MDedge Rheumatology

CLEVELAND – Patients with axial spondyloarthritis or psoriatic arthritis who used Janus kinase (JAK) inhibitors did not have higher risk of myocardial infarction, stroke, or venous thromboembolism (VTE), compared with those who used tumor necrosis factor inhibitors (TNFi), according to new research.

The information was presented in a poster at the annual meeting of the Spondyloarthritis Research and Treatment Network (SPARTAN).

Patients with axial spondyloarthritis (axSpA) and psoriatic arthritis (PsA) have increased cardiovascular risk compared with the general population. Emerging evidence has suggested that TNFi may protect the cardiovascular system and that there are cardiovascular and thrombotic concerns with JAK inhibitors.

Sali Merjanah, MD, a rheumatology fellow at Boston University, and colleagues, compared how drugs in the two treatment classes affected the likelihood of major adverse cardiovascular events (MACE) or VTE. MACE in this study were myocardial infarction and stroke.

In a search of the Marketscan Database during 2006-2021, the researchers identified 1,621 TNFi and 47 JAK inhibitor users with 273 and 8 cases of MACE, respectively. They identified 2,507 TNFi and 96 JAK users with 452 and 26 cases of VTE, respectively. Patients were aged 18-65 years and had at least one inpatient or two outpatient axSpA or PsA ICD-9 or ICD-10 diagnosis codes separated by at least 7 days.

The likelihood of MACE was 14% lower among JAK inhibitor users than TNFi users (the reference group), whereas the likelihood of VTE was 39% higher for JAK inhibitor users, but neither comparison was statistically significant. JAK/TNFi nonusers had a statistically significant 27% greater likelihood of MACE than did TNFi users. The likelihood for VTE was 12% higher for JAK/TNFi nonusers, compared with TNFi users, but this finding was not statistically significant. The researchers adjusted comparisons for age, medications, and comorbidities.
 

Small numbers complicate the research

Lianne Gensler, MD, director of the Ankylosing Spondylitis Clinic at the University of California, San Francisco, who was not part of the study, said the limitations the authors list are important to note. The researchers said that the study’s small number of JAK inhibitor users, short duration of exposure, and low event rate limit its precision, and there is potential misclassification of TNF/JAK inhibitor exposure, as well as confounding by indication.

Dr. Gensler noted that these same limitations apply to studies of patients with RA as well that try to answer the question of risk for MACE and malignancy when using these drugs,

“MACE is a rare event, malignancy is a rare event. So it’s like finding a needle in a haystack, and the haystack is really big. You either have to enrich the haystack with more needles or you have to make a smaller haystack,” Dr. Gensler said.

Nevertheless, she said, she credits the researchers for bringing the available information to light.

“I think we have to do this many different ways to try to get at the answer in a partial way,” she said.

The data were drawn from 2006 to 2021, but JAK inhibitors have only been approved for axSpA in the last one and a half years and for PsA at the end of 2017.

Additionally, the people taking JAK inhibitors would have likely already failed TNFis, she said, adding that this can make it hard to tell whether an event was linked with the JAK or the TNFi.
 

Nonusers may have other risk factors

She pointed out that in this study patients who were not using TNF or JAK inhibitors had slightly higher risk numerically for both MACE and VTE than did those using TNFis.

“There, the assumption is always that this is confounding by indication, meaning it is likely that the people who are nonusers have other risk factors for MACE, which is why we’re not giving them these drugs.”

Having heart failure, for instance, is a contraindication for using a TNF inhibitor, she noted. “So it’s not that these are protective compared to nonusers. It’s probably that the nonuser has higher risk and is not getting treated with these drugs to begin with.”

The authors properly concluded from the data that patients using JAK inhibitors did not have higher risk of MACE or VTE, compared with those who used TNFis, she said, but larger studies with more follow-up are needed.

“No evidence doesn’t mean no effect,” she said. “Part of it depends on the [statistical] power and the population you’re studying.”

Dr. Gensler is a consultant for AbbVie, Acceleron, Eli Lilly, Janssen, Novartis, Pfizer, and UCB; and has received grant support from Novartis and UCB. The authors’ financial relationships were not available.

CLEVELAND – Patients with axial spondyloarthritis or psoriatic arthritis who used Janus kinase (JAK) inhibitors did not have higher risk of myocardial infarction, stroke, or venous thromboembolism (VTE), compared with those who used tumor necrosis factor inhibitors (TNFi), according to new research.

The information was presented in a poster at the annual meeting of the Spondyloarthritis Research and Treatment Network (SPARTAN).

Patients with axial spondyloarthritis (axSpA) and psoriatic arthritis (PsA) have increased cardiovascular risk compared with the general population. Emerging evidence has suggested that TNFi may protect the cardiovascular system and that there are cardiovascular and thrombotic concerns with JAK inhibitors.

Sali Merjanah, MD, a rheumatology fellow at Boston University, and colleagues, compared how drugs in the two treatment classes affected the likelihood of major adverse cardiovascular events (MACE) or VTE. MACE in this study were myocardial infarction and stroke.

In a search of the Marketscan Database during 2006-2021, the researchers identified 1,621 TNFi and 47 JAK inhibitor users with 273 and 8 cases of MACE, respectively. They identified 2,507 TNFi and 96 JAK users with 452 and 26 cases of VTE, respectively. Patients were aged 18-65 years and had at least one inpatient or two outpatient axSpA or PsA ICD-9 or ICD-10 diagnosis codes separated by at least 7 days.

The likelihood of MACE was 14% lower among JAK inhibitor users than TNFi users (the reference group), whereas the likelihood of VTE was 39% higher for JAK inhibitor users, but neither comparison was statistically significant. JAK/TNFi nonusers had a statistically significant 27% greater likelihood of MACE than did TNFi users. The likelihood for VTE was 12% higher for JAK/TNFi nonusers, compared with TNFi users, but this finding was not statistically significant. The researchers adjusted comparisons for age, medications, and comorbidities.
 

Small numbers complicate the research

Lianne Gensler, MD, director of the Ankylosing Spondylitis Clinic at the University of California, San Francisco, who was not part of the study, said the limitations the authors list are important to note. The researchers said that the study’s small number of JAK inhibitor users, short duration of exposure, and low event rate limit its precision, and there is potential misclassification of TNF/JAK inhibitor exposure, as well as confounding by indication.

Dr. Gensler noted that these same limitations apply to studies of patients with RA as well that try to answer the question of risk for MACE and malignancy when using these drugs,

“MACE is a rare event, malignancy is a rare event. So it’s like finding a needle in a haystack, and the haystack is really big. You either have to enrich the haystack with more needles or you have to make a smaller haystack,” Dr. Gensler said.

Nevertheless, she said, she credits the researchers for bringing the available information to light.

“I think we have to do this many different ways to try to get at the answer in a partial way,” she said.

The data were drawn from 2006 to 2021, but JAK inhibitors have only been approved for axSpA in the last one and a half years and for PsA at the end of 2017.

Additionally, the people taking JAK inhibitors would have likely already failed TNFis, she said, adding that this can make it hard to tell whether an event was linked with the JAK or the TNFi.
 

Nonusers may have other risk factors

She pointed out that in this study patients who were not using TNF or JAK inhibitors had slightly higher risk numerically for both MACE and VTE than did those using TNFis.

“There, the assumption is always that this is confounding by indication, meaning it is likely that the people who are nonusers have other risk factors for MACE, which is why we’re not giving them these drugs.”

Having heart failure, for instance, is a contraindication for using a TNF inhibitor, she noted. “So it’s not that these are protective compared to nonusers. It’s probably that the nonuser has higher risk and is not getting treated with these drugs to begin with.”

