Personalized predictions to identify individuals most likely to achieve 10% weight loss with a lifestyle intervention
Authors' conclusion
The Look AHEAD intervention would achieve a 10% average weight reduction if targeted to those most likely to benefit. Future research must seek external validation of these predictions. We make this algorithm available with instructions for use to demonstrate its potential capacity to inform shared decision-making and patient-centered care.
Study context
- Population
- Participants of Action for Health in Diabetes (Look AHEAD), a national, multisite clinical trial (2001–2012)
- Comparison
- Lifestyle intervention targeted to predicted responders vs untargeted
- Primary endpoint
- Predicted individual treatment effects on weight loss of the Look AHEAD lifestyle intervention; heterogeneity in treatment response
Methodological detailsmachine-learning prediction model, national, multisite clinical trial data
- Machine-learning prediction model
- National, multisite clinical trial data
Primary result
As reported in the abstract
Heterogeneity of individual treatment effects
- Share of sample predicted to have a treatment effect within ±2% weight loss from the average treatment effect
- two-thirds
- Average observed weight loss in the intervention group if targeted to the 69% of patients expected to meet a 7% weight-loss target at 1 year
- 10%
Original publication
Personalized predictions to identify individuals most likely to achieve 10% weight loss with a lifestyle intervention. Obesity (Silver Spring). Published 12 March 2025. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →