Case vignette: A 16-year-old Nepali-born English-speaking adolescent presents for a well-child visit and notes concerns for anxiety, depression, and a history of trauma. She resides with her parents who work in hospitality with limited time off, and thus she presented for the initial office visit with a neighbor. Parents were not readily available to discuss treatment recommendations, including medication options. The teen shares a number of challenges that makes coming to appointments difficult. You also notice that the patient currently is not enrolled in insurance, though she appears eligible.

The above vignette highlights various social issues and concerns that impact access to healthcare and overall health/well-being. Social determinants of health (SDOH) and factors centered on mental health are now widely known to impact pediatric health and wellbeing. The Office of Disease Prevention and Health Promotion defines SDOH as “conditions in the environments in which people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning, and quality-of-life outcomes and risks.” SDOH can be grouped into five domains: Economic Stability, Education Access and Quality, Health Care Access and Quality, Neighborhood and Built Environment, and Social and Community Context.¹

Dr. Abdul-Karim

Additionally, when considering determinants that impact the mental health of children, it is prudent to consider parental psychosocial factors and adverse childhood experiences (ACEs), such as witnessing interpersonal violence, child abuse, parental substance use, and parental depression.² All these factors have been shown to impact an individual’s mental and physical health not only contemporaneously but also later in life.³

Screening Tool for Pediatric Social Histories

One screening tool to assist with gathering an expanded pediatric social history is called IHELP, developed by Kenyon et al,⁴ with further derivations from Colvin et al.⁵ Utilizing this tool can assist providers with identifying social needs.

The tool begins with a framing statement — “Let me ask you some questions I ask every family” — then proceeds to discuss relevant topics as shared below:

I: Income; Insurance

• Do you have any concerns about making ends meet?
• Do you have any concerns about your child’s health insurance?

H: Hunger, Housing Conditions; Homeless

• Do you have any concerns about having enough food?
• Have you ever been worried whether your food would run out before you got money to buy more?
• Within the past year has the food you bought ever not lasted, and you didn’t have money to get more?
• Do you have any concerns about poor housing conditions like mice, mold, or cockroaches?
• Do you have any concerns about being evicted or not being able to pay the rent?
• Do you have any concerns about not being able to pay your mortgage?

E: Education; Ensuring Safety (Violence)

• Do you have any concerns about your child’s educational needs?
• [DO NOT ASK IN FRONT OF CHILD 3 OR OLDER OR IN FRONT OF OTHER PARTNER] “From speaking to families, I have learned that violence in the home is common and now I ask all families about violence in the home. Do you have any concerns about violence in your home?”

L: Legal status (Immigration)

• What hospital was your child born in?
• If not in the United States: “Are you aware that your child may be eligible for benefits even though they were not born in the US? If you would like, I can have a social worker come talk to you about some possible benefits your child may be eligible for. Would you like me to do that?”

P: Power of Attorney; Guardianship

• Are you the biological mother or father of this child?
• [If not] “Can you show me the power of attorney or guardianship document you have?”
• **PATIENTS >17+ with Mental Incapacity: Ask for Guardianship.

This tool can help with identifying families with significant social needs so that one can attain further historical information and subsequently share resources to assist with any challenges.
 

Consider the Role of Adverse Childhood Experiences

Additionally, as noted, ACEs often play an important role in overall health and well-being; they include experiencing childhood abuse, neglect, and/or household dysfunction. The impact of these early exposures can lead to toxic stress that can negatively alter the brain and the body’s response to stress over time.³ There are various tools readily available online that can assist with identifying ACEs and interpreting their prevalence. The American Academy of Pediatrics has an updated page of commonly used screening tools. Early identification and intervention can help mitigate the impact of these experiences on long-term outcomes.

Important Considerations Regarding Screening for SDOH and/or ACEs:

• Please consider if screening is helpful in your space, recognizing that there are benefits and potential ethical considerations to screen or not. Ensure an interdisciplinary approach if screening is implemented to ensure that the patient’s experience and well-being is prioritized.
• Try to be intentional in your communication with parents. The patient and family are our teachers and know best what they need.
• Consider what is available in your community and what can be offered to ensure that parents and families are appropriate and eligible for a particular resource.
• Encourage continuous collaboration and partnership with community providers who offer resources that a family may benefit from to ensure that the resource continues to be available.

Returning to the Vignette

Administering the IHELP tool has led to identifying that the adolescent’s insurance has lapsed, but she remains eligible, and the family seeks support to re-enroll. The family shares concerns regarding educational needs, as the child has not attended school for the past year and is not on track to graduate. The IHELP tool also helps you identify inconsistent transportation availability. Ultimately, a social work consultation is placed which assists with re-enrolling in insurance for the child and obtaining a bus pass for in-person visits. The patient is also supported in enrolling in the use of a videoconferencing platform for virtual visits. You and your team reach out to the school, which provides valuable information regarding the child’s status and how best to support re-engagement. On follow-up, she is now readily engaged in appointments and shares she is no longer worrying about transportation, which has been helpful. She has started initial conversations with the school and has a condensed schedule for reintegration.

Dr. Abdul-Karim, a child and adolescent psychiatrist, is assistant professor of psychiatry at the University of Vermont, Burlington. She said she had no relevant financial disclosures. Email her at [email protected].

References

1. Office of Disease Prevention and Health Promotion, US Department of Health & Human Services. Social Determinants of Health. https://odphp.health.gov/healthypeople/priority-areas/social-determinants-health

2. Cotton N and Shim R. J Am Acad Child Adolesc Psychiatry. 2022 Nov;61(11):1385-1389. doi: 10.1016/j.jaac.2022.04.020.

3. US Centers for Disease Control and Prevention. Adverse Childhood Experiences (ACEs): Preventing Early Trauma to Improve Adult Health. https://www.cdc.gov/vitalsigns/aces/index.html.

4. Kenyon C et al. Pediatrics. 2007 Sep;120(3):e734-e738. doi: 10.1542/peds.2006-2495.

5. Colvin JD et al. Acad Pediatr. 2016 Mar;16(2):168-174. doi: 10.1016/j.acap.2015.06.001.

Case vignette: A 16-year-old Nepali-born English-speaking adolescent presents for a well-child visit and notes concerns for anxiety, depression, and a history of trauma. She resides with her parents who work in hospitality with limited time off, and thus she presented for the initial office visit with a neighbor. Parents were not readily available to discuss treatment recommendations, including medication options. The teen shares a number of challenges that makes coming to appointments difficult. You also notice that the patient currently is not enrolled in insurance, though she appears eligible.

The above vignette highlights various social issues and concerns that impact access to healthcare and overall health/well-being. Social determinants of health (SDOH) and factors centered on mental health are now widely known to impact pediatric health and wellbeing. The Office of Disease Prevention and Health Promotion defines SDOH as “conditions in the environments in which people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning, and quality-of-life outcomes and risks.” SDOH can be grouped into five domains: Economic Stability, Education Access and Quality, Health Care Access and Quality, Neighborhood and Built Environment, and Social and Community Context.¹

Dr. Abdul-Karim

Additionally, when considering determinants that impact the mental health of children, it is prudent to consider parental psychosocial factors and adverse childhood experiences (ACEs), such as witnessing interpersonal violence, child abuse, parental substance use, and parental depression.² All these factors have been shown to impact an individual’s mental and physical health not only contemporaneously but also later in life.³

Screening Tool for Pediatric Social Histories

One screening tool to assist with gathering an expanded pediatric social history is called IHELP, developed by Kenyon et al,⁴ with further derivations from Colvin et al.⁵ Utilizing this tool can assist providers with identifying social needs.

The tool begins with a framing statement — “Let me ask you some questions I ask every family” — then proceeds to discuss relevant topics as shared below:

I: Income; Insurance

• Do you have any concerns about making ends meet?
• Do you have any concerns about your child’s health insurance?

H: Hunger, Housing Conditions; Homeless

• Do you have any concerns about having enough food?
• Have you ever been worried whether your food would run out before you got money to buy more?
• Within the past year has the food you bought ever not lasted, and you didn’t have money to get more?
• Do you have any concerns about poor housing conditions like mice, mold, or cockroaches?
• Do you have any concerns about being evicted or not being able to pay the rent?
• Do you have any concerns about not being able to pay your mortgage?

E: Education; Ensuring Safety (Violence)

• Do you have any concerns about your child’s educational needs?
• [DO NOT ASK IN FRONT OF CHILD 3 OR OLDER OR IN FRONT OF OTHER PARTNER] “From speaking to families, I have learned that violence in the home is common and now I ask all families about violence in the home. Do you have any concerns about violence in your home?”

L: Legal status (Immigration)

• What hospital was your child born in?
• If not in the United States: “Are you aware that your child may be eligible for benefits even though they were not born in the US? If you would like, I can have a social worker come talk to you about some possible benefits your child may be eligible for. Would you like me to do that?”

P: Power of Attorney; Guardianship

• Are you the biological mother or father of this child?
• [If not] “Can you show me the power of attorney or guardianship document you have?”
• **PATIENTS >17+ with Mental Incapacity: Ask for Guardianship.

This tool can help with identifying families with significant social needs so that one can attain further historical information and subsequently share resources to assist with any challenges.
 

Consider the Role of Adverse Childhood Experiences

Additionally, as noted, ACEs often play an important role in overall health and well-being; they include experiencing childhood abuse, neglect, and/or household dysfunction. The impact of these early exposures can lead to toxic stress that can negatively alter the brain and the body’s response to stress over time.³ There are various tools readily available online that can assist with identifying ACEs and interpreting their prevalence. The American Academy of Pediatrics has an updated page of commonly used screening tools. Early identification and intervention can help mitigate the impact of these experiences on long-term outcomes.

Important Considerations Regarding Screening for SDOH and/or ACEs:

• Please consider if screening is helpful in your space, recognizing that there are benefits and potential ethical considerations to screen or not. Ensure an interdisciplinary approach if screening is implemented to ensure that the patient’s experience and well-being is prioritized.
• Try to be intentional in your communication with parents. The patient and family are our teachers and know best what they need.
• Consider what is available in your community and what can be offered to ensure that parents and families are appropriate and eligible for a particular resource.
• Encourage continuous collaboration and partnership with community providers who offer resources that a family may benefit from to ensure that the resource continues to be available.

Returning to the Vignette

Administering the IHELP tool has led to identifying that the adolescent’s insurance has lapsed, but she remains eligible, and the family seeks support to re-enroll. The family shares concerns regarding educational needs, as the child has not attended school for the past year and is not on track to graduate. The IHELP tool also helps you identify inconsistent transportation availability. Ultimately, a social work consultation is placed which assists with re-enrolling in insurance for the child and obtaining a bus pass for in-person visits. The patient is also supported in enrolling in the use of a videoconferencing platform for virtual visits. You and your team reach out to the school, which provides valuable information regarding the child’s status and how best to support re-engagement. On follow-up, she is now readily engaged in appointments and shares she is no longer worrying about transportation, which has been helpful. She has started initial conversations with the school and has a condensed schedule for reintegration.

Dr. Abdul-Karim, a child and adolescent psychiatrist, is assistant professor of psychiatry at the University of Vermont, Burlington. She said she had no relevant financial disclosures. Email her at [email protected].

References

1. Office of Disease Prevention and Health Promotion, US Department of Health & Human Services. Social Determinants of Health. https://odphp.health.gov/healthypeople/priority-areas/social-determinants-health

2. Cotton N and Shim R. J Am Acad Child Adolesc Psychiatry. 2022 Nov;61(11):1385-1389. doi: 10.1016/j.jaac.2022.04.020.

3. US Centers for Disease Control and Prevention. Adverse Childhood Experiences (ACEs): Preventing Early Trauma to Improve Adult Health. https://www.cdc.gov/vitalsigns/aces/index.html.

4. Kenyon C et al. Pediatrics. 2007 Sep;120(3):e734-e738. doi: 10.1542/peds.2006-2495.

5. Colvin JD et al. Acad Pediatr. 2016 Mar;16(2):168-174. doi: 10.1016/j.acap.2015.06.001.

Case vignette: A 16-year-old Nepali-born English-speaking adolescent presents for a well-child visit and notes concerns for anxiety, depression, and a history of trauma. She resides with her parents who work in hospitality with limited time off, and thus she presented for the initial office visit with a neighbor. Parents were not readily available to discuss treatment recommendations, including medication options. The teen shares a number of challenges that makes coming to appointments difficult. You also notice that the patient currently is not enrolled in insurance, though she appears eligible.

The above vignette highlights various social issues and concerns that impact access to healthcare and overall health/well-being. Social determinants of health (SDOH) and factors centered on mental health are now widely known to impact pediatric health and wellbeing. The Office of Disease Prevention and Health Promotion defines SDOH as “conditions in the environments in which people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning, and quality-of-life outcomes and risks.” SDOH can be grouped into five domains: Economic Stability, Education Access and Quality, Health Care Access and Quality, Neighborhood and Built Environment, and Social and Community Context.¹

Dr. Abdul-Karim

Additionally, when considering determinants that impact the mental health of children, it is prudent to consider parental psychosocial factors and adverse childhood experiences (ACEs), such as witnessing interpersonal violence, child abuse, parental substance use, and parental depression.² All these factors have been shown to impact an individual’s mental and physical health not only contemporaneously but also later in life.³

Screening Tool for Pediatric Social Histories

One screening tool to assist with gathering an expanded pediatric social history is called IHELP, developed by Kenyon et al,⁴ with further derivations from Colvin et al.⁵ Utilizing this tool can assist providers with identifying social needs.

The tool begins with a framing statement — “Let me ask you some questions I ask every family” — then proceeds to discuss relevant topics as shared below:

I: Income; Insurance

• Do you have any concerns about making ends meet?
• Do you have any concerns about your child’s health insurance?

H: Hunger, Housing Conditions; Homeless

• Do you have any concerns about having enough food?
• Have you ever been worried whether your food would run out before you got money to buy more?
• Within the past year has the food you bought ever not lasted, and you didn’t have money to get more?
• Do you have any concerns about poor housing conditions like mice, mold, or cockroaches?
• Do you have any concerns about being evicted or not being able to pay the rent?
• Do you have any concerns about not being able to pay your mortgage?

E: Education; Ensuring Safety (Violence)

• Do you have any concerns about your child’s educational needs?
• [DO NOT ASK IN FRONT OF CHILD 3 OR OLDER OR IN FRONT OF OTHER PARTNER] “From speaking to families, I have learned that violence in the home is common and now I ask all families about violence in the home. Do you have any concerns about violence in your home?”

L: Legal status (Immigration)

• What hospital was your child born in?
• If not in the United States: “Are you aware that your child may be eligible for benefits even though they were not born in the US? If you would like, I can have a social worker come talk to you about some possible benefits your child may be eligible for. Would you like me to do that?”

P: Power of Attorney; Guardianship

• Are you the biological mother or father of this child?
• [If not] “Can you show me the power of attorney or guardianship document you have?”
• **PATIENTS >17+ with Mental Incapacity: Ask for Guardianship.

This tool can help with identifying families with significant social needs so that one can attain further historical information and subsequently share resources to assist with any challenges.
 

Consider the Role of Adverse Childhood Experiences

Additionally, as noted, ACEs often play an important role in overall health and well-being; they include experiencing childhood abuse, neglect, and/or household dysfunction. The impact of these early exposures can lead to toxic stress that can negatively alter the brain and the body’s response to stress over time.³ There are various tools readily available online that can assist with identifying ACEs and interpreting their prevalence. The American Academy of Pediatrics has an updated page of commonly used screening tools. Early identification and intervention can help mitigate the impact of these experiences on long-term outcomes.

