AI Article Synopsis

  • A clinical risk model was created to identify individuals at higher risk for developing new-onset diabetes, helping to target those who would benefit most from weight loss medication.
  • The study analyzed data from over 21,000 patients without type 2 diabetes, assessing 27 risk factors and ultimately identifying five key predictors linked to new-onset diabetes.
  • The model demonstrated strong accuracy and differentiation in predicting risk levels and showed varying degrees of benefit from weight-loss therapy based on an individual's risk status.

Article Abstract

Aims: To develop a clinical risk model to identify individuals at higher risk of developing new-onset diabetes and who might benefit more from weight loss pharmacotherapy.

Materials And Methods: A total of 21 143 patients without type 2 diabetes at baseline from two TIMI clinical trials of stable cardiovascular patients were divided into a derivation (~2/3) and validation (~1/3) cohort. The primary outcome was new-onset diabetes. Twenty-seven candidate risk variables were considered, and variable selection was performed using multivariable Cox regression. The final model was evaluated for discrimination and calibration, and for its ability to identify patients who experienced a larger benefit from the weight loss medication lorcaserin in terms of risk of new-onset diabetes.

Results: During a median (interquartile range) follow-up of 2.3 (1.8-2.7) years, new-onset diabetes occurred in 1013 patients (7.7%). The final model included five independent predictors (glycated haemoglobin, fasting glucose, age, body mass index, and triglycerides/high-density lipoprotein). The clinical risk model showed good discrimination (Harrell's C-indices 0.802, 95% confidence interval [CI] 0.788-0.817 and 0.807, 95% CI 0.788-0.826) in the derivation and validation cohorts. The calibration plot demonstrated adequate calibration (2.5-year area under the curve was 81.2 [79.1-83.5]). While hazard ratios for new-onset diabetes with a weight-loss therapy were comparable across risk groups (annual risks of <1%, 1%-5%, and >5%), there was a sixfold gradient in absolute risk reduction from lowest to highest risk group (p = 0.027).

Conclusions: The developed clinical risk model effectively predicts new-onset diabetes, with potential implications for personalized patient care and therapeutic decision making.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11410501PMC
http://dx.doi.org/10.1111/dom.15798DOI Listing

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