: specification curve analysis. Don’t be deterred. It means that they analyze the data in thousands of ways using computers. Each way is a specification. In the end, the specifications give rise to a curve of hazard ratios for red meat and mortality. Another name for this approach is multiverse analysis.

For their paper in the Journal of Clinical Epidemiology, aptly named “Grilling the Data,” they didn’t just conjure up the many analytic ways to study the red meat–mortality question. Instead, they used a published systematic review of 15 studies on unprocessed red meat and early mortality. The studies included in this review reported 70 unique ways to analyze the association. 
 

Is Red Meat Good or Bad?

Their first finding was that this analysis yielded widely disparate effect estimates, from 0.63 (reduced risk for early death) to 2.31 (a higher risk). The median hazard ratio was 1.14 with an interquartile range (IQR) of 1.02-1.23. One might conclude from this that eating red meat is associated with a slightly higher risk for early mortality. 

Their second step was to calculate how many ways (specifications) there were to analyze the data by totaling all possible combinations of choices in the 70 ways found in the systematic review. 

They calculated a total of 10 quadrillion possible unique analyses. A quadrillion is 1 with 15 zeros. Computing power cannot handle that amount of analyses yet. So, they generated 20 random unique combinations of covariates, which narrowed the number of analyses to about 1400. About 200 of these were excluded due to implausibly wide confidence intervals. 

Voilà. They now had about 1200 different ways to analyze a dataset; they chose an NHANES longitudinal cohort study from 2007-2014. They deemed each of the more than 1200 approaches plausible because they were derived from peer-reviewed papers written by experts in epidemiology. 
 

Specification Curve Analyses Results 

Each analysis (or specification) yielded a hazard ratio for red meat exposure and death.

• The median HR was 0.94 (IQR, 0.83-1.05) for the effect of red meat on all-cause mortality — ie, not significant.
• The range of hazard ratios was large. They went from 0.51 — a 49% reduced risk for early mortality — to 1.75: a 75% increase in early mortality.
• Among all analyses, 36% yielded hazard ratios above 1.0 and 64% less than 1.0.
• As for statistical significance, defined as P ≤.05, only 4% (or 48 specifications) met this threshold. Zeraatkar reminded me that this is what you’d expect if unprocessed red meat has no effect on longevity.
• Of the 48 analyses deemed statistically significant, 40 indicated that red meat consumption reduced early death and eight indicated that eating red meat led to higher mortality.
• Nearly half the analyses yielded unexciting point estimates, with hazard ratios between 0.90 and 1.10.

Paradigm Changing 

As a user of evidence, I find this a potentially paradigm-changing study. Observational studies far outnumber randomized trials. For many medical questions, observational data are all we have. 

Now think about every observational study published. The authors tell you — post hoc — which method they used to analyze the data. The key point is that it is one method. 

Dr. Zeraatkar and colleagues have shown that there are thousands of plausible ways to analyze the data, and this can lead to very different findings. In the specific question of red meat and mortality, their many analyses yielded a null result. 

Now imagine other cases where the researchers did many analyses of a dataset and chose to publish only the significant ones. Observational studies are rarely preregistered, so a reader cannot know how a result would vary depending on analytic choices. A specification curve analysis of a dataset provides a much broader picture. In the case of red meat, you see some significant results, but the vast majority hover around null. 

What about the difficulty in analyzing a dataset 1000 different ways? Dr. Zeraatkar told me that it is harder than just choosing one method, but it’s not impossible. 

The main barrier to adopting this multiverse approach to data, she noted, was not the extra work but the entrenched belief among researchers that there is a best way to analyze data. 

I hope you read this paper and think about it every time you read an observational study that finds a positive or negative association between two things. Ask: What if the researchers were as careful as Dr. Zeraatkar and colleagues and did multiple different analyses? Would the finding hold up to a series of plausible analytic choices? 