The authors properly concluded from the data that patients using JAK inhibitors did not have higher risk of MACE or VTE, compared with those who used TNFis, she said, but larger studies with more follow-up are needed.

“No evidence doesn’t mean no effect,” she said. “Part of it depends on the [statistical] power and the population you’re studying.”

Dr. Gensler is a consultant for AbbVie, Acceleron, Eli Lilly, Janssen, Novartis, Pfizer, and UCB; and has received grant support from Novartis and UCB. The authors’ financial relationships were not available.

CLEVELAND – Patients with axial spondyloarthritis or psoriatic arthritis who used Janus kinase (JAK) inhibitors did not have higher risk of myocardial infarction, stroke, or venous thromboembolism (VTE), compared with those who used tumor necrosis factor inhibitors (TNFi), according to new research.

The information was presented in a poster at the annual meeting of the Spondyloarthritis Research and Treatment Network (SPARTAN).

Patients with axial spondyloarthritis (axSpA) and psoriatic arthritis (PsA) have increased cardiovascular risk compared with the general population. Emerging evidence has suggested that TNFi may protect the cardiovascular system and that there are cardiovascular and thrombotic concerns with JAK inhibitors.

Sali Merjanah, MD, a rheumatology fellow at Boston University, and colleagues, compared how drugs in the two treatment classes affected the likelihood of major adverse cardiovascular events (MACE) or VTE. MACE in this study were myocardial infarction and stroke.

In a search of the Marketscan Database during 2006-2021, the researchers identified 1,621 TNFi and 47 JAK inhibitor users with 273 and 8 cases of MACE, respectively. They identified 2,507 TNFi and 96 JAK users with 452 and 26 cases of VTE, respectively. Patients were aged 18-65 years and had at least one inpatient or two outpatient axSpA or PsA ICD-9 or ICD-10 diagnosis codes separated by at least 7 days.

The likelihood of MACE was 14% lower among JAK inhibitor users than TNFi users (the reference group), whereas the likelihood of VTE was 39% higher for JAK inhibitor users, but neither comparison was statistically significant. JAK/TNFi nonusers had a statistically significant 27% greater likelihood of MACE than did TNFi users. The likelihood for VTE was 12% higher for JAK/TNFi nonusers, compared with TNFi users, but this finding was not statistically significant. The researchers adjusted comparisons for age, medications, and comorbidities.
 

Small numbers complicate the research

Lianne Gensler, MD, director of the Ankylosing Spondylitis Clinic at the University of California, San Francisco, who was not part of the study, said the limitations the authors list are important to note. The researchers said that the study’s small number of JAK inhibitor users, short duration of exposure, and low event rate limit its precision, and there is potential misclassification of TNF/JAK inhibitor exposure, as well as confounding by indication.

Dr. Gensler noted that these same limitations apply to studies of patients with RA as well that try to answer the question of risk for MACE and malignancy when using these drugs,

“MACE is a rare event, malignancy is a rare event. So it’s like finding a needle in a haystack, and the haystack is really big. You either have to enrich the haystack with more needles or you have to make a smaller haystack,” Dr. Gensler said.

Nevertheless, she said, she credits the researchers for bringing the available information to light.

“I think we have to do this many different ways to try to get at the answer in a partial way,” she said.

The data were drawn from 2006 to 2021, but JAK inhibitors have only been approved for axSpA in the last one and a half years and for PsA at the end of 2017.

Additionally, the people taking JAK inhibitors would have likely already failed TNFis, she said, adding that this can make it hard to tell whether an event was linked with the JAK or the TNFi.
 

Nonusers may have other risk factors

She pointed out that in this study patients who were not using TNF or JAK inhibitors had slightly higher risk numerically for both MACE and VTE than did those using TNFis.

“There, the assumption is always that this is confounding by indication, meaning it is likely that the people who are nonusers have other risk factors for MACE, which is why we’re not giving them these drugs.”

Having heart failure, for instance, is a contraindication for using a TNF inhibitor, she noted. “So it’s not that these are protective compared to nonusers. It’s probably that the nonuser has higher risk and is not getting treated with these drugs to begin with.”

The authors properly concluded from the data that patients using JAK inhibitors did not have higher risk of MACE or VTE, compared with those who used TNFis, she said, but larger studies with more follow-up are needed.

“No evidence doesn’t mean no effect,” she said. “Part of it depends on the [statistical] power and the population you’re studying.”

Dr. Gensler is a consultant for AbbVie, Acceleron, Eli Lilly, Janssen, Novartis, Pfizer, and UCB; and has received grant support from Novartis and UCB. The authors’ financial relationships were not available.

AURORA, COLO. – Artificial Intelligence has arrived at medical offices, whether or not clinicians feel ready for it.

AI might result in more accurate, efficient, and cost-effective care. But it’s possible it could cause harm. That’s according to Benjamin Collins, MD, at Vanderbilt University Medical Center, Nashville, Tenn., who spoke on the subject at the annual meeting of the Society of General Internal Medicine.

Understanding the nuances of AI is even more important because of the quick development of the algorithms.

“When I submitted this workshop, there was no ChatGPT,” said Dr. Collins, referring to Chat Generative Pre-trained Transformer, a recently released natural language processing model. “A lot has already changed.”
 

Biased data

Biased data are perhaps the biggest pitfall of AI algorithms, Dr. Collins said. If garbage data go in, garbage predictions come out.

If the dataset that trains the algorithm underrepresents a particular gender or ethnic group, for example, the algorithm may not respond accurately to prompts. When an AI tool compounds existing inequalities related to socioeconomic status, ethnicity, or sexual orientation, the algorithm is biased, according to Harvard researchers.

“People often assume that artificial intelligence is free of bias due to the use of scientific processes and its development,” he said. “But whatever flaws exist in data collection and old data can lead to poor representation or underrepresentation in the data used to train the AI tool.”

Racial minorities are underrepresented in studies; therefore, data input into an AI tool might skew results for these patients.

The Framingham Heart Study, for example, which began in 1948, examined heart disease in mainly White participants. The findings from the study resulted in the creation of a sex-specific algorithm that was used to estimate the 10-year cardiovascular risk of a patient. While the cardiovascular risk score was accurate for White persons, it was less accurate for Black patients.

A study published in Science in 2019 revealed bias in an algorithm that used health care costs as a proxy for health needs. Because less money was spent on Black patients who had the same level of need as their White counterparts, the output inaccurately showed that Black patients were healthier and thus did not require extra care.

Developers can also be a source of bias, inasmuch as AI often reflects preexisting human biases, Dr. Collins said.

“Algorithmic bias presents a clear risk of harm that clinicians must play against the benefits of using AI,” Dr. Collins said. “That risk of harm is often disproportionately distributed to marginalized populations.”

As clinicians use AI algorithms to diagnose and detect disease, predict outcomes, and guide treatment, trouble comes when those algorithms perform well for some patients and poorly for others. This gap can exacerbate existing disparities in health care outcomes.

Dr. Collins advised clinicians to push to find out what data were used to train AI algorithms to determine how bias could have influenced the model and whether the developers risk-adjusted for bias. If the training data are not available, clinicians should ask their employers and AI developers to know more about the system.

Clinicians may face the so-called black box phenomenon, which occurs when developers cannot or will not explain what data went into an AI model, Dr. Collins said.

According to Stanford (Calif.) University, AI must be trained on large datasets of images that have been annotated by human experts. Those datasets can cost millions of dollars to create, meaning corporations often fund them and do not always share the data publicly.

Some groups, such as Stanford’s Center for Artificial Intelligence in Medicine and Imaging, are working to acquire annotated datasets so researchers who train AI models can know where the data came from.

Paul Haidet, MD, MPH, an internist at Penn State College of Medicine, Hershey, sees the technology as a tool that requires careful handling.

