Data-driven prioritization of high-risk individuals for weight loss interventions

, our machine learning framework identified the 20 most informative features, from among thousands tested, that predict future onset of 18 complications of obesity, providing information beyond BMI. An integrated model (OBSCORE) successfully stratified individuals into risk groups based on incidence over 10 years: for example, 5.7%, 1.8%, 0.9%, 0.4% and 0.1% for cardiovascular mortality. We demonstrate generalizability of the model in independent populations of European and non-European ancestry and, in SURMOUNT-1 trial participants, show that weight loss was similar across baseline OBSCORE risk groups and that predicted risks decreased following treatment with tirzepatide. In summary, OBSCORE provides a framework for prioritizing high-risk individuals with overweight or obesity based on their risk of obesity-related complications, complementing BMI-based frameworks.

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Publication Details

Journal
Nature Medicine
Published
2026-04-30
DOI
https://doi.org/10.1038/s41591-026-04353-2
Citations
1
Primary Topic
Bariatric Surgery and Outcomes
Type
article
Field-Weighted Citation Impact
25.27
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article

Data-driven prioritization of high-risk individuals for weight loss interventions

Maik Pietzner, Ida Moeller, Kamil Demircan, Alice Williamson et al.
1 citations
Nature Medicine
Bariatric Surgery and Outcomes
25.27
article

Data-driven prioritization of high-risk individuals for weight loss interventions

Maik Pietzner, Ida Moeller, Kamil Demircan, Alice Williamson, Sarah Finer, Aleksander L. Hansen, Gabi Kastenmüller, Julia Carrasco-Zanini, Claudia Langenberg, Carl Beuchel, Linsey Jackson, David A van Heel, Matthew Coghlan, Werner Römisch-Margl, Nicholas J Wareham
article en
1 citations

Abstract

, our machine learning framework identified the 20 most informative features, from among thousands tested, that predict future onset of 18 complications of obesity, providing information beyond BMI. An integrated model (OBSCORE) successfully stratified individuals into risk groups based on incidence over 10 years: for example, 5.7%, 1.8%, 0.9%, 0.4% and 0.1% for cardiovascular mortality. We demonstrate generalizability of the model in independent populations of European and non-European ancestry and, in SURMOUNT-1 trial participants, show that weight loss was similar across baseline OBSCORE risk groups and that predicted risks decreased following treatment with tirzepatide. In summary, OBSCORE provides a framework for prioritizing high-risk individuals with overweight or obesity based on their risk of obesity-related complications, complementing BMI-based frameworks.

Nature Medicine
Steno Diabetes Centers (DK), Queen Mary University of London (GB), Eli Lilly (United States) (US), Helmholtz Zentrum München (DE), Wellcome/MRC Institute of Metabolic Science (GB), Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE), Max Planck Institute for Molecular Genetics (DE), MRC Epidemiology Unit (GB), Charité - Universitätsmedizin Berlin (DE)
Good health and well-being
Openalex Percentile: Top 0%
Bariatric Surgery and Outcomes
25.27
DOIOpen Access PDFOpenAlex
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