Latest / Morning Medical with Dr. Chow / Weight Management Pills, PMOS Insights, and AI in Healthcare

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Weight Management Pills, PMOS Insights, and AI in Healthcare · Morning Medical with Dr. Chow

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  Welcome to another episode of Morning Medical with Dr.
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  Chow.
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  I'm Dr.
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  Chi-Ming Chow, your host, here to bring you the latest updates in medical and health news from
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  around the globe.
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  Today, we're diving into a fascinating development in the field of weight management
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  that could have significant implications for those dealing with obesity.
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  Let's talk about a new daily pill that's generating a lot of buzz.
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  This pill aims to help individuals maintain their weight loss after they've stopped using
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  obesity jabs.
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  The drug, known as orforglipron, is already available in the United States and might soon
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  hit the market in the United Kingdom.
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  According to the latest research, patients who took this tablet every day for a year were able
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  to avoid regaining much of the weight they had lost.
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  This is particularly noteworthy because weight regain is a well-known challenge when patients
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  stop taking GLP-1 injections, which are a class of drugs used for weight loss.
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  The study, which was published in the journal Nature Medicine, was funded by Eli Lilly, the
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  manufacturer of both orforglipron and the weight loss injection Mounjaro.
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  While the results are promising, experts emphasize the need for more research to
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  determine the long-term effectiveness of the pill.
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  It's possible that patients might need to remain on this treatment indefinitely, which is
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  a consideration for those thinking about switching from injections to pills.
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  Dr.
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  Marie Spreckley, an expert in weight management from the University of Cambridge, points out
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  that taking a pill could be more appealing to patients than injections.
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  However, she cautions that we still don't know how sustainable these effects will be over
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  longer periods.
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  Her insights underscore the growing understanding that obesity is a chronic,
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  relapsing disease that often requires continuous treatment and support.
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  Orforglipron works by mimicking a natural hormone that reduces appetite and increases the
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  feeling of fullness.
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  In the United States, it is priced at around one hundred forty-nine dollars per month for
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  the lowest dose, which is significantly cheaper than some injectable GLP-1 options, which can
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  cost over one thousand dollars a month.
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  In a study involving three hundred seventy-six participants who had previously been on GLP-1
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  jabs like tirzepatide or semaglutide, results showed that those who switched to orforglipron
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  maintained over seventy percent of their weight loss.
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  In contrast, those given a placebo maintained about thirty-eight to fifty percent of their
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  weight loss.
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  While the side effects such as nausea, constipation, and diarrhea were common, they
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  were mostly mild.
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  Dr.
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  Simon Cork from Anglia Ruskin University highlights this study as a major step forward,
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  addressing the issue of weight rebound with injectable GLP-1 medications.
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  He also notes that patients on the oral medication maintained improvements in blood
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  pressure, lipids, and blood glucose, which could help mitigate long-term health risks
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  associated with obesity, like heart disease.
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  Today, we're delving into a study that's stirring up quite the conversation in the
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  oncology community.
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  The focus?
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  GLP-1 receptor agonists and their potential impact on breast cancer outcomes.
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  A recent retrospective study has suggested that the use of GLP-1 agonists, which are typically
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  employed for diabetes or obesity management, might be linked to lower all-cause mortality
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  and improved recurrence-free survival in breast cancer patients.
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  But, as with many things that sound too good to be true, there's a catch.
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  The study, published in JAMA Network Open, reports some striking figures.
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  For patients with breast cancer who also have diabetes, the use of GLP-1 agonists was
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  associated with a whopping 91 percent lower risk of all-cause mortality compared to those
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  treated with insulin or metformin.
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  For those with obesity, the risk was 65 percent lower compared to no GLP-1 drug use.
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  However, when compared with SGLT2 inhibitors, the initial analysis did not show a significant
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  mortality benefit, though further adjustments did indicate a modest advantage favoring GLP-1
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  use.
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  Despite these promising numbers, the study has faced criticism from several experts.
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  Paul Pharoah from Cedars-Sinai Medical Center described the results as "too good to be true,"
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  highlighting the enormous effect sizes that seem implausible based on existing randomized
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  trials of GLP-1 drugs.
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  He pointed out that the observed reductions in mortality and recurrence risk are far greater
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  than what is typically seen with even the most effective chemotherapy regimens.