“It takes a while to learn how to use a stethoscope, and AI is like that,” Dr. Haidet said. “The thing about AI, though, is that it can be just dropped into a system and no one knows how it works.”

Dr. Haidet said he likes knowing how the sausage is made, something AI developers are often reticent to make known.

“If you’re just putting blind faith in a tool, that’s scary,” Dr. Haidet said.
 

Transparency and ‘explainability’

The ability to explain what goes into tools is essential to maintaining trust in the health care system, Dr. Collins said.

“Part of knowing how much trust to place in the system is the transparency of those systems and the ability to audit how well the algorithm is performing,” Dr. Collins said. “The system should also regularly report to users the level of certainty with which it is providing an output rather than providing a simple binary output.”

Dr. Collins recommends that providers develop an understanding of the limits of AI regulations as well, which might including learning how the system was approved and how it is monitored.

“The FDA has oversight over some applications of AI and health care for software as a medical device, but there’s currently no dedicated process to evaluate the systems for the presence of bias,” Dr. Collins said. “The gaps in regulation leave the door open for the use of AI in clinical care that contain significant biases.”

Dr. Haidet likened AI tools to the Global Positioning System: A good GPS system will let users see alternate routes, opt out of toll roads or highways, and will highlight why routes have changed. But users need to understand how to read the map so they can tell when something seems amiss.

Dr. Collins and Dr. Haidet report no relevant financial relationships

A version of this article first appeared on Medscape.com.

AURORA, COLO. – Artificial Intelligence has arrived at medical offices, whether or not clinicians feel ready for it.

AI might result in more accurate, efficient, and cost-effective care. But it’s possible it could cause harm. That’s according to Benjamin Collins, MD, at Vanderbilt University Medical Center, Nashville, Tenn., who spoke on the subject at the annual meeting of the Society of General Internal Medicine.

Understanding the nuances of AI is even more important because of the quick development of the algorithms.

“When I submitted this workshop, there was no ChatGPT,” said Dr. Collins, referring to Chat Generative Pre-trained Transformer, a recently released natural language processing model. “A lot has already changed.”
 

Biased data

Biased data are perhaps the biggest pitfall of AI algorithms, Dr. Collins said. If garbage data go in, garbage predictions come out.

If the dataset that trains the algorithm underrepresents a particular gender or ethnic group, for example, the algorithm may not respond accurately to prompts. When an AI tool compounds existing inequalities related to socioeconomic status, ethnicity, or sexual orientation, the algorithm is biased, according to Harvard researchers.

“People often assume that artificial intelligence is free of bias due to the use of scientific processes and its development,” he said. “But whatever flaws exist in data collection and old data can lead to poor representation or underrepresentation in the data used to train the AI tool.”

Racial minorities are underrepresented in studies; therefore, data input into an AI tool might skew results for these patients.

The Framingham Heart Study, for example, which began in 1948, examined heart disease in mainly White participants. The findings from the study resulted in the creation of a sex-specific algorithm that was used to estimate the 10-year cardiovascular risk of a patient. While the cardiovascular risk score was accurate for White persons, it was less accurate for Black patients.

A study published in Science in 2019 revealed bias in an algorithm that used health care costs as a proxy for health needs. Because less money was spent on Black patients who had the same level of need as their White counterparts, the output inaccurately showed that Black patients were healthier and thus did not require extra care.

Developers can also be a source of bias, inasmuch as AI often reflects preexisting human biases, Dr. Collins said.

“Algorithmic bias presents a clear risk of harm that clinicians must play against the benefits of using AI,” Dr. Collins said. “That risk of harm is often disproportionately distributed to marginalized populations.”

As clinicians use AI algorithms to diagnose and detect disease, predict outcomes, and guide treatment, trouble comes when those algorithms perform well for some patients and poorly for others. This gap can exacerbate existing disparities in health care outcomes.

Dr. Collins advised clinicians to push to find out what data were used to train AI algorithms to determine how bias could have influenced the model and whether the developers risk-adjusted for bias. If the training data are not available, clinicians should ask their employers and AI developers to know more about the system.

Clinicians may face the so-called black box phenomenon, which occurs when developers cannot or will not explain what data went into an AI model, Dr. Collins said.

According to Stanford (Calif.) University, AI must be trained on large datasets of images that have been annotated by human experts. Those datasets can cost millions of dollars to create, meaning corporations often fund them and do not always share the data publicly.

Some groups, such as Stanford’s Center for Artificial Intelligence in Medicine and Imaging, are working to acquire annotated datasets so researchers who train AI models can know where the data came from.

Paul Haidet, MD, MPH, an internist at Penn State College of Medicine, Hershey, sees the technology as a tool that requires careful handling.

“It takes a while to learn how to use a stethoscope, and AI is like that,” Dr. Haidet said. “The thing about AI, though, is that it can be just dropped into a system and no one knows how it works.”

Dr. Haidet said he likes knowing how the sausage is made, something AI developers are often reticent to make known.

“If you’re just putting blind faith in a tool, that’s scary,” Dr. Haidet said.
 

Transparency and ‘explainability’

The ability to explain what goes into tools is essential to maintaining trust in the health care system, Dr. Collins said.

“Part of knowing how much trust to place in the system is the transparency of those systems and the ability to audit how well the algorithm is performing,” Dr. Collins said. “The system should also regularly report to users the level of certainty with which it is providing an output rather than providing a simple binary output.”

Dr. Collins recommends that providers develop an understanding of the limits of AI regulations as well, which might including learning how the system was approved and how it is monitored.

“The FDA has oversight over some applications of AI and health care for software as a medical device, but there’s currently no dedicated process to evaluate the systems for the presence of bias,” Dr. Collins said. “The gaps in regulation leave the door open for the use of AI in clinical care that contain significant biases.”

Dr. Haidet likened AI tools to the Global Positioning System: A good GPS system will let users see alternate routes, opt out of toll roads or highways, and will highlight why routes have changed. But users need to understand how to read the map so they can tell when something seems amiss.

Dr. Collins and Dr. Haidet report no relevant financial relationships

A version of this article first appeared on Medscape.com.

AURORA, COLO. – Artificial Intelligence has arrived at medical offices, whether or not clinicians feel ready for it.

AI might result in more accurate, efficient, and cost-effective care. But it’s possible it could cause harm. That’s according to Benjamin Collins, MD, at Vanderbilt University Medical Center, Nashville, Tenn., who spoke on the subject at the annual meeting of the Society of General Internal Medicine.

Understanding the nuances of AI is even more important because of the quick development of the algorithms.

“When I submitted this workshop, there was no ChatGPT,” said Dr. Collins, referring to Chat Generative Pre-trained Transformer, a recently released natural language processing model. “A lot has already changed.”
 

Biased data

Biased data are perhaps the biggest pitfall of AI algorithms, Dr. Collins said. If garbage data go in, garbage predictions come out.

If the dataset that trains the algorithm underrepresents a particular gender or ethnic group, for example, the algorithm may not respond accurately to prompts. When an AI tool compounds existing inequalities related to socioeconomic status, ethnicity, or sexual orientation, the algorithm is biased, according to Harvard researchers.

“People often assume that artificial intelligence is free of bias due to the use of scientific processes and its development,” he said. “But whatever flaws exist in data collection and old data can lead to poor representation or underrepresentation in the data used to train the AI tool.”

Racial minorities are underrepresented in studies; therefore, data input into an AI tool might skew results for these patients.

The Framingham Heart Study, for example, which began in 1948, examined heart disease in mainly White participants. The findings from the study resulted in the creation of a sex-specific algorithm that was used to estimate the 10-year cardiovascular risk of a patient. While the cardiovascular risk score was accurate for White persons, it was less accurate for Black patients.

