ArticleBMC endocrine disorders2026
Predictive models of adverse outcomes of overweight or obesity: a nationwide cohort validation.
Article in BMC endocrine disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundObesity and overweight have a wide range of adverse clinical outcomes. Predictive models could help clinicians identify individuals with obesity and overweight at greater risk for obesity-related complications, enabling personalized shared decision-making about obesity treatment. We previously developed a set of predictive models of adverse clinical outcomes of obesity and overweight using electronic health record (EHR) data of a large health system in Massachusetts. However, these models have not been validated on data from other sources.
methodsWe validated 12 predictive models for cardiometabolic, oncologic and musculoskeletal complications of excess weight using a linked EHR and claims dataset of a national patient cohort (Optum
resultsA 5% randomly selected validation dataset included 437,223 patients (51.9% women) with a mean age of 51.4 years and a mean BMI of 31.9 kg/m
conclusionsA set of EHR-based predictive models of adverse outcomes of obesity and overweight was generalizable to a large national cohort. These findings suggest potential clinical and population health applications for predictive models in treatment of individual patients with obesity / overweight, as well as in population management and quality improvement. CLINICAL TRIAL NUMBER: Not applicable.
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