Important Considerations Regarding Screening for SDOH and/or ACEs:

• Please consider if screening is helpful in your space, recognizing that there are benefits and potential ethical considerations to screen or not. Ensure an interdisciplinary approach if screening is implemented to ensure that the patient’s experience and well-being is prioritized.
• Try to be intentional in your communication with parents. The patient and family are our teachers and know best what they need.
• Consider what is available in your community and what can be offered to ensure that parents and families are appropriate and eligible for a particular resource.
• Encourage continuous collaboration and partnership with community providers who offer resources that a family may benefit from to ensure that the resource continues to be available.

Returning to the Vignette

Administering the IHELP tool has led to identifying that the adolescent’s insurance has lapsed, but she remains eligible, and the family seeks support to re-enroll. The family shares concerns regarding educational needs, as the child has not attended school for the past year and is not on track to graduate. The IHELP tool also helps you identify inconsistent transportation availability. Ultimately, a social work consultation is placed which assists with re-enrolling in insurance for the child and obtaining a bus pass for in-person visits. The patient is also supported in enrolling in the use of a videoconferencing platform for virtual visits. You and your team reach out to the school, which provides valuable information regarding the child’s status and how best to support re-engagement. On follow-up, she is now readily engaged in appointments and shares she is no longer worrying about transportation, which has been helpful. She has started initial conversations with the school and has a condensed schedule for reintegration.

Dr. Abdul-Karim, a child and adolescent psychiatrist, is assistant professor of psychiatry at the University of Vermont, Burlington. She said she had no relevant financial disclosures. Email her at [email protected].

References

1. Office of Disease Prevention and Health Promotion, US Department of Health & Human Services. Social Determinants of Health. https://odphp.health.gov/healthypeople/priority-areas/social-determinants-health

2. Cotton N and Shim R. J Am Acad Child Adolesc Psychiatry. 2022 Nov;61(11):1385-1389. doi: 10.1016/j.jaac.2022.04.020.

3. US Centers for Disease Control and Prevention. Adverse Childhood Experiences (ACEs): Preventing Early Trauma to Improve Adult Health. https://www.cdc.gov/vitalsigns/aces/index.html.

4. Kenyon C et al. Pediatrics. 2007 Sep;120(3):e734-e738. doi: 10.1542/peds.2006-2495.

5. Colvin JD et al. Acad Pediatr. 2016 Mar;16(2):168-174. doi: 10.1016/j.acap.2015.06.001.

A long-term brain imaging study in aging adults showed faster rates of atrophy in certain brain structures to be associated with the risk of developing mild cognitive impairment (MCI).

While some brain atrophy is expected in aging, high levels of atrophy in the white matter and high enlargement in the ventricles are associated with earlier progression from normal cognition to MCI, the study found. The researchers also identified diabetes and atypical levels of amyloid beta protein in the cerebrospinal fluid as risk factors for brain atrophy and MCI.

For their research, published online on JAMA Network Open, Yuto Uchida, MD, PhD, and his colleagues at the Johns Hopkins University School of Medicine in Baltimore, Maryland, looked at data for 185 individuals (mean age, 55.4 years; 63% women) who were cognitively normal at baseline and followed for a median of 20 years.

All had been enrolled in a longitudinal cohort study on biomarkers of cognitive decline conducted at Johns Hopkins. Each participant underwent a median of five structural MRI studies during the follow-up period as well as annual cognitive testing. Altogether 60 individuals developed MCI, with eight of them progressing to dementia.

“We hypothesized that annual rates of change of segmental brain volumes would be associated with vascular risk factors among middle-aged and older adults and that these trends would be associated with the progression from normal cognition to MCI,” Uchida and colleagues wrote.
 

Uniquely Long Follow-Up

Most longitudinal studies using structural MRI count a decade or less of follow-up, the study authors noted. This makes it difficult to discern whether the annual rates of change of brain volumes are affected by vascular risk factors or are useful in predicting MCI, they said. Individual differences in brain aging make population-based studies less informative.

This study’s long timeframe allowed for tracking of brain changes “on an individual basis, which facilitates the differentiation between interindividual and intraindividual variations and leads to more accurate estimations of rates of brain atrophy,” Uchida and colleagues wrote.

People with high levels of atrophy in the white matter and enlargement in the ventricles saw earlier progression to MCI (hazard ratio [HR], 1.86; 95% CI, 1.24-2.49; P = .001). Diabetes mellitus was associated with progression to MCI (HR, 1.41; 95% CI, 1.06-1.76; P = .04), as was a low CSF Abeta42:Abeta40 ratio (HR, 1.48; 95% CI, 1.09-1.88; P = .04).

People with both diabetes and an abnormal amyloid profile were even more vulnerable to developing MCI (HR, 1.55; 95% CI, 1.13-1.98; P = .03). This indicated “a synergic association of diabetes and amyloid pathology with MCI progression,” Uchida and colleagues wrote, noting that insulin resistance has been shown to promote the formation of amyloid plaques, a hallmark of Alzheimer’s disease.

The findings also underscore that “white matter volume changes are closely associated with cognitive function in aging, suggesting that white matter degeneration may play a crucial role in cognitive decline,” the authors noted.

Uchida and colleagues acknowledged the modest size and imbalanced sex ratio of their study cohort as potential weaknesses, as well as the fact that the imaging technologies had changed over the course of the study. Most of the participants were White with family histories of dementia.
 

Findings May Lead to Targeted Interventions

In an editorial comment accompanying Uchida and colleagues’ study, Shohei Fujita, MD, PhD, of Massachusetts General Hospital, Boston, said that, while a more diverse population sample would be desirable and should be sought for future studies, the results nonetheless highlight “the potential of long-term longitudinal brain MRI datasets in elucidating the interplay of risk factors underlying cognitive decline and the potential benefits of controlling diabetes to reduce the risk of progression” along the Alzheimer’s disease continuum.

The findings may prove informative, Fujita said, in developing “targeted interventions for those most susceptible to progressive brain changes, potentially combining lifestyle modifications and pharmacological treatments.”

Uchida and colleagues’ study was funded by the Alzheimer’s Association, the National Alzheimer’s Coordinating Center, and the National Institutes of Health. The study’s corresponding author, Kenichi Oishi, disclosed funding from the Richman Family Foundation, Richman, the Sharp Family Foundation, and others. Uchida and Fujita reported no relevant financial conflicts of interest.

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

A long-term brain imaging study in aging adults showed faster rates of atrophy in certain brain structures to be associated with the risk of developing mild cognitive impairment (MCI).

While some brain atrophy is expected in aging, high levels of atrophy in the white matter and high enlargement in the ventricles are associated with earlier progression from normal cognition to MCI, the study found. The researchers also identified diabetes and atypical levels of amyloid beta protein in the cerebrospinal fluid as risk factors for brain atrophy and MCI.

For their research, published online on JAMA Network Open, Yuto Uchida, MD, PhD, and his colleagues at the Johns Hopkins University School of Medicine in Baltimore, Maryland, looked at data for 185 individuals (mean age, 55.4 years; 63% women) who were cognitively normal at baseline and followed for a median of 20 years.

All had been enrolled in a longitudinal cohort study on biomarkers of cognitive decline conducted at Johns Hopkins. Each participant underwent a median of five structural MRI studies during the follow-up period as well as annual cognitive testing. Altogether 60 individuals developed MCI, with eight of them progressing to dementia.

“We hypothesized that annual rates of change of segmental brain volumes would be associated with vascular risk factors among middle-aged and older adults and that these trends would be associated with the progression from normal cognition to MCI,” Uchida and colleagues wrote.
 

Uniquely Long Follow-Up

Most longitudinal studies using structural MRI count a decade or less of follow-up, the study authors noted. This makes it difficult to discern whether the annual rates of change of brain volumes are affected by vascular risk factors or are useful in predicting MCI, they said. Individual differences in brain aging make population-based studies less informative.

This study’s long timeframe allowed for tracking of brain changes “on an individual basis, which facilitates the differentiation between interindividual and intraindividual variations and leads to more accurate estimations of rates of brain atrophy,” Uchida and colleagues wrote.

People with high levels of atrophy in the white matter and enlargement in the ventricles saw earlier progression to MCI (hazard ratio [HR], 1.86; 95% CI, 1.24-2.49; P = .001). Diabetes mellitus was associated with progression to MCI (HR, 1.41; 95% CI, 1.06-1.76; P = .04), as was a low CSF Abeta42:Abeta40 ratio (HR, 1.48; 95% CI, 1.09-1.88; P = .04).

People with both diabetes and an abnormal amyloid profile were even more vulnerable to developing MCI (HR, 1.55; 95% CI, 1.13-1.98; P = .03). This indicated “a synergic association of diabetes and amyloid pathology with MCI progression,” Uchida and colleagues wrote, noting that insulin resistance has been shown to promote the formation of amyloid plaques, a hallmark of Alzheimer’s disease.

The findings also underscore that “white matter volume changes are closely associated with cognitive function in aging, suggesting that white matter degeneration may play a crucial role in cognitive decline,” the authors noted.

Uchida and colleagues acknowledged the modest size and imbalanced sex ratio of their study cohort as potential weaknesses, as well as the fact that the imaging technologies had changed over the course of the study. Most of the participants were White with family histories of dementia.
 

Findings May Lead to Targeted Interventions

In an editorial comment accompanying Uchida and colleagues’ study, Shohei Fujita, MD, PhD, of Massachusetts General Hospital, Boston, said that, while a more diverse population sample would be desirable and should be sought for future studies, the results nonetheless highlight “the potential of long-term longitudinal brain MRI datasets in elucidating the interplay of risk factors underlying cognitive decline and the potential benefits of controlling diabetes to reduce the risk of progression” along the Alzheimer’s disease continuum.

The findings may prove informative, Fujita said, in developing “targeted interventions for those most susceptible to progressive brain changes, potentially combining lifestyle modifications and pharmacological treatments.”

Uchida and colleagues’ study was funded by the Alzheimer’s Association, the National Alzheimer’s Coordinating Center, and the National Institutes of Health. The study’s corresponding author, Kenichi Oishi, disclosed funding from the Richman Family Foundation, Richman, the Sharp Family Foundation, and others. Uchida and Fujita reported no relevant financial conflicts of interest.

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

A long-term brain imaging study in aging adults showed faster rates of atrophy in certain brain structures to be associated with the risk of developing mild cognitive impairment (MCI).

While some brain atrophy is expected in aging, high levels of atrophy in the white matter and high enlargement in the ventricles are associated with earlier progression from normal cognition to MCI, the study found. The researchers also identified diabetes and atypical levels of amyloid beta protein in the cerebrospinal fluid as risk factors for brain atrophy and MCI.

For their research, published online on JAMA Network Open, Yuto Uchida, MD, PhD, and his colleagues at the Johns Hopkins University School of Medicine in Baltimore, Maryland, looked at data for 185 individuals (mean age, 55.4 years; 63% women) who were cognitively normal at baseline and followed for a median of 20 years.

All had been enrolled in a longitudinal cohort study on biomarkers of cognitive decline conducted at Johns Hopkins. Each participant underwent a median of five structural MRI studies during the follow-up period as well as annual cognitive testing. Altogether 60 individuals developed MCI, with eight of them progressing to dementia.

“We hypothesized that annual rates of change of segmental brain volumes would be associated with vascular risk factors among middle-aged and older adults and that these trends would be associated with the progression from normal cognition to MCI,” Uchida and colleagues wrote.
 

Uniquely Long Follow-Up

Most longitudinal studies using structural MRI count a decade or less of follow-up, the study authors noted. This makes it difficult to discern whether the annual rates of change of brain volumes are affected by vascular risk factors or are useful in predicting MCI, they said. Individual differences in brain aging make population-based studies less informative.

This study’s long timeframe allowed for tracking of brain changes “on an individual basis, which facilitates the differentiation between interindividual and intraindividual variations and leads to more accurate estimations of rates of brain atrophy,” Uchida and colleagues wrote.

People with high levels of atrophy in the white matter and enlargement in the ventricles saw earlier progression to MCI (hazard ratio [HR], 1.86; 95% CI, 1.24-2.49; P = .001). Diabetes mellitus was associated with progression to MCI (HR, 1.41; 95% CI, 1.06-1.76; P = .04), as was a low CSF Abeta42:Abeta40 ratio (HR, 1.48; 95% CI, 1.09-1.88; P = .04).

People with both diabetes and an abnormal amyloid profile were even more vulnerable to developing MCI (HR, 1.55; 95% CI, 1.13-1.98; P = .03). This indicated “a synergic association of diabetes and amyloid pathology with MCI progression,” Uchida and colleagues wrote, noting that insulin resistance has been shown to promote the formation of amyloid plaques, a hallmark of Alzheimer’s disease.

The findings also underscore that “white matter volume changes are closely associated with cognitive function in aging, suggesting that white matter degeneration may play a crucial role in cognitive decline,” the authors noted.

Uchida and colleagues acknowledged the modest size and imbalanced sex ratio of their study cohort as potential weaknesses, as well as the fact that the imaging technologies had changed over the course of the study. Most of the participants were White with family histories of dementia.
 

Findings May Lead to Targeted Interventions

In an editorial comment accompanying Uchida and colleagues’ study, Shohei Fujita, MD, PhD, of Massachusetts General Hospital, Boston, said that, while a more diverse population sample would be desirable and should be sought for future studies, the results nonetheless highlight “the potential of long-term longitudinal brain MRI datasets in elucidating the interplay of risk factors underlying cognitive decline and the potential benefits of controlling diabetes to reduce the risk of progression” along the Alzheimer’s disease continuum.

The findings may prove informative, Fujita said, in developing “targeted interventions for those most susceptible to progressive brain changes, potentially combining lifestyle modifications and pharmacological treatments.”

Uchida and colleagues’ study was funded by the Alzheimer’s Association, the National Alzheimer’s Coordinating Center, and the National Institutes of Health. The study’s corresponding author, Kenichi Oishi, disclosed funding from the Richman Family Foundation, Richman, the Sharp Family Foundation, and others. Uchida and Fujita reported no relevant financial conflicts of interest.

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

Family physician burnout rates are among the highest in medicine. More than half (51%) reported burnout in a Medscape report from January 2024; only emergency physicians (63%) and obstetricians/gynecologists and oncologists (both 53%) had higher rates.

In a recent study, researchers examined what’s driving the burnout through a serial cross-sectional survey of family physicians. Authors conclude that reducing burnout may be most effective with a focus on two factors: Decreasing time spent at home on electronic health record (EHR) tasks and building stronger nurse-physician teams.

Findings by Lisa S. Rotenstein, MD, MBA, MSc, Division of Clinical Informatics, Department of Medicine, University of California, San Francisco, and colleagues were published in JAMA Network Open. The findings debunk some longstanding assumptions, Christine A. Sinsky, MD, vice president of professional satisfaction with the American Medical Association, wrote in an editorial.

“This study advances our understanding that addressing physician burnout is not about more EHR training and not specifically about moving to paying for value; rather, it is about developing stronger nurse-physician core teams. These are novel and important findings with actionable lessons for physician and health system leaders,” Sinsky wrote.
 

More Than 10,000 Physicians; 100% Response Rate

The study included 10,315 physicians who answered questions related to burnout on the American Board of Family Medicine’s Continuous Certification Questionnaire between 2017 and 2023. Researchers achieved a 100% response rate by requiring diplomates to complete the survey before submitting their exam.

The median age of respondents was 50 years. More than half (57.8%) were employees, 11.3% were full owners of their practices, and 3.2% were contractors. Responses indicated that 10% practiced as solo physicians, 20.4% were in a practice with more than 20 physicians, and the rest were in a practice with 2-19 physicians. More than three fourths of the physicians practiced in an urban/suburban setting, and 13.5% practiced in a rural setting.

Physicians’ perceptions that EHR use at home was appropriate were associated with 0.58 times the odds of burnout (95% CI, 0.53-0.64; P < .001), and high team efficiency was associated with 0.61 times the odds of burnout (95% CI, 0.56-0.67).

