MDedge Endocrinology

VENICE, ITALY — Obesity as defined by adiposity measures corresponds to a lower body mass index (BMI) cutoff (≥ 27) in men and women of middle age or older than does the widely used conventional obesity threshold of ≥ 30, shows a study performed in Italy.

Presenting at this year’s European Congress on Obesity (ECO), researchers from the University of Rome Tor Vergata and University of Modena and Reggio Emilia, Italy, and Beirut Arab University, Lebanon, conducted the study to compare the validity of the traditional World Health Organization (WHO) BMI threshold for obesity classification (≥ 30) vs adiposity levels as an alternative measure in middle-aged and older Italians. 

Marwan El Ghoch, PhD, a professor in the Department of Biomedical, Metabolic and Neuroscience, University of Modena and Reggio Emilia, presented the findings as a poster (GC4.152). “If you classify obesity with only BMI and without consideration of body composition, then this will not be enough. I believe BMI can be considered as a screening starting point, but we need to understand the body composition of fat and muscle too,” he said.

“We recommend this new cutoff point be applied in clinical settings when screening individuals for obesity in Italy,” El Ghoch asserted.

BMI Limitations Misses Body Composition 

If obesity is a chronic disease defined as excessive accumulation of body fat and leading to increased risk for disease, disability, and mortality, then “the identification of obesity based on body fat measurements is the most reliable method,” but he acknowledged that measuring this is not readily available in most clinical settings, and as such, “simple BMI has a place,” Dr. El Ghoch said.

“Use of BMI has its limitations, for example, it does not distinguish between body composition compartments — so between muscle and fat mass, nor does it detect changes across the lifespan of an individual [for example, the shift to more fat and less muscle with age] and it varies by ethnicity,” he pointed out. 

This led El Ghoch to ask whether using BMI as a threshold for obesity was suitable for all age groups. 

The researchers included 4800 participants of mixed gender aged 40-80 years of age. Based on the WHO’s BMI classification, 1087 people had normal body weight, 1826 had overweight, and 1887 had obesity. The participants were then categorized by adiposity status on the basis of the total body fat percentage as measured by dual-energy x-ray absorptiometry (DXA), and obesity was predicted by statistical analysis.

The analysis found that around 38% of men and 41% of women had a BMI ≥ 30 based on conventional BMI criteria, indicating obesity. However, when assessed according to body fat percentage, around 71% of the men and 64% of the women were determined to have obesity. 

Dr. El Ghoch and his colleagues calculated that a lower BMI cutoff of around 27 for obesity in people older than 40 years may be more appropriate than the existing BMI threshold of 30. 

The researchers noted some limitations of their work, including that it was a single-center, cross-sectional observational study conducted in one area of Italy. In addition, they did not account for possible confounders, such as dietary habits, and physical activity patterns, and sleep health, all of which can increase the likelihood of obesity and may interact with age-related differences. 

Missing a Significant Proportion of the Population at Risk for Obesity-Related Diseases

In an interview, Luca Busetto, MD, obesity specialist and research assistant at the Center for the Study and the Integrated Treatment of the Obesity, University of Padova, Italy, and local ECO president, commented on the study and the issue of BMI as a measure and threshold. “I think the problem we face with a classic cutoff using BMI is that we miss a significant group of people who have BMI less than 30 but have a high fat mass,” he said, adding, “but these people have the same risk of developing chronic diseases as those people with higher BMI. If they have a bad fat distribution, then their risk of complications is even higher. 

“Dr El Ghoch’s study underlines the lack of treatment for this significant part of the population,” he remarked. “We also need to use waist circumference and waist-to-height [ratio] as additional measures in this population.” 

Dr. Busetto also presented a population-based study at ECO that included over 400,000 people with a follow-up of 8 years. “We found the risk of developing obesity complications, including type 2 diabetes, hypertension, osteoarthritis, and cardiovascular disease, is not only dependent on BMI but [also] dependent on your waist-to-height ratio,” he said, highlighting that “some of these complications are only predicted by the waist-to-height ratio and not by your BMI — in particular cardiovascular diseases.

“I honestly think any screening process today needs to include both BMI and waist-to-height ratio. Having a DXA scan is great in a specialist setting, but routinely we need a measure that is valid in every office in every country and small town.”

Francesco Rubino, MD, chair of metabolic and bariatric surgery at King›s College London, United Kingdom, also remarked that understanding the changes in fat and lean mass proportions and distribution in middle years will affect health in later life, and importantly from a clinical perspective, it is a time where there is still some opportunity to intervene. 

Reflecting further on how it underscores the limitations of BMI in misclassifying people as having obesity or not, Rubino asked, “Importantly, does this make a difference to health and longevity? Really, we need an active measure of adiposity first, and then even if we do say someone has obesity — so excess adiposity — then does this translate into illness, because [excess adiposity] does not translate into disease for every individual?

“Any measure we use as a diagnostic criterion needs to reflect the ongoing disease in an individual, not only the risk of future disease — because not every person experiences this. As a doctor, we deal with the individual and how the diagnosis of disease relates to the individual in a clinic now, as well as the risk of tomorrow,” he concluded. 

Dr. El Ghoch declares no conflicts of interest. Dr. Rubino disclosed that he has received research grants from Novo Nordisk, Medtronic, and Johnson & Johnson. He has undertaken paid consultancy work for GI Dynamics and received honoraria for lectures from Medtronic, Novo Nordisk, and Johnson & Johnson. He is a member of the data safety monitoring board for GT Metabolic Solutions and has provided scientific advice to Keyron, MetaDeq, GHP Scientific, and ViBo Health for no remuneration. Dr. Busetto discloses relationships with Burno Farmaceutici, Novo Nordisk, PronoKal, Rhythm, and Therascience. 

A version of this article appeared on Medscape.com.

VENICE, ITALY — Obesity as defined by adiposity measures corresponds to a lower body mass index (BMI) cutoff (≥ 27) in men and women of middle age or older than does the widely used conventional obesity threshold of ≥ 30, shows a study performed in Italy.

Presenting at this year’s European Congress on Obesity (ECO), researchers from the University of Rome Tor Vergata and University of Modena and Reggio Emilia, Italy, and Beirut Arab University, Lebanon, conducted the study to compare the validity of the traditional World Health Organization (WHO) BMI threshold for obesity classification (≥ 30) vs adiposity levels as an alternative measure in middle-aged and older Italians. 

Marwan El Ghoch, PhD, a professor in the Department of Biomedical, Metabolic and Neuroscience, University of Modena and Reggio Emilia, presented the findings as a poster (GC4.152). “If you classify obesity with only BMI and without consideration of body composition, then this will not be enough. I believe BMI can be considered as a screening starting point, but we need to understand the body composition of fat and muscle too,” he said.

“We recommend this new cutoff point be applied in clinical settings when screening individuals for obesity in Italy,” El Ghoch asserted.

BMI Limitations Misses Body Composition 

If obesity is a chronic disease defined as excessive accumulation of body fat and leading to increased risk for disease, disability, and mortality, then “the identification of obesity based on body fat measurements is the most reliable method,” but he acknowledged that measuring this is not readily available in most clinical settings, and as such, “simple BMI has a place,” Dr. El Ghoch said.

“Use of BMI has its limitations, for example, it does not distinguish between body composition compartments — so between muscle and fat mass, nor does it detect changes across the lifespan of an individual [for example, the shift to more fat and less muscle with age] and it varies by ethnicity,” he pointed out. 

This led El Ghoch to ask whether using BMI as a threshold for obesity was suitable for all age groups. 

The researchers included 4800 participants of mixed gender aged 40-80 years of age. Based on the WHO’s BMI classification, 1087 people had normal body weight, 1826 had overweight, and 1887 had obesity. The participants were then categorized by adiposity status on the basis of the total body fat percentage as measured by dual-energy x-ray absorptiometry (DXA), and obesity was predicted by statistical analysis.

The analysis found that around 38% of men and 41% of women had a BMI ≥ 30 based on conventional BMI criteria, indicating obesity. However, when assessed according to body fat percentage, around 71% of the men and 64% of the women were determined to have obesity. 

Dr. El Ghoch and his colleagues calculated that a lower BMI cutoff of around 27 for obesity in people older than 40 years may be more appropriate than the existing BMI threshold of 30. 

The researchers noted some limitations of their work, including that it was a single-center, cross-sectional observational study conducted in one area of Italy. In addition, they did not account for possible confounders, such as dietary habits, and physical activity patterns, and sleep health, all of which can increase the likelihood of obesity and may interact with age-related differences. 

Missing a Significant Proportion of the Population at Risk for Obesity-Related Diseases

In an interview, Luca Busetto, MD, obesity specialist and research assistant at the Center for the Study and the Integrated Treatment of the Obesity, University of Padova, Italy, and local ECO president, commented on the study and the issue of BMI as a measure and threshold. “I think the problem we face with a classic cutoff using BMI is that we miss a significant group of people who have BMI less than 30 but have a high fat mass,” he said, adding, “but these people have the same risk of developing chronic diseases as those people with higher BMI. If they have a bad fat distribution, then their risk of complications is even higher. 

“Dr El Ghoch’s study underlines the lack of treatment for this significant part of the population,” he remarked. “We also need to use waist circumference and waist-to-height [ratio] as additional measures in this population.” 

Dr. Busetto also presented a population-based study at ECO that included over 400,000 people with a follow-up of 8 years. “We found the risk of developing obesity complications, including type 2 diabetes, hypertension, osteoarthritis, and cardiovascular disease, is not only dependent on BMI but [also] dependent on your waist-to-height ratio,” he said, highlighting that “some of these complications are only predicted by the waist-to-height ratio and not by your BMI — in particular cardiovascular diseases.

“I honestly think any screening process today needs to include both BMI and waist-to-height ratio. Having a DXA scan is great in a specialist setting, but routinely we need a measure that is valid in every office in every country and small town.”

Francesco Rubino, MD, chair of metabolic and bariatric surgery at King›s College London, United Kingdom, also remarked that understanding the changes in fat and lean mass proportions and distribution in middle years will affect health in later life, and importantly from a clinical perspective, it is a time where there is still some opportunity to intervene. 

Reflecting further on how it underscores the limitations of BMI in misclassifying people as having obesity or not, Rubino asked, “Importantly, does this make a difference to health and longevity? Really, we need an active measure of adiposity first, and then even if we do say someone has obesity — so excess adiposity — then does this translate into illness, because [excess adiposity] does not translate into disease for every individual?

“Any measure we use as a diagnostic criterion needs to reflect the ongoing disease in an individual, not only the risk of future disease — because not every person experiences this. As a doctor, we deal with the individual and how the diagnosis of disease relates to the individual in a clinic now, as well as the risk of tomorrow,” he concluded. 

Dr. El Ghoch declares no conflicts of interest. Dr. Rubino disclosed that he has received research grants from Novo Nordisk, Medtronic, and Johnson & Johnson. He has undertaken paid consultancy work for GI Dynamics and received honoraria for lectures from Medtronic, Novo Nordisk, and Johnson & Johnson. He is a member of the data safety monitoring board for GT Metabolic Solutions and has provided scientific advice to Keyron, MetaDeq, GHP Scientific, and ViBo Health for no remuneration. Dr. Busetto discloses relationships with Burno Farmaceutici, Novo Nordisk, PronoKal, Rhythm, and Therascience. 

A version of this article appeared on Medscape.com.

VENICE, ITALY — Obesity as defined by adiposity measures corresponds to a lower body mass index (BMI) cutoff (≥ 27) in men and women of middle age or older than does the widely used conventional obesity threshold of ≥ 30, shows a study performed in Italy.

Presenting at this year’s European Congress on Obesity (ECO), researchers from the University of Rome Tor Vergata and University of Modena and Reggio Emilia, Italy, and Beirut Arab University, Lebanon, conducted the study to compare the validity of the traditional World Health Organization (WHO) BMI threshold for obesity classification (≥ 30) vs adiposity levels as an alternative measure in middle-aged and older Italians. 

Marwan El Ghoch, PhD, a professor in the Department of Biomedical, Metabolic and Neuroscience, University of Modena and Reggio Emilia, presented the findings as a poster (GC4.152). “If you classify obesity with only BMI and without consideration of body composition, then this will not be enough. I believe BMI can be considered as a screening starting point, but we need to understand the body composition of fat and muscle too,” he said.

“We recommend this new cutoff point be applied in clinical settings when screening individuals for obesity in Italy,” El Ghoch asserted.

BMI Limitations Misses Body Composition 

If obesity is a chronic disease defined as excessive accumulation of body fat and leading to increased risk for disease, disability, and mortality, then “the identification of obesity based on body fat measurements is the most reliable method,” but he acknowledged that measuring this is not readily available in most clinical settings, and as such, “simple BMI has a place,” Dr. El Ghoch said.

“Use of BMI has its limitations, for example, it does not distinguish between body composition compartments — so between muscle and fat mass, nor does it detect changes across the lifespan of an individual [for example, the shift to more fat and less muscle with age] and it varies by ethnicity,” he pointed out. 

This led El Ghoch to ask whether using BMI as a threshold for obesity was suitable for all age groups. 

The researchers included 4800 participants of mixed gender aged 40-80 years of age. Based on the WHO’s BMI classification, 1087 people had normal body weight, 1826 had overweight, and 1887 had obesity. The participants were then categorized by adiposity status on the basis of the total body fat percentage as measured by dual-energy x-ray absorptiometry (DXA), and obesity was predicted by statistical analysis.

The analysis found that around 38% of men and 41% of women had a BMI ≥ 30 based on conventional BMI criteria, indicating obesity. However, when assessed according to body fat percentage, around 71% of the men and 64% of the women were determined to have obesity. 

Dr. El Ghoch and his colleagues calculated that a lower BMI cutoff of around 27 for obesity in people older than 40 years may be more appropriate than the existing BMI threshold of 30. 

The researchers noted some limitations of their work, including that it was a single-center, cross-sectional observational study conducted in one area of Italy. In addition, they did not account for possible confounders, such as dietary habits, and physical activity patterns, and sleep health, all of which can increase the likelihood of obesity and may interact with age-related differences. 

Missing a Significant Proportion of the Population at Risk for Obesity-Related Diseases

In an interview, Luca Busetto, MD, obesity specialist and research assistant at the Center for the Study and the Integrated Treatment of the Obesity, University of Padova, Italy, and local ECO president, commented on the study and the issue of BMI as a measure and threshold. “I think the problem we face with a classic cutoff using BMI is that we miss a significant group of people who have BMI less than 30 but have a high fat mass,” he said, adding, “but these people have the same risk of developing chronic diseases as those people with higher BMI. If they have a bad fat distribution, then their risk of complications is even higher. 

“Dr El Ghoch’s study underlines the lack of treatment for this significant part of the population,” he remarked. “We also need to use waist circumference and waist-to-height [ratio] as additional measures in this population.” 

Dr. Busetto also presented a population-based study at ECO that included over 400,000 people with a follow-up of 8 years. “We found the risk of developing obesity complications, including type 2 diabetes, hypertension, osteoarthritis, and cardiovascular disease, is not only dependent on BMI but [also] dependent on your waist-to-height ratio,” he said, highlighting that “some of these complications are only predicted by the waist-to-height ratio and not by your BMI — in particular cardiovascular diseases.

“I honestly think any screening process today needs to include both BMI and waist-to-height ratio. Having a DXA scan is great in a specialist setting, but routinely we need a measure that is valid in every office in every country and small town.”

Francesco Rubino, MD, chair of metabolic and bariatric surgery at King›s College London, United Kingdom, also remarked that understanding the changes in fat and lean mass proportions and distribution in middle years will affect health in later life, and importantly from a clinical perspective, it is a time where there is still some opportunity to intervene. 

Reflecting further on how it underscores the limitations of BMI in misclassifying people as having obesity or not, Rubino asked, “Importantly, does this make a difference to health and longevity? Really, we need an active measure of adiposity first, and then even if we do say someone has obesity — so excess adiposity — then does this translate into illness, because [excess adiposity] does not translate into disease for every individual?

“Any measure we use as a diagnostic criterion needs to reflect the ongoing disease in an individual, not only the risk of future disease — because not every person experiences this. As a doctor, we deal with the individual and how the diagnosis of disease relates to the individual in a clinic now, as well as the risk of tomorrow,” he concluded. 

