Institute of Cardiometabolism and Nutrition (ICAN), Nutrition Department, Assistance Publique-Hôpitaux de Paris, Pitié-Salpêtrière Hospital, 46-83 Boulevard de l'Hôpital, F-75013, Paris, France.
Team 6 Nutriomics, UPMC Université Paris 06 and Inserm, UMR_S 1166, Sorbonne Universités, Paris, France.
Diabetologia. 2017 Oct;60(10):1892-1902. doi: 10.1007/s00125-017-4371-7. Epub 2017 Jul 21.
AIMS/HYPOTHESIS: Not all people with type 2 diabetes who undergo bariatric surgery achieve diabetes remission. Thus it is critical to develop methods for predicting outcomes that are applicable for clinical practice. The DiaRem score is relevant for predicting diabetes remission post-Roux-en-Y gastric bypass (RYGB), but it is not accurate for all individuals across the entire spectrum of scores. We aimed to develop an improved scoring system for predicting diabetes remission following RYGB (the Advanced-DiaRem [Ad-DiaRem]).
We used a retrospective French cohort (n = 1866) that included 352 individuals with type 2 diabetes followed for 1 year post-RYGB. We developed the Ad-DiaRem in a test cohort (n = 213) and examined its accuracy in independent cohorts from France (n = 134) and Israel (n = 99).
Adding two clinical variables (diabetes duration and number of glucose-lowering agents) to the original DiaRem and modifying the penalties for each category led to improved predictive performance for Ad-DiaRem. Ad-DiaRem displayed improved area under the receiver operating characteristic curve and predictive accuracy compared with DiaRem (0.911 vs 0.856 and 0.841 vs 0.789, respectively; p = 0.03); thus correcting classification for 8% of those initially misclassified with DiaRem. With Ad-DiaRem, there were also fewer misclassifications of individuals with mid-range scores. This improved predictive performance was confirmed in independent cohorts.
CONCLUSIONS/INTERPRETATION: We propose the Ad-DiaRem, which includes two additional clinical variables, as an optimised tool with improved accuracy to predict diabetes remission 1 year post-RYGB. This tool might be helpful for personalised management of individuals with diabetes when considering bariatric surgery in routine care, ultimately contributing to precision medicine.
目的/假设：并非所有接受减重手术的 2 型糖尿病患者都能实现糖尿病缓解。因此，开发适用于临床实践的预测结果的方法至关重要。DiaRem 评分可用于预测 Roux-en-Y 胃旁路术（RYGB）后的糖尿病缓解，但对于整个评分范围内的所有个体并不准确。我们旨在开发一种用于预测 RYGB 后糖尿病缓解的改良评分系统（Advanced-DiaRem [Ad-DiaRem]）。
我们使用了一个回顾性的法国队列（n=1866），其中包括 352 例接受 RYGB 治疗后随访 1 年的 2 型糖尿病患者。我们在一个测试队列（n=213）中开发了 Ad-DiaRem，并在法国（n=134）和以色列（n=99）的独立队列中检验了其准确性。
在原始 DiaRem 中添加两个临床变量（糖尿病病程和降糖药物种类）并修改每个类别下的惩罚，可提高 Ad-DiaRem 的预测性能。与 DiaRem 相比，Ad-DiaRem 的曲线下面积和预测准确性得到改善（分别为 0.911 与 0.856 和 0.841 与 0.789；p=0.03）；从而纠正了 8%的最初被 DiaRem 错误分类的患者。使用 Ad-DiaRem，还减少了中等评分患者的错误分类。这种改进的预测性能在独立队列中也得到了证实。
结论/解释：我们提出了 Ad-DiaRem，它包含了两个额外的临床变量，是一种准确性提高的优化工具，可用于预测 RYGB 后 1 年的糖尿病缓解。在常规护理中考虑减重手术时，该工具可能有助于对糖尿病患者进行个体化管理，最终有助于精准医学。