Physician collaboration with a registered nurse was associated with greater odds of high team efficiency (odds ratio [OR], 1.35; 95% CI, 1.22-1.50). Collaboration with a physician assistant was associated with greater odds of appropriate home EHR time (OR, 1.13; 95% CI, 1.03-1.24).
 

Numbers Needed to Treat

“When translated to a number needed to treat, these ORs suggest that eight additional physicians perceiving appropriate home EHR time would result in prevention of one additional case of burnout, and nine additional physicians perceiving high team efficiency would result in prevention of one case of burnout,” the authors wrote.

The authors also noted that EHR proficiency was not associated with burnout (OR, 0.93; 95% CI, 0.85-1.02; P = .12). Self-reported EHR proficiency remained high and steady over the study period.

“It is time to lay to rest the myth of the technology-resistant physician,” Sinsky wrote in the editorial. “The problem is not the end user.”

Sinsky said the findings also show that value-based compensation “is not a panacea” and, in fact, participation in such payment programs was associated with both more time working on the EHR at home and lower team efficiency.

Fee-for-service models are often painted as the culprit, she noted.

“The key in either compensation model is to direct sufficient financial resources to primary care to cover the costs of optimal team size, skill level, and stability. In my experience, this is a minimum of two clinical assistants (including at least one nurse) per 1.0 clinical full-time equivalent physician, with the same team of individuals working together on a daily basis to develop trust, reliance, and efficiencies.”
 

Medical Assistants (MAs) Replacing Nurses on Core Teams

In many cases, nurses have been replaced on core clinical teams by MAs, who, with a narrower scope of practice, put work back on the physician’s plate, Sinsky noted, and the MAs also often work in pools rather than with one physician.

“The result is that nurses in many settings are sequestered in a room with a computer and a telephone, with limited direct interactions with their patients or physicians, and physicians spend more time each day on tasks that do not require their medical training,” Sinsky wrote.

Strengths of the study include the large sample size, a 100% response rate to the survey, and consistency of findings over the 6 years.

Steven Waldren, MD, MS, chief medical informatics officer for the American Academy of Family Physicians, said the results of the study confirm what the organization knows to be true through various analyses and talks with doctors: “Even if you can just focus on documentation and improve that, it gives docs hope that other things can happen and actually improve. We saw a decrease in burnout in just solving that one problem.”

Team-based care also allows physicians to talk through challenges and off-load tasks, which allows them to focus on patient care, he said.

Waldren added that some technology upgrades can help reduce burnout without adding staff. He pointed to promising technology in managing EHR inbox messages and in artificial intelligence (AI) solutions for developing a visit summary and patient instructions that can then be reviewed by a physician.

He gave an example of ambient documentation. “We’ve seen that it reduces the amount of documentation time by 60%-70%,” he said. The products in this space record the physician-patient conversation and generate a summary to be reviewed by the physician for accuracy.

“These tools now are highly accurate,” he said. They are also able to remove clinically irrelevant details. He said, for example, if a patient talks about her recent golf outing on a trip to Ireland, the program will record only that she recently had an international trip to Ireland and remove the golf details. The technology has been available for many months, he said.

Sonia Rivera-Martinez, DO, an associate professor of family medicine at the New York Institute of Technology College of Osteopathic Medicine in Old Westbury, New York, said AI solutions are impressive but expensive, which is why her practice has not upgraded to AI-generated visit summaries.

She said even in her academic setting where there is less pressure to see several patients per hour, after-hours EHR work is a reality for her and her colleagues as seeing patients is paired with the demands of teaching students. Her practice is also part of an accountable care organization, which adds its own set of documentation demands.
 

Nearly 30 Hours a Week of EHR Work at Home

Rivera-Martinez estimated that she spends 20-30 hours each week doing EHR tasks at home and said the study authors have highlighted an important problem.

She said she has also seen the value of strong nurse-physician teams in her practice. The two nurses in her practice, for instance, know they have permission to administer flu shots and do other routine tasks without the physicians having to place the order. “But I can’t say it eliminates having to do work outside (of work hours).”

She said before current EHR documentation demands, “I used to be able to finish a progress note in less than 5 minutes.” Now, she said, with her medically complex patient population, it takes her 20-30 minutes to complete a patient’s progress note.

The findings of the study have particular significance with the rising prevalence of burnout among family physicians, the authors wrote. “Clinical leaders and policymakers seeking to develop care delivery models that enable sustainable primary care practice should focus on ensuring adequate team support and acceptable EHR workloads for physicians.”

This study was funded by the United States Office of the National Coordinator for Health Information Technology and Department of Health and Human Services. Additionally, Rotenstein’s time was funded by The Physicians Foundation. Rotenstein reported personal fees from Phreesia; stock grants from serving on the advisory board of Augmedix; and grants from the Agency for Healthcare Research and Quality, American Medical Association, The Physicians Foundation, and Association of Chiefs and Leaders of General Internal Medicine outside the submitted work. Nathaniel Hendrix reported grants from the Office of the National Coordinator for Health Information Technology during the conduct of the study. One coauthor reported a cooperative agreement from the Office of the National Coordinator for Health Information Technology (now Assistant Secretary for Technology Policy/Office of the National Coordinator for Health Information Technology). Another coauthor reported that the University of California, San Francisco, has received funding from the Office of the National Coordinator for Health Information Technology to partner with the American Board of Family Medicine to revise the survey over time to better capture interoperability. Sinsky, Rivera-Martinez, and Waldren reported no relevant financial relationships.

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

Family physician burnout rates are among the highest in medicine. More than half (51%) reported burnout in a Medscape report from January 2024; only emergency physicians (63%) and obstetricians/gynecologists and oncologists (both 53%) had higher rates.

In a recent study, researchers examined what’s driving the burnout through a serial cross-sectional survey of family physicians. Authors conclude that reducing burnout may be most effective with a focus on two factors: Decreasing time spent at home on electronic health record (EHR) tasks and building stronger nurse-physician teams.

Findings by Lisa S. Rotenstein, MD, MBA, MSc, Division of Clinical Informatics, Department of Medicine, University of California, San Francisco, and colleagues were published in JAMA Network Open. The findings debunk some longstanding assumptions, Christine A. Sinsky, MD, vice president of professional satisfaction with the American Medical Association, wrote in an editorial.

“This study advances our understanding that addressing physician burnout is not about more EHR training and not specifically about moving to paying for value; rather, it is about developing stronger nurse-physician core teams. These are novel and important findings with actionable lessons for physician and health system leaders,” Sinsky wrote.
 

More Than 10,000 Physicians; 100% Response Rate

The study included 10,315 physicians who answered questions related to burnout on the American Board of Family Medicine’s Continuous Certification Questionnaire between 2017 and 2023. Researchers achieved a 100% response rate by requiring diplomates to complete the survey before submitting their exam.

The median age of respondents was 50 years. More than half (57.8%) were employees, 11.3% were full owners of their practices, and 3.2% were contractors. Responses indicated that 10% practiced as solo physicians, 20.4% were in a practice with more than 20 physicians, and the rest were in a practice with 2-19 physicians. More than three fourths of the physicians practiced in an urban/suburban setting, and 13.5% practiced in a rural setting.

Physicians’ perceptions that EHR use at home was appropriate were associated with 0.58 times the odds of burnout (95% CI, 0.53-0.64; P < .001), and high team efficiency was associated with 0.61 times the odds of burnout (95% CI, 0.56-0.67).

Physician collaboration with a registered nurse was associated with greater odds of high team efficiency (odds ratio [OR], 1.35; 95% CI, 1.22-1.50). Collaboration with a physician assistant was associated with greater odds of appropriate home EHR time (OR, 1.13; 95% CI, 1.03-1.24).
 

Numbers Needed to Treat

“When translated to a number needed to treat, these ORs suggest that eight additional physicians perceiving appropriate home EHR time would result in prevention of one additional case of burnout, and nine additional physicians perceiving high team efficiency would result in prevention of one case of burnout,” the authors wrote.

The authors also noted that EHR proficiency was not associated with burnout (OR, 0.93; 95% CI, 0.85-1.02; P = .12). Self-reported EHR proficiency remained high and steady over the study period.

“It is time to lay to rest the myth of the technology-resistant physician,” Sinsky wrote in the editorial. “The problem is not the end user.”

Sinsky said the findings also show that value-based compensation “is not a panacea” and, in fact, participation in such payment programs was associated with both more time working on the EHR at home and lower team efficiency.

Fee-for-service models are often painted as the culprit, she noted.

“The key in either compensation model is to direct sufficient financial resources to primary care to cover the costs of optimal team size, skill level, and stability. In my experience, this is a minimum of two clinical assistants (including at least one nurse) per 1.0 clinical full-time equivalent physician, with the same team of individuals working together on a daily basis to develop trust, reliance, and efficiencies.”
 

Medical Assistants (MAs) Replacing Nurses on Core Teams

In many cases, nurses have been replaced on core clinical teams by MAs, who, with a narrower scope of practice, put work back on the physician’s plate, Sinsky noted, and the MAs also often work in pools rather than with one physician.

“The result is that nurses in many settings are sequestered in a room with a computer and a telephone, with limited direct interactions with their patients or physicians, and physicians spend more time each day on tasks that do not require their medical training,” Sinsky wrote.

Strengths of the study include the large sample size, a 100% response rate to the survey, and consistency of findings over the 6 years.

Steven Waldren, MD, MS, chief medical informatics officer for the American Academy of Family Physicians, said the results of the study confirm what the organization knows to be true through various analyses and talks with doctors: “Even if you can just focus on documentation and improve that, it gives docs hope that other things can happen and actually improve. We saw a decrease in burnout in just solving that one problem.”

Team-based care also allows physicians to talk through challenges and off-load tasks, which allows them to focus on patient care, he said.

Waldren added that some technology upgrades can help reduce burnout without adding staff. He pointed to promising technology in managing EHR inbox messages and in artificial intelligence (AI) solutions for developing a visit summary and patient instructions that can then be reviewed by a physician.

He gave an example of ambient documentation. “We’ve seen that it reduces the amount of documentation time by 60%-70%,” he said. The products in this space record the physician-patient conversation and generate a summary to be reviewed by the physician for accuracy.

“These tools now are highly accurate,” he said. They are also able to remove clinically irrelevant details. He said, for example, if a patient talks about her recent golf outing on a trip to Ireland, the program will record only that she recently had an international trip to Ireland and remove the golf details. The technology has been available for many months, he said.

Sonia Rivera-Martinez, DO, an associate professor of family medicine at the New York Institute of Technology College of Osteopathic Medicine in Old Westbury, New York, said AI solutions are impressive but expensive, which is why her practice has not upgraded to AI-generated visit summaries.

She said even in her academic setting where there is less pressure to see several patients per hour, after-hours EHR work is a reality for her and her colleagues as seeing patients is paired with the demands of teaching students. Her practice is also part of an accountable care organization, which adds its own set of documentation demands.
 

Nearly 30 Hours a Week of EHR Work at Home

Rivera-Martinez estimated that she spends 20-30 hours each week doing EHR tasks at home and said the study authors have highlighted an important problem.

She said she has also seen the value of strong nurse-physician teams in her practice. The two nurses in her practice, for instance, know they have permission to administer flu shots and do other routine tasks without the physicians having to place the order. “But I can’t say it eliminates having to do work outside (of work hours).”

She said before current EHR documentation demands, “I used to be able to finish a progress note in less than 5 minutes.” Now, she said, with her medically complex patient population, it takes her 20-30 minutes to complete a patient’s progress note.

The findings of the study have particular significance with the rising prevalence of burnout among family physicians, the authors wrote. “Clinical leaders and policymakers seeking to develop care delivery models that enable sustainable primary care practice should focus on ensuring adequate team support and acceptable EHR workloads for physicians.”

This study was funded by the United States Office of the National Coordinator for Health Information Technology and Department of Health and Human Services. Additionally, Rotenstein’s time was funded by The Physicians Foundation. Rotenstein reported personal fees from Phreesia; stock grants from serving on the advisory board of Augmedix; and grants from the Agency for Healthcare Research and Quality, American Medical Association, The Physicians Foundation, and Association of Chiefs and Leaders of General Internal Medicine outside the submitted work. Nathaniel Hendrix reported grants from the Office of the National Coordinator for Health Information Technology during the conduct of the study. One coauthor reported a cooperative agreement from the Office of the National Coordinator for Health Information Technology (now Assistant Secretary for Technology Policy/Office of the National Coordinator for Health Information Technology). Another coauthor reported that the University of California, San Francisco, has received funding from the Office of the National Coordinator for Health Information Technology to partner with the American Board of Family Medicine to revise the survey over time to better capture interoperability. Sinsky, Rivera-Martinez, and Waldren reported no relevant financial relationships.

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

Family physician burnout rates are among the highest in medicine. More than half (51%) reported burnout in a Medscape report from January 2024; only emergency physicians (63%) and obstetricians/gynecologists and oncologists (both 53%) had higher rates.

In a recent study, researchers examined what’s driving the burnout through a serial cross-sectional survey of family physicians. Authors conclude that reducing burnout may be most effective with a focus on two factors: Decreasing time spent at home on electronic health record (EHR) tasks and building stronger nurse-physician teams.

Findings by Lisa S. Rotenstein, MD, MBA, MSc, Division of Clinical Informatics, Department of Medicine, University of California, San Francisco, and colleagues were published in JAMA Network Open. The findings debunk some longstanding assumptions, Christine A. Sinsky, MD, vice president of professional satisfaction with the American Medical Association, wrote in an editorial.

“This study advances our understanding that addressing physician burnout is not about more EHR training and not specifically about moving to paying for value; rather, it is about developing stronger nurse-physician core teams. These are novel and important findings with actionable lessons for physician and health system leaders,” Sinsky wrote.
 

More Than 10,000 Physicians; 100% Response Rate

The study included 10,315 physicians who answered questions related to burnout on the American Board of Family Medicine’s Continuous Certification Questionnaire between 2017 and 2023. Researchers achieved a 100% response rate by requiring diplomates to complete the survey before submitting their exam.

The median age of respondents was 50 years. More than half (57.8%) were employees, 11.3% were full owners of their practices, and 3.2% were contractors. Responses indicated that 10% practiced as solo physicians, 20.4% were in a practice with more than 20 physicians, and the rest were in a practice with 2-19 physicians. More than three fourths of the physicians practiced in an urban/suburban setting, and 13.5% practiced in a rural setting.

Physicians’ perceptions that EHR use at home was appropriate were associated with 0.58 times the odds of burnout (95% CI, 0.53-0.64; P < .001), and high team efficiency was associated with 0.61 times the odds of burnout (95% CI, 0.56-0.67).

Physician collaboration with a registered nurse was associated with greater odds of high team efficiency (odds ratio [OR], 1.35; 95% CI, 1.22-1.50). Collaboration with a physician assistant was associated with greater odds of appropriate home EHR time (OR, 1.13; 95% CI, 1.03-1.24).
 

Numbers Needed to Treat

“When translated to a number needed to treat, these ORs suggest that eight additional physicians perceiving appropriate home EHR time would result in prevention of one additional case of burnout, and nine additional physicians perceiving high team efficiency would result in prevention of one case of burnout,” the authors wrote.

The authors also noted that EHR proficiency was not associated with burnout (OR, 0.93; 95% CI, 0.85-1.02; P = .12). Self-reported EHR proficiency remained high and steady over the study period.

“It is time to lay to rest the myth of the technology-resistant physician,” Sinsky wrote in the editorial. “The problem is not the end user.”

Sinsky said the findings also show that value-based compensation “is not a panacea” and, in fact, participation in such payment programs was associated with both more time working on the EHR at home and lower team efficiency.

Fee-for-service models are often painted as the culprit, she noted.