A study published in Science in 2019 revealed bias in an algorithm that used health care costs as a proxy for health needs. Because less money was spent on Black patients who had the same level of need as their White counterparts, the output inaccurately showed that Black patients were healthier and thus did not require extra care.

Developers can also be a source of bias, inasmuch as AI often reflects preexisting human biases, Dr. Collins said.

“Algorithmic bias presents a clear risk of harm that clinicians must play against the benefits of using AI,” Dr. Collins said. “That risk of harm is often disproportionately distributed to marginalized populations.”

As clinicians use AI algorithms to diagnose and detect disease, predict outcomes, and guide treatment, trouble comes when those algorithms perform well for some patients and poorly for others. This gap can exacerbate existing disparities in health care outcomes.

Dr. Collins advised clinicians to push to find out what data were used to train AI algorithms to determine how bias could have influenced the model and whether the developers risk-adjusted for bias. If the training data are not available, clinicians should ask their employers and AI developers to know more about the system.

Clinicians may face the so-called black box phenomenon, which occurs when developers cannot or will not explain what data went into an AI model, Dr. Collins said.

According to Stanford (Calif.) University, AI must be trained on large datasets of images that have been annotated by human experts. Those datasets can cost millions of dollars to create, meaning corporations often fund them and do not always share the data publicly.

Some groups, such as Stanford’s Center for Artificial Intelligence in Medicine and Imaging, are working to acquire annotated datasets so researchers who train AI models can know where the data came from.

Paul Haidet, MD, MPH, an internist at Penn State College of Medicine, Hershey, sees the technology as a tool that requires careful handling.

“It takes a while to learn how to use a stethoscope, and AI is like that,” Dr. Haidet said. “The thing about AI, though, is that it can be just dropped into a system and no one knows how it works.”

Dr. Haidet said he likes knowing how the sausage is made, something AI developers are often reticent to make known.

“If you’re just putting blind faith in a tool, that’s scary,” Dr. Haidet said.
 

Transparency and ‘explainability’

The ability to explain what goes into tools is essential to maintaining trust in the health care system, Dr. Collins said.

“Part of knowing how much trust to place in the system is the transparency of those systems and the ability to audit how well the algorithm is performing,” Dr. Collins said. “The system should also regularly report to users the level of certainty with which it is providing an output rather than providing a simple binary output.”

Dr. Collins recommends that providers develop an understanding of the limits of AI regulations as well, which might including learning how the system was approved and how it is monitored.

“The FDA has oversight over some applications of AI and health care for software as a medical device, but there’s currently no dedicated process to evaluate the systems for the presence of bias,” Dr. Collins said. “The gaps in regulation leave the door open for the use of AI in clinical care that contain significant biases.”

Dr. Haidet likened AI tools to the Global Positioning System: A good GPS system will let users see alternate routes, opt out of toll roads or highways, and will highlight why routes have changed. But users need to understand how to read the map so they can tell when something seems amiss.

Dr. Collins and Dr. Haidet report no relevant financial relationships

A version of this article first appeared on Medscape.com.

AURORA, COLO. – How often do you talk with patients about how to lower their out-of-pocket costs for medical care?

For most clinicians, the answer is: not often enough. But having those conversations can improve medication adherence and strengthen the patient-clinician relationship, according to panelists at the annual meeting of the Society of General Internal Medicine.

The inverse association between out-of-pocket expenditures and fidelity to prescriptions is clear. A 2020 study by the IQVIA Institute for Human Data Science, for example, found that rates of prescription abandonment are less than 5% when a given medication carries no out-of-pocket cost for patients. That figure rises to 45% when the cost is more than $125, and to 60% when it exceeds $500. One in five Americans said cost prevented them from adhering to medication regimens, according to a new study in JAMA Network Open.

The researchers surveyed more than 2,000 men and women, 40.4% of whom were aged 75 or older. They found that nearly 90% of respondents said they would not be uncomfortable being asked about drug costs before a visit with a physician. A similar share (89.5%) said they would welcome the use by their physician of a real-time tool to determine the cost of their medication.

But the survey results contained a note of warning for clinicians: A significant number of respondents said they would be “extremely” upset if the cost of their medication exceeded the estimate from the pricing tool. And many also said they would be “moderately” or “extremely” angry if their physician used a pricing tool but failed to share the results with them.

“Real-time benefit tools may support medication cost conversations and cost-conscious prescribing, and patients are enthusiastic about their use,” the authors write. “However, if disclosed prices are inaccurate, there is potential for harm through loss of confidence in the physician and nonadherence to prescribed medications.”

While having conversations about cost can be difficult for both clinicians and patients, studies have shown that patients who discuss cost concerns with their doctors feel as if they have stronger relationships as a result.

Clinicians often avoid conversations about out-of-pocket expenses because they don’t know specific price information, they lack solutions to address cost, or they are uncomfortable bringing up the issue.

One member of the audience at the SGIM meeting recalled a patient who worked in a warehouse for a large company. The man, who had type 2 diabetes, had medical insurance, but even with insurance, insulin was going to cost him $150 per month. He struggled to afford the necessary treatment.

“He looked at me and said, ‘What do they want me to do? Do they want me to actually not be able to work for them and not manage my diabetes?’ ”

The clinician said he offered empathy in the moment but felt he could do little else.

Panelists acknowledged that clinicians are crunched on time when seeing patients, but being willing to initiate conversations about cost with patients and to offer resources can help patients get necessary treatment.
 

Start the conversation

Panel member Caroline Sloan, MD, an assistant professor of medicine at Duke University, Durham, N.C., said making patients aware that you know cost can make a big difference.

The American College of Physicians advises clinicians to ask patients whether they are worried about the cost of care and to not assume which patients may have concerns.

The conversation could be started like this: “I’d like to discuss any concerns you might have about the cost of your health care.”

Normalize the concern by making it more general, and reassure your patient that your goal is to get them the best care. Say something like, “I’ve heard from many patients the cost of medications or tests is becoming hard to manage.”

Once a patient’s concerns are clear, you can direct them to resources for assistance in reducing their costs, Dr. Sloan said, such as ClearHealthCosts, FAIR Health, Healthcare Bluebook, New Choice Health, GoodRx, PharmacyChecker, HealthWell Foundation, Patient Advocate Foundation, Good Days, Good Health Will, Mercy Medical Angels, and the American Association of Family Physicians Neighborhood Navigator.

Dr. Sloan said she knows clinicians don’t have time to understand every insurance plan and other issues related to cost. “But at least know to ask about costs,” she said. “Practice, practice, practice. It feels awkward at first, but it gets easier every time.”

A version of this article first appeared on Medscape.com.

AURORA, COLO. – How often do you talk with patients about how to lower their out-of-pocket costs for medical care?

For most clinicians, the answer is: not often enough. But having those conversations can improve medication adherence and strengthen the patient-clinician relationship, according to panelists at the annual meeting of the Society of General Internal Medicine.

The inverse association between out-of-pocket expenditures and fidelity to prescriptions is clear. A 2020 study by the IQVIA Institute for Human Data Science, for example, found that rates of prescription abandonment are less than 5% when a given medication carries no out-of-pocket cost for patients. That figure rises to 45% when the cost is more than $125, and to 60% when it exceeds $500. One in five Americans said cost prevented them from adhering to medication regimens, according to a new study in JAMA Network Open.

The researchers surveyed more than 2,000 men and women, 40.4% of whom were aged 75 or older. They found that nearly 90% of respondents said they would not be uncomfortable being asked about drug costs before a visit with a physician. A similar share (89.5%) said they would welcome the use by their physician of a real-time tool to determine the cost of their medication.