Dr. El Ghoch declares no conflicts of interest. Dr. Rubino disclosed that he has received research grants from Novo Nordisk, Medtronic, and Johnson & Johnson. He has undertaken paid consultancy work for GI Dynamics and received honoraria for lectures from Medtronic, Novo Nordisk, and Johnson & Johnson. He is a member of the data safety monitoring board for GT Metabolic Solutions and has provided scientific advice to Keyron, MetaDeq, GHP Scientific, and ViBo Health for no remuneration. Dr. Busetto discloses relationships with Burno Farmaceutici, Novo Nordisk, PronoKal, Rhythm, and Therascience. 

A version of this article appeared on Medscape.com.

Over the past few decades, the US Food and Drug Administration (FDA) has increasingly relied on surrogate measures such as blood tests instead of clinical outcomes for medication approvals. But critics say the agency lacks consistent standards to ensure the surrogate aligns with clinical outcomes that matter to patients — things like improvements in symptoms and gains in function.

Sometimes those decisions backfire. Consider: In July 2021, the FDA approved aducanumab for the treatment of Alzheimer’s disease, bucking the advice of an advisory panel for the agency that questioned the effectiveness of the medication. Regulators relied on data from the drugmaker, Biogen, showing the monoclonal antibody could reduce levels of amyloid beta plaques in blood — a surrogate marker officials hoped would translate to clinical benefit.

The FDA’s decision triggered significant controversy, and Biogen in January announced it is pulling it from the market this year, citing disappointing sales.

Although the case of aducanumab might seem extreme, given the stakes — Alzheimer’s remains a disease without an effective treatment — it’s far from unusual.

“When we prescribe a drug, there is an underlying assumption that the FDA has done its due diligence to confirm the drug is safe and of benefit,” said Reshma Ramachandran, MD, MPP, MHS, a researcher at Yale School of Medicine, New Haven, Connecticut, and a coauthor of a recent review of surrogate outcomes. “In fact, we found either no evidence or low-quality evidence.” Such markers are associated with clinical outcomes. “We just don’t know if they work meaningfully to treat the patient’s condition. The results were pretty shocking for us,” she said.

The FDA in 2018 released an Adult Surrogate Endpoint Table listing markers that can be used as substitutes for clinical outcomes to more quickly test, review, and approve new therapies. The analysis found the majority of these endpoints lacked subsequent confirmations, defined as published meta-analyses of clinical studies to validate the association between the marker and a clinical outcome important to patients.

In a paper published in JAMA, Dr. Ramachandran and her colleagues looked at 37 surrogate endpoints for nearly 3 dozen nononcologic diseases in the table.

Approval with surrogate markers implies responsibility for postapproval or validation studies — not just lab measures or imaging findings but mortality, morbidity, or improved quality of life, said Joshua D. Wallach, PhD, MS, assistant professor in the department of epidemiology at the Emory Rollins School of Public Health in Atlanta and lead author of the JAMA review.

Dr. Wallach said surrogate markers are easier to measure and do not require large and long trials. But the FDA has not provided clear rules for what makes a surrogate marker valid in clinical trials.

“They’ve said that at a minimum, it requires meta-analytical evidence from studies that have looked at the correlation or the association between the surrogate and the clinical outcome,” Dr. Wallach said. “Our understanding was that if that’s a minimum expectation, we should be able to find those studies in the literature. And the reality is that we were unable to find evidence from those types of studies supporting the association between the surrogate and the clinical outcome.”

Physicians generally do not receive training about the FDA approval process and the difference between biomarkers, surrogate markers, and clinical endpoints, Dr. Ramachandran said. “Our study shows that things are much more uncertain than we thought when it comes to the prescribing of new drugs,” she said.
 

Surrogate Markers on the Rise

Dr. Wallach’s group looked for published meta-analyses compiling randomized controlled trials reporting surrogate endpoints for more than 3 dozen chronic nononcologic conditions, including type 2 diabetes, Alzheimer’s, kidney disease, HIV, gout, and lupus. They found no meta-analyses at all for 59% of the surrogate markers, while for those that were studied, few reported high-strength evidence of an association with clinical outcomes.

The findings echo previous research. In a 2020 study in JAMA Network Open, researchers tallied primary endpoints for all FDA approvals of new drugs and therapies during three 3-year periods: 1995-1997, 2005-2007, and 2015-2017. The proportion of products whose approvals were based on the use of clinical endpoints decreased from 43.8% in 1995-1997 to 28.4% in 2005-2007 to 23.3% in 2015-2017. The share based on surrogate endpoints rose from 43.3% to roughly 60% over the same interval.

A 2017 study in the Journal of Health Economics found the use of “imperfect” surrogate endpoints helped support the approval of an average of 16 new drugs per year between 2010 and 2014 compared with six per year from 1998 to 2008.

Similar concerns about weak associations between surrogate markers and drugs used to treat cancer have been documented before, including in a 2020 study published in eClinicalMedicine. The researchers found the surrogate endpoints in the FDA table either were not tested or were tested but proven to be weak surrogates.

“And yet the FDA considered these as good enough not only for accelerated approval but also for regular approval,” said Bishal Gyawali, MD, PhD, associate professor in the department of oncology at Queen’s University, Kingston, Ontario, Canada, who led the group.

The use of surrogate endpoints is also increasing in Europe, said Huseyin Naci, MHS, PhD, associate professor of health policy at the London School of Economics and Political Science in England. He cited a cohort study of 298 randomized clinical trials (RCTs) in JAMA Oncology suggesting “contemporary oncology RCTs now largely measure putative surrogate endpoints.” Dr. Wallach called the FDA’s surrogate table “a great first step toward transparency. But a key column is missing from that table, telling us what is the basis for which the FDA allows drug companies to use the recognized surrogate markers. What is the evidence they are considering?”

If the agency allows companies the flexibility to validate surrogate endpoints, postmarketing studies designed to confirm the clinical utility of those endpoints should follow.

“We obviously want physicians to be guided by evidence when they’re selecting treatments, and they need to be able to interpret the clinical benefits of the drug that they’re prescribing,” he said. “This is really about having the research consumer, patients, and physicians, as well as industry, understand why certain markers are considered and not considered.”

Dr. Wallach reported receiving grants from the FDA (through the Yale University — Mayo Clinic Center of Excellence in Regulatory Science and Innovation), National Institute on Alcohol Abuse and Alcoholism (1K01AA028258), and Johnson & Johnson (through the Yale University Open Data Access Project); and consulting fees from Hagens Berman Sobol Shapiro LLP and Dugan Law Firm APLC outside the submitted work. Dr. Ramachandran reported receiving grants from the Stavros Niarchos Foundation and FDA; receiving consulting fees from ReAct Action on Antibiotic Resistance strategy policy program outside the submitted work; and serving in an unpaid capacity as chair of the FDA task force for the nonprofit organization Doctors for America and in an unpaid capacity as board president for Universities Allied for Essential Medicines North America.
 

A version of this article appeared on Medscape.com.

Over the past few decades, the US Food and Drug Administration (FDA) has increasingly relied on surrogate measures such as blood tests instead of clinical outcomes for medication approvals. But critics say the agency lacks consistent standards to ensure the surrogate aligns with clinical outcomes that matter to patients — things like improvements in symptoms and gains in function.

Sometimes those decisions backfire. Consider: In July 2021, the FDA approved aducanumab for the treatment of Alzheimer’s disease, bucking the advice of an advisory panel for the agency that questioned the effectiveness of the medication. Regulators relied on data from the drugmaker, Biogen, showing the monoclonal antibody could reduce levels of amyloid beta plaques in blood — a surrogate marker officials hoped would translate to clinical benefit.

The FDA’s decision triggered significant controversy, and Biogen in January announced it is pulling it from the market this year, citing disappointing sales.

Although the case of aducanumab might seem extreme, given the stakes — Alzheimer’s remains a disease without an effective treatment — it’s far from unusual.

“When we prescribe a drug, there is an underlying assumption that the FDA has done its due diligence to confirm the drug is safe and of benefit,” said Reshma Ramachandran, MD, MPP, MHS, a researcher at Yale School of Medicine, New Haven, Connecticut, and a coauthor of a recent review of surrogate outcomes. “In fact, we found either no evidence or low-quality evidence.” Such markers are associated with clinical outcomes. “We just don’t know if they work meaningfully to treat the patient’s condition. The results were pretty shocking for us,” she said.

The FDA in 2018 released an Adult Surrogate Endpoint Table listing markers that can be used as substitutes for clinical outcomes to more quickly test, review, and approve new therapies. The analysis found the majority of these endpoints lacked subsequent confirmations, defined as published meta-analyses of clinical studies to validate the association between the marker and a clinical outcome important to patients.

In a paper published in JAMA, Dr. Ramachandran and her colleagues looked at 37 surrogate endpoints for nearly 3 dozen nononcologic diseases in the table.

Approval with surrogate markers implies responsibility for postapproval or validation studies — not just lab measures or imaging findings but mortality, morbidity, or improved quality of life, said Joshua D. Wallach, PhD, MS, assistant professor in the department of epidemiology at the Emory Rollins School of Public Health in Atlanta and lead author of the JAMA review.

Dr. Wallach said surrogate markers are easier to measure and do not require large and long trials. But the FDA has not provided clear rules for what makes a surrogate marker valid in clinical trials.

“They’ve said that at a minimum, it requires meta-analytical evidence from studies that have looked at the correlation or the association between the surrogate and the clinical outcome,” Dr. Wallach said. “Our understanding was that if that’s a minimum expectation, we should be able to find those studies in the literature. And the reality is that we were unable to find evidence from those types of studies supporting the association between the surrogate and the clinical outcome.”

Physicians generally do not receive training about the FDA approval process and the difference between biomarkers, surrogate markers, and clinical endpoints, Dr. Ramachandran said. “Our study shows that things are much more uncertain than we thought when it comes to the prescribing of new drugs,” she said.
 

Surrogate Markers on the Rise

Dr. Wallach’s group looked for published meta-analyses compiling randomized controlled trials reporting surrogate endpoints for more than 3 dozen chronic nononcologic conditions, including type 2 diabetes, Alzheimer’s, kidney disease, HIV, gout, and lupus. They found no meta-analyses at all for 59% of the surrogate markers, while for those that were studied, few reported high-strength evidence of an association with clinical outcomes.

The findings echo previous research. In a 2020 study in JAMA Network Open, researchers tallied primary endpoints for all FDA approvals of new drugs and therapies during three 3-year periods: 1995-1997, 2005-2007, and 2015-2017. The proportion of products whose approvals were based on the use of clinical endpoints decreased from 43.8% in 1995-1997 to 28.4% in 2005-2007 to 23.3% in 2015-2017. The share based on surrogate endpoints rose from 43.3% to roughly 60% over the same interval.

A 2017 study in the Journal of Health Economics found the use of “imperfect” surrogate endpoints helped support the approval of an average of 16 new drugs per year between 2010 and 2014 compared with six per year from 1998 to 2008.

Similar concerns about weak associations between surrogate markers and drugs used to treat cancer have been documented before, including in a 2020 study published in eClinicalMedicine. The researchers found the surrogate endpoints in the FDA table either were not tested or were tested but proven to be weak surrogates.

“And yet the FDA considered these as good enough not only for accelerated approval but also for regular approval,” said Bishal Gyawali, MD, PhD, associate professor in the department of oncology at Queen’s University, Kingston, Ontario, Canada, who led the group.

The use of surrogate endpoints is also increasing in Europe, said Huseyin Naci, MHS, PhD, associate professor of health policy at the London School of Economics and Political Science in England. He cited a cohort study of 298 randomized clinical trials (RCTs) in JAMA Oncology suggesting “contemporary oncology RCTs now largely measure putative surrogate endpoints.” Dr. Wallach called the FDA’s surrogate table “a great first step toward transparency. But a key column is missing from that table, telling us what is the basis for which the FDA allows drug companies to use the recognized surrogate markers. What is the evidence they are considering?”

If the agency allows companies the flexibility to validate surrogate endpoints, postmarketing studies designed to confirm the clinical utility of those endpoints should follow.

“We obviously want physicians to be guided by evidence when they’re selecting treatments, and they need to be able to interpret the clinical benefits of the drug that they’re prescribing,” he said. “This is really about having the research consumer, patients, and physicians, as well as industry, understand why certain markers are considered and not considered.”

Dr. Wallach reported receiving grants from the FDA (through the Yale University — Mayo Clinic Center of Excellence in Regulatory Science and Innovation), National Institute on Alcohol Abuse and Alcoholism (1K01AA028258), and Johnson & Johnson (through the Yale University Open Data Access Project); and consulting fees from Hagens Berman Sobol Shapiro LLP and Dugan Law Firm APLC outside the submitted work. Dr. Ramachandran reported receiving grants from the Stavros Niarchos Foundation and FDA; receiving consulting fees from ReAct Action on Antibiotic Resistance strategy policy program outside the submitted work; and serving in an unpaid capacity as chair of the FDA task force for the nonprofit organization Doctors for America and in an unpaid capacity as board president for Universities Allied for Essential Medicines North America.
 

A version of this article appeared on Medscape.com.

Over the past few decades, the US Food and Drug Administration (FDA) has increasingly relied on surrogate measures such as blood tests instead of clinical outcomes for medication approvals. But critics say the agency lacks consistent standards to ensure the surrogate aligns with clinical outcomes that matter to patients — things like improvements in symptoms and gains in function.

Sometimes those decisions backfire. Consider: In July 2021, the FDA approved aducanumab for the treatment of Alzheimer’s disease, bucking the advice of an advisory panel for the agency that questioned the effectiveness of the medication. Regulators relied on data from the drugmaker, Biogen, showing the monoclonal antibody could reduce levels of amyloid beta plaques in blood — a surrogate marker officials hoped would translate to clinical benefit.

The FDA’s decision triggered significant controversy, and Biogen in January announced it is pulling it from the market this year, citing disappointing sales.

Although the case of aducanumab might seem extreme, given the stakes — Alzheimer’s remains a disease without an effective treatment — it’s far from unusual.

“When we prescribe a drug, there is an underlying assumption that the FDA has done its due diligence to confirm the drug is safe and of benefit,” said Reshma Ramachandran, MD, MPP, MHS, a researcher at Yale School of Medicine, New Haven, Connecticut, and a coauthor of a recent review of surrogate outcomes. “In fact, we found either no evidence or low-quality evidence.” Such markers are associated with clinical outcomes. “We just don’t know if they work meaningfully to treat the patient’s condition. The results were pretty shocking for us,” she said.

The FDA in 2018 released an Adult Surrogate Endpoint Table listing markers that can be used as substitutes for clinical outcomes to more quickly test, review, and approve new therapies. The analysis found the majority of these endpoints lacked subsequent confirmations, defined as published meta-analyses of clinical studies to validate the association between the marker and a clinical outcome important to patients.

In a paper published in JAMA, Dr. Ramachandran and her colleagues looked at 37 surrogate endpoints for nearly 3 dozen nononcologic diseases in the table.

Approval with surrogate markers implies responsibility for postapproval or validation studies — not just lab measures or imaging findings but mortality, morbidity, or improved quality of life, said Joshua D. Wallach, PhD, MS, assistant professor in the department of epidemiology at the Emory Rollins School of Public Health in Atlanta and lead author of the JAMA review.

Dr. Wallach said surrogate markers are easier to measure and do not require large and long trials. But the FDA has not provided clear rules for what makes a surrogate marker valid in clinical trials.

“They’ve said that at a minimum, it requires meta-analytical evidence from studies that have looked at the correlation or the association between the surrogate and the clinical outcome,” Dr. Wallach said. “Our understanding was that if that’s a minimum expectation, we should be able to find those studies in the literature. And the reality is that we were unable to find evidence from those types of studies supporting the association between the surrogate and the clinical outcome.”

Physicians generally do not receive training about the FDA approval process and the difference between biomarkers, surrogate markers, and clinical endpoints, Dr. Ramachandran said. “Our study shows that things are much more uncertain than we thought when it comes to the prescribing of new drugs,” she said.
 

Surrogate Markers on the Rise

Dr. Wallach’s group looked for published meta-analyses compiling randomized controlled trials reporting surrogate endpoints for more than 3 dozen chronic nononcologic conditions, including type 2 diabetes, Alzheimer’s, kidney disease, HIV, gout, and lupus. They found no meta-analyses at all for 59% of the surrogate markers, while for those that were studied, few reported high-strength evidence of an association with clinical outcomes.