“The key in either compensation model is to direct sufficient financial resources to primary care to cover the costs of optimal team size, skill level, and stability. In my experience, this is a minimum of two clinical assistants (including at least one nurse) per 1.0 clinical full-time equivalent physician, with the same team of individuals working together on a daily basis to develop trust, reliance, and efficiencies.”
 

Medical Assistants (MAs) Replacing Nurses on Core Teams

In many cases, nurses have been replaced on core clinical teams by MAs, who, with a narrower scope of practice, put work back on the physician’s plate, Sinsky noted, and the MAs also often work in pools rather than with one physician.

“The result is that nurses in many settings are sequestered in a room with a computer and a telephone, with limited direct interactions with their patients or physicians, and physicians spend more time each day on tasks that do not require their medical training,” Sinsky wrote.

Strengths of the study include the large sample size, a 100% response rate to the survey, and consistency of findings over the 6 years.

Steven Waldren, MD, MS, chief medical informatics officer for the American Academy of Family Physicians, said the results of the study confirm what the organization knows to be true through various analyses and talks with doctors: “Even if you can just focus on documentation and improve that, it gives docs hope that other things can happen and actually improve. We saw a decrease in burnout in just solving that one problem.”

Team-based care also allows physicians to talk through challenges and off-load tasks, which allows them to focus on patient care, he said.

Waldren added that some technology upgrades can help reduce burnout without adding staff. He pointed to promising technology in managing EHR inbox messages and in artificial intelligence (AI) solutions for developing a visit summary and patient instructions that can then be reviewed by a physician.

He gave an example of ambient documentation. “We’ve seen that it reduces the amount of documentation time by 60%-70%,” he said. The products in this space record the physician-patient conversation and generate a summary to be reviewed by the physician for accuracy.

“These tools now are highly accurate,” he said. They are also able to remove clinically irrelevant details. He said, for example, if a patient talks about her recent golf outing on a trip to Ireland, the program will record only that she recently had an international trip to Ireland and remove the golf details. The technology has been available for many months, he said.

Sonia Rivera-Martinez, DO, an associate professor of family medicine at the New York Institute of Technology College of Osteopathic Medicine in Old Westbury, New York, said AI solutions are impressive but expensive, which is why her practice has not upgraded to AI-generated visit summaries.

She said even in her academic setting where there is less pressure to see several patients per hour, after-hours EHR work is a reality for her and her colleagues as seeing patients is paired with the demands of teaching students. Her practice is also part of an accountable care organization, which adds its own set of documentation demands.
 

Nearly 30 Hours a Week of EHR Work at Home

Rivera-Martinez estimated that she spends 20-30 hours each week doing EHR tasks at home and said the study authors have highlighted an important problem.

She said she has also seen the value of strong nurse-physician teams in her practice. The two nurses in her practice, for instance, know they have permission to administer flu shots and do other routine tasks without the physicians having to place the order. “But I can’t say it eliminates having to do work outside (of work hours).”

She said before current EHR documentation demands, “I used to be able to finish a progress note in less than 5 minutes.” Now, she said, with her medically complex patient population, it takes her 20-30 minutes to complete a patient’s progress note.

The findings of the study have particular significance with the rising prevalence of burnout among family physicians, the authors wrote. “Clinical leaders and policymakers seeking to develop care delivery models that enable sustainable primary care practice should focus on ensuring adequate team support and acceptable EHR workloads for physicians.”

This study was funded by the United States Office of the National Coordinator for Health Information Technology and Department of Health and Human Services. Additionally, Rotenstein’s time was funded by The Physicians Foundation. Rotenstein reported personal fees from Phreesia; stock grants from serving on the advisory board of Augmedix; and grants from the Agency for Healthcare Research and Quality, American Medical Association, The Physicians Foundation, and Association of Chiefs and Leaders of General Internal Medicine outside the submitted work. Nathaniel Hendrix reported grants from the Office of the National Coordinator for Health Information Technology during the conduct of the study. One coauthor reported a cooperative agreement from the Office of the National Coordinator for Health Information Technology (now Assistant Secretary for Technology Policy/Office of the National Coordinator for Health Information Technology). Another coauthor reported that the University of California, San Francisco, has received funding from the Office of the National Coordinator for Health Information Technology to partner with the American Board of Family Medicine to revise the survey over time to better capture interoperability. Sinsky, Rivera-Martinez, and Waldren reported no relevant financial relationships.

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

Guidance from professional societies on how to handle the risk for pulmonary aspiration during general anesthesia or deep sedation for patients taking glucagon-like peptide 1 receptor agonists (GLP-1 RAs) continues to evolve, as does the US Food and Drug Administration’s (FDA’s) labeling for the drugs. The changes can be challenging to keep up with, and endocrinologists seem to be making their own decisions based on clinical experience and their interpretations of the potential impact and value of the emerging information.

The latest FDA label change warns about the risk for pulmonary aspiration but notes “insufficient” data to inform recommendations to mitigate the risk in vulnerable patients. Yet, the latest multi-society guidance, led by the American Society of Anesthesiologists (ASA) and based on consensus, not evidence, has nuanced advice for managing patients at risk.

Does the FDA’s label change make a difference regarding the multi-society guidance, which was published earlier? “The answer is no,” Girish Joshi, MD, vice chair, ASA Committee on Practice Parameters, told this news organization. “The concern of increased pulmonary aspiration in patients who are on GLP-1 receptor agonists has been known, and that concern still exists. So, we started with not an assumption but the premise that patients on GLP-1 receptor agonists are at a higher risk of aspiration during sedation, analgesia, and/or general anesthesia. The FDA basically confirms what we say in the guidance.”

Joshi, professor in the Anesthesiology and Pain Management Department at UT Southwestern Medical Center, Dallas, aimed to make the guidance, which was published simultaneously in several society journals, more implementable with a letter to the editor of Anesthesiology. The key, he said, is to identify patients at higher risk for aspiration; all others would follow treatment as usual.

The letter highlights three overarching recommendations and then expands upon them: Standardized preoperative assessment for risk for delayed gastric emptying (yes/no); selective preoperative care plan based on delayed gastric emptying assessment and shared decision-making; and on the day of the procedure, reassess for delayed gastric emptying and mitigate risk if there is clinical concern.

But it seems as though, for now, endocrinologists are managing these patients as they see fit, within the parameters of any institutional guidance requirements. Here is what they said about their practice:

Amy E. Rothberg, MD, DABOM, director of the Weight Management Program & Rewind at the University of Michigan, Ann Arbor, Michigan, said, “I think it makes sense to inform our patients of the labeling and rare but potential adverse effects if they intend to undergo anesthesia for a scheduled procedure/surgery. There is never no risk of aspiration during anesthesia.”

“I find it a bit curious that ASA implies that those who experience GI side effects are more likely than those who do not to have this potential risk. I doubt there is evidence that those without GI side effects are necessarily ‘safer’ and a study to determine that is unlikely to take be conducted.”

“My institution does require a 1-week pause on GLP-1s for those undergoing anesthesia for surgery,” she added. “That’s not evidence-based either, but probably reduces the risk of aspiration during anesthesia — but I don’t know what the actual denominator is for aspiration in those who continued vs those who took a pause from GLP-1s. Pausing does certainly (anecdotally) increase the traffic of communications between physicians and their patients about what to do in the interval.”

Anne Peters, MD, a professor of clinical medicine and a clinical scholar at the Keck School of Medicine of the University of Southern California, Los Angeles, said, “The FDA label change is a warning that really doesn’t say exactly who on GLP-1 RAs is at highest risk or what to do, and if any intervention has been shown to help. The ASA recommendations seem much more nuanced and practical, including point-of-care gastric ultrasound to see if there is retained food/fluid prior to surgery.”

“In my practice, I individualize what I say, depending on the person and the circumstance,” she said. “Mostly, I have people hold one dose before planned surgery, so they have been 10 days at least without a dose. But if worried about gastrointestinal symptoms or gastroparesis, I have them do a clear liquid diet for 24 hours presurgery. Or at least avoid heavy fat meals the day before.”

“There is a risk of aspiration with anything that slows gastric emptying — maybe even in patients with gastroparesis at baseline due to physiologic, not pharmacological, reasons — and anesthesiologists should be aware of the need to assess patients individually.”

Michael A. Weintraub, MD, of NYU Langone Health Diabetes & Endocrine Associates in New York City, observed, “The risk of a pulmonary aspiration event with GLP-1 medication is quite rare, but not zero. On the other hand, stopping the GLP-1 can cause hyperglycemia or rebound weight gain. Furthermore, it can become complicated to restart GLP1 dosing, particularly given the existing medication shortages.”

“In most cases, stopping a weekly GLP-1 medication 1 week prior to the procedure minimizes the risks of pulmonary aspiration and prevents any worsening hyperglycemia or weight gain,” he said. However, taking the drug 7 days prior to the procedure is optimal. “That way, they would be due for the next dose on the day of the procedure, and taking it the day following procedure minimizes disruption in their once-weekly regimen.”

Malini Gupta, MD, director of G2Endo Endocrinology & Metabolism, Memphis, Tennessee, advised that physicians weigh the risk of stopping the medication (which can cause a glycemic spike) vs risk for aspiration.

“In my opinion, all patients should follow a strict liquid diet or NPO status prior to a surgery to further decrease the risk of aspiration,” she said. “I generally hold the GLP-1 RA for a week before a surgery. If additional glycemic control is necessary, I will add to or adjust one of the patient’s other diabetes medications.”

Jaime Almandoz, MD, associate professor of medicine and medical director of the Weight Wellness Program in Dallas, said, “As endocrinologists, we typically rely on our anesthesia colleagues for guidance on perioperative management. In light of emerging guidelines for holding GLP-1 medications, we also recommend patients adopt a liquid diet 24 hours prior to surgery, along with the fasting protocol.”

“For those managing diabetes with GLP-1 therapies, it is crucial to establish a blood sugar management plan while off these medications, especially during fasting or postoperative periods, which can be further influenced by many factors, including nausea, pain medications, and antibiotics after the procedure.”

Joshi added that at Parkland Hospital in Dallas, “we do a huge number of cases using the same information. We identify patients who are at risk, and then we tell our proceduralists and our surgeons if they’re in the escalating phase of the dosing or if they have GI symptoms; don’t even schedule them as an elective case; wait till the escalation phase is over and then schedule them.”

“That way,” he said, “it becomes logistically easy to manage because the recommendation from the group is that patients who are at higher risk should receive a 24-hour liquid diet — the same as colonoscopy. But sometimes it can be challenging to do so.”

Joshi has received honoraria for consultation from Merck Sharp & Dohme, Vertex Pharmaceuticals, and Haisco-USA Pharmaceuticals. Gupta is on the speakers bureau for Amgen (Tepezza) and IBSA (Tirosint) and is a creative consultant for AbbVie. Almandoz serves on advisory boards for Novo Nordisk, Eli Lilly, and Boehringer Ingelheim. The other experts declared no relevant relationships.
 

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

Guidance from professional societies on how to handle the risk for pulmonary aspiration during general anesthesia or deep sedation for patients taking glucagon-like peptide 1 receptor agonists (GLP-1 RAs) continues to evolve, as does the US Food and Drug Administration’s (FDA’s) labeling for the drugs. The changes can be challenging to keep up with, and endocrinologists seem to be making their own decisions based on clinical experience and their interpretations of the potential impact and value of the emerging information.

The latest FDA label change warns about the risk for pulmonary aspiration but notes “insufficient” data to inform recommendations to mitigate the risk in vulnerable patients. Yet, the latest multi-society guidance, led by the American Society of Anesthesiologists (ASA) and based on consensus, not evidence, has nuanced advice for managing patients at risk.

Does the FDA’s label change make a difference regarding the multi-society guidance, which was published earlier? “The answer is no,” Girish Joshi, MD, vice chair, ASA Committee on Practice Parameters, told this news organization. “The concern of increased pulmonary aspiration in patients who are on GLP-1 receptor agonists has been known, and that concern still exists. So, we started with not an assumption but the premise that patients on GLP-1 receptor agonists are at a higher risk of aspiration during sedation, analgesia, and/or general anesthesia. The FDA basically confirms what we say in the guidance.”

Joshi, professor in the Anesthesiology and Pain Management Department at UT Southwestern Medical Center, Dallas, aimed to make the guidance, which was published simultaneously in several society journals, more implementable with a letter to the editor of Anesthesiology. The key, he said, is to identify patients at higher risk for aspiration; all others would follow treatment as usual.

The letter highlights three overarching recommendations and then expands upon them: Standardized preoperative assessment for risk for delayed gastric emptying (yes/no); selective preoperative care plan based on delayed gastric emptying assessment and shared decision-making; and on the day of the procedure, reassess for delayed gastric emptying and mitigate risk if there is clinical concern.

But it seems as though, for now, endocrinologists are managing these patients as they see fit, within the parameters of any institutional guidance requirements. Here is what they said about their practice:

Amy E. Rothberg, MD, DABOM, director of the Weight Management Program & Rewind at the University of Michigan, Ann Arbor, Michigan, said, “I think it makes sense to inform our patients of the labeling and rare but potential adverse effects if they intend to undergo anesthesia for a scheduled procedure/surgery. There is never no risk of aspiration during anesthesia.”

“I find it a bit curious that ASA implies that those who experience GI side effects are more likely than those who do not to have this potential risk. I doubt there is evidence that those without GI side effects are necessarily ‘safer’ and a study to determine that is unlikely to take be conducted.”

“My institution does require a 1-week pause on GLP-1s for those undergoing anesthesia for surgery,” she added. “That’s not evidence-based either, but probably reduces the risk of aspiration during anesthesia — but I don’t know what the actual denominator is for aspiration in those who continued vs those who took a pause from GLP-1s. Pausing does certainly (anecdotally) increase the traffic of communications between physicians and their patients about what to do in the interval.”

Anne Peters, MD, a professor of clinical medicine and a clinical scholar at the Keck School of Medicine of the University of Southern California, Los Angeles, said, “The FDA label change is a warning that really doesn’t say exactly who on GLP-1 RAs is at highest risk or what to do, and if any intervention has been shown to help. The ASA recommendations seem much more nuanced and practical, including point-of-care gastric ultrasound to see if there is retained food/fluid prior to surgery.”

“In my practice, I individualize what I say, depending on the person and the circumstance,” she said. “Mostly, I have people hold one dose before planned surgery, so they have been 10 days at least without a dose. But if worried about gastrointestinal symptoms or gastroparesis, I have them do a clear liquid diet for 24 hours presurgery. Or at least avoid heavy fat meals the day before.”

“There is a risk of aspiration with anything that slows gastric emptying — maybe even in patients with gastroparesis at baseline due to physiologic, not pharmacological, reasons — and anesthesiologists should be aware of the need to assess patients individually.”

Michael A. Weintraub, MD, of NYU Langone Health Diabetes & Endocrine Associates in New York City, observed, “The risk of a pulmonary aspiration event with GLP-1 medication is quite rare, but not zero. On the other hand, stopping the GLP-1 can cause hyperglycemia or rebound weight gain. Furthermore, it can become complicated to restart GLP1 dosing, particularly given the existing medication shortages.”

“In most cases, stopping a weekly GLP-1 medication 1 week prior to the procedure minimizes the risks of pulmonary aspiration and prevents any worsening hyperglycemia or weight gain,” he said. However, taking the drug 7 days prior to the procedure is optimal. “That way, they would be due for the next dose on the day of the procedure, and taking it the day following procedure minimizes disruption in their once-weekly regimen.”

Malini Gupta, MD, director of G2Endo Endocrinology & Metabolism, Memphis, Tennessee, advised that physicians weigh the risk of stopping the medication (which can cause a glycemic spike) vs risk for aspiration.

