Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, U.K.
Department of Diabetes and Endocrinology, University Hospitals Birmingham NHS Foundation Trust, Birmingham, U.K.
Diabetes Care. 2021 Nov;44(11):2626-2641. doi: 10.2337/dc21-0166.
Remission of type 2 diabetes following bariatric surgery is well established, but identifying patients who will go into remission is challenging.
To perform a systematic review of currently available diabetes remission prediction models, compare their performance, and evaluate their applicability in clinical settings.
A comprehensive systematic literature search of MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, Embase, and Cochrane Central Register of Controlled Trials (CENTRAL) was undertaken. The search was restricted to studies published in the last 15 years and in the English language.
All studies developing or validating a prediction model for diabetes remission in adults after bariatric surgery were included.
The search identified 4,165 references, of which 38 were included for data extraction. We identified 16 model development and 22 validation studies.
Of the 16 model development studies, 11 developed scoring systems and 5 proposed logistic regression models. In model development studies, 10 models showed excellent discrimination with area under the receiver operating characteristic curve ≥0.800. Two of these prediction models, ABCD and DiaRem, were widely externally validated in different populations, in a variety of bariatric procedures, and for both short- and long-term diabetes remission. Newer prediction models showed excellent discrimination in test studies, but external validation was limited.
While the key messages were consistent, a large proportion of the studies were conducted in small cohorts of patients with short duration of follow-up.
Among the prediction models identified, the ABCD and DiaRem models were the most widely validated and showed acceptable to excellent discrimination. More studies validating newer models and focusing on long-term diabetes remission are needed.
减重手术后 2 型糖尿病的缓解已得到充分证实，但确定哪些患者将进入缓解期具有挑战性。
对目前可用的糖尿病缓解预测模型进行系统回顾，比较它们的性能，并评估它们在临床环境中的适用性。
对 MEDLINE、MEDLINE 正在处理的文献及其他非索引引文、Embase 和 Cochrane 对照试验中心注册库（CENTRAL）进行了全面的系统文献检索。检索限制为过去 15 年发表的英文研究。
所有开发或验证减重手术后成年人糖尿病缓解预测模型的研究均被纳入。
搜索共确定了 4165 篇参考文献，其中 38 篇被纳入数据提取。我们确定了 16 项模型开发和 22 项验证研究。
在 16 项模型开发研究中，11 项开发了评分系统，5 项提出了逻辑回归模型。在模型开发研究中，有 10 个模型的受试者工作特征曲线下面积（AUC）≥0.800，具有出色的区分能力。其中两个预测模型，ABCD 和 DiaRem，在不同人群、各种减重手术中以及短期和长期糖尿病缓解方面得到了广泛的外部验证。新的预测模型在测试研究中显示出出色的区分能力，但外部验证有限。
虽然主要信息是一致的，但很大一部分研究是在随访时间短、患者数量少的小队列中进行的。
在所确定的预测模型中，ABCD 和 DiaRem 模型得到了最广泛的验证，具有可接受至出色的区分能力。需要更多验证新模型并关注长期糖尿病缓解的研究。