The findings echo previous research. In a 2020 study in JAMA Network Open, researchers tallied primary endpoints for all FDA approvals of new drugs and therapies during three 3-year periods: 1995-1997, 2005-2007, and 2015-2017. The proportion of products whose approvals were based on the use of clinical endpoints decreased from 43.8% in 1995-1997 to 28.4% in 2005-2007 to 23.3% in 2015-2017. The share based on surrogate endpoints rose from 43.3% to roughly 60% over the same interval.

A 2017 study in the Journal of Health Economics found the use of “imperfect” surrogate endpoints helped support the approval of an average of 16 new drugs per year between 2010 and 2014 compared with six per year from 1998 to 2008.

Similar concerns about weak associations between surrogate markers and drugs used to treat cancer have been documented before, including in a 2020 study published in eClinicalMedicine. The researchers found the surrogate endpoints in the FDA table either were not tested or were tested but proven to be weak surrogates.

“And yet the FDA considered these as good enough not only for accelerated approval but also for regular approval,” said Bishal Gyawali, MD, PhD, associate professor in the department of oncology at Queen’s University, Kingston, Ontario, Canada, who led the group.

The use of surrogate endpoints is also increasing in Europe, said Huseyin Naci, MHS, PhD, associate professor of health policy at the London School of Economics and Political Science in England. He cited a cohort study of 298 randomized clinical trials (RCTs) in JAMA Oncology suggesting “contemporary oncology RCTs now largely measure putative surrogate endpoints.” Dr. Wallach called the FDA’s surrogate table “a great first step toward transparency. But a key column is missing from that table, telling us what is the basis for which the FDA allows drug companies to use the recognized surrogate markers. What is the evidence they are considering?”

If the agency allows companies the flexibility to validate surrogate endpoints, postmarketing studies designed to confirm the clinical utility of those endpoints should follow.

“We obviously want physicians to be guided by evidence when they’re selecting treatments, and they need to be able to interpret the clinical benefits of the drug that they’re prescribing,” he said. “This is really about having the research consumer, patients, and physicians, as well as industry, understand why certain markers are considered and not considered.”

Dr. Wallach reported receiving grants from the FDA (through the Yale University — Mayo Clinic Center of Excellence in Regulatory Science and Innovation), National Institute on Alcohol Abuse and Alcoholism (1K01AA028258), and Johnson & Johnson (through the Yale University Open Data Access Project); and consulting fees from Hagens Berman Sobol Shapiro LLP and Dugan Law Firm APLC outside the submitted work. Dr. Ramachandran reported receiving grants from the Stavros Niarchos Foundation and FDA; receiving consulting fees from ReAct Action on Antibiotic Resistance strategy policy program outside the submitted work; and serving in an unpaid capacity as chair of the FDA task force for the nonprofit organization Doctors for America and in an unpaid capacity as board president for Universities Allied for Essential Medicines North America.
 

A version of this article appeared on Medscape.com.

The annual production of plastic worldwide has increased exponentially from about 2 million tons in 1950 to 460 million tons in 2019, and current levels are expected to triple by 2060.

Plastic contains more than 10,000 chemicals, including carcinogenic substances and endocrine disruptors. Plastic and associated chemicals are responsible for widespread pollution, contaminating aquatic (marine and freshwater), terrestrial, and atmospheric environments globally.

Atmospheric concentrations of plastic particles are on the rise, to the extent that in a remote station in the Eastern Alps in Austria, the contribution of micro- and nanoplastics (MNPs) to organic matter was comparable to data collected at an urban site.

The ocean is the ultimate destination for much of the plastic. All oceans, on the surface and in the depths, contain plastic, which is even found in polar sea ice. Many plastics seem to resist decomposition in the ocean and could persist in the environment for decades. Macro- and microplastic (MP) particles have been identified in hundreds of marine species, including species consumed by humans.

The quantity and fate of MP particles (> 10 µm) and smaller nanoplastics (< 10 µm) in aquatic environments are poorly understood, but what is most concerning is their ability to cross biologic barriers and the potential harm associated with their mobility in biologic systems.
 

MNP Exposure

MNPs can originate from a wide variety of sources, including food, beverages, and food product packaging. Water bottles represent a significant source of ingestible MNPs for people in their daily lives. Recent estimates, using stimulated Raman scattering imaging, documented a concentration of MNP of approximately 2.4 ± 1.3 × 10⁵ particles per liter of bottled water. Around 90% are nanoplastics, which is two to three orders of magnitude higher than previously reported results for larger MPs.

MNPs enter the body primarily through ingestion or inhalation. For example, MNPs can be ingested by drinking liquids or eating food that has been stored or heated in plastic containers from which they have leaked or by using toothpaste that contains them. Infants are exposed to MPs from artificial milk preparation in polypropylene baby bottles, with higher levels than previously detected and ranging from 14,600 to 4,550,000 particles per capita per day.
 

MNP and Biologic Systems

The possible formation of hetero-aggregates between nanoplastics and natural organic matter has long been recognized as a potential challenge in the analysis of nanoplastics and can influence toxicologic results in biologic exposure. The direct visualization of such hetero-aggregates in real-world samples supports these concerns, but the analysis of MNPs with traditional techniques remains challenging. Unlike engineered nanoparticles (prepared in the laboratory as model systems), the nanoplastics in the environment are label-free and exhibit significant heterogeneity in chemical composition and morphology.

A systematic analysis of evidence on the toxic effects of MNPs on murine models, however, showed that 52.78% of biologic endpoints (related to glucose metabolism, reproduction, oxidative stress, and lipid metabolism) were significantly affected by MNP exposure.
 

Between Risk and Toxicity

MNP can enter the body in vivo through the digestive tract, respiratory tract, and skin contact. On average, humans could ingest from 0.1 to 5 g of MNP per week through various exposure routes.

MNPs are a potential risk factor for cardiovascular diseases, as suggested by a recent study on 257 patients with carotid atheromatous plaques. In 58.4% of cases, polyvinyl chloride was detected in the carotid artery plaque, with an average level of 5.2 ± 2.4 μg/mg of plaque. Patients with MNPs inside the atheroma had a higher risk (relative risk, 4.53) for a composite cardiovascular event of myocardial infarction, stroke, or death from any cause at 34 months of follow-up than participants where MNPs were not detectable inside the atheromatous plaque.

The potential link between inflammatory bowel disease (IBD) and MPs has been hypothesized by a study that reported a higher fecal MP concentration in patients with IBD than in healthy individuals. Fecal MP level was correlated with disease severity.

However, these studies have not demonstrated a causal relationship between MNPs and disease, and the way MNPs may influence cellular functions and induce stress responses is not yet well understood.
 

Future Scenarios

Current evidence confirms the fragmentation of plastic beyond the micrometer level and has unequivocally detected nanoplastics in real samples. As with many other particle distributions of the same size in the natural world, there are substantially more nanoplastics, despite their invisibility with conventional imaging techniques, than particles larger than the micron size.

The initial results of studies on MNPs in humans will stimulate future research on the amounts of MNPs that accumulate in tissue over a person’s lifetime. Researchers also will examine how the particles’ characteristics, including their chemical composition, size, and shape, can influence organs and tissues.

The way MNPs can cause harm, including through effects on the immune system and microbiome, will need to be clarified by investigating possible direct cytotoxic effects, consistent with the introductory statement of the Organization for Economic Cooperation and Development global policy forum on plastics, which states, “Plastic pollution is one of the great environmental challenges of the 21st century, causing wide-ranging damage to ecosystems and human health.”

This story was translated from Univadis Italy, which is part of the Medscape professional network, using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.

The annual production of plastic worldwide has increased exponentially from about 2 million tons in 1950 to 460 million tons in 2019, and current levels are expected to triple by 2060.

Plastic contains more than 10,000 chemicals, including carcinogenic substances and endocrine disruptors. Plastic and associated chemicals are responsible for widespread pollution, contaminating aquatic (marine and freshwater), terrestrial, and atmospheric environments globally.

Atmospheric concentrations of plastic particles are on the rise, to the extent that in a remote station in the Eastern Alps in Austria, the contribution of micro- and nanoplastics (MNPs) to organic matter was comparable to data collected at an urban site.

The ocean is the ultimate destination for much of the plastic. All oceans, on the surface and in the depths, contain plastic, which is even found in polar sea ice. Many plastics seem to resist decomposition in the ocean and could persist in the environment for decades. Macro- and microplastic (MP) particles have been identified in hundreds of marine species, including species consumed by humans.

The quantity and fate of MP particles (> 10 µm) and smaller nanoplastics (< 10 µm) in aquatic environments are poorly understood, but what is most concerning is their ability to cross biologic barriers and the potential harm associated with their mobility in biologic systems.
 

MNP Exposure

MNPs can originate from a wide variety of sources, including food, beverages, and food product packaging. Water bottles represent a significant source of ingestible MNPs for people in their daily lives. Recent estimates, using stimulated Raman scattering imaging, documented a concentration of MNP of approximately 2.4 ± 1.3 × 10⁵ particles per liter of bottled water. Around 90% are nanoplastics, which is two to three orders of magnitude higher than previously reported results for larger MPs.

MNPs enter the body primarily through ingestion or inhalation. For example, MNPs can be ingested by drinking liquids or eating food that has been stored or heated in plastic containers from which they have leaked or by using toothpaste that contains them. Infants are exposed to MPs from artificial milk preparation in polypropylene baby bottles, with higher levels than previously detected and ranging from 14,600 to 4,550,000 particles per capita per day.
 

MNP and Biologic Systems

The possible formation of hetero-aggregates between nanoplastics and natural organic matter has long been recognized as a potential challenge in the analysis of nanoplastics and can influence toxicologic results in biologic exposure. The direct visualization of such hetero-aggregates in real-world samples supports these concerns, but the analysis of MNPs with traditional techniques remains challenging. Unlike engineered nanoparticles (prepared in the laboratory as model systems), the nanoplastics in the environment are label-free and exhibit significant heterogeneity in chemical composition and morphology.

A systematic analysis of evidence on the toxic effects of MNPs on murine models, however, showed that 52.78% of biologic endpoints (related to glucose metabolism, reproduction, oxidative stress, and lipid metabolism) were significantly affected by MNP exposure.
 

Between Risk and Toxicity

MNP can enter the body in vivo through the digestive tract, respiratory tract, and skin contact. On average, humans could ingest from 0.1 to 5 g of MNP per week through various exposure routes.

MNPs are a potential risk factor for cardiovascular diseases, as suggested by a recent study on 257 patients with carotid atheromatous plaques. In 58.4% of cases, polyvinyl chloride was detected in the carotid artery plaque, with an average level of 5.2 ± 2.4 μg/mg of plaque. Patients with MNPs inside the atheroma had a higher risk (relative risk, 4.53) for a composite cardiovascular event of myocardial infarction, stroke, or death from any cause at 34 months of follow-up than participants where MNPs were not detectable inside the atheromatous plaque.

The potential link between inflammatory bowel disease (IBD) and MPs has been hypothesized by a study that reported a higher fecal MP concentration in patients with IBD than in healthy individuals. Fecal MP level was correlated with disease severity.

However, these studies have not demonstrated a causal relationship between MNPs and disease, and the way MNPs may influence cellular functions and induce stress responses is not yet well understood.
 

Future Scenarios

Current evidence confirms the fragmentation of plastic beyond the micrometer level and has unequivocally detected nanoplastics in real samples. As with many other particle distributions of the same size in the natural world, there are substantially more nanoplastics, despite their invisibility with conventional imaging techniques, than particles larger than the micron size.

The initial results of studies on MNPs in humans will stimulate future research on the amounts of MNPs that accumulate in tissue over a person’s lifetime. Researchers also will examine how the particles’ characteristics, including their chemical composition, size, and shape, can influence organs and tissues.

The way MNPs can cause harm, including through effects on the immune system and microbiome, will need to be clarified by investigating possible direct cytotoxic effects, consistent with the introductory statement of the Organization for Economic Cooperation and Development global policy forum on plastics, which states, “Plastic pollution is one of the great environmental challenges of the 21st century, causing wide-ranging damage to ecosystems and human health.”

This story was translated from Univadis Italy, which is part of the Medscape professional network, using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.

The annual production of plastic worldwide has increased exponentially from about 2 million tons in 1950 to 460 million tons in 2019, and current levels are expected to triple by 2060.

Plastic contains more than 10,000 chemicals, including carcinogenic substances and endocrine disruptors. Plastic and associated chemicals are responsible for widespread pollution, contaminating aquatic (marine and freshwater), terrestrial, and atmospheric environments globally.

Atmospheric concentrations of plastic particles are on the rise, to the extent that in a remote station in the Eastern Alps in Austria, the contribution of micro- and nanoplastics (MNPs) to organic matter was comparable to data collected at an urban site.

The ocean is the ultimate destination for much of the plastic. All oceans, on the surface and in the depths, contain plastic, which is even found in polar sea ice. Many plastics seem to resist decomposition in the ocean and could persist in the environment for decades. Macro- and microplastic (MP) particles have been identified in hundreds of marine species, including species consumed by humans.

The quantity and fate of MP particles (> 10 µm) and smaller nanoplastics (< 10 µm) in aquatic environments are poorly understood, but what is most concerning is their ability to cross biologic barriers and the potential harm associated with their mobility in biologic systems.
 

MNP Exposure

MNPs can originate from a wide variety of sources, including food, beverages, and food product packaging. Water bottles represent a significant source of ingestible MNPs for people in their daily lives. Recent estimates, using stimulated Raman scattering imaging, documented a concentration of MNP of approximately 2.4 ± 1.3 × 10⁵ particles per liter of bottled water. Around 90% are nanoplastics, which is two to three orders of magnitude higher than previously reported results for larger MPs.

MNPs enter the body primarily through ingestion or inhalation. For example, MNPs can be ingested by drinking liquids or eating food that has been stored or heated in plastic containers from which they have leaked or by using toothpaste that contains them. Infants are exposed to MPs from artificial milk preparation in polypropylene baby bottles, with higher levels than previously detected and ranging from 14,600 to 4,550,000 particles per capita per day.
 

MNP and Biologic Systems

The possible formation of hetero-aggregates between nanoplastics and natural organic matter has long been recognized as a potential challenge in the analysis of nanoplastics and can influence toxicologic results in biologic exposure. The direct visualization of such hetero-aggregates in real-world samples supports these concerns, but the analysis of MNPs with traditional techniques remains challenging. Unlike engineered nanoparticles (prepared in the laboratory as model systems), the nanoplastics in the environment are label-free and exhibit significant heterogeneity in chemical composition and morphology.

A systematic analysis of evidence on the toxic effects of MNPs on murine models, however, showed that 52.78% of biologic endpoints (related to glucose metabolism, reproduction, oxidative stress, and lipid metabolism) were significantly affected by MNP exposure.
 

Between Risk and Toxicity

MNP can enter the body in vivo through the digestive tract, respiratory tract, and skin contact. On average, humans could ingest from 0.1 to 5 g of MNP per week through various exposure routes.

MNPs are a potential risk factor for cardiovascular diseases, as suggested by a recent study on 257 patients with carotid atheromatous plaques. In 58.4% of cases, polyvinyl chloride was detected in the carotid artery plaque, with an average level of 5.2 ± 2.4 μg/mg of plaque. Patients with MNPs inside the atheroma had a higher risk (relative risk, 4.53) for a composite cardiovascular event of myocardial infarction, stroke, or death from any cause at 34 months of follow-up than participants where MNPs were not detectable inside the atheromatous plaque.

The potential link between inflammatory bowel disease (IBD) and MPs has been hypothesized by a study that reported a higher fecal MP concentration in patients with IBD than in healthy individuals. Fecal MP level was correlated with disease severity.

However, these studies have not demonstrated a causal relationship between MNPs and disease, and the way MNPs may influence cellular functions and induce stress responses is not yet well understood.
 

Future Scenarios

Current evidence confirms the fragmentation of plastic beyond the micrometer level and has unequivocally detected nanoplastics in real samples. As with many other particle distributions of the same size in the natural world, there are substantially more nanoplastics, despite their invisibility with conventional imaging techniques, than particles larger than the micron size.

The initial results of studies on MNPs in humans will stimulate future research on the amounts of MNPs that accumulate in tissue over a person’s lifetime. Researchers also will examine how the particles’ characteristics, including their chemical composition, size, and shape, can influence organs and tissues.