Nutritional epidemiology would benefit greatly from this approach. But so would any observational study of an exposure and outcome. I suspect that the number of “positive” associations would diminish. And that would not be a bad thing.

 

Dr. Mandrola, a clinical electrophysiologist at Baptist Medical Associates, Louisville, Kentucky, disclosed no relevant financial relationships.

A version of this article appeared on Medscape.com.

Observational studies on red meat consumption and lifespan are prime examples of attempts to find signal in a sea of noise. 

Randomized controlled trials are the best way to sort cause from mere correlation. But these are not possible in most matters of food consumption. So, we look back and observe groups with different exposures.

My most frequent complaint about these nonrandom comparison studies has been the chance that the two groups differ in important ways, and it’s these differences — not the food in question — that account for the disparate outcomes.

But selection biases are only one issue. There is also the matter of analytic flexibility. Observational studies are born from large databases. Researchers have many choices in how to analyze all these data.

A few years ago, Brian Nosek, PhD, and colleagues elegantly showed that analytic choices can affect results. His Many Analysts, One Data Set study had little uptake in the medical community, perhaps because he studied a social science question.
 

Multiple Ways to Slice the Data

Recently, a group from McMaster University, led by Dena Zeraatkar, PhD, has confirmed the analytic choices problem, using the question of red meat consumption and mortality. 

Their idea was simple: Because there are many plausible and defensible ways to analyze a dataset, we should not choose one method; rather, we should choose thousands, combine the results, and see where the truth lies. 

You might wonder how there could be thousands of ways to analyze a dataset. I surely did. 

The answer stems from the choices that researchers face. For instance, there is the selection of eligible participants, the choice of analytic model (logistic, Poisson, etc.), and covariates for which to adjust. Think exponents when combining possible choices.

Dr. Zeraatkar and colleagues are research methodologists, so, sadly, they are comfortable with the clunky name of this approach: specification curve analysis. Don’t be deterred. It means that they analyze the data in thousands of ways using computers. Each way is a specification. In the end, the specifications give rise to a curve of hazard ratios for red meat and mortality. Another name for this approach is multiverse analysis.

For their paper in the Journal of Clinical Epidemiology, aptly named “Grilling the Data,” they didn’t just conjure up the many analytic ways to study the red meat–mortality question. Instead, they used a published systematic review of 15 studies on unprocessed red meat and early mortality. The studies included in this review reported 70 unique ways to analyze the association. 
 

Is Red Meat Good or Bad?

Their first finding was that this analysis yielded widely disparate effect estimates, from 0.63 (reduced risk for early death) to 2.31 (a higher risk). The median hazard ratio was 1.14 with an interquartile range (IQR) of 1.02-1.23. One might conclude from this that eating red meat is associated with a slightly higher risk for early mortality. 

Their second step was to calculate how many ways (specifications) there were to analyze the data by totaling all possible combinations of choices in the 70 ways found in the systematic review. 

They calculated a total of 10 quadrillion possible unique analyses. A quadrillion is 1 with 15 zeros. Computing power cannot handle that amount of analyses yet. So, they generated 20 random unique combinations of covariates, which narrowed the number of analyses to about 1400. About 200 of these were excluded due to implausibly wide confidence intervals. 

Voilà. They now had about 1200 different ways to analyze a dataset; they chose an NHANES longitudinal cohort study from 2007-2014. They deemed each of the more than 1200 approaches plausible because they were derived from peer-reviewed papers written by experts in epidemiology. 
 

Specification Curve Analyses Results 

Each analysis (or specification) yielded a hazard ratio for red meat exposure and death.

