• Robert J Romanelli, Sylvia Sudat, Qiwen Huang, Alice R Pressman, and Kristen Azar.
• Palo Alto Medical Foundation Research Institute, Center for Health Systems Research, Sutter Health, Palo Alto, California. Electronic address: romanerj1@sutterhealth.org.
• Am J Prev Med. 2020 Mar 1; 58 (3): 427-435.

IntroductionThe purpose of this study was to develop and validate a predictive model for the early identification of nonresponders to a 12-month lifestyle change program in clinical practice.MethodsInvestigators identified lifestyle change program participants in the electronic health records of a large healthcare delivery system between 2010 and 2017. Nonresponse was defined as weight gain or no weight loss at 12 months from the program initiation (baseline). Logistic regression with percentage weight change at 2-12 weeks from baseline was used as an independent predictor of nonresponse. Baseline demographics and clinical characteristics were also tested as potential predictors. The authors performed ten-fold cross-validation for model assessment and examined model performance with the area under the receiver operating characteristic curve, sensitivity, specificity, and positive and negative predictive values. The analyses were conducted in 2019.ResultsAmong 947 program participants, 30% were classified as nonresponders at 12 months. The model with the best discrimination of responders from nonresponders included weight change at 12 weeks from baseline as the sole predictor (area under the receiver operating characteristic curve, 0.789). Sensitivity and positive predictive value were maximized at 0.56 (specificity and negative predictive value, 0.81 each).ConclusionsIn a cohort of lifestyle change program participants from clinical practice, percentage weight change at 12 weeks from baseline can serve as a single indicator of nonresponse at the completion of the 12-month program. Clinicians can easily apply this algorithm to identify and assess participants in potential need of adjunctive or alternative therapy to maximize treatment outcomes.Copyright © 2019 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

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