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  Mangesh Thorat from Queen Mary University of London also raised concerns about the study's
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  data quality.
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  He noted significant gaps, such as incomplete information on estrogen receptor status and
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  treatment history.
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  For instance, estrogen receptor status was known for only about 20 percent of the
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  population, whereas in well-curated datasets, this figure should be near 100 percent.
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  Similarly, details on surgery, radiotherapy, and systemic therapy were sparse, with surgery
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  information available for less than 10 percent of patients.
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  The study, led by Bernard Fuemmeler and his team from the Massey Comprehensive Cancer
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  Center, utilized data from the TriNetX database, which included over eight hundred
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  thousand women diagnosed with breast cancer across sixty-eight healthcare organizations in
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  the United States.
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  While the researchers are optimistic about their findings, they acknowledge the study's
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  limitations, including its retrospective nature and reliance on a U.S.-centric database, which
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  might limit the generalizability of the results.
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  Ultimately, while the potential for GLP-1 agonists to influence breast cancer outcomes is
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  intriguing, the current evidence is not without its caveats.
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  Experts are calling for prospective studies to better understand the risks and benefits of
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  GLP-1 receptor agonist treatment in breast cancer patients, as well as to determine the
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  optimal timing and tailoring of such therapies.
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  Until then, it's essential to approach these findings with cautious optimism and a critical
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  eye.
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  Today, we're turning our attention to a significant update in the world of
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  endocrinology that could reshape how we understand and treat a common hormonal
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  condition affecting millions of women globally.
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  The condition formerly known as polycystic ovary syndrome, or PCOS, has been renamed
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  polyendocrine metabolic ovarian syndrome, abbreviated as PMOS.
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  This change aims to provide a more accurate depiction of the condition and improve patient
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  care.
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  Polyendocrine metabolic ovarian syndrome affects about one in eight women worldwide and
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  is characterized by hormonal imbalances that can impact a range of bodily functions,
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  including weight, metabolic and mental health, the reproductive system, and skin.
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  The old term, polycystic ovary syndrome, was often misleading, as it focused solely on
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  ovarian cysts, which are not present in all cases.
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  Instead, PMOS highlights the broader endocrine and metabolic issues involved.
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  The decision to rename the condition was the result of a 14-year collaboration between
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  experts and patients, culminating in a publication in The Lancet.
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  Dr.
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  Melanie Cree, a pediatric endocrinology expert at the University of Colorado Anschutz,
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  explained that the term PCOS was confusing because not all women with the condition have
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  cysts in their ovaries.
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  By adopting a more comprehensive name, the hope is to push for better care and understanding.
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  PMOS is linked to metabolic syndrome, a cluster of conditions that elevate the risk of
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  developing type 2 diabetes, heart disease, and stroke.
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  While the exact cause of PMOS remains unclear, genetic factors and obesity are believed to
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  play significant roles.
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  Dr.
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  Sarah Hutto from the University of Minnesota Medical School noted that these hormonal
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  fluctuations can lead to symptoms such as irregular menstrual cycles, increased androgen
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  levels causing acne, and hair growth or thinning.
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  Diagnosing PMOS can be challenging due to the variability in symptoms.
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  In teenagers, diagnosis typically requires both irregular periods and signs of elevated
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  androgens, which might manifest as severe acne or chest hair.
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  Despite these challenges, effective management strategies are available.
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  Treatment for PMOS often begins with lifestyle changes, such as reducing processed food
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  intake, increasing physical activity, and ensuring adequate sleep.
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  Dr.
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  Cree emphasizes the science behind these recommendations, noting that high insulin
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  levels can lead to increased testosterone production, exacerbating symptoms.
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  Beyond lifestyle adjustments, medications like Metformin, which sensitizes insulin, and
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  hormonal treatments, such as birth control, can help manage the condition.
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  The name change to PMOS is more than just a rebranding; it's an effort to enhance awareness
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  and improve care strategies.
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  By spreading the word through medical societies and conferences, researchers and doctors hope
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  to better educate both the public and healthcare providers about the condition.
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  As Dr.
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  Cree and her colleagues champion this change, the ultimate goal is to provide more
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  individualized and effective treatment options for those affected by PMOS.
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  In recent years, the integration of artificial intelligence into the healthcare system has
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  sparked significant debate.