But the survey results contained a note of warning for clinicians: A significant number of respondents said they would be “extremely” upset if the cost of their medication exceeded the estimate from the pricing tool. And many also said they would be “moderately” or “extremely” angry if their physician used a pricing tool but failed to share the results with them.

“Real-time benefit tools may support medication cost conversations and cost-conscious prescribing, and patients are enthusiastic about their use,” the authors write. “However, if disclosed prices are inaccurate, there is potential for harm through loss of confidence in the physician and nonadherence to prescribed medications.”

While having conversations about cost can be difficult for both clinicians and patients, studies have shown that patients who discuss cost concerns with their doctors feel as if they have stronger relationships as a result.

Clinicians often avoid conversations about out-of-pocket expenses because they don’t know specific price information, they lack solutions to address cost, or they are uncomfortable bringing up the issue.

One member of the audience at the SGIM meeting recalled a patient who worked in a warehouse for a large company. The man, who had type 2 diabetes, had medical insurance, but even with insurance, insulin was going to cost him $150 per month. He struggled to afford the necessary treatment.

“He looked at me and said, ‘What do they want me to do? Do they want me to actually not be able to work for them and not manage my diabetes?’ ”

The clinician said he offered empathy in the moment but felt he could do little else.

Panelists acknowledged that clinicians are crunched on time when seeing patients, but being willing to initiate conversations about cost with patients and to offer resources can help patients get necessary treatment.
 

Start the conversation

Panel member Caroline Sloan, MD, an assistant professor of medicine at Duke University, Durham, N.C., said making patients aware that you know cost can make a big difference.

The American College of Physicians advises clinicians to ask patients whether they are worried about the cost of care and to not assume which patients may have concerns.

The conversation could be started like this: “I’d like to discuss any concerns you might have about the cost of your health care.”

Normalize the concern by making it more general, and reassure your patient that your goal is to get them the best care. Say something like, “I’ve heard from many patients the cost of medications or tests is becoming hard to manage.”

Once a patient’s concerns are clear, you can direct them to resources for assistance in reducing their costs, Dr. Sloan said, such as ClearHealthCosts, FAIR Health, Healthcare Bluebook, New Choice Health, GoodRx, PharmacyChecker, HealthWell Foundation, Patient Advocate Foundation, Good Days, Good Health Will, Mercy Medical Angels, and the American Association of Family Physicians Neighborhood Navigator.

Dr. Sloan said she knows clinicians don’t have time to understand every insurance plan and other issues related to cost. “But at least know to ask about costs,” she said. “Practice, practice, practice. It feels awkward at first, but it gets easier every time.”

A version of this article first appeared on Medscape.com.

AURORA, COLO. – How often do you talk with patients about how to lower their out-of-pocket costs for medical care?

For most clinicians, the answer is: not often enough. But having those conversations can improve medication adherence and strengthen the patient-clinician relationship, according to panelists at the annual meeting of the Society of General Internal Medicine.

The inverse association between out-of-pocket expenditures and fidelity to prescriptions is clear. A 2020 study by the IQVIA Institute for Human Data Science, for example, found that rates of prescription abandonment are less than 5% when a given medication carries no out-of-pocket cost for patients. That figure rises to 45% when the cost is more than $125, and to 60% when it exceeds $500. One in five Americans said cost prevented them from adhering to medication regimens, according to a new study in JAMA Network Open.

The researchers surveyed more than 2,000 men and women, 40.4% of whom were aged 75 or older. They found that nearly 90% of respondents said they would not be uncomfortable being asked about drug costs before a visit with a physician. A similar share (89.5%) said they would welcome the use by their physician of a real-time tool to determine the cost of their medication.

But the survey results contained a note of warning for clinicians: A significant number of respondents said they would be “extremely” upset if the cost of their medication exceeded the estimate from the pricing tool. And many also said they would be “moderately” or “extremely” angry if their physician used a pricing tool but failed to share the results with them.

“Real-time benefit tools may support medication cost conversations and cost-conscious prescribing, and patients are enthusiastic about their use,” the authors write. “However, if disclosed prices are inaccurate, there is potential for harm through loss of confidence in the physician and nonadherence to prescribed medications.”

While having conversations about cost can be difficult for both clinicians and patients, studies have shown that patients who discuss cost concerns with their doctors feel as if they have stronger relationships as a result.

Clinicians often avoid conversations about out-of-pocket expenses because they don’t know specific price information, they lack solutions to address cost, or they are uncomfortable bringing up the issue.

One member of the audience at the SGIM meeting recalled a patient who worked in a warehouse for a large company. The man, who had type 2 diabetes, had medical insurance, but even with insurance, insulin was going to cost him $150 per month. He struggled to afford the necessary treatment.

“He looked at me and said, ‘What do they want me to do? Do they want me to actually not be able to work for them and not manage my diabetes?’ ”

The clinician said he offered empathy in the moment but felt he could do little else.

Panelists acknowledged that clinicians are crunched on time when seeing patients, but being willing to initiate conversations about cost with patients and to offer resources can help patients get necessary treatment.
 

Start the conversation

Panel member Caroline Sloan, MD, an assistant professor of medicine at Duke University, Durham, N.C., said making patients aware that you know cost can make a big difference.

The American College of Physicians advises clinicians to ask patients whether they are worried about the cost of care and to not assume which patients may have concerns.

The conversation could be started like this: “I’d like to discuss any concerns you might have about the cost of your health care.”

Normalize the concern by making it more general, and reassure your patient that your goal is to get them the best care. Say something like, “I’ve heard from many patients the cost of medications or tests is becoming hard to manage.”

Once a patient’s concerns are clear, you can direct them to resources for assistance in reducing their costs, Dr. Sloan said, such as ClearHealthCosts, FAIR Health, Healthcare Bluebook, New Choice Health, GoodRx, PharmacyChecker, HealthWell Foundation, Patient Advocate Foundation, Good Days, Good Health Will, Mercy Medical Angels, and the American Association of Family Physicians Neighborhood Navigator.

Dr. Sloan said she knows clinicians don’t have time to understand every insurance plan and other issues related to cost. “But at least know to ask about costs,” she said. “Practice, practice, practice. It feels awkward at first, but it gets easier every time.”

A version of this article first appeared on Medscape.com.

Key clinical point: The risk for all-cause mortality is higher among elderly patients with vs without rheumatoid arthritis (RA) who undergo percutaneous coronary intervention (PCI), with the risk being the highest among those with elderly-onset RA (disease presentation after 65 years of age).

Major finding: During the 10-year follow-up, all-cause mortality-associated survival rates were significantly lower in patients with vs without RA (53.7% vs 58.3%; log-rank P < .001) and in patients with elderly-onset vs young-onset RA (48.1% vs 73.7%; log-rank P < .001). Trends were similar for cardiovascular disease-associated survival rates (all log-rank P < .001).

Study details: This was a population-based retrospective cohort study including 74,623 patients age ≥ 65 years with (n = 14,074) or without (n = 60,549) RA who were diagnosed with acute coronary syndrome and underwent PCI.

Disclosures: This study was funded by Soonchunhyang University, South Korea, and the Asan Foundation, South Korea. The authors declared no conflicts of interest.

Source: Kim BY et al. Outcomes of percutaneous coronary intervention in elderly patients with rheumatoid arthritis: A nationwide population-based cohort study. Healthcare (Basel). 2023;11(10):1381 (May 10). Doi: 10.3390/healthcare11101381

Key clinical point: The risk for all-cause mortality is higher among elderly patients with vs without rheumatoid arthritis (RA) who undergo percutaneous coronary intervention (PCI), with the risk being the highest among those with elderly-onset RA (disease presentation after 65 years of age).