“In my opinion, all patients should follow a strict liquid diet or NPO status prior to a surgery to further decrease the risk of aspiration,” she said. “I generally hold the GLP-1 RA for a week before a surgery. If additional glycemic control is necessary, I will add to or adjust one of the patient’s other diabetes medications.”

Jaime Almandoz, MD, associate professor of medicine and medical director of the Weight Wellness Program in Dallas, said, “As endocrinologists, we typically rely on our anesthesia colleagues for guidance on perioperative management. In light of emerging guidelines for holding GLP-1 medications, we also recommend patients adopt a liquid diet 24 hours prior to surgery, along with the fasting protocol.”

“For those managing diabetes with GLP-1 therapies, it is crucial to establish a blood sugar management plan while off these medications, especially during fasting or postoperative periods, which can be further influenced by many factors, including nausea, pain medications, and antibiotics after the procedure.”

Joshi added that at Parkland Hospital in Dallas, “we do a huge number of cases using the same information. We identify patients who are at risk, and then we tell our proceduralists and our surgeons if they’re in the escalating phase of the dosing or if they have GI symptoms; don’t even schedule them as an elective case; wait till the escalation phase is over and then schedule them.”

“That way,” he said, “it becomes logistically easy to manage because the recommendation from the group is that patients who are at higher risk should receive a 24-hour liquid diet — the same as colonoscopy. But sometimes it can be challenging to do so.”

Joshi has received honoraria for consultation from Merck Sharp & Dohme, Vertex Pharmaceuticals, and Haisco-USA Pharmaceuticals. Gupta is on the speakers bureau for Amgen (Tepezza) and IBSA (Tirosint) and is a creative consultant for AbbVie. Almandoz serves on advisory boards for Novo Nordisk, Eli Lilly, and Boehringer Ingelheim. The other experts declared no relevant relationships.
 

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

Guidance from professional societies on how to handle the risk for pulmonary aspiration during general anesthesia or deep sedation for patients taking glucagon-like peptide 1 receptor agonists (GLP-1 RAs) continues to evolve, as does the US Food and Drug Administration’s (FDA’s) labeling for the drugs. The changes can be challenging to keep up with, and endocrinologists seem to be making their own decisions based on clinical experience and their interpretations of the potential impact and value of the emerging information.

The latest FDA label change warns about the risk for pulmonary aspiration but notes “insufficient” data to inform recommendations to mitigate the risk in vulnerable patients. Yet, the latest multi-society guidance, led by the American Society of Anesthesiologists (ASA) and based on consensus, not evidence, has nuanced advice for managing patients at risk.

Does the FDA’s label change make a difference regarding the multi-society guidance, which was published earlier? “The answer is no,” Girish Joshi, MD, vice chair, ASA Committee on Practice Parameters, told this news organization. “The concern of increased pulmonary aspiration in patients who are on GLP-1 receptor agonists has been known, and that concern still exists. So, we started with not an assumption but the premise that patients on GLP-1 receptor agonists are at a higher risk of aspiration during sedation, analgesia, and/or general anesthesia. The FDA basically confirms what we say in the guidance.”

Joshi, professor in the Anesthesiology and Pain Management Department at UT Southwestern Medical Center, Dallas, aimed to make the guidance, which was published simultaneously in several society journals, more implementable with a letter to the editor of Anesthesiology. The key, he said, is to identify patients at higher risk for aspiration; all others would follow treatment as usual.

The letter highlights three overarching recommendations and then expands upon them: Standardized preoperative assessment for risk for delayed gastric emptying (yes/no); selective preoperative care plan based on delayed gastric emptying assessment and shared decision-making; and on the day of the procedure, reassess for delayed gastric emptying and mitigate risk if there is clinical concern.

But it seems as though, for now, endocrinologists are managing these patients as they see fit, within the parameters of any institutional guidance requirements. Here is what they said about their practice:

Amy E. Rothberg, MD, DABOM, director of the Weight Management Program & Rewind at the University of Michigan, Ann Arbor, Michigan, said, “I think it makes sense to inform our patients of the labeling and rare but potential adverse effects if they intend to undergo anesthesia for a scheduled procedure/surgery. There is never no risk of aspiration during anesthesia.”

“I find it a bit curious that ASA implies that those who experience GI side effects are more likely than those who do not to have this potential risk. I doubt there is evidence that those without GI side effects are necessarily ‘safer’ and a study to determine that is unlikely to take be conducted.”

“My institution does require a 1-week pause on GLP-1s for those undergoing anesthesia for surgery,” she added. “That’s not evidence-based either, but probably reduces the risk of aspiration during anesthesia — but I don’t know what the actual denominator is for aspiration in those who continued vs those who took a pause from GLP-1s. Pausing does certainly (anecdotally) increase the traffic of communications between physicians and their patients about what to do in the interval.”

Anne Peters, MD, a professor of clinical medicine and a clinical scholar at the Keck School of Medicine of the University of Southern California, Los Angeles, said, “The FDA label change is a warning that really doesn’t say exactly who on GLP-1 RAs is at highest risk or what to do, and if any intervention has been shown to help. The ASA recommendations seem much more nuanced and practical, including point-of-care gastric ultrasound to see if there is retained food/fluid prior to surgery.”

“In my practice, I individualize what I say, depending on the person and the circumstance,” she said. “Mostly, I have people hold one dose before planned surgery, so they have been 10 days at least without a dose. But if worried about gastrointestinal symptoms or gastroparesis, I have them do a clear liquid diet for 24 hours presurgery. Or at least avoid heavy fat meals the day before.”

“There is a risk of aspiration with anything that slows gastric emptying — maybe even in patients with gastroparesis at baseline due to physiologic, not pharmacological, reasons — and anesthesiologists should be aware of the need to assess patients individually.”

Michael A. Weintraub, MD, of NYU Langone Health Diabetes & Endocrine Associates in New York City, observed, “The risk of a pulmonary aspiration event with GLP-1 medication is quite rare, but not zero. On the other hand, stopping the GLP-1 can cause hyperglycemia or rebound weight gain. Furthermore, it can become complicated to restart GLP1 dosing, particularly given the existing medication shortages.”

“In most cases, stopping a weekly GLP-1 medication 1 week prior to the procedure minimizes the risks of pulmonary aspiration and prevents any worsening hyperglycemia or weight gain,” he said. However, taking the drug 7 days prior to the procedure is optimal. “That way, they would be due for the next dose on the day of the procedure, and taking it the day following procedure minimizes disruption in their once-weekly regimen.”

Malini Gupta, MD, director of G2Endo Endocrinology & Metabolism, Memphis, Tennessee, advised that physicians weigh the risk of stopping the medication (which can cause a glycemic spike) vs risk for aspiration.

“In my opinion, all patients should follow a strict liquid diet or NPO status prior to a surgery to further decrease the risk of aspiration,” she said. “I generally hold the GLP-1 RA for a week before a surgery. If additional glycemic control is necessary, I will add to or adjust one of the patient’s other diabetes medications.”

Jaime Almandoz, MD, associate professor of medicine and medical director of the Weight Wellness Program in Dallas, said, “As endocrinologists, we typically rely on our anesthesia colleagues for guidance on perioperative management. In light of emerging guidelines for holding GLP-1 medications, we also recommend patients adopt a liquid diet 24 hours prior to surgery, along with the fasting protocol.”

“For those managing diabetes with GLP-1 therapies, it is crucial to establish a blood sugar management plan while off these medications, especially during fasting or postoperative periods, which can be further influenced by many factors, including nausea, pain medications, and antibiotics after the procedure.”

Joshi added that at Parkland Hospital in Dallas, “we do a huge number of cases using the same information. We identify patients who are at risk, and then we tell our proceduralists and our surgeons if they’re in the escalating phase of the dosing or if they have GI symptoms; don’t even schedule them as an elective case; wait till the escalation phase is over and then schedule them.”

“That way,” he said, “it becomes logistically easy to manage because the recommendation from the group is that patients who are at higher risk should receive a 24-hour liquid diet — the same as colonoscopy. But sometimes it can be challenging to do so.”

Joshi has received honoraria for consultation from Merck Sharp & Dohme, Vertex Pharmaceuticals, and Haisco-USA Pharmaceuticals. Gupta is on the speakers bureau for Amgen (Tepezza) and IBSA (Tirosint) and is a creative consultant for AbbVie. Almandoz serves on advisory boards for Novo Nordisk, Eli Lilly, and Boehringer Ingelheim. The other experts declared no relevant relationships.
 

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

The recent US Food and Drug Administration (FDA) clearance of two over-the-counter (OTC) continuous glucose monitors (CGMs) — Dexcom’s Stelo and Abbott’s Lingo — has sparked interest in potentially expanding their use to those without diabetes or prediabetes.

There are several valid questions about how the general population might benefit from CGMs. Can they motivate those struggling with overweight to shed pounds? Would they prompt users to follow more healthful eating patterns? Can they act as a canary in the coal mine, alerting users to prediabetes? 

The short answer to these questions is, we don’t know.

“Glucose levels fluctuate in everyone in response to meals, exercise, stress, etc, but there has been no credible research to support CGM use by most people who do not have diabetes,” Jill Crandall, MD, chief of endocrinology at Albert Einstein College of Medicine and Montefiore Health System in New York City, said in an interview.

“The utility of CGM for people without diabetes hasn’t been established and the drive to market CGM as an OTC device seems largely driven by financial considerations,” Crandall said. She advocates instead for a strategy directed at more meaningful objectives.

“For now, efforts should be focused on making CGMs available to patients who will clearly benefit — ie, people with diabetes, especially those who are using insulin and those who are struggling to achieve desired levels of glucose control.” 

Nicole Spartano, PhD, assistant professor of medicine in endocrinology, diabetes, nutrition and weight management at Boston University’s Chobanian & Avedisian School of Medicine in Massachusetts, agreed with this assessment.

“It is definitely too early to make recommendations for patients without diabetes based on their CGM data,” said Spartano, who also serves as the director of the Glucose Monitoring Station at the Framingham Heart Study in Framingham, Massachusetts. “We simply do not have enough follow-up data to tell us which CGM metrics are associated with higher risk for disease.” 

Spartano served as the lead author of a recent study showing time spent in various CGM ranges in a large cohort of individuals without diabetes using the Dexcom G6 Pro model. In the future, she said the data may be used to establish reference ranges for clinicians and individuals.

“We are working on another paper surveying diabetologists and CGM experts about how they interpret CGM reports from individuals without diabetes,” she said in an interview. Although the data are not yet published, Spartano said, “we are finding that clinicians are currently very discordant in how they interpret these reports.”
 

Potential Benefits Right Now

Satish Garg, MD, director of the Adult Clinic at the Barbara Davis Center for Diabetes at the University of Colorado Anschutz Medical Campus, Aurora, and editor-in-chief of Diabetes Technology & Therapeutics, is convinced that glucose should be considered another vital sign, like blood pressure, pulse rate, respiration rate, and body temperature. Therefore, he sees the use of a CGM in people without diabetes as a way to build awareness and perhaps prompt behavior modification.

“Someone with an A1c of 4.9 on a normal day may notice that they’ve gained a little bit of weight, and if they use an OTC CGM and start seeing changes, it might help them to modulate their diet themselves, whether they see a dietitian or not,” Garg said.

He gave the example of “a natural behavioral change” occurring when someone using a CGM declines to eat a post-meal dessert after seeing their blood glucose had already risen to 170.

Wearing a CGM also has the potential to alert the user to high blood glucose, leading them to an earlier diagnosis of prediabetes or diabetes, Shichun Bao, MD, PhD, Diabetes Technology Program Leader at the Vanderbilt Eskind Diabetes Clinic of Vanderbilt University in Nashville, Tennessee, said in an interview. She has had cases where a family member of someone with diabetes used the patient’s fingerstick meter, found that their glucose was 280, and self-diagnosed with diabetes.

“It’s the same thing with the CGM,” she said. “If they somehow did not know they have diabetes and they wear a CGM and it shows their sugar is high, that will help them to know to see their provider to get a diagnosis, get treated, and track progression.”

Given the shortage of endocrinologists and long waits for appointments in the United States and elsewhere, it is very likely that primary care physicians will be the ones fielding questions from individuals without diabetes interested in purchasing an OTC CGM. Internist Douglas Paauw, MD, a professor at the University of Washington School of Medicine, Seattle, said in an interview that, for his practice, “the benefits outweigh some of the limitations.”

“I don’t really think somebody who doesn’t have diabetes needs to be using a CGM all the time or long term,” he said. “But I have used it in a few people without diabetes, and I think if someone can afford to use it for 2-4 weeks, especially if they’ve been gaining weight, then they can really recognize what happens to their bodies when they eat certain foods.”

Paauw added that CGMs are a more effective means of teaching his patients than them receiving a lecture from him on healthy eating. “There’s nothing like immediate feedback on what happens to your body to change behavior.”

Similarly, William Golden, medical director at Arkansas Medicaid and professor of medicine and public health at the University of Arkansas for Medical Sciences, Little Rock, said in an interview that “it is difficult to justify coverage for CGMs on demand — but if people want to invest in their own devices and the technology motivates them to eat better and/or lose weight, then there are benefits to be had.” 
 

Potential Downsides

Although it may seem simple to use an OTC CGM to measure blood glucose on the fly, in the real world it can take patients time to understand these devices, “especially the first day or so, when users are going to get false lows,” Bao said. “Clinicians need to tell them if you don’t feel like your sugar is low and the device says it’s low, whether they do or don’t have diabetes, they should do a fingerstick glucose test to confirm the low before rushing to take in sugar. On the other hand, if they drink a lot of juice, their sugar will go high. So, it can create problems and false results either way.”

Many factors affect glucose, she said. “When you’re sick, glucose can go high, and when you’re very sick, in the ICU, sometimes it can be low. It depends on the situation.” Bao noted that certain vitamins and drugs can also interfere with readings.

Bao doesn’t see value in having people without diabetes monitor their glucose continuously. “If they want to see what foods or exercise do to their body, they will probably benefit from a short trial to gain some insight; otherwise, they’re wasting money,” she said.

Another potential downside is that there’s no head-to-head comparison data with the approved devices, Garg said. “But it’s clear to us that Stelo’s range is very narrow, 70 to 200, whereas the Lingo ranges are pretty much full, from 40 to 400 or 55 to 400. So, we don’t know the accuracy of these sensors.”

Golden observed that for certain patients, CGMs may lead to psychological distress rather than providing a sense of control over their blood glucose levels.

“I have had a nondiabetic patient or two that obsessed about their blood sugars and a device would only magnify their anxiety/neurosis,” he said. “The bottom line is that it’s a tool for a balanced approach to health management, but the daily results must be kept in perspective!”
 

Educate Patients, Primary Care Physicians

To maximize potential benefits for patients without diabetes, clinicians need to be well trained in the use and interpretation of results from the devices, Bao said. They can then better educate their patients, including discussing with them possible pitfalls surrounding their use. 

“For example, a patient may see that their blood glucose, as measured by a fingerstick, is 95, whereas the CGM says 140, and ask, ‘Which one do I trust?’ ”

This is where the patient can be educated about the difference between interstitial glucose, as measured by the CGM, and blood glucose, as measured by the fingerstick. Because it takes about 15 minutes for blood glucose to get to the interstitial tissue, there’s lag time, and the two measurements will differ.

“A discrepancy of 20% is totally acceptable for that reason,” Bao said.

She has also seen several examples where patients were misled by their CGM when its censor became dislodged.

“Sometimes when a sensor has moved, the patient may push it back in because they don’t want to throw it away. But it doesn’t work that way, and they end up with inaccurate readings.” 

At a minimum, Bao added, clinicians and patients should read the package insert but also be aware that it doesn’t list everything that might go wrong or interfere with the device’s accuracy.

Manufacturers of OTC devices should be training primary care and family practice doctors in their use, given the expected “huge” influx of patients wanting to use them, according to Garg.