The way MNPs can cause harm, including through effects on the immune system and microbiome, will need to be clarified by investigating possible direct cytotoxic effects, consistent with the introductory statement of the Organization for Economic Cooperation and Development global policy forum on plastics, which states, “Plastic pollution is one of the great environmental challenges of the 21st century, causing wide-ranging damage to ecosystems and human health.”

This story was translated from Univadis Italy, which is part of the Medscape professional network, using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.

SAN FRANCISCO — Discussion of gestational weight gain occurred in only half of first-time obstetric visits, most often brought up by the provider, according to data presented at the annual clinical and scientific meeting of the American College of Obstetricians and Gynecologists.

“Weight can be a challenging and sensitive topic at a healthcare visit,” Malini Harinath, an undergraduate research assistant at Magee-Women’s Research Institute at University of Pittsburgh Medical Center, told attendees. “Providers discussed weight gain recommendations in less than half of conversations.”

The researchers analyzed an existing dataset of audio-recorded first obstetric visits to find out how often gestational weight gain was brought up, who initiated the discussion, whether ACOG guidelines were discussed, and what the provider’s comments were.

Among 150 visits, half (50%) involved discussion of weight, with patients bringing it up 24% of the time and providers bringing it up 72% of the time. In the other 3% of visits, it was brought up by a third party, such as a partner or other family member with the patient.

Only two of those visits mentioned body mass index (BMI) specifically, and ACOG guidelines on gestational weight gain were brought up in only six visits (8% of the visits where weight was mentioned). However, mention of recommendations on gestational weight gain was more frequent, coming up in nearly half (46.7%) of the visits where weight was mentioned, though that was still just 23% of all visits.

Concern about weight was brought up in 25.3% of visits where weight was discussed, and the provider’s reassurance to the patient occurred in about a third (32%) of those visits. General comments about the patient’s body occurred in 16% of visits, such as a clinician saying, “Usually we start trying [to find the heartbeat] at about 15 weeks, but you are so skinny we might be able to find it now.”

Ms. Harinath intends to look in future research at whether patient race or BMI are associated with the frequency and content of gestational weight gain conversations and to explore how patients react to different ways that discussion of weight is brought up.

Katherine Kaak, MD, a second-year resident at the University of Tennessee Graduate School of Medicine in Knoxville, was surprised that weight was brought up in only half of the visits. “The clinical takeaway is just how important counseling in the prenatal time is and how a lot of this discussion is preventive medicine,” Dr. Kaak said. “Even though we think of those visits as being quick, it’s good to keep in mind that we need to really take our time and make sure we counsel the patient as best we can.”

There’s a fair amount of research suggesting that existing recommendations on gestational weight gain are not very good because they’re very generic, Jill Maples, PhD, associate professor of ob.gyn. research at the University of Tennessee Graduate School of Medicine, said in an interview. For example, the guidelines are generally the same for everyone with a BMI over 30, but a person with a BMI of 30 is very different from someone with a BMI of 50, she said.

“There’s not even a lot of clarity on what is appropriate weight gain for that group because some people have seen good outcomes on the lower end of gestational weight gain,” Dr. Maples said. She said it’s important that clinicians not forget about the importance of these discussions, however, because lifestyle habits and gestational weight gain are related to maternal and neonatal outcomes.

The authors, Dr. Kaak, and Dr. Maples had no disclosures. The research was funded by the National Institute on Drug Abuse.

SAN FRANCISCO — Discussion of gestational weight gain occurred in only half of first-time obstetric visits, most often brought up by the provider, according to data presented at the annual clinical and scientific meeting of the American College of Obstetricians and Gynecologists.

“Weight can be a challenging and sensitive topic at a healthcare visit,” Malini Harinath, an undergraduate research assistant at Magee-Women’s Research Institute at University of Pittsburgh Medical Center, told attendees. “Providers discussed weight gain recommendations in less than half of conversations.”

The researchers analyzed an existing dataset of audio-recorded first obstetric visits to find out how often gestational weight gain was brought up, who initiated the discussion, whether ACOG guidelines were discussed, and what the provider’s comments were.

Among 150 visits, half (50%) involved discussion of weight, with patients bringing it up 24% of the time and providers bringing it up 72% of the time. In the other 3% of visits, it was brought up by a third party, such as a partner or other family member with the patient.

Only two of those visits mentioned body mass index (BMI) specifically, and ACOG guidelines on gestational weight gain were brought up in only six visits (8% of the visits where weight was mentioned). However, mention of recommendations on gestational weight gain was more frequent, coming up in nearly half (46.7%) of the visits where weight was mentioned, though that was still just 23% of all visits.

Concern about weight was brought up in 25.3% of visits where weight was discussed, and the provider’s reassurance to the patient occurred in about a third (32%) of those visits. General comments about the patient’s body occurred in 16% of visits, such as a clinician saying, “Usually we start trying [to find the heartbeat] at about 15 weeks, but you are so skinny we might be able to find it now.”

Ms. Harinath intends to look in future research at whether patient race or BMI are associated with the frequency and content of gestational weight gain conversations and to explore how patients react to different ways that discussion of weight is brought up.

Katherine Kaak, MD, a second-year resident at the University of Tennessee Graduate School of Medicine in Knoxville, was surprised that weight was brought up in only half of the visits. “The clinical takeaway is just how important counseling in the prenatal time is and how a lot of this discussion is preventive medicine,” Dr. Kaak said. “Even though we think of those visits as being quick, it’s good to keep in mind that we need to really take our time and make sure we counsel the patient as best we can.”

There’s a fair amount of research suggesting that existing recommendations on gestational weight gain are not very good because they’re very generic, Jill Maples, PhD, associate professor of ob.gyn. research at the University of Tennessee Graduate School of Medicine, said in an interview. For example, the guidelines are generally the same for everyone with a BMI over 30, but a person with a BMI of 30 is very different from someone with a BMI of 50, she said.

“There’s not even a lot of clarity on what is appropriate weight gain for that group because some people have seen good outcomes on the lower end of gestational weight gain,” Dr. Maples said. She said it’s important that clinicians not forget about the importance of these discussions, however, because lifestyle habits and gestational weight gain are related to maternal and neonatal outcomes.

The authors, Dr. Kaak, and Dr. Maples had no disclosures. The research was funded by the National Institute on Drug Abuse.

SAN FRANCISCO — Discussion of gestational weight gain occurred in only half of first-time obstetric visits, most often brought up by the provider, according to data presented at the annual clinical and scientific meeting of the American College of Obstetricians and Gynecologists.

“Weight can be a challenging and sensitive topic at a healthcare visit,” Malini Harinath, an undergraduate research assistant at Magee-Women’s Research Institute at University of Pittsburgh Medical Center, told attendees. “Providers discussed weight gain recommendations in less than half of conversations.”

The researchers analyzed an existing dataset of audio-recorded first obstetric visits to find out how often gestational weight gain was brought up, who initiated the discussion, whether ACOG guidelines were discussed, and what the provider’s comments were.

Among 150 visits, half (50%) involved discussion of weight, with patients bringing it up 24% of the time and providers bringing it up 72% of the time. In the other 3% of visits, it was brought up by a third party, such as a partner or other family member with the patient.

Only two of those visits mentioned body mass index (BMI) specifically, and ACOG guidelines on gestational weight gain were brought up in only six visits (8% of the visits where weight was mentioned). However, mention of recommendations on gestational weight gain was more frequent, coming up in nearly half (46.7%) of the visits where weight was mentioned, though that was still just 23% of all visits.

Concern about weight was brought up in 25.3% of visits where weight was discussed, and the provider’s reassurance to the patient occurred in about a third (32%) of those visits. General comments about the patient’s body occurred in 16% of visits, such as a clinician saying, “Usually we start trying [to find the heartbeat] at about 15 weeks, but you are so skinny we might be able to find it now.”

Ms. Harinath intends to look in future research at whether patient race or BMI are associated with the frequency and content of gestational weight gain conversations and to explore how patients react to different ways that discussion of weight is brought up.

Katherine Kaak, MD, a second-year resident at the University of Tennessee Graduate School of Medicine in Knoxville, was surprised that weight was brought up in only half of the visits. “The clinical takeaway is just how important counseling in the prenatal time is and how a lot of this discussion is preventive medicine,” Dr. Kaak said. “Even though we think of those visits as being quick, it’s good to keep in mind that we need to really take our time and make sure we counsel the patient as best we can.”

There’s a fair amount of research suggesting that existing recommendations on gestational weight gain are not very good because they’re very generic, Jill Maples, PhD, associate professor of ob.gyn. research at the University of Tennessee Graduate School of Medicine, said in an interview. For example, the guidelines are generally the same for everyone with a BMI over 30, but a person with a BMI of 30 is very different from someone with a BMI of 50, she said.

“There’s not even a lot of clarity on what is appropriate weight gain for that group because some people have seen good outcomes on the lower end of gestational weight gain,” Dr. Maples said. She said it’s important that clinicians not forget about the importance of these discussions, however, because lifestyle habits and gestational weight gain are related to maternal and neonatal outcomes.

The authors, Dr. Kaak, and Dr. Maples had no disclosures. The research was funded by the National Institute on Drug Abuse.

TOPLINE: 

Individuals with overweight and obesity who reach a weight-loss plateau at around 6 months on a healthy weight-loss diet may not achieve further weight reduction after switching to a different weight-loss diet.

METHODOLOGY:

• Dietary and lifestyle interventions initially result in rapid weight loss, followed by a weight-loss plateau after a few months and weight regain within a year or two, and diet fatigue has been proposed as a cause but not studied.
• This secondary analysis of a randomized trial assessed weight-loss trajectories before and after switching from a healthy low-carbohydrate (LC) diet to a healthy low-fat (LF) diet (or vice versa) in individuals with overweight and obesity.
• Overall, 42 participants (mean age, 42 years; 64% women; 87% White individuals) recruited from a local community in Palo Alto, California, were assigned to the LF or LC diet for the first 6 months, after which they were switched to the other diet for the remaining 6 months.
• Data from the DIETFITS trial, wherein participants remained either on the LF or LC diet for 12 months, were used as historical control.

The primary outcome was percent weight change at 3-6 months vs that observed at 6-9 months.

TAKEAWAY:

• The combined average weight loss was 7% (95% CI, 8%-6%) during the first 3 months, declining to 2% (95% CI, 3%-1%) between 3 and 6 months. On switching diets, the weight loss further slowed to 1% (95% CI, 2%-0.4%) between 6 and 9 months, with a modest increase in weight of 0.6% (95% CI, −0.1% to 1.3%) between 9 and 12 months.
• By diet order, participants in the LF first arm did not plateau and experienced a similar weight loss from 6 to 9 months as they had experienced from 3 to 6 months (relative change, −0.1%; 95% CI, −1.5% to 1.3%), while the LC first arm essentially nullified the 3-6 month weight loss during the 6-9 month LF phase (relative change, 2.2%; 95% CI, 0.7%-3.6%).
• For the LC first arm, low-density lipoprotein increased at 3 months and decreased when the participants switched to LF at 6 months, whereas the opposite effect was seen for the transition from LF to LC. Triglyceride levels decreased in both intervention arms.
• Insulin levels decreased in both dietary intervention arms between baseline and 6 months and plateaued following the 6-month dietary switch.

IN PRACTICE:

“This suggests that the weight-loss plateau typically seen at 6 months is physiological and cannot be overcome by simply switching to a different weight-loss diet,” wrote the authors. “As a person transitions from a weight loss to weight maintenance phase, a shift in the approach used may be required.”

SOURCE:

The study, led by Matthew J. Landry, Stanford Prevention Research Center, School of Medicine, Stanford University, California, was published in Scientific Reports.

LIMITATIONS:

The study results showed some possible differential trends but also highlighted the small sample size and large variability. Participants may have been unable to provide accurate estimates of self-reported energy intake. The authors also acknowledged that regular physical activity may have contributed to the maintenance of weight loss observed in this study.

DISCLOSURES:

The study was supported by the Hass Avocado Board; Human Health Service grant (General Clinical Research Centers and National Center for Research Resources, National Institutes of Health); National Heart, Lung, and Blood Institute; and Stanford Diabetes Research Center. The authors declared no conflicts of interest.

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

TOPLINE: 

Individuals with overweight and obesity who reach a weight-loss plateau at around 6 months on a healthy weight-loss diet may not achieve further weight reduction after switching to a different weight-loss diet.

METHODOLOGY:

• Dietary and lifestyle interventions initially result in rapid weight loss, followed by a weight-loss plateau after a few months and weight regain within a year or two, and diet fatigue has been proposed as a cause but not studied.
• This secondary analysis of a randomized trial assessed weight-loss trajectories before and after switching from a healthy low-carbohydrate (LC) diet to a healthy low-fat (LF) diet (or vice versa) in individuals with overweight and obesity.
• Overall, 42 participants (mean age, 42 years; 64% women; 87% White individuals) recruited from a local community in Palo Alto, California, were assigned to the LF or LC diet for the first 6 months, after which they were switched to the other diet for the remaining 6 months.
• Data from the DIETFITS trial, wherein participants remained either on the LF or LC diet for 12 months, were used as historical control.

The primary outcome was percent weight change at 3-6 months vs that observed at 6-9 months.

TAKEAWAY:

• The combined average weight loss was 7% (95% CI, 8%-6%) during the first 3 months, declining to 2% (95% CI, 3%-1%) between 3 and 6 months. On switching diets, the weight loss further slowed to 1% (95% CI, 2%-0.4%) between 6 and 9 months, with a modest increase in weight of 0.6% (95% CI, −0.1% to 1.3%) between 9 and 12 months.
• By diet order, participants in the LF first arm did not plateau and experienced a similar weight loss from 6 to 9 months as they had experienced from 3 to 6 months (relative change, −0.1%; 95% CI, −1.5% to 1.3%), while the LC first arm essentially nullified the 3-6 month weight loss during the 6-9 month LF phase (relative change, 2.2%; 95% CI, 0.7%-3.6%).
• For the LC first arm, low-density lipoprotein increased at 3 months and decreased when the participants switched to LF at 6 months, whereas the opposite effect was seen for the transition from LF to LC. Triglyceride levels decreased in both intervention arms.
• Insulin levels decreased in both dietary intervention arms between baseline and 6 months and plateaued following the 6-month dietary switch.

IN PRACTICE:

“This suggests that the weight-loss plateau typically seen at 6 months is physiological and cannot be overcome by simply switching to a different weight-loss diet,” wrote the authors. “As a person transitions from a weight loss to weight maintenance phase, a shift in the approach used may be required.”

SOURCE:

The study, led by Matthew J. Landry, Stanford Prevention Research Center, School of Medicine, Stanford University, California, was published in Scientific Reports.

LIMITATIONS:

The study results showed some possible differential trends but also highlighted the small sample size and large variability. Participants may have been unable to provide accurate estimates of self-reported energy intake. The authors also acknowledged that regular physical activity may have contributed to the maintenance of weight loss observed in this study.

DISCLOSURES:

The study was supported by the Hass Avocado Board; Human Health Service grant (General Clinical Research Centers and National Center for Research Resources, National Institutes of Health); National Heart, Lung, and Blood Institute; and Stanford Diabetes Research Center. The authors declared no conflicts of interest.

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

TOPLINE: 

Individuals with overweight and obesity who reach a weight-loss plateau at around 6 months on a healthy weight-loss diet may not achieve further weight reduction after switching to a different weight-loss diet.

METHODOLOGY:

• Dietary and lifestyle interventions initially result in rapid weight loss, followed by a weight-loss plateau after a few months and weight regain within a year or two, and diet fatigue has been proposed as a cause but not studied.
• This secondary analysis of a randomized trial assessed weight-loss trajectories before and after switching from a healthy low-carbohydrate (LC) diet to a healthy low-fat (LF) diet (or vice versa) in individuals with overweight and obesity.
• Overall, 42 participants (mean age, 42 years; 64% women; 87% White individuals) recruited from a local community in Palo Alto, California, were assigned to the LF or LC diet for the first 6 months, after which they were switched to the other diet for the remaining 6 months.
• Data from the DIETFITS trial, wherein participants remained either on the LF or LC diet for 12 months, were used as historical control.

The primary outcome was percent weight change at 3-6 months vs that observed at 6-9 months.