• The median HR was 0.94 (IQR, 0.83-1.05) for the effect of red meat on all-cause mortality — ie, not significant.
• The range of hazard ratios was large. They went from 0.51 — a 49% reduced risk for early mortality — to 1.75: a 75% increase in early mortality.
• Among all analyses, 36% yielded hazard ratios above 1.0 and 64% less than 1.0.
• As for statistical significance, defined as P ≤.05, only 4% (or 48 specifications) met this threshold. Zeraatkar reminded me that this is what you’d expect if unprocessed red meat has no effect on longevity.
• Of the 48 analyses deemed statistically significant, 40 indicated that red meat consumption reduced early death and eight indicated that eating red meat led to higher mortality.
• Nearly half the analyses yielded unexciting point estimates, with hazard ratios between 0.90 and 1.10.

Paradigm Changing 

As a user of evidence, I find this a potentially paradigm-changing study. Observational studies far outnumber randomized trials. For many medical questions, observational data are all we have. 

Now think about every observational study published. The authors tell you — post hoc — which method they used to analyze the data. The key point is that it is one method. 

Dr. Zeraatkar and colleagues have shown that there are thousands of plausible ways to analyze the data, and this can lead to very different findings. In the specific question of red meat and mortality, their many analyses yielded a null result. 

Now imagine other cases where the researchers did many analyses of a dataset and chose to publish only the significant ones. Observational studies are rarely preregistered, so a reader cannot know how a result would vary depending on analytic choices. A specification curve analysis of a dataset provides a much broader picture. In the case of red meat, you see some significant results, but the vast majority hover around null. 

What about the difficulty in analyzing a dataset 1000 different ways? Dr. Zeraatkar told me that it is harder than just choosing one method, but it’s not impossible. 

The main barrier to adopting this multiverse approach to data, she noted, was not the extra work but the entrenched belief among researchers that there is a best way to analyze data. 

I hope you read this paper and think about it every time you read an observational study that finds a positive or negative association between two things. Ask: What if the researchers were as careful as Dr. Zeraatkar and colleagues and did multiple different analyses? Would the finding hold up to a series of plausible analytic choices? 

Nutritional epidemiology would benefit greatly from this approach. But so would any observational study of an exposure and outcome. I suspect that the number of “positive” associations would diminish. And that would not be a bad thing.

 

Dr. Mandrola, a clinical electrophysiologist at Baptist Medical Associates, Louisville, Kentucky, disclosed no relevant financial relationships.

A version of this article appeared on Medscape.com.

Observational studies on red meat consumption and lifespan are prime examples of attempts to find signal in a sea of noise. 

Randomized controlled trials are the best way to sort cause from mere correlation. But these are not possible in most matters of food consumption. So, we look back and observe groups with different exposures.

My most frequent complaint about these nonrandom comparison studies has been the chance that the two groups differ in important ways, and it’s these differences — not the food in question — that account for the disparate outcomes.

But selection biases are only one issue. There is also the matter of analytic flexibility. Observational studies are born from large databases. Researchers have many choices in how to analyze all these data.

A few years ago, Brian Nosek, PhD, and colleagues elegantly showed that analytic choices can affect results. His Many Analysts, One Data Set study had little uptake in the medical community, perhaps because he studied a social science question.
 

Multiple Ways to Slice the Data

Recently, a group from McMaster University, led by Dena Zeraatkar, PhD, has confirmed the analytic choices problem, using the question of red meat consumption and mortality. 

Their idea was simple: Because there are many plausible and defensible ways to analyze a dataset, we should not choose one method; rather, we should choose thousands, combine the results, and see where the truth lies. 

You might wonder how there could be thousands of ways to analyze a dataset. I surely did. 

The answer stems from the choices that researchers face. For instance, there is the selection of eligible participants, the choice of analytic model (logistic, Poisson, etc.), and covariates for which to adjust. Think exponents when combining possible choices.

Dr. Zeraatkar and colleagues are research methodologists, so, sadly, they are comfortable with the clunky name of this approach: specification curve analysis. Don’t be deterred. It means that they analyze the data in thousands of ways using computers. Each way is a specification. In the end, the specifications give rise to a curve of hazard ratios for red meat and mortality. Another name for this approach is multiverse analysis.

