Published in:
01-06-2020 | Obesity | Original Contributions
Comparison of Four Risk Prediction Models for Diabetes Remission after Roux-en-Y Gastric Bypass Surgery in Obese Chinese Patients with Type 2 Diabetes Mellitus
Published in: Obesity Surgery | Issue 6/2020
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Background
Roux-en-Y gastric bypass (RYGB) is a major type of bariatric surgery. Various models have been established for facilitating clinical decision-making and predicting outcomes after RYGB; the ABCD, DiaRem, advanced-DiaRem (Ad-DiaRem), and DiaBetter scores are among the most commonly used risk prediction models. However, these models were primarily developed based on retrospective analyses of patients from Western countries at 1 year after RYGB. The present study was to assess the performance of these models and identify the optimal model, for predicting postoperative diabetes remission in diabetic Chinese patients.
Methods
The present study included a total of 253 RYGB patients; 214 completed a 1-year follow-up and 131 completed a 3-year follow-up. The assessments and comparisons of the predictive performance of the four models were based on both discrimination and calibration measures. Discrimination was assessed according to the area under the receiver operating characteristic curve (AUC), and calibration was evaluated by Hosmer-Lemeshow goodness-of-fit tests and predicted-to-observed ratios.
Results
One hundred thirteen (52.8%) in the 1-year follow-up group and 59 (45.0%) in the 3-year follow-up group achieved complete diabetes remission. Although all models showed similar discriminatory capacity and good calibration, the DiaBetter model exhibited the best predictive performance (1-year follow-up, AUC 0.760, 95% confidence interval [CI] 0.697–0.815, predicted-to-observed ratio 1.04; 3-year follow-up, AUC 0.804, 95% CI 0.726–0.868, predicted-to-observed ratio 0.95).
Conclusions
The present results indicated that the DiaBetter model is the optimal model for predicting postoperative diabetes remission in diabetic Chinese individuals, due to its excellent predictive accuracy and ready availability for use in clinical practice.