TAKEAWAY:

• The combined average weight loss was 7% (95% CI, 8%-6%) during the first 3 months, declining to 2% (95% CI, 3%-1%) between 3 and 6 months. On switching diets, the weight loss further slowed to 1% (95% CI, 2%-0.4%) between 6 and 9 months, with a modest increase in weight of 0.6% (95% CI, −0.1% to 1.3%) between 9 and 12 months.
• By diet order, participants in the LF first arm did not plateau and experienced a similar weight loss from 6 to 9 months as they had experienced from 3 to 6 months (relative change, −0.1%; 95% CI, −1.5% to 1.3%), while the LC first arm essentially nullified the 3-6 month weight loss during the 6-9 month LF phase (relative change, 2.2%; 95% CI, 0.7%-3.6%).
• For the LC first arm, low-density lipoprotein increased at 3 months and decreased when the participants switched to LF at 6 months, whereas the opposite effect was seen for the transition from LF to LC. Triglyceride levels decreased in both intervention arms.
• Insulin levels decreased in both dietary intervention arms between baseline and 6 months and plateaued following the 6-month dietary switch.

IN PRACTICE:

“This suggests that the weight-loss plateau typically seen at 6 months is physiological and cannot be overcome by simply switching to a different weight-loss diet,” wrote the authors. “As a person transitions from a weight loss to weight maintenance phase, a shift in the approach used may be required.”

SOURCE:

The study, led by Matthew J. Landry, Stanford Prevention Research Center, School of Medicine, Stanford University, California, was published in Scientific Reports.

LIMITATIONS:

The study results showed some possible differential trends but also highlighted the small sample size and large variability. Participants may have been unable to provide accurate estimates of self-reported energy intake. The authors also acknowledged that regular physical activity may have contributed to the maintenance of weight loss observed in this study.

DISCLOSURES:

The study was supported by the Hass Avocado Board; Human Health Service grant (General Clinical Research Centers and National Center for Research Resources, National Institutes of Health); National Heart, Lung, and Blood Institute; and Stanford Diabetes Research Center. The authors declared no conflicts of interest.

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

WASHINGTON — Ablation of the gastric fundus to reduce production of the “hunger hormone” ghrelin resulted in decreased appetite and significant weight loss among participants in a small first-in-human trial.

“Patients reported a decrease in hunger, appetite, and cravings and an increase in control over [their] eating,” said senior study investigator Christopher McGowan, MD, AGAF, a gastroenterologist in private practice and medical director of True You Weight Loss in Cary, North Carolina.

Brian Strickland Photography

Major Findings

In the trial, 10 women (mean age, 38 years; mean body mass index, 40.2) underwent endoscopic fundic mucosal ablation via hybrid argon plasma coagulation in an ambulatory setting under general anesthesia from November 1, 2022, to April 14, 2023. The procedure took less than an hour on average, and the technique gave them easy access to the fundus, Dr. McGowan said.

Compared with baseline, there were multiple beneficial outcomes at 6 months:

• 45% less circulating ghrelin in the blood.
• 53% drop in ghrelin-producing cells in the fundus.
• 42% reduction in stomach capacity.
• 43% decrease in hunger, appetite, and cravings.
• 7.7% body weight loss.

Over the 6 months of the study, mean ghrelin concentrations dropped from 461.6 pg/mL at baseline to 254.8 pg/mL (P = .006).

It is fascinating that the hormone ghrelin decreased just by ablating, said Loren Laine, MD, AGAF, professor of medicine (digestive diseases) at Yale School of Medicine and chair of DDW 2024. “They used the same device that we use to treat bleeding ulcers or lesions in the stomach and applied it broadly over the whole upper part of the stomach.”

Another Anti-Obesity Tool?

“We’re all familiar with the epidemic that is obesity affecting nearly one in two adults, and the profound impact that it has on patients’ health, their quality of life, as well as the healthcare system,” Dr. McGowan said. “It’s clear that we need every tool possible to address this because we know that obesity is not a matter of willpower. It’s a disease.”

Gastric fundus ablation “may represent, and frankly should represent, a treatment option for the greater than 100 million US adults with obesity,” he added.

Not every patient wants to or can access GLP-1 medications, Dr. McGowan said. Also, “there’s a difference between taking a medication long-term, requiring an injection every week, vs a single intervention in time that carries forward.”

Ablation could also help people transition after they stop GLP-1 medications to help them maintain their weight loss, he said.

Weight loss is the endpoint you care about the most, said Dr. Laine, who co-moderated the press briefing.

Though the weight loss of 7.7% was not a large percentage, it was only 10 patients. We will have to see whether the total body weight loss is different when they do the procedure in more patients or if they can combine different mechanisms, Dr. Laine said.

It remains unclear whether gastric fundus ablation would be a stand-alone procedure or used in combination with another endoscopic weight-management intervention, bariatric surgery, or medication.

The endoscopic sleeve, which is a stomach-reducing procedure, is very effective, but it doesn’t diminish hunger, Dr. McGowan said. Combining it with ablation may be “a best-of-both-worlds scenario.”

Dr. Laine added that another open question is whether the gastric fundal accommodation will be associated with any side effects such as dyspepsia.

Dr. McGowan reported consulting for Boston Scientific and Apollo Endosurgery. Dr. Laine reported no relevant financial relationships.

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

WASHINGTON — Ablation of the gastric fundus to reduce production of the “hunger hormone” ghrelin resulted in decreased appetite and significant weight loss among participants in a small first-in-human trial.

“Patients reported a decrease in hunger, appetite, and cravings and an increase in control over [their] eating,” said senior study investigator Christopher McGowan, MD, AGAF, a gastroenterologist in private practice and medical director of True You Weight Loss in Cary, North Carolina.

Brian Strickland Photography

Major Findings

In the trial, 10 women (mean age, 38 years; mean body mass index, 40.2) underwent endoscopic fundic mucosal ablation via hybrid argon plasma coagulation in an ambulatory setting under general anesthesia from November 1, 2022, to April 14, 2023. The procedure took less than an hour on average, and the technique gave them easy access to the fundus, Dr. McGowan said.

Compared with baseline, there were multiple beneficial outcomes at 6 months:

• 45% less circulating ghrelin in the blood.
• 53% drop in ghrelin-producing cells in the fundus.
• 42% reduction in stomach capacity.
• 43% decrease in hunger, appetite, and cravings.
• 7.7% body weight loss.

Over the 6 months of the study, mean ghrelin concentrations dropped from 461.6 pg/mL at baseline to 254.8 pg/mL (P = .006).

It is fascinating that the hormone ghrelin decreased just by ablating, said Loren Laine, MD, AGAF, professor of medicine (digestive diseases) at Yale School of Medicine and chair of DDW 2024. “They used the same device that we use to treat bleeding ulcers or lesions in the stomach and applied it broadly over the whole upper part of the stomach.”

Another Anti-Obesity Tool?

“We’re all familiar with the epidemic that is obesity affecting nearly one in two adults, and the profound impact that it has on patients’ health, their quality of life, as well as the healthcare system,” Dr. McGowan said. “It’s clear that we need every tool possible to address this because we know that obesity is not a matter of willpower. It’s a disease.”

Gastric fundus ablation “may represent, and frankly should represent, a treatment option for the greater than 100 million US adults with obesity,” he added.

Not every patient wants to or can access GLP-1 medications, Dr. McGowan said. Also, “there’s a difference between taking a medication long-term, requiring an injection every week, vs a single intervention in time that carries forward.”

Ablation could also help people transition after they stop GLP-1 medications to help them maintain their weight loss, he said.

Weight loss is the endpoint you care about the most, said Dr. Laine, who co-moderated the press briefing.

Though the weight loss of 7.7% was not a large percentage, it was only 10 patients. We will have to see whether the total body weight loss is different when they do the procedure in more patients or if they can combine different mechanisms, Dr. Laine said.

It remains unclear whether gastric fundus ablation would be a stand-alone procedure or used in combination with another endoscopic weight-management intervention, bariatric surgery, or medication.

The endoscopic sleeve, which is a stomach-reducing procedure, is very effective, but it doesn’t diminish hunger, Dr. McGowan said. Combining it with ablation may be “a best-of-both-worlds scenario.”

Dr. Laine added that another open question is whether the gastric fundal accommodation will be associated with any side effects such as dyspepsia.

Dr. McGowan reported consulting for Boston Scientific and Apollo Endosurgery. Dr. Laine reported no relevant financial relationships.

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

WASHINGTON — Ablation of the gastric fundus to reduce production of the “hunger hormone” ghrelin resulted in decreased appetite and significant weight loss among participants in a small first-in-human trial.

“Patients reported a decrease in hunger, appetite, and cravings and an increase in control over [their] eating,” said senior study investigator Christopher McGowan, MD, AGAF, a gastroenterologist in private practice and medical director of True You Weight Loss in Cary, North Carolina.

Brian Strickland Photography

Major Findings

In the trial, 10 women (mean age, 38 years; mean body mass index, 40.2) underwent endoscopic fundic mucosal ablation via hybrid argon plasma coagulation in an ambulatory setting under general anesthesia from November 1, 2022, to April 14, 2023. The procedure took less than an hour on average, and the technique gave them easy access to the fundus, Dr. McGowan said.

Compared with baseline, there were multiple beneficial outcomes at 6 months:

• 45% less circulating ghrelin in the blood.
• 53% drop in ghrelin-producing cells in the fundus.
• 42% reduction in stomach capacity.
• 43% decrease in hunger, appetite, and cravings.
• 7.7% body weight loss.

Over the 6 months of the study, mean ghrelin concentrations dropped from 461.6 pg/mL at baseline to 254.8 pg/mL (P = .006).

It is fascinating that the hormone ghrelin decreased just by ablating, said Loren Laine, MD, AGAF, professor of medicine (digestive diseases) at Yale School of Medicine and chair of DDW 2024. “They used the same device that we use to treat bleeding ulcers or lesions in the stomach and applied it broadly over the whole upper part of the stomach.”

Another Anti-Obesity Tool?

“We’re all familiar with the epidemic that is obesity affecting nearly one in two adults, and the profound impact that it has on patients’ health, their quality of life, as well as the healthcare system,” Dr. McGowan said. “It’s clear that we need every tool possible to address this because we know that obesity is not a matter of willpower. It’s a disease.”

Gastric fundus ablation “may represent, and frankly should represent, a treatment option for the greater than 100 million US adults with obesity,” he added.

Not every patient wants to or can access GLP-1 medications, Dr. McGowan said. Also, “there’s a difference between taking a medication long-term, requiring an injection every week, vs a single intervention in time that carries forward.”

Ablation could also help people transition after they stop GLP-1 medications to help them maintain their weight loss, he said.

Weight loss is the endpoint you care about the most, said Dr. Laine, who co-moderated the press briefing.

Though the weight loss of 7.7% was not a large percentage, it was only 10 patients. We will have to see whether the total body weight loss is different when they do the procedure in more patients or if they can combine different mechanisms, Dr. Laine said.

It remains unclear whether gastric fundus ablation would be a stand-alone procedure or used in combination with another endoscopic weight-management intervention, bariatric surgery, or medication.

The endoscopic sleeve, which is a stomach-reducing procedure, is very effective, but it doesn’t diminish hunger, Dr. McGowan said. Combining it with ablation may be “a best-of-both-worlds scenario.”

Dr. Laine added that another open question is whether the gastric fundal accommodation will be associated with any side effects such as dyspepsia.

Dr. McGowan reported consulting for Boston Scientific and Apollo Endosurgery. Dr. Laine reported no relevant financial relationships.

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

Serious mental illness (SMI), including bipolar disorder or schizophrenia spectrum disorders, is associated with a twofold increased risk for comorbid physical illness, results of a new meta-analysis showed.

“Although treatment of physical and mental health remains siloed in many health services globally, the high prevalence of physical multimorbidity attests to the urgent need for integrated care models that address both physical and mental health outcomes in people with severe mental illness,” the authors, led by Sean Halstead, MD, of The University of Queensland Medical School in Brisbane, Australia, wrote.

The findings were published online in The Lancet Psychiatry.
 

Shorter Lifespan?

SMI is associated with reduced life expectancy, and experts speculate that additional chronic illnesses — whether physical or psychiatric — may underlie this association.

While previous research has paired SMI with comorbid physical illnesses, the researchers noted that this study is the first to focus on both physical and psychiatric multimorbidity in individuals with SMI.

The investigators conducted a meta-analysis of 82 observational studies comprising 1.6 million individuals with SMI and 13.2 million control subjects to determine the risk for physical or psychiatric multimorbidity.

Studies were included if participants were diagnosed with either a schizophrenia spectrum disorder or bipolar disorder, and the study assessed either physical multimorbidity (at least two physical health conditions) or psychiatric multimorbidity (at least three psychiatric conditions), including the initial SMI.

Investigators found that individuals with SMI had more than a twofold increased risk for physical multimorbidity than those without SMI (odds ratio [OR], 2.40; 95% CI, 1.57-3.65; P = .0009).

Physical multimorbidity, which included cardiovascular, endocrine, neurological rental, gastrointestinal, musculoskeletal, and infectious disorders, was prevalent at similar rates in both schizophrenia spectrum disorder and bipolar disorder.

The ratio of physical multimorbidity was about four times higher in younger populations with SMI (mean age ≤ 40; OR, 3.99; 95% CI, 1.43-11.10) than in older populations (mean age > 40; OR, 1.55; 95% CI, 0.96-2.51; subgroup differences, P = .0013).

In terms of absolute prevalence, 25% of those with SMI had a physical multimorbidity, and 14% had a psychiatric multimorbidity, which were primarily anxiety and substance use disorders.

Investigators speculated that physical multimorbidity in SMI could stem from side effects of psychotropic medications, which are known to cause rapid cardiometabolic changes, including weight gain. In addition, lifestyle factors or nonmodifiable risk factors could also contribute to physical multimorbidity.

The study’s limitations included its small sample sizes for subgroup analyses and insufficient analysis for significant covariates, including smoking rates and symptom severity.

“While health services and treatment guidelines often operate on the assumption that individuals have a single principal diagnosis, these results attest to the clinical complexity many people with severe mental illness face in relation to burden of chronic disease,” the investigators wrote. They added that a greater understanding of the epidemiological manifestations of multimorbidity in SMI is “imperative.”

There was no source of funding for this study. Dr. Halstead is supported by the Australian Research Training Program scholarship. Other disclosures were noted in the original article.

A version of this article appeared on Medscape.com .

Serious mental illness (SMI), including bipolar disorder or schizophrenia spectrum disorders, is associated with a twofold increased risk for comorbid physical illness, results of a new meta-analysis showed.

“Although treatment of physical and mental health remains siloed in many health services globally, the high prevalence of physical multimorbidity attests to the urgent need for integrated care models that address both physical and mental health outcomes in people with severe mental illness,” the authors, led by Sean Halstead, MD, of The University of Queensland Medical School in Brisbane, Australia, wrote.

The findings were published online in The Lancet Psychiatry.
 

Shorter Lifespan?

SMI is associated with reduced life expectancy, and experts speculate that additional chronic illnesses — whether physical or psychiatric — may underlie this association.

While previous research has paired SMI with comorbid physical illnesses, the researchers noted that this study is the first to focus on both physical and psychiatric multimorbidity in individuals with SMI.

The investigators conducted a meta-analysis of 82 observational studies comprising 1.6 million individuals with SMI and 13.2 million control subjects to determine the risk for physical or psychiatric multimorbidity.

Studies were included if participants were diagnosed with either a schizophrenia spectrum disorder or bipolar disorder, and the study assessed either physical multimorbidity (at least two physical health conditions) or psychiatric multimorbidity (at least three psychiatric conditions), including the initial SMI.

Investigators found that individuals with SMI had more than a twofold increased risk for physical multimorbidity than those without SMI (odds ratio [OR], 2.40; 95% CI, 1.57-3.65; P = .0009).

Physical multimorbidity, which included cardiovascular, endocrine, neurological rental, gastrointestinal, musculoskeletal, and infectious disorders, was prevalent at similar rates in both schizophrenia spectrum disorder and bipolar disorder.

The ratio of physical multimorbidity was about four times higher in younger populations with SMI (mean age ≤ 40; OR, 3.99; 95% CI, 1.43-11.10) than in older populations (mean age > 40; OR, 1.55; 95% CI, 0.96-2.51; subgroup differences, P = .0013).