For their paper in the Journal of Clinical Epidemiology, aptly named “Grilling the Data,” they didn’t just conjure up the many analytic ways to study the red meat–mortality question. Instead, they used a published systematic review of 15 studies on unprocessed red meat and early mortality. The studies included in this review reported 70 unique ways to analyze the association. 
 

Is Red Meat Good or Bad?

Their first finding was that this analysis yielded widely disparate effect estimates, from 0.63 (reduced risk for early death) to 2.31 (a higher risk). The median hazard ratio was 1.14 with an interquartile range (IQR) of 1.02-1.23. One might conclude from this that eating red meat is associated with a slightly higher risk for early mortality. 

Their second step was to calculate how many ways (specifications) there were to analyze the data by totaling all possible combinations of choices in the 70 ways found in the systematic review. 

They calculated a total of 10 quadrillion possible unique analyses. A quadrillion is 1 with 15 zeros. Computing power cannot handle that amount of analyses yet. So, they generated 20 random unique combinations of covariates, which narrowed the number of analyses to about 1400. About 200 of these were excluded due to implausibly wide confidence intervals. 

Voilà. They now had about 1200 different ways to analyze a dataset; they chose an NHANES longitudinal cohort study from 2007-2014. They deemed each of the more than 1200 approaches plausible because they were derived from peer-reviewed papers written by experts in epidemiology. 
 

Specification Curve Analyses Results 

Each analysis (or specification) yielded a hazard ratio for red meat exposure and death.

• The median HR was 0.94 (IQR, 0.83-1.05) for the effect of red meat on all-cause mortality — ie, not significant.
• The range of hazard ratios was large. They went from 0.51 — a 49% reduced risk for early mortality — to 1.75: a 75% increase in early mortality.
• Among all analyses, 36% yielded hazard ratios above 1.0 and 64% less than 1.0.
• As for statistical significance, defined as P ≤.05, only 4% (or 48 specifications) met this threshold. Zeraatkar reminded me that this is what you’d expect if unprocessed red meat has no effect on longevity.
• Of the 48 analyses deemed statistically significant, 40 indicated that red meat consumption reduced early death and eight indicated that eating red meat led to higher mortality.
• Nearly half the analyses yielded unexciting point estimates, with hazard ratios between 0.90 and 1.10.

Paradigm Changing 

As a user of evidence, I find this a potentially paradigm-changing study. Observational studies far outnumber randomized trials. For many medical questions, observational data are all we have. 

Now think about every observational study published. The authors tell you — post hoc — which method they used to analyze the data. The key point is that it is one method. 

Dr. Zeraatkar and colleagues have shown that there are thousands of plausible ways to analyze the data, and this can lead to very different findings. In the specific question of red meat and mortality, their many analyses yielded a null result. 

Now imagine other cases where the researchers did many analyses of a dataset and chose to publish only the significant ones. Observational studies are rarely preregistered, so a reader cannot know how a result would vary depending on analytic choices. A specification curve analysis of a dataset provides a much broader picture. In the case of red meat, you see some significant results, but the vast majority hover around null. 

What about the difficulty in analyzing a dataset 1000 different ways? Dr. Zeraatkar told me that it is harder than just choosing one method, but it’s not impossible. 

The main barrier to adopting this multiverse approach to data, she noted, was not the extra work but the entrenched belief among researchers that there is a best way to analyze data. 

I hope you read this paper and think about it every time you read an observational study that finds a positive or negative association between two things. Ask: What if the researchers were as careful as Dr. Zeraatkar and colleagues and did multiple different analyses? Would the finding hold up to a series of plausible analytic choices? 

Nutritional epidemiology would benefit greatly from this approach. But so would any observational study of an exposure and outcome. I suspect that the number of “positive” associations would diminish. And that would not be a bad thing.

 

Dr. Mandrola, a clinical electrophysiologist at Baptist Medical Associates, Louisville, Kentucky, disclosed no relevant financial relationships.

A version of this article appeared on Medscape.com.