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Early Weight Loss and Treatment Response: Data From a Lifestyle Change Program in Clinical Practice
- Source :
- Am J Prev Med
- Publication Year :
- 2020
- Publisher :
- Elsevier BV, 2020.
-
Abstract
- Introduction The 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. Methods Investigators 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. Results Among 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). Conclusions In 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.
- Subjects :
- Adult
Male
medicine.medical_specialty
Epidemiology
Health Promotion
Weight Gain
Logistic regression
Risk Assessment
01 natural sciences
Article
Cohort Studies
03 medical and health sciences
0302 clinical medicine
Risk Factors
Weight loss
Positive predicative value
Weight Loss
Electronic Health Records
Humans
Medicine
030212 general & internal medicine
0101 mathematics
Baseline (configuration management)
Life Style
Aged
Receiver operating characteristic
business.industry
010102 general mathematics
Weight change
Public Health, Environmental and Occupational Health
Middle Aged
Overweight
Logistic Models
ROC Curve
Cohort
Physical therapy
Female
medicine.symptom
business
Weight gain
Program Evaluation
Subjects
Details
- ISSN :
- 07493797
- Volume :
- 58
- Database :
- OpenAIRE
- Journal :
- American Journal of Preventive Medicine
- Accession number :
- edsair.doi.dedup.....9638eaf48528f0309f79109307e92f04