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Endocrine Abstracts (2022) 81 P583 | DOI: 10.1530/endoabs.81.P583

1University of Milan, Milan, Italy; 2Pennington Biomedical Research Center, Baton Rouge, Louisiana, United States; 3SAM Clinical Research Center, San Antonio, Texas, United States; 4Health & Care, sro, Prague, Czech Republic; 5Central Alabama Research, Birmingham, Alabama, United States; 6Medicome Sp z o o, Oswiecim, Poland; 7Poznan University of Medical Sciences, Poznan, Poland; 8NZOZ Specjalistyczny Osrodek Internistyczno - Diabetologiczny, Bialystok, Poland; 9University of Copenhagen, Frederiksberg C, Denmark; 10Wake Research - Clinical Research Center of Nevada, LLC, Las Vegas, Nevada, United States; 11Centrum Badawcze Wspolczesnej Terapii, Warszawa, Poland; 12ALL Medical Research, LLC, Cooper City, Florida, United States; 13Sterling Research Group, Ltd, Cincinnati, Ohio, United States; 14Debreceni Egyetem Klinikai Kozpont, Debrecen, Hungary; 15Coastal Carolina Research Center, North Charleston, South Carolina, United States; 16Aintree University Hospital, Liverpool, United Kingdom; 17Care-Safe LLC, Boston, Massachusetts, United States; 18Gelesis, Inc, Boston, Massachusetts, United States


Introduction: Methods to predict clinically meaningful weight loss can help tailor treatment for people with overweight or obesity. LIGHT-UP (NCT03058029), is a multicenter, double-blind, randomized, placebo-controlled study over 25 weeks including 254 people with prediabetes or type 2 diabetes (127 each in the Gelesis200 and placebo arms) with a body mass index between 27 and 40 kg/m2, which demonstrated that Gelesis200 offers a compelling new potential approach in the management of overweight and obesity. A stepwise logistic regression analysis was conducted on data from the LIGHT-UP study to identify variables at baseline that reliably predict body weight (BW) Responders and Super-Responders (≤ 5% BW loss and ≤ 10% BW loss, respectively, from baseline at Week 25).

Methods: Two stepwise logistic regression analyses were conducted for each study arm (Gelesis 200 placebo). The dependent variables were the percentage of participants who were Responders and Super-Responders. The independent baseline variables included in the models were the ones hypothesized to potentially predict BW loss at Week 25 [e.g., gender, age, BW, body mass index, height, waist circumference, waist-to-height ratio (WHR), fasting plasma glucose, and fasting serum insulin].

Results: After WHR was included in the model, there were no other variables that were significant in the prediction of Responders or Super-Responders. The final regression model shows that for a 0.1 change in the WHR (e.g., from 0.6 to 0.7), the probability for a Responder increases from 53% to 66%, and the probability for a Super-Responder increases from 24% to 39%. For a 0.2 change in the WHR (e.g., from 0.6 to 0.8), the probability for a Responder increases from 53% to 78%, and the probability for a Super-Responder increases from 24% to 56%. None of the independent variables was a significant predictor of Responders or Super-Responders in the placebo arm.

Conclusion: The results of this study suggest that a higher baseline WHR is predictive of an increased rate of Responders and Super-Responders. It is well known that WHR is strongly correlated with fat mass and insulin resistance. With respect to weight loss, it can be speculated that Gelesis 200 is more effective in people with higher insulin resistance. If the findings of the LIGHT-UP study are replicated in larger clinical studies, baseline WHR would become a simple tool for clinicians to identify individuals likely to achieve meaningful weight loss on Gelesis200.

Volume 81

European Congress of Endocrinology 2022

Milan, Italy
21 May 2022 - 24 May 2022

European Society of Endocrinology 

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