Tracking Treatment Response and Outcomes in Adults with Obesity and Overweight Using Data and Machine Learning in a Single-Center Observational Study

What this Trial Is About

Researchers are conducting an observational study at a single center to collect data retrospectively and prospectively on patients diagnosed with obesity or overweight. The study aims to develop predictive models for how patients respond to obesity treatments using statistical and machine learning methods exclusively for research. The study includes patients whose first visit was from January 1, 2000, onward, including those who died or were lost to follow-up. Data will be gathered from electronic health records, including instrumental and lab tests, pharmacological treatments, and group-based educational and behavioral therapies following routine clinical practice and guidelines. An interim analysis will focus on the retrospective cohort with at least five years of follow-up. Data collection will continue for five years after the study starts, covering therapeutic interventions and outcomes. Participants will have their health records reviewed for information on treatment responses and outcomes, including cardiometabolic events up to 10 years. The study will identify obesity phenotypes and their links to clinical outcomes. There is no interventional treatment instead, researchers will analyze existing and ongoing clinical data. The study duration extends to March 2038, with ongoing data collection and follow-up.

ASSESSMENT OF THE NATURAL HISTORY AND PROGNOSTIC FACTORS OF THERAPEUTIC RESPONSE IN SUB-PHENOTYPES OF PATIENTS WITH OBESITY: THE BOLOBE STUDY