In terms of absolute prevalence, 25% of those with SMI had a physical multimorbidity, and 14% had a psychiatric multimorbidity, which were primarily anxiety and substance use disorders.

Investigators speculated that physical multimorbidity in SMI could stem from side effects of psychotropic medications, which are known to cause rapid cardiometabolic changes, including weight gain. In addition, lifestyle factors or nonmodifiable risk factors could also contribute to physical multimorbidity.

The study’s limitations included its small sample sizes for subgroup analyses and insufficient analysis for significant covariates, including smoking rates and symptom severity.

“While health services and treatment guidelines often operate on the assumption that individuals have a single principal diagnosis, these results attest to the clinical complexity many people with severe mental illness face in relation to burden of chronic disease,” the investigators wrote. They added that a greater understanding of the epidemiological manifestations of multimorbidity in SMI is “imperative.”

There was no source of funding for this study. Dr. Halstead is supported by the Australian Research Training Program scholarship. Other disclosures were noted in the original article.

A version of this article appeared on Medscape.com .

Serious mental illness (SMI), including bipolar disorder or schizophrenia spectrum disorders, is associated with a twofold increased risk for comorbid physical illness, results of a new meta-analysis showed.

“Although treatment of physical and mental health remains siloed in many health services globally, the high prevalence of physical multimorbidity attests to the urgent need for integrated care models that address both physical and mental health outcomes in people with severe mental illness,” the authors, led by Sean Halstead, MD, of The University of Queensland Medical School in Brisbane, Australia, wrote.

The findings were published online in The Lancet Psychiatry.
 

Shorter Lifespan?

SMI is associated with reduced life expectancy, and experts speculate that additional chronic illnesses — whether physical or psychiatric — may underlie this association.

While previous research has paired SMI with comorbid physical illnesses, the researchers noted that this study is the first to focus on both physical and psychiatric multimorbidity in individuals with SMI.

The investigators conducted a meta-analysis of 82 observational studies comprising 1.6 million individuals with SMI and 13.2 million control subjects to determine the risk for physical or psychiatric multimorbidity.

Studies were included if participants were diagnosed with either a schizophrenia spectrum disorder or bipolar disorder, and the study assessed either physical multimorbidity (at least two physical health conditions) or psychiatric multimorbidity (at least three psychiatric conditions), including the initial SMI.

Investigators found that individuals with SMI had more than a twofold increased risk for physical multimorbidity than those without SMI (odds ratio [OR], 2.40; 95% CI, 1.57-3.65; P = .0009).

Physical multimorbidity, which included cardiovascular, endocrine, neurological rental, gastrointestinal, musculoskeletal, and infectious disorders, was prevalent at similar rates in both schizophrenia spectrum disorder and bipolar disorder.

The ratio of physical multimorbidity was about four times higher in younger populations with SMI (mean age ≤ 40; OR, 3.99; 95% CI, 1.43-11.10) than in older populations (mean age > 40; OR, 1.55; 95% CI, 0.96-2.51; subgroup differences, P = .0013).

In terms of absolute prevalence, 25% of those with SMI had a physical multimorbidity, and 14% had a psychiatric multimorbidity, which were primarily anxiety and substance use disorders.

Investigators speculated that physical multimorbidity in SMI could stem from side effects of psychotropic medications, which are known to cause rapid cardiometabolic changes, including weight gain. In addition, lifestyle factors or nonmodifiable risk factors could also contribute to physical multimorbidity.

The study’s limitations included its small sample sizes for subgroup analyses and insufficient analysis for significant covariates, including smoking rates and symptom severity.

“While health services and treatment guidelines often operate on the assumption that individuals have a single principal diagnosis, these results attest to the clinical complexity many people with severe mental illness face in relation to burden of chronic disease,” the investigators wrote. They added that a greater understanding of the epidemiological manifestations of multimorbidity in SMI is “imperative.”

There was no source of funding for this study. Dr. Halstead is supported by the Australian Research Training Program scholarship. Other disclosures were noted in the original article.

A version of this article appeared on Medscape.com .

A 50-year-old woman with a history of class 3 obesity, gastroesophageal reflux disease, prediabetes, metabolic dysfunction–associated steatotic liver disease, asthma, and depression returns to our weight management clinic with weight regain 4 years after Roux-en-Y gastric bypass. 

Her initial body weight was 389 lb (176.8 kg; body mass index [BMI], 65), and her nadir weight after surgery was 183 lb (83.2 kg; BMI, 30.5), representing a total weight loss of 53%. During the initial 2 years after surgery, she experienced multiple life stressors and was treated with venlafaxine for mild depression. She regained 25 lb (11.4 kg). Over the next 2 years, she gained another 20 lb (9.1 kg), for a total of 45 lb (20.5 kg) above nadir.

The patient reported increased nighttime consumption of alcohol including vodka, wine, and beer of over 20 drinks per week for the past 2 years. Her laboratory profile showed an elevated fasting glucose level (106 mg/dL, formerly 98 mg/dL), an elevated gamma-glutamyl transferase (GGT) level, and iron deficiency anemia. She admitted to regularly missing doses of postbariatric vitamins and minerals.
 

Ask Patients About Alcohol Use

It’s important to ask patients with significant weight regain after metabolic and bariatric surgery (MBS) about alcohol intake, because patients who have MBS are at an increased risk of developing alcohol use disorder (AUD).

The American Society for Metabolic and Bariatric Surgery recommends screening for alcohol intake both before and after MBS. Underreporting of alcohol consumption is common, but an elevated GGT level or elevated liver enzyme levels can indicate alcohol use. Depression and anxiety exacerbated by life stressors often accompany excessive alcohol intake.

Some antiobesity medications that regulate appetite may also help limit excessive alcohol intake. Naltrexone is used both for the treatment of AUD and for weight management, often in combination with bupropion). In a patient with weight regain and AUD, naltrexone alone would be a reasonable treatment option, although weight loss would probably be modest. The addition of bupropion to naltrexone would probably produce more weight loss; average total body weight loss with bupropion-naltrexone in clinical trials was about 6%. One cautionary note on bupropion: A patient’s seizure history should be elicited, because people with AUD are at increased risk for seizures in the withdrawal stage and bupropion can make those seizures more likely. 

Glucagon-like peptide 1 (GLP-1) receptor agonists (eg, liraglutide and semaglutide) and dual GLP-1/GIP (glucose-dependent insulinotropic polypeptide receptor agonists) (eg, tirzepatide) are second-generation antiobesity medications that produce more weight loss than first-generation agents such as bupropion/naltrexone. Of note, prior bariatric surgery was an exclusion criterion in the clinical trials assessing the efficacy of these agents for weight loss. The use of GLP-1 receptor agonists after MBS in people with inadequate weight loss or weight regain has been an area of active research. The BARI-OPTIMISE randomized clinical trial published in 2023 assessed the safety and efficacy of liraglutide 3.0 mg daily in patients with inadequate weight loss after MBS. The mean body weight reduction was 8.82% in the liraglutide group vs 0.54% in the placebo group. 

There is also emerging interest in the potential of GLP-1 receptor agonists in AUD. These medications act on the central nervous system to influence reward pathways. In rodents, studies have shown that GLP-1 receptor agonist administration reduces alcohol intake, although most studies have focused on short-term effects.

A series of experiments assessed the effects of semaglutide on alcohol intake in rodents. The authors found that semaglutide lowered the alcohol-induced release of dopamine and enhanced dopamine metabolism within the nucleus accumbens.

Evidence in humans is still limited, with only one published randomized controlled trial to date. In the 26-week study, weekly exenatide was not superior to placebo in reducing the number of heavy drinking days in patients with AUD who also received cognitive-behavioral therapy. An exploratory analysis in a subgroup of patients with obesity and AUD showed that exenatide reduced alcohol consumption. Of note, exenatide is rarely used in clinical practice because it does not produce substantial weight loss.

Liraglutide was chosen for this patient because of the established efficacy for this agent in patients with a history of MBS. In addition, patients often anecdotally report reduced desire for alcohol while taking a GLP-1 receptor agonist. Although GLP-1 receptor agonists have been shown to reduce alcohol intake in animal studies, their efficacy and safety in humans with AUD are not yet well established.
 

Back to Our Patient: 

Given the patient’s weight regain, an upper gastrointestinal series was performed to rule out gastro-gastric fistula or other anatomic abnormalities. After fistula was ruled out, she was prescribed liraglutide for weight management, which was titrated from 0.6 mg/d to 3 mg/d per the prescribing guidelines. 

With the use of liraglutide over the next year, the patient maintained a stable weight of 200 lb (90.9 kg) and noted that along with reduced appetite, her cravings for alcohol had diminished and she no longer felt the urge to drink alcohol at night. Her fasting glucose and GGT levels normalized. She began to see a nutritionist regularly and was planning to rejoin a bariatric support group.

Dr. Schmitz is an instructor in the Department of Medicine, Division of Endocrinology, Diabetes, and Metabolism, Weill Cornell Medicine, New York. She has disclosed no relevant financial relationships. Dr. Kashyap is a assistant chief of clinical affairs, Division of Endocrinology, Diabetes and Metabolism, Weill Cornell New York Presbyterian, New York. She disclosed ties to GI Dynamics.

A version of this article appeared on Medscape.com.

A 50-year-old woman with a history of class 3 obesity, gastroesophageal reflux disease, prediabetes, metabolic dysfunction–associated steatotic liver disease, asthma, and depression returns to our weight management clinic with weight regain 4 years after Roux-en-Y gastric bypass. 

Her initial body weight was 389 lb (176.8 kg; body mass index [BMI], 65), and her nadir weight after surgery was 183 lb (83.2 kg; BMI, 30.5), representing a total weight loss of 53%. During the initial 2 years after surgery, she experienced multiple life stressors and was treated with venlafaxine for mild depression. She regained 25 lb (11.4 kg). Over the next 2 years, she gained another 20 lb (9.1 kg), for a total of 45 lb (20.5 kg) above nadir.

The patient reported increased nighttime consumption of alcohol including vodka, wine, and beer of over 20 drinks per week for the past 2 years. Her laboratory profile showed an elevated fasting glucose level (106 mg/dL, formerly 98 mg/dL), an elevated gamma-glutamyl transferase (GGT) level, and iron deficiency anemia. She admitted to regularly missing doses of postbariatric vitamins and minerals.
 

Ask Patients About Alcohol Use

It’s important to ask patients with significant weight regain after metabolic and bariatric surgery (MBS) about alcohol intake, because patients who have MBS are at an increased risk of developing alcohol use disorder (AUD).

The American Society for Metabolic and Bariatric Surgery recommends screening for alcohol intake both before and after MBS. Underreporting of alcohol consumption is common, but an elevated GGT level or elevated liver enzyme levels can indicate alcohol use. Depression and anxiety exacerbated by life stressors often accompany excessive alcohol intake.

Some antiobesity medications that regulate appetite may also help limit excessive alcohol intake. Naltrexone is used both for the treatment of AUD and for weight management, often in combination with bupropion). In a patient with weight regain and AUD, naltrexone alone would be a reasonable treatment option, although weight loss would probably be modest. The addition of bupropion to naltrexone would probably produce more weight loss; average total body weight loss with bupropion-naltrexone in clinical trials was about 6%. One cautionary note on bupropion: A patient’s seizure history should be elicited, because people with AUD are at increased risk for seizures in the withdrawal stage and bupropion can make those seizures more likely. 

Glucagon-like peptide 1 (GLP-1) receptor agonists (eg, liraglutide and semaglutide) and dual GLP-1/GIP (glucose-dependent insulinotropic polypeptide receptor agonists) (eg, tirzepatide) are second-generation antiobesity medications that produce more weight loss than first-generation agents such as bupropion/naltrexone. Of note, prior bariatric surgery was an exclusion criterion in the clinical trials assessing the efficacy of these agents for weight loss. The use of GLP-1 receptor agonists after MBS in people with inadequate weight loss or weight regain has been an area of active research. The BARI-OPTIMISE randomized clinical trial published in 2023 assessed the safety and efficacy of liraglutide 3.0 mg daily in patients with inadequate weight loss after MBS. The mean body weight reduction was 8.82% in the liraglutide group vs 0.54% in the placebo group. 

There is also emerging interest in the potential of GLP-1 receptor agonists in AUD. These medications act on the central nervous system to influence reward pathways. In rodents, studies have shown that GLP-1 receptor agonist administration reduces alcohol intake, although most studies have focused on short-term effects.

A series of experiments assessed the effects of semaglutide on alcohol intake in rodents. The authors found that semaglutide lowered the alcohol-induced release of dopamine and enhanced dopamine metabolism within the nucleus accumbens.

Evidence in humans is still limited, with only one published randomized controlled trial to date. In the 26-week study, weekly exenatide was not superior to placebo in reducing the number of heavy drinking days in patients with AUD who also received cognitive-behavioral therapy. An exploratory analysis in a subgroup of patients with obesity and AUD showed that exenatide reduced alcohol consumption. Of note, exenatide is rarely used in clinical practice because it does not produce substantial weight loss.

Liraglutide was chosen for this patient because of the established efficacy for this agent in patients with a history of MBS. In addition, patients often anecdotally report reduced desire for alcohol while taking a GLP-1 receptor agonist. Although GLP-1 receptor agonists have been shown to reduce alcohol intake in animal studies, their efficacy and safety in humans with AUD are not yet well established.
 

Back to Our Patient: 

Given the patient’s weight regain, an upper gastrointestinal series was performed to rule out gastro-gastric fistula or other anatomic abnormalities. After fistula was ruled out, she was prescribed liraglutide for weight management, which was titrated from 0.6 mg/d to 3 mg/d per the prescribing guidelines. 

With the use of liraglutide over the next year, the patient maintained a stable weight of 200 lb (90.9 kg) and noted that along with reduced appetite, her cravings for alcohol had diminished and she no longer felt the urge to drink alcohol at night. Her fasting glucose and GGT levels normalized. She began to see a nutritionist regularly and was planning to rejoin a bariatric support group.

Dr. Schmitz is an instructor in the Department of Medicine, Division of Endocrinology, Diabetes, and Metabolism, Weill Cornell Medicine, New York. She has disclosed no relevant financial relationships. Dr. Kashyap is a assistant chief of clinical affairs, Division of Endocrinology, Diabetes and Metabolism, Weill Cornell New York Presbyterian, New York. She disclosed ties to GI Dynamics.

A version of this article appeared on Medscape.com.

A 50-year-old woman with a history of class 3 obesity, gastroesophageal reflux disease, prediabetes, metabolic dysfunction–associated steatotic liver disease, asthma, and depression returns to our weight management clinic with weight regain 4 years after Roux-en-Y gastric bypass. 

Her initial body weight was 389 lb (176.8 kg; body mass index [BMI], 65), and her nadir weight after surgery was 183 lb (83.2 kg; BMI, 30.5), representing a total weight loss of 53%. During the initial 2 years after surgery, she experienced multiple life stressors and was treated with venlafaxine for mild depression. She regained 25 lb (11.4 kg). Over the next 2 years, she gained another 20 lb (9.1 kg), for a total of 45 lb (20.5 kg) above nadir.

The patient reported increased nighttime consumption of alcohol including vodka, wine, and beer of over 20 drinks per week for the past 2 years. Her laboratory profile showed an elevated fasting glucose level (106 mg/dL, formerly 98 mg/dL), an elevated gamma-glutamyl transferase (GGT) level, and iron deficiency anemia. She admitted to regularly missing doses of postbariatric vitamins and minerals.
 

Ask Patients About Alcohol Use

It’s important to ask patients with significant weight regain after metabolic and bariatric surgery (MBS) about alcohol intake, because patients who have MBS are at an increased risk of developing alcohol use disorder (AUD).

The American Society for Metabolic and Bariatric Surgery recommends screening for alcohol intake both before and after MBS. Underreporting of alcohol consumption is common, but an elevated GGT level or elevated liver enzyme levels can indicate alcohol use. Depression and anxiety exacerbated by life stressors often accompany excessive alcohol intake.

Some antiobesity medications that regulate appetite may also help limit excessive alcohol intake. Naltrexone is used both for the treatment of AUD and for weight management, often in combination with bupropion). In a patient with weight regain and AUD, naltrexone alone would be a reasonable treatment option, although weight loss would probably be modest. The addition of bupropion to naltrexone would probably produce more weight loss; average total body weight loss with bupropion-naltrexone in clinical trials was about 6%. One cautionary note on bupropion: A patient’s seizure history should be elicited, because people with AUD are at increased risk for seizures in the withdrawal stage and bupropion can make those seizures more likely. 