Major finding: During the 10-year follow-up, all-cause mortality-associated survival rates were significantly lower in patients with vs without RA (53.7% vs 58.3%; log-rank P < .001) and in patients with elderly-onset vs young-onset RA (48.1% vs 73.7%; log-rank P < .001). Trends were similar for cardiovascular disease-associated survival rates (all log-rank P < .001).

Study details: This was a population-based retrospective cohort study including 74,623 patients age ≥ 65 years with (n = 14,074) or without (n = 60,549) RA who were diagnosed with acute coronary syndrome and underwent PCI.

Disclosures: This study was funded by Soonchunhyang University, South Korea, and the Asan Foundation, South Korea. The authors declared no conflicts of interest.

Source: Kim BY et al. Outcomes of percutaneous coronary intervention in elderly patients with rheumatoid arthritis: A nationwide population-based cohort study. Healthcare (Basel). 2023;11(10):1381 (May 10). Doi: 10.3390/healthcare11101381

Key clinical point: The risk for all-cause mortality is higher among elderly patients with vs without rheumatoid arthritis (RA) who undergo percutaneous coronary intervention (PCI), with the risk being the highest among those with elderly-onset RA (disease presentation after 65 years of age).

Major finding: During the 10-year follow-up, all-cause mortality-associated survival rates were significantly lower in patients with vs without RA (53.7% vs 58.3%; log-rank P < .001) and in patients with elderly-onset vs young-onset RA (48.1% vs 73.7%; log-rank P < .001). Trends were similar for cardiovascular disease-associated survival rates (all log-rank P < .001).

Study details: This was a population-based retrospective cohort study including 74,623 patients age ≥ 65 years with (n = 14,074) or without (n = 60,549) RA who were diagnosed with acute coronary syndrome and underwent PCI.

Disclosures: This study was funded by Soonchunhyang University, South Korea, and the Asan Foundation, South Korea. The authors declared no conflicts of interest.

Source: Kim BY et al. Outcomes of percutaneous coronary intervention in elderly patients with rheumatoid arthritis: A nationwide population-based cohort study. Healthcare (Basel). 2023;11(10):1381 (May 10). Doi: 10.3390/healthcare11101381

Key clinical point: Patients with rheumatoid arthritis (RA) were at an increased risk for Parkinson disease (PD), and patients with seropositive RA had an augmented risk for PD.

Major finding: The risk for PD was 1.74-fold higher in patients with RA vs control individuals without RA (adjusted hazard ratio [aHR] 1.74; 95% CI 1.52-1.99), 1.95-fold higher in patients with seropositive RA vs control individuals without RA (aHR 1.95; 95% CI 1.68-2.26), and 1.61-fold higher in patients with seropositive vs seronegative RA (aHR 1.61; 95% CI 1.20-2.16).

Study details: Findings are from a retrospective cohort study including 54,680 patients with RA (seropositive RA n = 39,010, and seronegative RA n = 15,670) and 273,400 age- and sex-matched control individuals without RA.

Disclosures: This study did not declare the source of funding or any conflicts of interest.

Source: Kang J et al. Rheumatoid arthritis and risk of Parkinson disease in Korea. JAMA Neurol. 2023 (May 1). Doi: 10.1001/jamaneurol.2023.0932

Key clinical point: Patients with rheumatoid arthritis (RA) were at an increased risk for Parkinson disease (PD), and patients with seropositive RA had an augmented risk for PD.

Major finding: The risk for PD was 1.74-fold higher in patients with RA vs control individuals without RA (adjusted hazard ratio [aHR] 1.74; 95% CI 1.52-1.99), 1.95-fold higher in patients with seropositive RA vs control individuals without RA (aHR 1.95; 95% CI 1.68-2.26), and 1.61-fold higher in patients with seropositive vs seronegative RA (aHR 1.61; 95% CI 1.20-2.16).

Study details: Findings are from a retrospective cohort study including 54,680 patients with RA (seropositive RA n = 39,010, and seronegative RA n = 15,670) and 273,400 age- and sex-matched control individuals without RA.

Disclosures: This study did not declare the source of funding or any conflicts of interest.

Source: Kang J et al. Rheumatoid arthritis and risk of Parkinson disease in Korea. JAMA Neurol. 2023 (May 1). Doi: 10.1001/jamaneurol.2023.0932

Key clinical point: Patients with rheumatoid arthritis (RA) were at an increased risk for Parkinson disease (PD), and patients with seropositive RA had an augmented risk for PD.

Major finding: The risk for PD was 1.74-fold higher in patients with RA vs control individuals without RA (adjusted hazard ratio [aHR] 1.74; 95% CI 1.52-1.99), 1.95-fold higher in patients with seropositive RA vs control individuals without RA (aHR 1.95; 95% CI 1.68-2.26), and 1.61-fold higher in patients with seropositive vs seronegative RA (aHR 1.61; 95% CI 1.20-2.16).

Study details: Findings are from a retrospective cohort study including 54,680 patients with RA (seropositive RA n = 39,010, and seronegative RA n = 15,670) and 273,400 age- and sex-matched control individuals without RA.

Disclosures: This study did not declare the source of funding or any conflicts of interest.

Source: Kang J et al. Rheumatoid arthritis and risk of Parkinson disease in Korea. JAMA Neurol. 2023 (May 1). Doi: 10.1001/jamaneurol.2023.0932

Key clinical point: Monotherapy or combination therapy with tumor necrosis factor inhibitors (TNFi) and interleukin-6 receptor inhibitors (IL-6Ri) led to similar clinical outcomes in biologic/targeted synthetic disease-modifying antirheumatic drug (b/tsDMARD)-experienced patients with rheumatoid arthritis (RA).

Major finding: Over 6 months, TNFi and IL-6Ri monotherapies were associated with comparable odds of achieving Clinical Disease Activity Index-based low disease activity (adjusted odds ratio [aOR] 0.99; 95% CI 0.59-1.67) and ≥0.22-unit improvement in Health Assessment Questionnaire-Disability Index (aOR 1.13; 95% CI 0.72-1.77), with results being similar with combination therapy.

Study details: This retrospective observational study included 2739 b/tsDMARD-experienced patients with RA and moderate or high disease activity who initiated TNFi or IL-6Ri monotherapy or combination therapy.

Disclosures: The registry was sponsored by CorEvitas, LLC, and this analysis was funded by Sanofi and Regeneron. Seven authors declared being current or former employees or owning stocks, stock options, or patents of Sanofi or CorEvitas, LLC. Several authors reported ties with Sanofi, Regeneron, and other sources.

Source: Sebba A et al. Comparative effectiveness of TNF inhibitor vs IL-6 receptor inhibitor as monotherapy or combination therapy with methotrexate in biologic-experienced patients with rheumatoid arthritis: An analysis from the CorEvitas RA Registry. Clin Rheumatol. 2023 (Apr 15). Doi: 10.1007/s10067-023-06588-7

Key clinical point: Monotherapy or combination therapy with tumor necrosis factor inhibitors (TNFi) and interleukin-6 receptor inhibitors (IL-6Ri) led to similar clinical outcomes in biologic/targeted synthetic disease-modifying antirheumatic drug (b/tsDMARD)-experienced patients with rheumatoid arthritis (RA).

Major finding: Over 6 months, TNFi and IL-6Ri monotherapies were associated with comparable odds of achieving Clinical Disease Activity Index-based low disease activity (adjusted odds ratio [aOR] 0.99; 95% CI 0.59-1.67) and ≥0.22-unit improvement in Health Assessment Questionnaire-Disability Index (aOR 1.13; 95% CI 0.72-1.77), with results being similar with combination therapy.

Study details: This retrospective observational study included 2739 b/tsDMARD-experienced patients with RA and moderate or high disease activity who initiated TNFi or IL-6Ri monotherapy or combination therapy.

