Jean Debédat1, Nataliya Sokolovska1,2, Muriel Coupaye3, Simona Panunzi4, Rima Chakaroun5,6, Laurent Genser7, Garance de Turenne1, Jean-Luc Bouillot8, Christine Poitou1,9, Jean-Michel Oppert9, Matthias Blüher5,6, Michael Stumvoll5,6, Geltrude Mingrone10,11, Séverine Ledoux3, Jean-Daniel Zucker1,2,12, Karine Clément1,2,9, Judith Aron-Wisnewsky13,2,9. 1. NutriOmics team, Sorbonne Université, INSERM, Paris, France. 2. Integromics team, Institute of Cardiometabolism and Nutrition (ICAN), Pitié-Salpêtrière Hospital, Paris, France. 3. Obesity Reference Center, Explorations Fonctionnelles Department, Louis Mourier Hospital, Assistance Publique Hôpitaux de Paris, Colombes, France. 4. BioMatLab, Institute for Systems Analysis and Computer Science (IASI), National Council for Research (CNR), Rome, Italy. 5. Department of Endocrinology and Nephrology, University of Leipzig, Leipzig, Germany. 6. Integrated Research and Treatment Center (IFB) Adiposity Diseases, University Medical Center, Leipzig, Germany. 7. Visceral Surgery Department, Pitié-Salpêtrière Hospital, Assistance Publique Hôpitaux de Paris, Paris, France. 8. Visceral Surgery Department, Ambroise Paré Hospital, Assistance Publique Hôpitaux de Paris, Paris, France. 9. Nutrition Department, Pitié-Salpêtrière Hospital, Assistance Publique Hôpitaux de Paris, Sorbonne Université, Paris, France. 10. Department of Internal Medicine, Catholic University, Rome, Italy. 11. Department of Diabetes and Nutritional Sciences, King's College London, London, U.K. 12. Unité de Modélisation Mathématique et Informatique des Systèmes Complexes (UMMISCO), L'Institut de Recherche pour le Développement (IRD), Sorbonne Université, Bondy, France. 13. NutriOmics team, Sorbonne Université, INSERM, Paris, France judith.aron-wisnewsky@psl.aphp.fr.
Abstract
OBJECTIVE: Roux-en-Y gastric bypass (RYGB) induces type 2 diabetes remission (DR) in 60% of patients at 1 year, yet long-term relapse occurs in half of these patients. Scoring methods to predict DR outcomes 1 year after surgery that include only baseline parameters cannot accurately predict 5-year DR (5y-DR). We aimed to develop a new score to better predict 5y-DR. RESEARCH DESIGN AND METHODS: We retrospectively included 175 RYGB patients with type 2 diabetes with 5-year follow-up. Using machine learning algorithms, we developed a scoring method, 5-year Advanced-Diabetes Remission (5y-Ad-DiaRem), predicting longer-term DR postsurgery by integrating medical history, bioclinical data, and antidiabetic treatments. The scoring method was based on odds ratios and variables significantly different between groups. This score was further validated in three independent RYGB cohorts from three European countries. RESULTS: Compared with 5y-DR patients, patients who had relapsed after 5 years exhibited more severe type 2 diabetes at baseline, lost significantly less weight during the 1st year after RYGB, and regained more weight afterward. The 5y-Ad-DiaRem includes baseline (diabetes duration, number of antidiabetic treatments, and HbA1c) and 1-year follow-up parameters (glycemia, number of antidiabetic treatments, remission status, 1st-year weight loss). The 5y-Ad-DiaRem was accurate (area under the receiver operating characteristic curve [AUROC], 90%; accuracy, 85%) at predicting 5y-DR, performed better than the Diabetes Remission score (DiaRem) and the Advanced-DiaRem (AUROC, 81% and 84%; accuracy, 79% and 78%, respectively), and correctly reclassified 13 of 39 patients misclassified with the DiaRem. The 5y-Ad-DiaRem robustness was confirmed in the independent cohorts. CONCLUSIONS: The 5y-Ad-DiaRem accurately predicts 5y-DR and appears relevant to identify patients at risk for relapse. Using this score could help personalize patient care after the 1st year post-RYGB to maximize weight loss, limit weight regains, and prevent relapse.
OBJECTIVE: Roux-en-Y gastric bypass (RYGB) induces type 2 diabetes remission (DR) in 60% of patients at 1 year, yet long-term relapse occurs in half of these patients. Scoring methods to predict DR outcomes 1 year after surgery that include only baseline parameters cannot accurately predict 5-year DR (5y-DR). We aimed to develop a new score to better predict 5y-DR. RESEARCH DESIGN AND METHODS: We retrospectively included 175 RYGB patients with type 2 diabetes with 5-year follow-up. Using machine learning algorithms, we developed a scoring method, 5-year Advanced-Diabetes Remission (5y-Ad-DiaRem), predicting longer-term DR postsurgery by integrating medical history, bioclinical data, and antidiabetic treatments. The scoring method was based on odds ratios and variables significantly different between groups. This score was further validated in three independent RYGB cohorts from three European countries. RESULTS: Compared with 5y-DR patients, patients who had relapsed after 5 years exhibited more severe type 2 diabetes at baseline, lost significantly less weight during the 1st year after RYGB, and regained more weight afterward. The 5y-Ad-DiaRem includes baseline (diabetes duration, number of antidiabetic treatments, and HbA1c) and 1-year follow-up parameters (glycemia, number of antidiabetic treatments, remission status, 1st-year weight loss). The 5y-Ad-DiaRem was accurate (area under the receiver operating characteristic curve [AUROC], 90%; accuracy, 85%) at predicting 5y-DR, performed better than the Diabetes Remission score (DiaRem) and the Advanced-DiaRem (AUROC, 81% and 84%; accuracy, 79% and 78%, respectively), and correctly reclassified 13 of 39 patients misclassified with the DiaRem. The 5y-Ad-DiaRem robustness was confirmed in the independent cohorts. CONCLUSIONS: The 5y-Ad-DiaRem accurately predicts 5y-DR and appears relevant to identify patients at risk for relapse. Using this score could help personalize patient care after the 1st year post-RYGB to maximize weight loss, limit weight regains, and prevent relapse.
Authors: Kajsa Sjöholm; Lena M S Carlsson; Magdalena Taube; Carel W le Roux; Per-Arne Svensson; Markku Peltonen Journal: Diabetes Care Date: 2020-09-01 Impact factor: 19.112