“If you are expecting endos or diabetes specialists to see these people, that’s never going to happen,” he said. “We have a big shortage of these specialists, so industry has to train these doctors. Patients will bring their doctor’s data, and the clinicians need to learn the basics of how to interpret the glucose values they see. Then they can treat these patients rather than shipping all of them to endos who likely are not available.”

Paauw agreed that CGM training should be directed largely toward primary care professionals, who can help their under-resourced endocrinologist colleagues from seeing an uptick in “the worried well.” 

“The bottom line is that primary care professionals do need to understand the CGM,” he said. “They do need to get comfortable with it. They do need to come up with opinions on how to use it. The public’s going to be using it, and we need to be competent in it and use our subspecialists appropriately.”

Spartano received funding for an investigator-initiated research grant from Novo Nordisk unrelated to the cited CGM studies. Garg , Bao, Paauw, Golden, and Crandall declared no relevant conflicts of interest.

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

The recent US Food and Drug Administration (FDA) clearance of two over-the-counter (OTC) continuous glucose monitors (CGMs) — Dexcom’s Stelo and Abbott’s Lingo — has sparked interest in potentially expanding their use to those without diabetes or prediabetes.

There are several valid questions about how the general population might benefit from CGMs. Can they motivate those struggling with overweight to shed pounds? Would they prompt users to follow more healthful eating patterns? Can they act as a canary in the coal mine, alerting users to prediabetes? 

The short answer to these questions is, we don’t know.

“Glucose levels fluctuate in everyone in response to meals, exercise, stress, etc, but there has been no credible research to support CGM use by most people who do not have diabetes,” Jill Crandall, MD, chief of endocrinology at Albert Einstein College of Medicine and Montefiore Health System in New York City, said in an interview.

“The utility of CGM for people without diabetes hasn’t been established and the drive to market CGM as an OTC device seems largely driven by financial considerations,” Crandall said. She advocates instead for a strategy directed at more meaningful objectives.

“For now, efforts should be focused on making CGMs available to patients who will clearly benefit — ie, people with diabetes, especially those who are using insulin and those who are struggling to achieve desired levels of glucose control.” 

Nicole Spartano, PhD, assistant professor of medicine in endocrinology, diabetes, nutrition and weight management at Boston University’s Chobanian & Avedisian School of Medicine in Massachusetts, agreed with this assessment.

“It is definitely too early to make recommendations for patients without diabetes based on their CGM data,” said Spartano, who also serves as the director of the Glucose Monitoring Station at the Framingham Heart Study in Framingham, Massachusetts. “We simply do not have enough follow-up data to tell us which CGM metrics are associated with higher risk for disease.” 

Spartano served as the lead author of a recent study showing time spent in various CGM ranges in a large cohort of individuals without diabetes using the Dexcom G6 Pro model. In the future, she said the data may be used to establish reference ranges for clinicians and individuals.

“We are working on another paper surveying diabetologists and CGM experts about how they interpret CGM reports from individuals without diabetes,” she said in an interview. Although the data are not yet published, Spartano said, “we are finding that clinicians are currently very discordant in how they interpret these reports.”
 

Potential Benefits Right Now

Satish Garg, MD, director of the Adult Clinic at the Barbara Davis Center for Diabetes at the University of Colorado Anschutz Medical Campus, Aurora, and editor-in-chief of Diabetes Technology & Therapeutics, is convinced that glucose should be considered another vital sign, like blood pressure, pulse rate, respiration rate, and body temperature. Therefore, he sees the use of a CGM in people without diabetes as a way to build awareness and perhaps prompt behavior modification.

“Someone with an A1c of 4.9 on a normal day may notice that they’ve gained a little bit of weight, and if they use an OTC CGM and start seeing changes, it might help them to modulate their diet themselves, whether they see a dietitian or not,” Garg said.

He gave the example of “a natural behavioral change” occurring when someone using a CGM declines to eat a post-meal dessert after seeing their blood glucose had already risen to 170.

Wearing a CGM also has the potential to alert the user to high blood glucose, leading them to an earlier diagnosis of prediabetes or diabetes, Shichun Bao, MD, PhD, Diabetes Technology Program Leader at the Vanderbilt Eskind Diabetes Clinic of Vanderbilt University in Nashville, Tennessee, said in an interview. She has had cases where a family member of someone with diabetes used the patient’s fingerstick meter, found that their glucose was 280, and self-diagnosed with diabetes.

“It’s the same thing with the CGM,” she said. “If they somehow did not know they have diabetes and they wear a CGM and it shows their sugar is high, that will help them to know to see their provider to get a diagnosis, get treated, and track progression.”

Given the shortage of endocrinologists and long waits for appointments in the United States and elsewhere, it is very likely that primary care physicians will be the ones fielding questions from individuals without diabetes interested in purchasing an OTC CGM. Internist Douglas Paauw, MD, a professor at the University of Washington School of Medicine, Seattle, said in an interview that, for his practice, “the benefits outweigh some of the limitations.”

“I don’t really think somebody who doesn’t have diabetes needs to be using a CGM all the time or long term,” he said. “But I have used it in a few people without diabetes, and I think if someone can afford to use it for 2-4 weeks, especially if they’ve been gaining weight, then they can really recognize what happens to their bodies when they eat certain foods.”

Paauw added that CGMs are a more effective means of teaching his patients than them receiving a lecture from him on healthy eating. “There’s nothing like immediate feedback on what happens to your body to change behavior.”

Similarly, William Golden, medical director at Arkansas Medicaid and professor of medicine and public health at the University of Arkansas for Medical Sciences, Little Rock, said in an interview that “it is difficult to justify coverage for CGMs on demand — but if people want to invest in their own devices and the technology motivates them to eat better and/or lose weight, then there are benefits to be had.” 
 

Potential Downsides

Although it may seem simple to use an OTC CGM to measure blood glucose on the fly, in the real world it can take patients time to understand these devices, “especially the first day or so, when users are going to get false lows,” Bao said. “Clinicians need to tell them if you don’t feel like your sugar is low and the device says it’s low, whether they do or don’t have diabetes, they should do a fingerstick glucose test to confirm the low before rushing to take in sugar. On the other hand, if they drink a lot of juice, their sugar will go high. So, it can create problems and false results either way.”

Many factors affect glucose, she said. “When you’re sick, glucose can go high, and when you’re very sick, in the ICU, sometimes it can be low. It depends on the situation.” Bao noted that certain vitamins and drugs can also interfere with readings.

Bao doesn’t see value in having people without diabetes monitor their glucose continuously. “If they want to see what foods or exercise do to their body, they will probably benefit from a short trial to gain some insight; otherwise, they’re wasting money,” she said.

Another potential downside is that there’s no head-to-head comparison data with the approved devices, Garg said. “But it’s clear to us that Stelo’s range is very narrow, 70 to 200, whereas the Lingo ranges are pretty much full, from 40 to 400 or 55 to 400. So, we don’t know the accuracy of these sensors.”

Golden observed that for certain patients, CGMs may lead to psychological distress rather than providing a sense of control over their blood glucose levels.

“I have had a nondiabetic patient or two that obsessed about their blood sugars and a device would only magnify their anxiety/neurosis,” he said. “The bottom line is that it’s a tool for a balanced approach to health management, but the daily results must be kept in perspective!”
 

Educate Patients, Primary Care Physicians

To maximize potential benefits for patients without diabetes, clinicians need to be well trained in the use and interpretation of results from the devices, Bao said. They can then better educate their patients, including discussing with them possible pitfalls surrounding their use. 

“For example, a patient may see that their blood glucose, as measured by a fingerstick, is 95, whereas the CGM says 140, and ask, ‘Which one do I trust?’ ”

This is where the patient can be educated about the difference between interstitial glucose, as measured by the CGM, and blood glucose, as measured by the fingerstick. Because it takes about 15 minutes for blood glucose to get to the interstitial tissue, there’s lag time, and the two measurements will differ.

“A discrepancy of 20% is totally acceptable for that reason,” Bao said.

She has also seen several examples where patients were misled by their CGM when its censor became dislodged.

“Sometimes when a sensor has moved, the patient may push it back in because they don’t want to throw it away. But it doesn’t work that way, and they end up with inaccurate readings.” 

At a minimum, Bao added, clinicians and patients should read the package insert but also be aware that it doesn’t list everything that might go wrong or interfere with the device’s accuracy.

Manufacturers of OTC devices should be training primary care and family practice doctors in their use, given the expected “huge” influx of patients wanting to use them, according to Garg.

“If you are expecting endos or diabetes specialists to see these people, that’s never going to happen,” he said. “We have a big shortage of these specialists, so industry has to train these doctors. Patients will bring their doctor’s data, and the clinicians need to learn the basics of how to interpret the glucose values they see. Then they can treat these patients rather than shipping all of them to endos who likely are not available.”

Paauw agreed that CGM training should be directed largely toward primary care professionals, who can help their under-resourced endocrinologist colleagues from seeing an uptick in “the worried well.” 

“The bottom line is that primary care professionals do need to understand the CGM,” he said. “They do need to get comfortable with it. They do need to come up with opinions on how to use it. The public’s going to be using it, and we need to be competent in it and use our subspecialists appropriately.”

Spartano received funding for an investigator-initiated research grant from Novo Nordisk unrelated to the cited CGM studies. Garg , Bao, Paauw, Golden, and Crandall declared no relevant conflicts of interest.

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

The recent US Food and Drug Administration (FDA) clearance of two over-the-counter (OTC) continuous glucose monitors (CGMs) — Dexcom’s Stelo and Abbott’s Lingo — has sparked interest in potentially expanding their use to those without diabetes or prediabetes.

There are several valid questions about how the general population might benefit from CGMs. Can they motivate those struggling with overweight to shed pounds? Would they prompt users to follow more healthful eating patterns? Can they act as a canary in the coal mine, alerting users to prediabetes? 

The short answer to these questions is, we don’t know.

“Glucose levels fluctuate in everyone in response to meals, exercise, stress, etc, but there has been no credible research to support CGM use by most people who do not have diabetes,” Jill Crandall, MD, chief of endocrinology at Albert Einstein College of Medicine and Montefiore Health System in New York City, said in an interview.

“The utility of CGM for people without diabetes hasn’t been established and the drive to market CGM as an OTC device seems largely driven by financial considerations,” Crandall said. She advocates instead for a strategy directed at more meaningful objectives.

“For now, efforts should be focused on making CGMs available to patients who will clearly benefit — ie, people with diabetes, especially those who are using insulin and those who are struggling to achieve desired levels of glucose control.” 

Nicole Spartano, PhD, assistant professor of medicine in endocrinology, diabetes, nutrition and weight management at Boston University’s Chobanian & Avedisian School of Medicine in Massachusetts, agreed with this assessment.

“It is definitely too early to make recommendations for patients without diabetes based on their CGM data,” said Spartano, who also serves as the director of the Glucose Monitoring Station at the Framingham Heart Study in Framingham, Massachusetts. “We simply do not have enough follow-up data to tell us which CGM metrics are associated with higher risk for disease.” 

Spartano served as the lead author of a recent study showing time spent in various CGM ranges in a large cohort of individuals without diabetes using the Dexcom G6 Pro model. In the future, she said the data may be used to establish reference ranges for clinicians and individuals.

“We are working on another paper surveying diabetologists and CGM experts about how they interpret CGM reports from individuals without diabetes,” she said in an interview. Although the data are not yet published, Spartano said, “we are finding that clinicians are currently very discordant in how they interpret these reports.”
 

Potential Benefits Right Now

Satish Garg, MD, director of the Adult Clinic at the Barbara Davis Center for Diabetes at the University of Colorado Anschutz Medical Campus, Aurora, and editor-in-chief of Diabetes Technology & Therapeutics, is convinced that glucose should be considered another vital sign, like blood pressure, pulse rate, respiration rate, and body temperature. Therefore, he sees the use of a CGM in people without diabetes as a way to build awareness and perhaps prompt behavior modification.

“Someone with an A1c of 4.9 on a normal day may notice that they’ve gained a little bit of weight, and if they use an OTC CGM and start seeing changes, it might help them to modulate their diet themselves, whether they see a dietitian or not,” Garg said.

He gave the example of “a natural behavioral change” occurring when someone using a CGM declines to eat a post-meal dessert after seeing their blood glucose had already risen to 170.

Wearing a CGM also has the potential to alert the user to high blood glucose, leading them to an earlier diagnosis of prediabetes or diabetes, Shichun Bao, MD, PhD, Diabetes Technology Program Leader at the Vanderbilt Eskind Diabetes Clinic of Vanderbilt University in Nashville, Tennessee, said in an interview. She has had cases where a family member of someone with diabetes used the patient’s fingerstick meter, found that their glucose was 280, and self-diagnosed with diabetes.

“It’s the same thing with the CGM,” she said. “If they somehow did not know they have diabetes and they wear a CGM and it shows their sugar is high, that will help them to know to see their provider to get a diagnosis, get treated, and track progression.”

Given the shortage of endocrinologists and long waits for appointments in the United States and elsewhere, it is very likely that primary care physicians will be the ones fielding questions from individuals without diabetes interested in purchasing an OTC CGM. Internist Douglas Paauw, MD, a professor at the University of Washington School of Medicine, Seattle, said in an interview that, for his practice, “the benefits outweigh some of the limitations.”

“I don’t really think somebody who doesn’t have diabetes needs to be using a CGM all the time or long term,” he said. “But I have used it in a few people without diabetes, and I think if someone can afford to use it for 2-4 weeks, especially if they’ve been gaining weight, then they can really recognize what happens to their bodies when they eat certain foods.”

Paauw added that CGMs are a more effective means of teaching his patients than them receiving a lecture from him on healthy eating. “There’s nothing like immediate feedback on what happens to your body to change behavior.”

Similarly, William Golden, medical director at Arkansas Medicaid and professor of medicine and public health at the University of Arkansas for Medical Sciences, Little Rock, said in an interview that “it is difficult to justify coverage for CGMs on demand — but if people want to invest in their own devices and the technology motivates them to eat better and/or lose weight, then there are benefits to be had.” 
 

Potential Downsides

Although it may seem simple to use an OTC CGM to measure blood glucose on the fly, in the real world it can take patients time to understand these devices, “especially the first day or so, when users are going to get false lows,” Bao said. “Clinicians need to tell them if you don’t feel like your sugar is low and the device says it’s low, whether they do or don’t have diabetes, they should do a fingerstick glucose test to confirm the low before rushing to take in sugar. On the other hand, if they drink a lot of juice, their sugar will go high. So, it can create problems and false results either way.”

Many factors affect glucose, she said. “When you’re sick, glucose can go high, and when you’re very sick, in the ICU, sometimes it can be low. It depends on the situation.” Bao noted that certain vitamins and drugs can also interfere with readings.

Bao doesn’t see value in having people without diabetes monitor their glucose continuously. “If they want to see what foods or exercise do to their body, they will probably benefit from a short trial to gain some insight; otherwise, they’re wasting money,” she said.

Another potential downside is that there’s no head-to-head comparison data with the approved devices, Garg said. “But it’s clear to us that Stelo’s range is very narrow, 70 to 200, whereas the Lingo ranges are pretty much full, from 40 to 400 or 55 to 400. So, we don’t know the accuracy of these sensors.”

Golden observed that for certain patients, CGMs may lead to psychological distress rather than providing a sense of control over their blood glucose levels.

“I have had a nondiabetic patient or two that obsessed about their blood sugars and a device would only magnify their anxiety/neurosis,” he said. “The bottom line is that it’s a tool for a balanced approach to health management, but the daily results must be kept in perspective!”
 

Educate Patients, Primary Care Physicians

To maximize potential benefits for patients without diabetes, clinicians need to be well trained in the use and interpretation of results from the devices, Bao said. They can then better educate their patients, including discussing with them possible pitfalls surrounding their use. 