Disclosures: The registry was sponsored by CorEvitas, LLC, and this analysis was funded by Sanofi and Regeneron. Seven authors declared being current or former employees or owning stocks, stock options, or patents of Sanofi or CorEvitas, LLC. Several authors reported ties with Sanofi, Regeneron, and other sources.

Source: Sebba A et al. Comparative effectiveness of TNF inhibitor vs IL-6 receptor inhibitor as monotherapy or combination therapy with methotrexate in biologic-experienced patients with rheumatoid arthritis: An analysis from the CorEvitas RA Registry. Clin Rheumatol. 2023 (Apr 15). Doi: 10.1007/s10067-023-06588-7

Key clinical point: Monotherapy or combination therapy with tumor necrosis factor inhibitors (TNFi) and interleukin-6 receptor inhibitors (IL-6Ri) led to similar clinical outcomes in biologic/targeted synthetic disease-modifying antirheumatic drug (b/tsDMARD)-experienced patients with rheumatoid arthritis (RA).

Major finding: Over 6 months, TNFi and IL-6Ri monotherapies were associated with comparable odds of achieving Clinical Disease Activity Index-based low disease activity (adjusted odds ratio [aOR] 0.99; 95% CI 0.59-1.67) and ≥0.22-unit improvement in Health Assessment Questionnaire-Disability Index (aOR 1.13; 95% CI 0.72-1.77), with results being similar with combination therapy.

Study details: This retrospective observational study included 2739 b/tsDMARD-experienced patients with RA and moderate or high disease activity who initiated TNFi or IL-6Ri monotherapy or combination therapy.

Disclosures: The registry was sponsored by CorEvitas, LLC, and this analysis was funded by Sanofi and Regeneron. Seven authors declared being current or former employees or owning stocks, stock options, or patents of Sanofi or CorEvitas, LLC. Several authors reported ties with Sanofi, Regeneron, and other sources.

Source: Sebba A et al. Comparative effectiveness of TNF inhibitor vs IL-6 receptor inhibitor as monotherapy or combination therapy with methotrexate in biologic-experienced patients with rheumatoid arthritis: An analysis from the CorEvitas RA Registry. Clin Rheumatol. 2023 (Apr 15). Doi: 10.1007/s10067-023-06588-7

Key clinical point: Patients with rheumatoid arthritis (RA) may be more susceptible to coronary atherosclerosis, and active intervention for RA may reduce the incidence of coronary atherosclerosis.

Major finding: Genetic predisposition to RA increased the risk for coronary atherosclerosis (odds ratio 1.0021; P < .05). However, genetic liability to coronary atherosclerosis did not increase the risk for RA (P  =  .06).

Study details: Findings are from a two-sample Mendelian randomization study that evaluated genetic variants associated with RA using the data of 14,361 patients and 42,923 control individuals and those associated with coronary atherosclerosis using data of 14,334 patients and 346,860 control individuals.

Disclosures: This study did not declare any specific source of funding. The authors declared no conflicts of interest.

Source: Nie Q et al. Rheumatoid arthritis and coronary atherosclerosis: A two-sample Mendelian randomization study. Front Cardiovasc Med. 2023;10:1033644 (Apr 28). Doi: 10.3389/fcvm.2023.1033644

Key clinical point: Patients with rheumatoid arthritis (RA) may be more susceptible to coronary atherosclerosis, and active intervention for RA may reduce the incidence of coronary atherosclerosis.

Major finding: Genetic predisposition to RA increased the risk for coronary atherosclerosis (odds ratio 1.0021; P < .05). However, genetic liability to coronary atherosclerosis did not increase the risk for RA (P  =  .06).

Study details: Findings are from a two-sample Mendelian randomization study that evaluated genetic variants associated with RA using the data of 14,361 patients and 42,923 control individuals and those associated with coronary atherosclerosis using data of 14,334 patients and 346,860 control individuals.

Disclosures: This study did not declare any specific source of funding. The authors declared no conflicts of interest.

Source: Nie Q et al. Rheumatoid arthritis and coronary atherosclerosis: A two-sample Mendelian randomization study. Front Cardiovasc Med. 2023;10:1033644 (Apr 28). Doi: 10.3389/fcvm.2023.1033644

Key clinical point: Patients with rheumatoid arthritis (RA) may be more susceptible to coronary atherosclerosis, and active intervention for RA may reduce the incidence of coronary atherosclerosis.

Major finding: Genetic predisposition to RA increased the risk for coronary atherosclerosis (odds ratio 1.0021; P < .05). However, genetic liability to coronary atherosclerosis did not increase the risk for RA (P  =  .06).

Study details: Findings are from a two-sample Mendelian randomization study that evaluated genetic variants associated with RA using the data of 14,361 patients and 42,923 control individuals and those associated with coronary atherosclerosis using data of 14,334 patients and 346,860 control individuals.

Disclosures: This study did not declare any specific source of funding. The authors declared no conflicts of interest.

Source: Nie Q et al. Rheumatoid arthritis and coronary atherosclerosis: A two-sample Mendelian randomization study. Front Cardiovasc Med. 2023;10:1033644 (Apr 28). Doi: 10.3389/fcvm.2023.1033644

Key clinical point: Risk for first primary cancer was not significantly different among patients with rheumatoid arthritis (RA) receiving Janus kinase inhibitors (JAKi) vs biologic disease-modifying antirheumatic drugs (bDMARD). However, excess risk cannot be ruled out among those receiving JAKi.

Major finding: Patients with RA treated with JAKi had a numerically higher but not statistically significantly higher risk for first primary cancer (hazard ratio 1.41; 95% CI 0.76-2.37) compared with those treated with bDMARD.

Study details: Findings are from an observational cohort study including patients with RA without prior cancer diagnosis who initiated JAKi (n = 875) or bDMARD (n = 4247).

Disclosures: This study received financial support from the Danish Rheumatism Association and Danish Cancer Society. Several authors declared being employees of, receiving research grants and honoraria from, participating in advisory boards of, or serving on steering committees for various sources.

Source: Westermann R et al. Cancer risk in patients with rheumatoid arthritis treated with Janus kinase inhibitors: A nationwide Danish register-based cohort study. Rheumatology (Oxford). 2023 (Apr 13). Doi: 10.1093/rheumatology/kead163

Key clinical point: Risk for first primary cancer was not significantly different among patients with rheumatoid arthritis (RA) receiving Janus kinase inhibitors (JAKi) vs biologic disease-modifying antirheumatic drugs (bDMARD). However, excess risk cannot be ruled out among those receiving JAKi.

Major finding: Patients with RA treated with JAKi had a numerically higher but not statistically significantly higher risk for first primary cancer (hazard ratio 1.41; 95% CI 0.76-2.37) compared with those treated with bDMARD.

Study details: Findings are from an observational cohort study including patients with RA without prior cancer diagnosis who initiated JAKi (n = 875) or bDMARD (n = 4247).

Disclosures: This study received financial support from the Danish Rheumatism Association and Danish Cancer Society. Several authors declared being employees of, receiving research grants and honoraria from, participating in advisory boards of, or serving on steering committees for various sources.

Source: Westermann R et al. Cancer risk in patients with rheumatoid arthritis treated with Janus kinase inhibitors: A nationwide Danish register-based cohort study. Rheumatology (Oxford). 2023 (Apr 13). Doi: 10.1093/rheumatology/kead163

Key clinical point: Risk for first primary cancer was not significantly different among patients with rheumatoid arthritis (RA) receiving Janus kinase inhibitors (JAKi) vs biologic disease-modifying antirheumatic drugs (bDMARD). However, excess risk cannot be ruled out among those receiving JAKi.