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  This technology, once considered a futuristic tool, is now a central component of healthcare
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  operations in the United States.
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  According to recent findings, around one-third of U.S.
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  adults have used artificial intelligence to gather health information, and more than 40
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  percent have uploaded personal medical data into an artificial intelligence tool.
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  Within clinical settings, artificial intelligence is utilized to write notes, triage
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  messages, predict readmissions, summarize charts, suggest differential diagnoses, and
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  even to make prescription decisions that were traditionally made by physicians.
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  While artificial intelligence offers the potential to enhance patient outcomes, improve
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  healthcare access, reduce costs, and alleviate clinician burnout, it also raises challenging
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  questions about its role in healthcare.
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  This concern extends beyond clinical environments to insurance companies, where
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  artificial intelligence is increasingly used to evaluate claims, guide prior authorization
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  decisions, and predict the necessary care for patients.
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  The rationale is clear: to boost efficiency, consistency, and cost control.
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  However, there is growing concern that insurers might be using artificial intelligence to
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  replace clinical review, potentially with minimal human oversight.
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  A survey conducted by the American Medical Association revealed that 61 percent of
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  physicians are worried that unregulated artificial intelligence use by payers could
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  lead to increased prior authorization denials.
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  Some cases have already been reported where denial decisions were made so swiftly that
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  meaningful physician review seemed improbable.
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  Michelle Mello, a health law scholar, highlighted concerns about the lack of human
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  review in artificial intelligence-driven recommendations, which could lead to wrongful
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  denials of care.
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  This situation underscores the potential risks when artificial intelligence is used as a
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  gatekeeper rather than a supportive tool.
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  The issue is not the deployment of artificial intelligence in healthcare settings, but how it
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  is utilized.
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  Artificial intelligence should serve as a tool to enhance human skill and knowledge, not as a
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  gatekeeper for care.
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  Fortunately, regulators are beginning to recognize this distinction.
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  The Centers for Medicare and Medicaid Services have stated that algorithms can assist in
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  coverage determinations but cannot override individual patient circumstances or replace
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  clinical judgment.
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  The American Medical Association has called for greater oversight of artificial intelligence
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  use by insurers, emphasizing the need for transparency, bias mitigation, and human review
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  in decisions affecting patient care.
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  Patients are also pushing back, with lawsuits alleging that artificial intelligence-driven
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  decisions have inappropriately denied care.
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  As these issues gain attention, questions about liability are emerging.
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  Who is responsible when an artificial intelligence system contributes to a negative
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  outcome?
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  If a clinician follows an artificial intelligence recommendation that results in a
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  poor health outcome, is that an error of clinical judgment or an algorithmic one?
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  And if an insurer's use of artificial intelligence to deny care leads to harm, where
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  does accountability lie?
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  With the insurance company, the artificial intelligence developer, or the data provider?
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  The legal framework for artificial intelligence in healthcare has not kept pace with the
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  technology.
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  Traditional models of malpractice assume a human decision-maker, but artificial
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  intelligence introduces a new layer between information and action—one that is often opaque
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  and constantly evolving.
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  Regulators need to establish clear boundaries for artificial intelligence use in healthcare.
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  Should artificial intelligence be used autonomously?
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  Where must a human remain the decision-maker?
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  What level of transparency is necessary for clinicians and patients to trust these systems?
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  And critically, who is accountable when things go wrong?
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  In clinical environments, the path forward is clear.
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  Artificial intelligence should augment, not replace, clinician judgment.
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  Outputs should be reviewable, explainable, and contestable, with clinicians remaining the
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  final decision-makers.
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  In the payer environment, standards must be equally robust.
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  Coverage decisions cannot be reduced to algorithmic outputs without meaningful human
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  oversight.
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  Models must be transparent, validated against clinical standards, and monitored for bias.
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  Clear accountability is essential to prevent a system where access to care is shaped by tools
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  that no one fully understands or owns.
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  Artificial intelligence is not the future of healthcare; it is our present.
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  The question now is whether we build a system where it serves patients or one where patients
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  are forced to serve the system.
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  It's crucial to define the role of artificial intelligence in healthcare now, while it's
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  still early enough to make informed decisions.
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  That wraps up today's episode of Morning Medical with Dr.
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  Chow.
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  Thank you for joining me as we explored these critical issues in healthcare.
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  Until next time, take care and stay informed.