“For example, a patient may see that their blood glucose, as measured by a fingerstick, is 95, whereas the CGM says 140, and ask, ‘Which one do I trust?’ ”

This is where the patient can be educated about the difference between interstitial glucose, as measured by the CGM, and blood glucose, as measured by the fingerstick. Because it takes about 15 minutes for blood glucose to get to the interstitial tissue, there’s lag time, and the two measurements will differ.

“A discrepancy of 20% is totally acceptable for that reason,” Bao said.

She has also seen several examples where patients were misled by their CGM when its censor became dislodged.

“Sometimes when a sensor has moved, the patient may push it back in because they don’t want to throw it away. But it doesn’t work that way, and they end up with inaccurate readings.” 

At a minimum, Bao added, clinicians and patients should read the package insert but also be aware that it doesn’t list everything that might go wrong or interfere with the device’s accuracy.

Manufacturers of OTC devices should be training primary care and family practice doctors in their use, given the expected “huge” influx of patients wanting to use them, according to Garg.

“If you are expecting endos or diabetes specialists to see these people, that’s never going to happen,” he said. “We have a big shortage of these specialists, so industry has to train these doctors. Patients will bring their doctor’s data, and the clinicians need to learn the basics of how to interpret the glucose values they see. Then they can treat these patients rather than shipping all of them to endos who likely are not available.”

Paauw agreed that CGM training should be directed largely toward primary care professionals, who can help their under-resourced endocrinologist colleagues from seeing an uptick in “the worried well.” 

“The bottom line is that primary care professionals do need to understand the CGM,” he said. “They do need to get comfortable with it. They do need to come up with opinions on how to use it. The public’s going to be using it, and we need to be competent in it and use our subspecialists appropriately.”

Spartano received funding for an investigator-initiated research grant from Novo Nordisk unrelated to the cited CGM studies. Garg , Bao, Paauw, Golden, and Crandall declared no relevant conflicts of interest.

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

A patient has cancer. It’s decision time.

Clinician and patient alike face, really, the ultimate challenge when making those decisions. They have to consider the patient’s individual circumstances, available treatment options, potential side effects, relevant clinical data such as the patient’s genetic profile and cancer specifics, and more.

“That’s a lot of information to hold,” said Uzma Asghar, PhD, MRCP, a British consultant medical oncologist at The Royal Marsden Hospital and a chief scientific officer at Concr LTD.

What if there were a way to test — quickly and accurately — all the potential paths forward?

That’s the goal of digital twins. An artificial intelligence (AI)–based program uses all the known data on patients and their types of illness and creates a “twin” that can be used over and over to simulate disease progression, test treatments, and predict individual responses to therapies.

“What the [digital twin] model can do for the clinician is to hold all that information and process it really quickly, within a couple of minutes,” Asghar noted.

A digital twin is more than just a computer model or simulation because it copies a real-world person and relies on real-world data. Some digital twin programs also integrate new information as it becomes available. This technology holds promise for personalized medicine, drug discovery, developing screening strategies, and better understanding diseases.
 

How to Deliver a Twin

To create a digital twin, experts develop a computer model with data to hone its expertise in an area of medicine, such as cancer types and treatments. Then “you train the model on information it’s seen, and then introduce a patient and patient’s information,” said Asghar.

Asghar is currently working with colleagues to develop digital twins that could eventually help solve the aforementioned cancer scenario — a doctor and patient decide the best course of cancer treatment. But their applications are manifold, particularly in clinical research.

Digital twins often include a machine learning component, which would fall under the umbrella term of AI, said Asghar, but it’s not like ChatGPT or other generative AI modules many people are now familiar with.

“The difference here is the model is not there to replace the clinician or to replace clinical trials,” Asghar noted. Instead, digital twins help make decisions faster in a way that can be more affordable.
 

Digital Twins to Predict Cancer Outcomes

Asghar is currently involved in UK clinical trials enrolling patients with cancer to test the accuracy of digital twin programs.

At this point, these studies do not yet use digital twins to guide the course of treatment, which is something they hope to do eventually. For now, they are still at the validation phase — the digital twin program makes predictions about the treatments and then the researchers later evaluate how accurate the predictions turned out to be based on real information from the enrolled patients.

Their current model gives predictions for RECIST (response evaluation criteria in solid tumor), treatment response, and survival. In addition to collecting data from ongoing clinical trials, they’ve used retrospective data, such as from the Cancer Tumor Atlas, to test the model.

“We’ve clinically validated it now in over 9000 patients,” said Asghar, who noted that they are constantly testing it on new patients. Their data include 30 chemotherapies and 23 cancer types, but they are focusing on four: Triple-negative breast cancer, cancer of unknown primary, pancreatic cancer, and colorectal cancer.

“The reason for choosing those four cancer types is that they are aggressive, their response to chemotherapy isn’t as great, and the outcome for those patient populations, there’s significant room for improvement,” Asghar explained.

Currently, Asghar said, the model is around 80%-90% correct in predicting what the actual clinical outcomes turn out to be.

The final stage of their work, before it becomes widely available to clinicians, will be to integrate it into a clinical trial in which some clinicians use the model to make decisions about treatment vs some who don’t use the model. By studying patient outcomes in both groups, they will be able to determine the value of the digital twin program they created.
 

What Else Can a Twin Do? A Lot

While a model that helps clinicians make decisions about cancer treatments may be among the first digital twin programs that become widely available, there are many other kinds of digital twins in the works.

For example, a digital twin could be used as a benchmark for a patient to determine how their cancer might have progressed without treatment. Say a patient’s tumor grew during treatment, it might seem like the treatment failed, but a digital twin might show that if left untreated, the tumor would have grown five times as fast, said Paul Macklin, PhD, professor in the Department of Intelligent Systems Engineering at Indiana University Bloomington.

Alternatively, if the virtual patient’s tumor is around the same size as the real patient’s tumor, “that means that treatment has lost its efficacy. It’s time to do something new,” said Macklin. And a digital twin could help with not only choosing a therapy but also choosing a dosing schedule, he noted.

The models can also be updated as new treatments come out, which could help clinicians virtually explore how they might affect a patient before having that patient switch treatments.

Digital twins could also assist in decision-making based on a patient’s priorities and real-life circumstances. “Maybe your priority is not necessarily to shrink this [tumor] at all costs ... maybe your priority is some mix of that and also quality of life,” Macklin said, referring to potential side effects. Or if someone lives 3 hours from the nearest cancer center, a digital twin could help determine whether less frequent treatments could still be effective.

And while much of the activity around digital twins in biomedical research has been focused on cancer, Asghar said the technology has the potential to be applied to other diseases as well. A digital twin for cardiovascular disease could help doctors choose the best treatment. It could also integrate new information from a smartwatch or glucose monitor to make better predictions and help doctors adjust the treatment plan.
 

Faster, More Effective Research With Twins

Because digital twin programs can quickly analyze large datasets, they can also make real-world studies more effective and efficient.

Though digital twins would not fully replace real clinical trials, they could help run through preliminary scenarios before starting a full clinical trial, which would “save everybody some money, time and pain and risk,” said Macklin.

It’s also possible to use digital twins to design better screening strategies for early cancer detection and monitoring, said Ioannis Zervantonakis, PhD, a bioengineering professor at the University of Pittsburgh.

Zervantonakis is tapping digital twin technology for research that homes in on understanding tumors. In this case, the digital twin is a virtual representation of a real tumor, complete with its complex network of cells and the surrounding tissue.

Zervantonakis’ lab is using the technology to study cell-cell interactions in the tumor microenvironment, with a focus on human epidermal growth factor receptor 2–targeted therapy resistance in breast cancer. The digital twin they developed will simulate tumor growth, predict drug response, analyze cellular interactions, and optimize treatment strategies.
 

The Long Push Forward

One big hurdle to making digital twins more widely available is that regulation for the technology is still in progress.

“We’re developing the technology, and what’s also happening is the regulatory framework is being developed in parallel. So we’re almost developing things blindly on the basis that we think this is what the regulators would want,” explained Asghar.

“It’s really important that these technologies are regulated properly, just like drugs, and that’s what we’re pushing and advocating for,” said Asghar, noting that people need to know that like drugs, a digital twin has strengths and limitations.

And while a digital twin can be a cost-saving approach in the long run, it does require funding to get a program built, and finding funds can be difficult because not everyone knows about the technology. More funding means more trials.

With more data, Asghar is hopeful that within a few years, a digital twin model could be available for clinicians to use to help inform treatment decisions. This could lead to more effective treatments and, ultimately, better patient outcomes.
 

A version of this article appeared on Medscape.com.

A patient has cancer. It’s decision time.

Clinician and patient alike face, really, the ultimate challenge when making those decisions. They have to consider the patient’s individual circumstances, available treatment options, potential side effects, relevant clinical data such as the patient’s genetic profile and cancer specifics, and more.

“That’s a lot of information to hold,” said Uzma Asghar, PhD, MRCP, a British consultant medical oncologist at The Royal Marsden Hospital and a chief scientific officer at Concr LTD.

What if there were a way to test — quickly and accurately — all the potential paths forward?

That’s the goal of digital twins. An artificial intelligence (AI)–based program uses all the known data on patients and their types of illness and creates a “twin” that can be used over and over to simulate disease progression, test treatments, and predict individual responses to therapies.

“What the [digital twin] model can do for the clinician is to hold all that information and process it really quickly, within a couple of minutes,” Asghar noted.

A digital twin is more than just a computer model or simulation because it copies a real-world person and relies on real-world data. Some digital twin programs also integrate new information as it becomes available. This technology holds promise for personalized medicine, drug discovery, developing screening strategies, and better understanding diseases.
 

How to Deliver a Twin

To create a digital twin, experts develop a computer model with data to hone its expertise in an area of medicine, such as cancer types and treatments. Then “you train the model on information it’s seen, and then introduce a patient and patient’s information,” said Asghar.

Asghar is currently working with colleagues to develop digital twins that could eventually help solve the aforementioned cancer scenario — a doctor and patient decide the best course of cancer treatment. But their applications are manifold, particularly in clinical research.

Digital twins often include a machine learning component, which would fall under the umbrella term of AI, said Asghar, but it’s not like ChatGPT or other generative AI modules many people are now familiar with.

“The difference here is the model is not there to replace the clinician or to replace clinical trials,” Asghar noted. Instead, digital twins help make decisions faster in a way that can be more affordable.
 

Digital Twins to Predict Cancer Outcomes

Asghar is currently involved in UK clinical trials enrolling patients with cancer to test the accuracy of digital twin programs.

At this point, these studies do not yet use digital twins to guide the course of treatment, which is something they hope to do eventually. For now, they are still at the validation phase — the digital twin program makes predictions about the treatments and then the researchers later evaluate how accurate the predictions turned out to be based on real information from the enrolled patients.

Their current model gives predictions for RECIST (response evaluation criteria in solid tumor), treatment response, and survival. In addition to collecting data from ongoing clinical trials, they’ve used retrospective data, such as from the Cancer Tumor Atlas, to test the model.

“We’ve clinically validated it now in over 9000 patients,” said Asghar, who noted that they are constantly testing it on new patients. Their data include 30 chemotherapies and 23 cancer types, but they are focusing on four: Triple-negative breast cancer, cancer of unknown primary, pancreatic cancer, and colorectal cancer.

“The reason for choosing those four cancer types is that they are aggressive, their response to chemotherapy isn’t as great, and the outcome for those patient populations, there’s significant room for improvement,” Asghar explained.

Currently, Asghar said, the model is around 80%-90% correct in predicting what the actual clinical outcomes turn out to be.

The final stage of their work, before it becomes widely available to clinicians, will be to integrate it into a clinical trial in which some clinicians use the model to make decisions about treatment vs some who don’t use the model. By studying patient outcomes in both groups, they will be able to determine the value of the digital twin program they created.
 

What Else Can a Twin Do? A Lot

While a model that helps clinicians make decisions about cancer treatments may be among the first digital twin programs that become widely available, there are many other kinds of digital twins in the works.

For example, a digital twin could be used as a benchmark for a patient to determine how their cancer might have progressed without treatment. Say a patient’s tumor grew during treatment, it might seem like the treatment failed, but a digital twin might show that if left untreated, the tumor would have grown five times as fast, said Paul Macklin, PhD, professor in the Department of Intelligent Systems Engineering at Indiana University Bloomington.

Alternatively, if the virtual patient’s tumor is around the same size as the real patient’s tumor, “that means that treatment has lost its efficacy. It’s time to do something new,” said Macklin. And a digital twin could help with not only choosing a therapy but also choosing a dosing schedule, he noted.

The models can also be updated as new treatments come out, which could help clinicians virtually explore how they might affect a patient before having that patient switch treatments.

Digital twins could also assist in decision-making based on a patient’s priorities and real-life circumstances. “Maybe your priority is not necessarily to shrink this [tumor] at all costs ... maybe your priority is some mix of that and also quality of life,” Macklin said, referring to potential side effects. Or if someone lives 3 hours from the nearest cancer center, a digital twin could help determine whether less frequent treatments could still be effective.

And while much of the activity around digital twins in biomedical research has been focused on cancer, Asghar said the technology has the potential to be applied to other diseases as well. A digital twin for cardiovascular disease could help doctors choose the best treatment. It could also integrate new information from a smartwatch or glucose monitor to make better predictions and help doctors adjust the treatment plan.
 

Faster, More Effective Research With Twins

Because digital twin programs can quickly analyze large datasets, they can also make real-world studies more effective and efficient.

Though digital twins would not fully replace real clinical trials, they could help run through preliminary scenarios before starting a full clinical trial, which would “save everybody some money, time and pain and risk,” said Macklin.

It’s also possible to use digital twins to design better screening strategies for early cancer detection and monitoring, said Ioannis Zervantonakis, PhD, a bioengineering professor at the University of Pittsburgh.

Zervantonakis is tapping digital twin technology for research that homes in on understanding tumors. In this case, the digital twin is a virtual representation of a real tumor, complete with its complex network of cells and the surrounding tissue.

Zervantonakis’ lab is using the technology to study cell-cell interactions in the tumor microenvironment, with a focus on human epidermal growth factor receptor 2–targeted therapy resistance in breast cancer. The digital twin they developed will simulate tumor growth, predict drug response, analyze cellular interactions, and optimize treatment strategies.
 

The Long Push Forward

One big hurdle to making digital twins more widely available is that regulation for the technology is still in progress.

“We’re developing the technology, and what’s also happening is the regulatory framework is being developed in parallel. So we’re almost developing things blindly on the basis that we think this is what the regulators would want,” explained Asghar.

“It’s really important that these technologies are regulated properly, just like drugs, and that’s what we’re pushing and advocating for,” said Asghar, noting that people need to know that like drugs, a digital twin has strengths and limitations.

And while a digital twin can be a cost-saving approach in the long run, it does require funding to get a program built, and finding funds can be difficult because not everyone knows about the technology. More funding means more trials.

With more data, Asghar is hopeful that within a few years, a digital twin model could be available for clinicians to use to help inform treatment decisions. This could lead to more effective treatments and, ultimately, better patient outcomes.
 

A version of this article appeared on Medscape.com.

A patient has cancer. It’s decision time.

Clinician and patient alike face, really, the ultimate challenge when making those decisions. They have to consider the patient’s individual circumstances, available treatment options, potential side effects, relevant clinical data such as the patient’s genetic profile and cancer specifics, and more.

“That’s a lot of information to hold,” said Uzma Asghar, PhD, MRCP, a British consultant medical oncologist at The Royal Marsden Hospital and a chief scientific officer at Concr LTD.

What if there were a way to test — quickly and accurately — all the potential paths forward?