Glucagon-like peptide 1 (GLP-1) receptor agonists (eg, liraglutide and semaglutide) and dual GLP-1/GIP (glucose-dependent insulinotropic polypeptide receptor agonists) (eg, tirzepatide) are second-generation antiobesity medications that produce more weight loss than first-generation agents such as bupropion/naltrexone. Of note, prior bariatric surgery was an exclusion criterion in the clinical trials assessing the efficacy of these agents for weight loss. The use of GLP-1 receptor agonists after MBS in people with inadequate weight loss or weight regain has been an area of active research. The BARI-OPTIMISE randomized clinical trial published in 2023 assessed the safety and efficacy of liraglutide 3.0 mg daily in patients with inadequate weight loss after MBS. The mean body weight reduction was 8.82% in the liraglutide group vs 0.54% in the placebo group. 

There is also emerging interest in the potential of GLP-1 receptor agonists in AUD. These medications act on the central nervous system to influence reward pathways. In rodents, studies have shown that GLP-1 receptor agonist administration reduces alcohol intake, although most studies have focused on short-term effects.

A series of experiments assessed the effects of semaglutide on alcohol intake in rodents. The authors found that semaglutide lowered the alcohol-induced release of dopamine and enhanced dopamine metabolism within the nucleus accumbens.

Evidence in humans is still limited, with only one published randomized controlled trial to date. In the 26-week study, weekly exenatide was not superior to placebo in reducing the number of heavy drinking days in patients with AUD who also received cognitive-behavioral therapy. An exploratory analysis in a subgroup of patients with obesity and AUD showed that exenatide reduced alcohol consumption. Of note, exenatide is rarely used in clinical practice because it does not produce substantial weight loss.

Liraglutide was chosen for this patient because of the established efficacy for this agent in patients with a history of MBS. In addition, patients often anecdotally report reduced desire for alcohol while taking a GLP-1 receptor agonist. Although GLP-1 receptor agonists have been shown to reduce alcohol intake in animal studies, their efficacy and safety in humans with AUD are not yet well established.
 

Back to Our Patient: 

Given the patient’s weight regain, an upper gastrointestinal series was performed to rule out gastro-gastric fistula or other anatomic abnormalities. After fistula was ruled out, she was prescribed liraglutide for weight management, which was titrated from 0.6 mg/d to 3 mg/d per the prescribing guidelines. 

With the use of liraglutide over the next year, the patient maintained a stable weight of 200 lb (90.9 kg) and noted that along with reduced appetite, her cravings for alcohol had diminished and she no longer felt the urge to drink alcohol at night. Her fasting glucose and GGT levels normalized. She began to see a nutritionist regularly and was planning to rejoin a bariatric support group.

Dr. Schmitz is an instructor in the Department of Medicine, Division of Endocrinology, Diabetes, and Metabolism, Weill Cornell Medicine, New York. She has disclosed no relevant financial relationships. Dr. Kashyap is a assistant chief of clinical affairs, Division of Endocrinology, Diabetes and Metabolism, Weill Cornell New York Presbyterian, New York. She disclosed ties to GI Dynamics.

A version of this article appeared on Medscape.com.

Large language models (LLM) such as ChatGPT have shown mixed results in the quality of their responses to consumer questions about cancer.

One recent study found AI chatbots to churn out incomplete, inaccurate, or even nonsensical cancer treatment recommendations, while another found them to generate largely accurate — if technical — responses to the most common cancer questions.

While researchers have seen success with purpose-built chatbots created to address patient concerns about specific cancers, the consensus to date has been that the generalized models like ChatGPT remain works in progress and that physicians should avoid pointing patients to them, for now.

Yet new findings suggest that these chatbots may do better than individual physicians, at least on some measures, when it comes to answering queries about cancer. For research published May 16 in JAMA Oncology (doi: 10.1001/jamaoncol.2024.0836), David Chen, a medical student at the University of Toronto, and his colleagues, isolated a random sample of 200 questions related to cancer care addressed to doctors on the public online forum Reddit. They then compared responses from oncologists with responses generated by three different AI chatbots. The blinded responses were rated for quality, readability, and empathy by six physicians, including oncologists and palliative and supportive care specialists.

Mr. Chen and colleagues’ research was modeled after a 2023 study that measured the quality of physician responses compared with chatbots for general medicine questions addressed to doctors on Reddit. That study found that the chatbots produced more empathetic-sounding answers, something Mr. Chen’s study also found. The best-performing chatbot in Mr. Chen and colleagues’ study, Claude AI, performed significantly higher than the Reddit physicians on all the domains evaluated: quality, empathy, and readability.
 

Q&A With Author of New Research

Mr. Chen discussed his new study’s implications during an interview with this news organization.

Question: What is novel about this study?

Mr. Chen: We’ve seen many evaluations of chatbots that test for medical accuracy, but this study occurs in the domain of oncology care, where there are unique psychosocial and emotional considerations that are not precisely reflected in a general medicine setting. In effect, this study is putting these chatbots through a harder challenge.



Question: Why would chatbot responses seem more empathetic than those of physicians?

Mr. Chen: With the physician responses that we observed in our sample data set, we saw that there was very high variation of amount of apparent effort [in the physician responses]. Some physicians would put in a lot of time and effort, thinking through their response, and others wouldn’t do so as much. These chatbots don’t face fatigue the way humans do, or burnout. So they’re able to consistently provide responses with less variation in empathy.



Question: Do chatbots just seem empathetic because they are chattier?

Mr. Chen: We did think of verbosity as a potential confounder in this study. So we set a word count limit for the chatbot responses to keep it in the range of the physician responses. That way, verbosity was no longer a significant factor.



Question: How were quality and empathy measured by the reviewers?

Mr. Chen: For our study we used two teams of readers, each team composed of three physicians. In terms of the actual metrics we used, they were pilot metrics. There are no well-defined measurement scales or checklists that we could use to measure empathy. This is an emerging field of research. So we came up by consensus with our own set of ratings, and we feel that this is an area for the research to define a standardized set of guidelines.

Another novel aspect of this study is that we separated out different dimensions of quality and empathy. A quality response didn’t just mean it was medically accurate — quality also had to do with the focus and completeness of the response.

With empathy there are cognitive and emotional dimensions. Cognitive empathy uses critical thinking to understand the person’s emotions and thoughts and then adjusting a response to fit that. A patient may not want the best medically indicated treatment for their condition, because they want to preserve their quality of life. The chatbot may be able to adjust its recommendation with consideration of some of those humanistic elements that the patient is presenting with.

Emotional empathy is more about being supportive of the patient’s emotions by using expressions like ‘I understand where you’re coming from.’ or, ‘I can see how that makes you feel.’



Question: Why would physicians, not patients, be the best evaluators of empathy?

Mr. Chen: We’re actually very interested in evaluating patient ratings of empathy. We are conducting a follow-up study that evaluates patient ratings of empathy to the same set of chatbot and physician responses,to see if there are differences.



Question: Should cancer patients go ahead and consult chatbots?

Mr. Chen: Although we did observe increases in all of the metrics compared with physicians, this is a very specialized evaluation scenario where we’re using these Reddit questions and responses.

Naturally, we would need to do a trial, a head to head randomized comparison of physicians versus chatbots.

This pilot study does highlight the promising potential of these chatbots to suggest responses. But we can’t fully recommend that they should be used as standalone clinical tools without physicians.

This Q&A was edited for clarity.

Large language models (LLM) such as ChatGPT have shown mixed results in the quality of their responses to consumer questions about cancer.

One recent study found AI chatbots to churn out incomplete, inaccurate, or even nonsensical cancer treatment recommendations, while another found them to generate largely accurate — if technical — responses to the most common cancer questions.

While researchers have seen success with purpose-built chatbots created to address patient concerns about specific cancers, the consensus to date has been that the generalized models like ChatGPT remain works in progress and that physicians should avoid pointing patients to them, for now.

Yet new findings suggest that these chatbots may do better than individual physicians, at least on some measures, when it comes to answering queries about cancer. For research published May 16 in JAMA Oncology (doi: 10.1001/jamaoncol.2024.0836), David Chen, a medical student at the University of Toronto, and his colleagues, isolated a random sample of 200 questions related to cancer care addressed to doctors on the public online forum Reddit. They then compared responses from oncologists with responses generated by three different AI chatbots. The blinded responses were rated for quality, readability, and empathy by six physicians, including oncologists and palliative and supportive care specialists.

Mr. Chen and colleagues’ research was modeled after a 2023 study that measured the quality of physician responses compared with chatbots for general medicine questions addressed to doctors on Reddit. That study found that the chatbots produced more empathetic-sounding answers, something Mr. Chen’s study also found. The best-performing chatbot in Mr. Chen and colleagues’ study, Claude AI, performed significantly higher than the Reddit physicians on all the domains evaluated: quality, empathy, and readability.
 

Q&A With Author of New Research

Mr. Chen discussed his new study’s implications during an interview with this news organization.

Question: What is novel about this study?

Mr. Chen: We’ve seen many evaluations of chatbots that test for medical accuracy, but this study occurs in the domain of oncology care, where there are unique psychosocial and emotional considerations that are not precisely reflected in a general medicine setting. In effect, this study is putting these chatbots through a harder challenge.



Question: Why would chatbot responses seem more empathetic than those of physicians?

Mr. Chen: With the physician responses that we observed in our sample data set, we saw that there was very high variation of amount of apparent effort [in the physician responses]. Some physicians would put in a lot of time and effort, thinking through their response, and others wouldn’t do so as much. These chatbots don’t face fatigue the way humans do, or burnout. So they’re able to consistently provide responses with less variation in empathy.



Question: Do chatbots just seem empathetic because they are chattier?

Mr. Chen: We did think of verbosity as a potential confounder in this study. So we set a word count limit for the chatbot responses to keep it in the range of the physician responses. That way, verbosity was no longer a significant factor.



Question: How were quality and empathy measured by the reviewers?

Mr. Chen: For our study we used two teams of readers, each team composed of three physicians. In terms of the actual metrics we used, they were pilot metrics. There are no well-defined measurement scales or checklists that we could use to measure empathy. This is an emerging field of research. So we came up by consensus with our own set of ratings, and we feel that this is an area for the research to define a standardized set of guidelines.

Another novel aspect of this study is that we separated out different dimensions of quality and empathy. A quality response didn’t just mean it was medically accurate — quality also had to do with the focus and completeness of the response.

With empathy there are cognitive and emotional dimensions. Cognitive empathy uses critical thinking to understand the person’s emotions and thoughts and then adjusting a response to fit that. A patient may not want the best medically indicated treatment for their condition, because they want to preserve their quality of life. The chatbot may be able to adjust its recommendation with consideration of some of those humanistic elements that the patient is presenting with.

Emotional empathy is more about being supportive of the patient’s emotions by using expressions like ‘I understand where you’re coming from.’ or, ‘I can see how that makes you feel.’



Question: Why would physicians, not patients, be the best evaluators of empathy?

Mr. Chen: We’re actually very interested in evaluating patient ratings of empathy. We are conducting a follow-up study that evaluates patient ratings of empathy to the same set of chatbot and physician responses,to see if there are differences.



Question: Should cancer patients go ahead and consult chatbots?

Mr. Chen: Although we did observe increases in all of the metrics compared with physicians, this is a very specialized evaluation scenario where we’re using these Reddit questions and responses.

Naturally, we would need to do a trial, a head to head randomized comparison of physicians versus chatbots.

This pilot study does highlight the promising potential of these chatbots to suggest responses. But we can’t fully recommend that they should be used as standalone clinical tools without physicians.

This Q&A was edited for clarity.

Large language models (LLM) such as ChatGPT have shown mixed results in the quality of their responses to consumer questions about cancer.

One recent study found AI chatbots to churn out incomplete, inaccurate, or even nonsensical cancer treatment recommendations, while another found them to generate largely accurate — if technical — responses to the most common cancer questions.

While researchers have seen success with purpose-built chatbots created to address patient concerns about specific cancers, the consensus to date has been that the generalized models like ChatGPT remain works in progress and that physicians should avoid pointing patients to them, for now.

Yet new findings suggest that these chatbots may do better than individual physicians, at least on some measures, when it comes to answering queries about cancer. For research published May 16 in JAMA Oncology (doi: 10.1001/jamaoncol.2024.0836), David Chen, a medical student at the University of Toronto, and his colleagues, isolated a random sample of 200 questions related to cancer care addressed to doctors on the public online forum Reddit. They then compared responses from oncologists with responses generated by three different AI chatbots. The blinded responses were rated for quality, readability, and empathy by six physicians, including oncologists and palliative and supportive care specialists.

Mr. Chen and colleagues’ research was modeled after a 2023 study that measured the quality of physician responses compared with chatbots for general medicine questions addressed to doctors on Reddit. That study found that the chatbots produced more empathetic-sounding answers, something Mr. Chen’s study also found. The best-performing chatbot in Mr. Chen and colleagues’ study, Claude AI, performed significantly higher than the Reddit physicians on all the domains evaluated: quality, empathy, and readability.
 

Q&A With Author of New Research

Mr. Chen discussed his new study’s implications during an interview with this news organization.

Question: What is novel about this study?

Mr. Chen: We’ve seen many evaluations of chatbots that test for medical accuracy, but this study occurs in the domain of oncology care, where there are unique psychosocial and emotional considerations that are not precisely reflected in a general medicine setting. In effect, this study is putting these chatbots through a harder challenge.



Question: Why would chatbot responses seem more empathetic than those of physicians?

Mr. Chen: With the physician responses that we observed in our sample data set, we saw that there was very high variation of amount of apparent effort [in the physician responses]. Some physicians would put in a lot of time and effort, thinking through their response, and others wouldn’t do so as much. These chatbots don’t face fatigue the way humans do, or burnout. So they’re able to consistently provide responses with less variation in empathy.



Question: Do chatbots just seem empathetic because they are chattier?

Mr. Chen: We did think of verbosity as a potential confounder in this study. So we set a word count limit for the chatbot responses to keep it in the range of the physician responses. That way, verbosity was no longer a significant factor.



Question: How were quality and empathy measured by the reviewers?

Mr. Chen: For our study we used two teams of readers, each team composed of three physicians. In terms of the actual metrics we used, they were pilot metrics. There are no well-defined measurement scales or checklists that we could use to measure empathy. This is an emerging field of research. So we came up by consensus with our own set of ratings, and we feel that this is an area for the research to define a standardized set of guidelines.

Another novel aspect of this study is that we separated out different dimensions of quality and empathy. A quality response didn’t just mean it was medically accurate — quality also had to do with the focus and completeness of the response.

With empathy there are cognitive and emotional dimensions. Cognitive empathy uses critical thinking to understand the person’s emotions and thoughts and then adjusting a response to fit that. A patient may not want the best medically indicated treatment for their condition, because they want to preserve their quality of life. The chatbot may be able to adjust its recommendation with consideration of some of those humanistic elements that the patient is presenting with.

Emotional empathy is more about being supportive of the patient’s emotions by using expressions like ‘I understand where you’re coming from.’ or, ‘I can see how that makes you feel.’



Question: Why would physicians, not patients, be the best evaluators of empathy?

Mr. Chen: We’re actually very interested in evaluating patient ratings of empathy. We are conducting a follow-up study that evaluates patient ratings of empathy to the same set of chatbot and physician responses,to see if there are differences.



Question: Should cancer patients go ahead and consult chatbots?

Mr. Chen: Although we did observe increases in all of the metrics compared with physicians, this is a very specialized evaluation scenario where we’re using these Reddit questions and responses.

Naturally, we would need to do a trial, a head to head randomized comparison of physicians versus chatbots.

This pilot study does highlight the promising potential of these chatbots to suggest responses. But we can’t fully recommend that they should be used as standalone clinical tools without physicians.

This Q&A was edited for clarity.

For years, scientists have sought to create a human artificial ovary, restoring fertility in patients without other options. The first cellular map of a human ovary, recently developed at the University of Michigan, Ann Arbor, represents a big leap forward in that quest.