Major finding: Patients with RA treated with JAKi had a numerically higher but not statistically significantly higher risk for first primary cancer (hazard ratio 1.41; 95% CI 0.76-2.37) compared with those treated with bDMARD.

Study details: Findings are from an observational cohort study including patients with RA without prior cancer diagnosis who initiated JAKi (n = 875) or bDMARD (n = 4247).

Disclosures: This study received financial support from the Danish Rheumatism Association and Danish Cancer Society. Several authors declared being employees of, receiving research grants and honoraria from, participating in advisory boards of, or serving on steering committees for various sources.

Source: Westermann R et al. Cancer risk in patients with rheumatoid arthritis treated with Janus kinase inhibitors: A nationwide Danish register-based cohort study. Rheumatology (Oxford). 2023 (Apr 13). Doi: 10.1093/rheumatology/kead163

Key clinical point: Human papillomavirus (HPV) infection was associated with an increased prevalence of rheumatoid arthritis (RA), whereas HPV immunization lowered RA prevalence in adults aged 18-59 years.

Major finding: A significant association was observed between HPV infection and increased prevalence of RA (adjusted odds ratio [aOR] 1.074; 95% CI 1.071-1.076), whereas HPV immunization was associated with a significantly reduced RA prevalence (aOR 0.477; 95% CI 0.472-0.481).

Study details: Findings are from a population-based cohort study including adults age 18-59 years with complete data on HPV infection and history of RA (n = 15,677) and those with complete data on HPV vaccination and history of RA (n = 8944).

Disclosures: This study was supported by the Nanjing Medical University Science, China, and Technology Development Fund and other sources. The authors declared no conflicts of interest.

Source: Yang G et al. Association between human papillomavirus infection or immunization and risk for rheumatoid arthritis. Front Immunol. 2023;14:1130217 (Apr 14). Doi: 10.3389/fimmu.2023.1130217

Key clinical point: Human papillomavirus (HPV) infection was associated with an increased prevalence of rheumatoid arthritis (RA), whereas HPV immunization lowered RA prevalence in adults aged 18-59 years.

Major finding: A significant association was observed between HPV infection and increased prevalence of RA (adjusted odds ratio [aOR] 1.074; 95% CI 1.071-1.076), whereas HPV immunization was associated with a significantly reduced RA prevalence (aOR 0.477; 95% CI 0.472-0.481).

Study details: Findings are from a population-based cohort study including adults age 18-59 years with complete data on HPV infection and history of RA (n = 15,677) and those with complete data on HPV vaccination and history of RA (n = 8944).

Disclosures: This study was supported by the Nanjing Medical University Science, China, and Technology Development Fund and other sources. The authors declared no conflicts of interest.

Source: Yang G et al. Association between human papillomavirus infection or immunization and risk for rheumatoid arthritis. Front Immunol. 2023;14:1130217 (Apr 14). Doi: 10.3389/fimmu.2023.1130217

Key clinical point: Human papillomavirus (HPV) infection was associated with an increased prevalence of rheumatoid arthritis (RA), whereas HPV immunization lowered RA prevalence in adults aged 18-59 years.

Major finding: A significant association was observed between HPV infection and increased prevalence of RA (adjusted odds ratio [aOR] 1.074; 95% CI 1.071-1.076), whereas HPV immunization was associated with a significantly reduced RA prevalence (aOR 0.477; 95% CI 0.472-0.481).

Study details: Findings are from a population-based cohort study including adults age 18-59 years with complete data on HPV infection and history of RA (n = 15,677) and those with complete data on HPV vaccination and history of RA (n = 8944).

Disclosures: This study was supported by the Nanjing Medical University Science, China, and Technology Development Fund and other sources. The authors declared no conflicts of interest.

Source: Yang G et al. Association between human papillomavirus infection or immunization and risk for rheumatoid arthritis. Front Immunol. 2023;14:1130217 (Apr 14). Doi: 10.3389/fimmu.2023.1130217

Key clinical point: Patients with rheumatoid arthritis (RA) with better overall disease activity and longer etanercept treatment duration are more likely to remain in remission after transition from methotrexate+etanercept combination therapy to methotrexate or etanercept monotherapy.

Major finding: At week 48, the likelihood of patients remaining in Simple Disease Activity Index-based remission or maintaining low disease activity was 1.12 times higher with long-term etanercept monotherapy (P  =  .044) but was 0.93 times lower with each 1-point increase in Patient Global Assessment of Disease Activity (P  =  .012) and C-reactive protein (P  =  .033).

Study details: Findings are from the phase 3, SEAM-RA trial including 253 patients with RA who achieved remission with 24 weeks of methotrexate+etanercept combination therapy and were randomly assigned to continue combination therapy or transition to methotrexate+placebo or etanercept+placebo.

Disclosures: A wholly owned subsidiary of Amgen Inc., Immunex, funded this study. Three authors declared being employees and stockholders of Amgen Inc., and four authors declared ties with various sources, including Amgen.

Source: Curtis JR R et al. Factors associated with maintenance of remission following change from combination therapy to monotherapy in patients with rheumatoid arthritis. J Rheumatol. 2023 (Apr 15). Doi: 10.3899/jrheum.2022-1008.

Key clinical point: Patients with rheumatoid arthritis (RA) with better overall disease activity and longer etanercept treatment duration are more likely to remain in remission after transition from methotrexate+etanercept combination therapy to methotrexate or etanercept monotherapy.

Major finding: At week 48, the likelihood of patients remaining in Simple Disease Activity Index-based remission or maintaining low disease activity was 1.12 times higher with long-term etanercept monotherapy (P  =  .044) but was 0.93 times lower with each 1-point increase in Patient Global Assessment of Disease Activity (P  =  .012) and C-reactive protein (P  =  .033).

Study details: Findings are from the phase 3, SEAM-RA trial including 253 patients with RA who achieved remission with 24 weeks of methotrexate+etanercept combination therapy and were randomly assigned to continue combination therapy or transition to methotrexate+placebo or etanercept+placebo.

Disclosures: A wholly owned subsidiary of Amgen Inc., Immunex, funded this study. Three authors declared being employees and stockholders of Amgen Inc., and four authors declared ties with various sources, including Amgen.

Source: Curtis JR R et al. Factors associated with maintenance of remission following change from combination therapy to monotherapy in patients with rheumatoid arthritis. J Rheumatol. 2023 (Apr 15). Doi: 10.3899/jrheum.2022-1008.

Key clinical point: Patients with rheumatoid arthritis (RA) with better overall disease activity and longer etanercept treatment duration are more likely to remain in remission after transition from methotrexate+etanercept combination therapy to methotrexate or etanercept monotherapy.

Major finding: At week 48, the likelihood of patients remaining in Simple Disease Activity Index-based remission or maintaining low disease activity was 1.12 times higher with long-term etanercept monotherapy (P  =  .044) but was 0.93 times lower with each 1-point increase in Patient Global Assessment of Disease Activity (P  =  .012) and C-reactive protein (P  =  .033).

Study details: Findings are from the phase 3, SEAM-RA trial including 253 patients with RA who achieved remission with 24 weeks of methotrexate+etanercept combination therapy and were randomly assigned to continue combination therapy or transition to methotrexate+placebo or etanercept+placebo.

Disclosures: A wholly owned subsidiary of Amgen Inc., Immunex, funded this study. Three authors declared being employees and stockholders of Amgen Inc., and four authors declared ties with various sources, including Amgen.

Source: Curtis JR R et al. Factors associated with maintenance of remission following change from combination therapy to monotherapy in patients with rheumatoid arthritis. J Rheumatol. 2023 (Apr 15). Doi: 10.3899/jrheum.2022-1008.