That’s the goal of digital twins. An artificial intelligence (AI)–based program uses all the known data on patients and their types of illness and creates a “twin” that can be used over and over to simulate disease progression, test treatments, and predict individual responses to therapies.

“What the [digital twin] model can do for the clinician is to hold all that information and process it really quickly, within a couple of minutes,” Asghar noted.

A digital twin is more than just a computer model or simulation because it copies a real-world person and relies on real-world data. Some digital twin programs also integrate new information as it becomes available. This technology holds promise for personalized medicine, drug discovery, developing screening strategies, and better understanding diseases.
 

How to Deliver a Twin

To create a digital twin, experts develop a computer model with data to hone its expertise in an area of medicine, such as cancer types and treatments. Then “you train the model on information it’s seen, and then introduce a patient and patient’s information,” said Asghar.

Asghar is currently working with colleagues to develop digital twins that could eventually help solve the aforementioned cancer scenario — a doctor and patient decide the best course of cancer treatment. But their applications are manifold, particularly in clinical research.

Digital twins often include a machine learning component, which would fall under the umbrella term of AI, said Asghar, but it’s not like ChatGPT or other generative AI modules many people are now familiar with.

“The difference here is the model is not there to replace the clinician or to replace clinical trials,” Asghar noted. Instead, digital twins help make decisions faster in a way that can be more affordable.
 

Digital Twins to Predict Cancer Outcomes

Asghar is currently involved in UK clinical trials enrolling patients with cancer to test the accuracy of digital twin programs.

At this point, these studies do not yet use digital twins to guide the course of treatment, which is something they hope to do eventually. For now, they are still at the validation phase — the digital twin program makes predictions about the treatments and then the researchers later evaluate how accurate the predictions turned out to be based on real information from the enrolled patients.

Their current model gives predictions for RECIST (response evaluation criteria in solid tumor), treatment response, and survival. In addition to collecting data from ongoing clinical trials, they’ve used retrospective data, such as from the Cancer Tumor Atlas, to test the model.

“We’ve clinically validated it now in over 9000 patients,” said Asghar, who noted that they are constantly testing it on new patients. Their data include 30 chemotherapies and 23 cancer types, but they are focusing on four: Triple-negative breast cancer, cancer of unknown primary, pancreatic cancer, and colorectal cancer.

“The reason for choosing those four cancer types is that they are aggressive, their response to chemotherapy isn’t as great, and the outcome for those patient populations, there’s significant room for improvement,” Asghar explained.

Currently, Asghar said, the model is around 80%-90% correct in predicting what the actual clinical outcomes turn out to be.

The final stage of their work, before it becomes widely available to clinicians, will be to integrate it into a clinical trial in which some clinicians use the model to make decisions about treatment vs some who don’t use the model. By studying patient outcomes in both groups, they will be able to determine the value of the digital twin program they created.
 

What Else Can a Twin Do? A Lot

While a model that helps clinicians make decisions about cancer treatments may be among the first digital twin programs that become widely available, there are many other kinds of digital twins in the works.

For example, a digital twin could be used as a benchmark for a patient to determine how their cancer might have progressed without treatment. Say a patient’s tumor grew during treatment, it might seem like the treatment failed, but a digital twin might show that if left untreated, the tumor would have grown five times as fast, said Paul Macklin, PhD, professor in the Department of Intelligent Systems Engineering at Indiana University Bloomington.

Alternatively, if the virtual patient’s tumor is around the same size as the real patient’s tumor, “that means that treatment has lost its efficacy. It’s time to do something new,” said Macklin. And a digital twin could help with not only choosing a therapy but also choosing a dosing schedule, he noted.

The models can also be updated as new treatments come out, which could help clinicians virtually explore how they might affect a patient before having that patient switch treatments.

Digital twins could also assist in decision-making based on a patient’s priorities and real-life circumstances. “Maybe your priority is not necessarily to shrink this [tumor] at all costs ... maybe your priority is some mix of that and also quality of life,” Macklin said, referring to potential side effects. Or if someone lives 3 hours from the nearest cancer center, a digital twin could help determine whether less frequent treatments could still be effective.

And while much of the activity around digital twins in biomedical research has been focused on cancer, Asghar said the technology has the potential to be applied to other diseases as well. A digital twin for cardiovascular disease could help doctors choose the best treatment. It could also integrate new information from a smartwatch or glucose monitor to make better predictions and help doctors adjust the treatment plan.
 

Faster, More Effective Research With Twins

Because digital twin programs can quickly analyze large datasets, they can also make real-world studies more effective and efficient.

Though digital twins would not fully replace real clinical trials, they could help run through preliminary scenarios before starting a full clinical trial, which would “save everybody some money, time and pain and risk,” said Macklin.

It’s also possible to use digital twins to design better screening strategies for early cancer detection and monitoring, said Ioannis Zervantonakis, PhD, a bioengineering professor at the University of Pittsburgh.

Zervantonakis is tapping digital twin technology for research that homes in on understanding tumors. In this case, the digital twin is a virtual representation of a real tumor, complete with its complex network of cells and the surrounding tissue.

Zervantonakis’ lab is using the technology to study cell-cell interactions in the tumor microenvironment, with a focus on human epidermal growth factor receptor 2–targeted therapy resistance in breast cancer. The digital twin they developed will simulate tumor growth, predict drug response, analyze cellular interactions, and optimize treatment strategies.
 

The Long Push Forward

One big hurdle to making digital twins more widely available is that regulation for the technology is still in progress.

“We’re developing the technology, and what’s also happening is the regulatory framework is being developed in parallel. So we’re almost developing things blindly on the basis that we think this is what the regulators would want,” explained Asghar.

“It’s really important that these technologies are regulated properly, just like drugs, and that’s what we’re pushing and advocating for,” said Asghar, noting that people need to know that like drugs, a digital twin has strengths and limitations.

And while a digital twin can be a cost-saving approach in the long run, it does require funding to get a program built, and finding funds can be difficult because not everyone knows about the technology. More funding means more trials.

With more data, Asghar is hopeful that within a few years, a digital twin model could be available for clinicians to use to help inform treatment decisions. This could lead to more effective treatments and, ultimately, better patient outcomes.
 

A version of this article appeared on Medscape.com.

Globally, nearly one in three cases of oral cancer can be attributed to use of smokeless tobacco and areca nut products, according to a new study from the International Agency for Research on Cancer (IARC), a part of the World Health Organization (WHO).

“Smokeless tobacco and areca nut products are available to consumers in many different forms across the world, but consuming smokeless tobacco and areca nut is linked to multiple diseases, including oral cancer,” Harriet Rumgay, PhD, a scientist in the Cancer Surveillance Branch at IARC and first author of the study in Lancet Oncology, said in a news release.

Worldwide, about 300 million people use smokeless tobacco and 600 million people use areca (also called betel) nut, one of the most popular psychoactive substances in the world after nicotine, alcohol, and caffeine. Smokeless tobacco products are consumed without burning and can be chewed, sucked, inhaled, applied locally, or ingested. Areca nut is the seed of the areca palm and can be consumed in various forms.

“Our estimates highlight the burden these products pose on health care and the importance of prevention strategies to reduce consumption of smokeless tobacco and areca nut,” Rumgay said.

According to the new report, in 2022, an estimated 120,200 of the 389,800 (30.8%) global cases of oral cancer were attributable to these products.

More than three quarters (77%) of attributable cases were among men and about one quarter (23%) among women.

The vast majority (96%) of all oral cancer cases caused by smokeless tobacco and areca nut use occurred in low- and middle-income countries.

Regions with the highest burden of oral cancers from these products were Southcentral Asia — with 105,500 of 120,200 cases (nearly 88%), including 83,400 in India, 9700 in Bangladesh, 8900 in Pakistan, and 1300 in Sri Lanka — followed by Southeastern Asia with a total of 3900 cases (1600 in Myanmar, 990 in Indonesia, and 785 in Thailand) and East Asia with 3300 cases (3200 in China).
 

Limitations and Action Points

The authors noted a limitation of the analysis is not accounting for the potential synergistic effects of combined use of smokeless tobacco or areca nut products with other risk factors for oral cancer, such as smoking tobacco or drinking alcohol.

The researchers explained that combined consumption of smokeless tobacco or areca nut, smoked tobacco, and alcohol has a “multiplicative effect” on oral cancer risk, with reported odds ratios increasing from 2.7 for smokeless tobacco only, 7.0 for smoked tobacco only, and 1.6 for alcohol only to 16.2 for all three exposures (vs no use).

However, the proportion of people who chewed tobacco and also smoked in countries with high smokeless tobacco or areca nut use was small. In India, for example, 6% of men and 0.5% of women in 2016-2017 were dual users of both smoked and smokeless tobacco, compared with 23% of men and 12% of women who only used smokeless tobacco.

Overall, curbing or preventing smokeless tobacco and areca nut use could help avoid many instances of oral cancer.

Despite “encouraging trends” in control of tobacco smoking in many regions of the world over the past two decades, progress in reducing the prevalence of smokeless tobacco consumption has stalled in many countries that are major consumers, the authors said.

Compounding the problem, areca nut does not fall within the WHO framework of tobacco control and there are very few areca nut control policies worldwide.

Smokeless tobacco control must be “prioritized” and a framework on areca nut control should be developed with guidelines to incorporate areca nut prevention into cancer control programs, the authors concluded.

Funding for the study was provided by the French National Cancer Institute. The authors had no relevant disclosures.

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

Globally, nearly one in three cases of oral cancer can be attributed to use of smokeless tobacco and areca nut products, according to a new study from the International Agency for Research on Cancer (IARC), a part of the World Health Organization (WHO).

“Smokeless tobacco and areca nut products are available to consumers in many different forms across the world, but consuming smokeless tobacco and areca nut is linked to multiple diseases, including oral cancer,” Harriet Rumgay, PhD, a scientist in the Cancer Surveillance Branch at IARC and first author of the study in Lancet Oncology, said in a news release.

Worldwide, about 300 million people use smokeless tobacco and 600 million people use areca (also called betel) nut, one of the most popular psychoactive substances in the world after nicotine, alcohol, and caffeine. Smokeless tobacco products are consumed without burning and can be chewed, sucked, inhaled, applied locally, or ingested. Areca nut is the seed of the areca palm and can be consumed in various forms.

“Our estimates highlight the burden these products pose on health care and the importance of prevention strategies to reduce consumption of smokeless tobacco and areca nut,” Rumgay said.

According to the new report, in 2022, an estimated 120,200 of the 389,800 (30.8%) global cases of oral cancer were attributable to these products.

More than three quarters (77%) of attributable cases were among men and about one quarter (23%) among women.

The vast majority (96%) of all oral cancer cases caused by smokeless tobacco and areca nut use occurred in low- and middle-income countries.

Regions with the highest burden of oral cancers from these products were Southcentral Asia — with 105,500 of 120,200 cases (nearly 88%), including 83,400 in India, 9700 in Bangladesh, 8900 in Pakistan, and 1300 in Sri Lanka — followed by Southeastern Asia with a total of 3900 cases (1600 in Myanmar, 990 in Indonesia, and 785 in Thailand) and East Asia with 3300 cases (3200 in China).
 

Limitations and Action Points

The authors noted a limitation of the analysis is not accounting for the potential synergistic effects of combined use of smokeless tobacco or areca nut products with other risk factors for oral cancer, such as smoking tobacco or drinking alcohol.

The researchers explained that combined consumption of smokeless tobacco or areca nut, smoked tobacco, and alcohol has a “multiplicative effect” on oral cancer risk, with reported odds ratios increasing from 2.7 for smokeless tobacco only, 7.0 for smoked tobacco only, and 1.6 for alcohol only to 16.2 for all three exposures (vs no use).

However, the proportion of people who chewed tobacco and also smoked in countries with high smokeless tobacco or areca nut use was small. In India, for example, 6% of men and 0.5% of women in 2016-2017 were dual users of both smoked and smokeless tobacco, compared with 23% of men and 12% of women who only used smokeless tobacco.

Overall, curbing or preventing smokeless tobacco and areca nut use could help avoid many instances of oral cancer.

Despite “encouraging trends” in control of tobacco smoking in many regions of the world over the past two decades, progress in reducing the prevalence of smokeless tobacco consumption has stalled in many countries that are major consumers, the authors said.

Compounding the problem, areca nut does not fall within the WHO framework of tobacco control and there are very few areca nut control policies worldwide.

Smokeless tobacco control must be “prioritized” and a framework on areca nut control should be developed with guidelines to incorporate areca nut prevention into cancer control programs, the authors concluded.

Funding for the study was provided by the French National Cancer Institute. The authors had no relevant disclosures.

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

Globally, nearly one in three cases of oral cancer can be attributed to use of smokeless tobacco and areca nut products, according to a new study from the International Agency for Research on Cancer (IARC), a part of the World Health Organization (WHO).

“Smokeless tobacco and areca nut products are available to consumers in many different forms across the world, but consuming smokeless tobacco and areca nut is linked to multiple diseases, including oral cancer,” Harriet Rumgay, PhD, a scientist in the Cancer Surveillance Branch at IARC and first author of the study in Lancet Oncology, said in a news release.

Worldwide, about 300 million people use smokeless tobacco and 600 million people use areca (also called betel) nut, one of the most popular psychoactive substances in the world after nicotine, alcohol, and caffeine. Smokeless tobacco products are consumed without burning and can be chewed, sucked, inhaled, applied locally, or ingested. Areca nut is the seed of the areca palm and can be consumed in various forms.

“Our estimates highlight the burden these products pose on health care and the importance of prevention strategies to reduce consumption of smokeless tobacco and areca nut,” Rumgay said.

According to the new report, in 2022, an estimated 120,200 of the 389,800 (30.8%) global cases of oral cancer were attributable to these products.

More than three quarters (77%) of attributable cases were among men and about one quarter (23%) among women.

The vast majority (96%) of all oral cancer cases caused by smokeless tobacco and areca nut use occurred in low- and middle-income countries.

Regions with the highest burden of oral cancers from these products were Southcentral Asia — with 105,500 of 120,200 cases (nearly 88%), including 83,400 in India, 9700 in Bangladesh, 8900 in Pakistan, and 1300 in Sri Lanka — followed by Southeastern Asia with a total of 3900 cases (1600 in Myanmar, 990 in Indonesia, and 785 in Thailand) and East Asia with 3300 cases (3200 in China).
 

Limitations and Action Points

The authors noted a limitation of the analysis is not accounting for the potential synergistic effects of combined use of smokeless tobacco or areca nut products with other risk factors for oral cancer, such as smoking tobacco or drinking alcohol.

The researchers explained that combined consumption of smokeless tobacco or areca nut, smoked tobacco, and alcohol has a “multiplicative effect” on oral cancer risk, with reported odds ratios increasing from 2.7 for smokeless tobacco only, 7.0 for smoked tobacco only, and 1.6 for alcohol only to 16.2 for all three exposures (vs no use).

However, the proportion of people who chewed tobacco and also smoked in countries with high smokeless tobacco or areca nut use was small. In India, for example, 6% of men and 0.5% of women in 2016-2017 were dual users of both smoked and smokeless tobacco, compared with 23% of men and 12% of women who only used smokeless tobacco.

Overall, curbing or preventing smokeless tobacco and areca nut use could help avoid many instances of oral cancer.

Despite “encouraging trends” in control of tobacco smoking in many regions of the world over the past two decades, progress in reducing the prevalence of smokeless tobacco consumption has stalled in many countries that are major consumers, the authors said.

Compounding the problem, areca nut does not fall within the WHO framework of tobacco control and there are very few areca nut control policies worldwide.

Smokeless tobacco control must be “prioritized” and a framework on areca nut control should be developed with guidelines to incorporate areca nut prevention into cancer control programs, the authors concluded.

Funding for the study was provided by the French National Cancer Institute. The authors had no relevant disclosures.

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