“You cannot build something if you don’t have the blueprint,” said biomedical engineer Ariella Shikanov, PhD, associate professor at University of Michigan, who helped create what she and colleagues call an atlas of the ovary. “By creating a map or an atlas, we can now follow what nature created and engineer the building blocks of an ovary — and build a nature-like structure.”

So far, the concept of an artificial ovary has been successful only in mice, with the development of a 3D-printed prosthetic ovary that enabled sterilized mice to have pups. Researchers hope that artificial human ovary technology could someday help women left infertile after cancer treatment, as well as patients who don›t respond to fertility treatments and those with premature ovarian failure.

But Dr. Shikanov believes this research will go even further, providing a valuable resource to scientists studying diseases and other conditions related to the ovary.

“Whenever people think about the ovary, if they think about it at all, they usually think about fertility,” said Dr. Shikanov. The ovary is so much more.

Besides producing and carrying a woman’s unfertilized eggs during her lifetime, the ovary is also responsible for endocrine function — the production of estrogen and progesterone, which in addition to supporting reproductive health, help maintain a woman’s cardiovascular, bone, and mental health.

“We don’t really understand everything that is happening in the ovary yet,” Dr. Shikanov said. “But we know it is an important organ.”
 

Mapping the Ovary

Because people don’t typically donate their ovaries, there are not many available for research, especially from younger reproductive age women, said Dr. Shikanov. So, the scientists set out to build a resource. They described their work in Science Advances.

To create their atlas, the researchers studied two premenopausal donor ovaries, profiling 18,000 genes in 257 regions. From three additional donor ovaries, they also generated single-cell RNA sequencing data for 21,198 cells.

“We identified four major cell types and four immune cell subtypes in the ovary,” said Dr. Shikanov. Taking samples from different areas of the ovary revealed distinct gene activities for oocytes, theca cells, and granulosa cells — expanding scientists’ understanding of the molecular programs driving ovarian follicle development.

What’s unique about their work is the focus on both single cell and spatial analysis, said study coauthor Jun Z. Li, PhD, associate chair of the University of Michigan’s department of computational medicine and bioinformatics. Specifically, they used a relatively new method called spatial transcriptomics, which allows them to see which genes are being activated and where.

“We are constructing the spatial arrangement of the cells in the ovary,” said Dr. Li. “This spatial analysis is like saying, ‘Let me look at where you are and who your neighbor is.’ ”

Their findings are built on other genetic and cellular research in the field, Dr. Li noted. Biomedical engineers in other areas of medicine are applying similar technologies to other organs including the heart, the breast, and bone — part of a larger project called the Human Cell Atlas.
 

Advancing Women’s Health Research

Historically, women’s health research has been underfunded and underrepresented, but the authors believe their atlas of the ovary is a significant step forward.

“There are a lot of biological questions that we don’t know the answers to about the ovary,” said Dr. Shikanov.

One of the biggest mysteries is why so many eggs never become fertilizable. Each human female is born with about one to two million ovarian follicles. Each follicle carries one immature egg. Around puberty, two thirds of these follicles die off. And most that are left never develop into fertilizable eggs.

“The majority of these follicles either just grow and secrete hormones or undergo atresia,” Dr. Shikanov said. “One question that we wanted to understand is, what determines an egg that can grow, ovulate, and become a fertilizable egg and potentially develop into a new human being from one that does not?”

Another big question researchers have is, what’s happening with other types of cells in the ovary — the supporting cells that produce endocrine hormones? Where are they located and what proteins and RNA are they making? Their research begins to unravel some of these questions and lays a foundation for future studies.

“We wanted to analyze the transcriptional signatures from specific regions and then do bioinformatical analysis and really combine structure, function, and transcriptional signatures,” Dr. Shikanov said.

Knowing the transcriptional signatures can help researchers understand disease mechanisms and then go on to develop treatments for these diseases.

Winifred Mak, MD, PhD, a reproductive endocrinologist and infertility specialist at Dell Medical School, University of Texas, Austin, studies cancer fertility preservation. “For me, it is interesting to see that there are so many different clusters of cells in the ovary that have been identified by this study that we were not necessarily aware of before,” said Dr. Mak, who is not involved in the new research. “Also, the identification of new genes not previously studied in the human ovary.”
 

What’s Next

Dozens of scientists who study reproductive health are already reaching out to the researchers about their work, Dr. Shikanov said.

“We get contacted almost every day from researchers all around the world asking for data sets or asking for details from this paper,” she said, “from people who study ovarian cancer, for example.”

Dr. Mak said having a map of a normal ovary could also help researchers who study premature ovarian insufficiency — why the ovary sometimes goes into premature menopause — and polycystic ovarian syndrome.

Another big area of research interest is ovarian aging. “Women live so much longer now, but we still reach menopause at the age of 50,” Dr. Shikanov said. “So, there are efforts going toward understanding ovarian aging and maybe preventing it to extend ovarian longevity.”

Dr. Mak said it will enable scientists to “look at different age women and see what genes change across the reproductive lifespan.”

The atlas may also eventually lead to treatments that help restore fertility in individuals who had and were treated for cancer as children, people who undergo sex transitions, and those whose reproductive organs have been impacted by trauma in conflict settings or accidents, Dr. Li said.

The applications are numerous and exciting, Dr. Shikanov said. “Our atlas is like a benchmark. Now researchers can collect ovaries from individuals with these diseases and conditions and try to compare what’s different.”

A version of this article appeared on Medscape.com.

For years, scientists have sought to create a human artificial ovary, restoring fertility in patients without other options. The first cellular map of a human ovary, recently developed at the University of Michigan, Ann Arbor, represents a big leap forward in that quest.

“You cannot build something if you don’t have the blueprint,” said biomedical engineer Ariella Shikanov, PhD, associate professor at University of Michigan, who helped create what she and colleagues call an atlas of the ovary. “By creating a map or an atlas, we can now follow what nature created and engineer the building blocks of an ovary — and build a nature-like structure.”

So far, the concept of an artificial ovary has been successful only in mice, with the development of a 3D-printed prosthetic ovary that enabled sterilized mice to have pups. Researchers hope that artificial human ovary technology could someday help women left infertile after cancer treatment, as well as patients who don›t respond to fertility treatments and those with premature ovarian failure.

But Dr. Shikanov believes this research will go even further, providing a valuable resource to scientists studying diseases and other conditions related to the ovary.

“Whenever people think about the ovary, if they think about it at all, they usually think about fertility,” said Dr. Shikanov. The ovary is so much more.

Besides producing and carrying a woman’s unfertilized eggs during her lifetime, the ovary is also responsible for endocrine function — the production of estrogen and progesterone, which in addition to supporting reproductive health, help maintain a woman’s cardiovascular, bone, and mental health.

“We don’t really understand everything that is happening in the ovary yet,” Dr. Shikanov said. “But we know it is an important organ.”
 

Mapping the Ovary

Because people don’t typically donate their ovaries, there are not many available for research, especially from younger reproductive age women, said Dr. Shikanov. So, the scientists set out to build a resource. They described their work in Science Advances.

To create their atlas, the researchers studied two premenopausal donor ovaries, profiling 18,000 genes in 257 regions. From three additional donor ovaries, they also generated single-cell RNA sequencing data for 21,198 cells.

“We identified four major cell types and four immune cell subtypes in the ovary,” said Dr. Shikanov. Taking samples from different areas of the ovary revealed distinct gene activities for oocytes, theca cells, and granulosa cells — expanding scientists’ understanding of the molecular programs driving ovarian follicle development.

What’s unique about their work is the focus on both single cell and spatial analysis, said study coauthor Jun Z. Li, PhD, associate chair of the University of Michigan’s department of computational medicine and bioinformatics. Specifically, they used a relatively new method called spatial transcriptomics, which allows them to see which genes are being activated and where.

“We are constructing the spatial arrangement of the cells in the ovary,” said Dr. Li. “This spatial analysis is like saying, ‘Let me look at where you are and who your neighbor is.’ ”

Their findings are built on other genetic and cellular research in the field, Dr. Li noted. Biomedical engineers in other areas of medicine are applying similar technologies to other organs including the heart, the breast, and bone — part of a larger project called the Human Cell Atlas.
 

Advancing Women’s Health Research

Historically, women’s health research has been underfunded and underrepresented, but the authors believe their atlas of the ovary is a significant step forward.

“There are a lot of biological questions that we don’t know the answers to about the ovary,” said Dr. Shikanov.

One of the biggest mysteries is why so many eggs never become fertilizable. Each human female is born with about one to two million ovarian follicles. Each follicle carries one immature egg. Around puberty, two thirds of these follicles die off. And most that are left never develop into fertilizable eggs.

“The majority of these follicles either just grow and secrete hormones or undergo atresia,” Dr. Shikanov said. “One question that we wanted to understand is, what determines an egg that can grow, ovulate, and become a fertilizable egg and potentially develop into a new human being from one that does not?”

Another big question researchers have is, what’s happening with other types of cells in the ovary — the supporting cells that produce endocrine hormones? Where are they located and what proteins and RNA are they making? Their research begins to unravel some of these questions and lays a foundation for future studies.

“We wanted to analyze the transcriptional signatures from specific regions and then do bioinformatical analysis and really combine structure, function, and transcriptional signatures,” Dr. Shikanov said.

Knowing the transcriptional signatures can help researchers understand disease mechanisms and then go on to develop treatments for these diseases.

Winifred Mak, MD, PhD, a reproductive endocrinologist and infertility specialist at Dell Medical School, University of Texas, Austin, studies cancer fertility preservation. “For me, it is interesting to see that there are so many different clusters of cells in the ovary that have been identified by this study that we were not necessarily aware of before,” said Dr. Mak, who is not involved in the new research. “Also, the identification of new genes not previously studied in the human ovary.”
 

What’s Next

Dozens of scientists who study reproductive health are already reaching out to the researchers about their work, Dr. Shikanov said.

“We get contacted almost every day from researchers all around the world asking for data sets or asking for details from this paper,” she said, “from people who study ovarian cancer, for example.”

Dr. Mak said having a map of a normal ovary could also help researchers who study premature ovarian insufficiency — why the ovary sometimes goes into premature menopause — and polycystic ovarian syndrome.

Another big area of research interest is ovarian aging. “Women live so much longer now, but we still reach menopause at the age of 50,” Dr. Shikanov said. “So, there are efforts going toward understanding ovarian aging and maybe preventing it to extend ovarian longevity.”

Dr. Mak said it will enable scientists to “look at different age women and see what genes change across the reproductive lifespan.”

The atlas may also eventually lead to treatments that help restore fertility in individuals who had and were treated for cancer as children, people who undergo sex transitions, and those whose reproductive organs have been impacted by trauma in conflict settings or accidents, Dr. Li said.

The applications are numerous and exciting, Dr. Shikanov said. “Our atlas is like a benchmark. Now researchers can collect ovaries from individuals with these diseases and conditions and try to compare what’s different.”

A version of this article appeared on Medscape.com.

For years, scientists have sought to create a human artificial ovary, restoring fertility in patients without other options. The first cellular map of a human ovary, recently developed at the University of Michigan, Ann Arbor, represents a big leap forward in that quest.

“You cannot build something if you don’t have the blueprint,” said biomedical engineer Ariella Shikanov, PhD, associate professor at University of Michigan, who helped create what she and colleagues call an atlas of the ovary. “By creating a map or an atlas, we can now follow what nature created and engineer the building blocks of an ovary — and build a nature-like structure.”

So far, the concept of an artificial ovary has been successful only in mice, with the development of a 3D-printed prosthetic ovary that enabled sterilized mice to have pups. Researchers hope that artificial human ovary technology could someday help women left infertile after cancer treatment, as well as patients who don›t respond to fertility treatments and those with premature ovarian failure.

But Dr. Shikanov believes this research will go even further, providing a valuable resource to scientists studying diseases and other conditions related to the ovary.

“Whenever people think about the ovary, if they think about it at all, they usually think about fertility,” said Dr. Shikanov. The ovary is so much more.

Besides producing and carrying a woman’s unfertilized eggs during her lifetime, the ovary is also responsible for endocrine function — the production of estrogen and progesterone, which in addition to supporting reproductive health, help maintain a woman’s cardiovascular, bone, and mental health.

“We don’t really understand everything that is happening in the ovary yet,” Dr. Shikanov said. “But we know it is an important organ.”
 

Mapping the Ovary

Because people don’t typically donate their ovaries, there are not many available for research, especially from younger reproductive age women, said Dr. Shikanov. So, the scientists set out to build a resource. They described their work in Science Advances.

To create their atlas, the researchers studied two premenopausal donor ovaries, profiling 18,000 genes in 257 regions. From three additional donor ovaries, they also generated single-cell RNA sequencing data for 21,198 cells.

“We identified four major cell types and four immune cell subtypes in the ovary,” said Dr. Shikanov. Taking samples from different areas of the ovary revealed distinct gene activities for oocytes, theca cells, and granulosa cells — expanding scientists’ understanding of the molecular programs driving ovarian follicle development.

What’s unique about their work is the focus on both single cell and spatial analysis, said study coauthor Jun Z. Li, PhD, associate chair of the University of Michigan’s department of computational medicine and bioinformatics. Specifically, they used a relatively new method called spatial transcriptomics, which allows them to see which genes are being activated and where.

“We are constructing the spatial arrangement of the cells in the ovary,” said Dr. Li. “This spatial analysis is like saying, ‘Let me look at where you are and who your neighbor is.’ ”

Their findings are built on other genetic and cellular research in the field, Dr. Li noted. Biomedical engineers in other areas of medicine are applying similar technologies to other organs including the heart, the breast, and bone — part of a larger project called the Human Cell Atlas.
 

Advancing Women’s Health Research

Historically, women’s health research has been underfunded and underrepresented, but the authors believe their atlas of the ovary is a significant step forward.

“There are a lot of biological questions that we don’t know the answers to about the ovary,” said Dr. Shikanov.

One of the biggest mysteries is why so many eggs never become fertilizable. Each human female is born with about one to two million ovarian follicles. Each follicle carries one immature egg. Around puberty, two thirds of these follicles die off. And most that are left never develop into fertilizable eggs.

“The majority of these follicles either just grow and secrete hormones or undergo atresia,” Dr. Shikanov said. “One question that we wanted to understand is, what determines an egg that can grow, ovulate, and become a fertilizable egg and potentially develop into a new human being from one that does not?”

Another big question researchers have is, what’s happening with other types of cells in the ovary — the supporting cells that produce endocrine hormones? Where are they located and what proteins and RNA are they making? Their research begins to unravel some of these questions and lays a foundation for future studies.

“We wanted to analyze the transcriptional signatures from specific regions and then do bioinformatical analysis and really combine structure, function, and transcriptional signatures,” Dr. Shikanov said.

Knowing the transcriptional signatures can help researchers understand disease mechanisms and then go on to develop treatments for these diseases.

Winifred Mak, MD, PhD, a reproductive endocrinologist and infertility specialist at Dell Medical School, University of Texas, Austin, studies cancer fertility preservation. “For me, it is interesting to see that there are so many different clusters of cells in the ovary that have been identified by this study that we were not necessarily aware of before,” said Dr. Mak, who is not involved in the new research. “Also, the identification of new genes not previously studied in the human ovary.”
 

What’s Next

Dozens of scientists who study reproductive health are already reaching out to the researchers about their work, Dr. Shikanov said.

“We get contacted almost every day from researchers all around the world asking for data sets or asking for details from this paper,” she said, “from people who study ovarian cancer, for example.”

Dr. Mak said having a map of a normal ovary could also help researchers who study premature ovarian insufficiency — why the ovary sometimes goes into premature menopause — and polycystic ovarian syndrome.

Another big area of research interest is ovarian aging. “Women live so much longer now, but we still reach menopause at the age of 50,” Dr. Shikanov said. “So, there are efforts going toward understanding ovarian aging and maybe preventing it to extend ovarian longevity.”

Dr. Mak said it will enable scientists to “look at different age women and see what genes change across the reproductive lifespan.”

The atlas may also eventually lead to treatments that help restore fertility in individuals who had and were treated for cancer as children, people who undergo sex transitions, and those whose reproductive organs have been impacted by trauma in conflict settings or accidents, Dr. Li said.

The applications are numerous and exciting, Dr. Shikanov said. “Our atlas is like a benchmark. Now researchers can collect ovaries from individuals with these diseases and conditions and try to compare what’s different.”

A version of this article appeared on Medscape.com.