Division of Endocrinology and Metabolism, Center for Diabetes and Metabolism Research, Laboratory of Diabetes and Islet Transplantation Research, West China Medical School, West China Hospital, Sichuan University, Guo Xue Lane 37, Chengdu, China.
Diabetes Trials Unit, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
Cardiovasc Diabetol. 2022 Sep 13;21(1):182. doi: 10.1186/s12933-022-01622-5.
People with intermediate hyperglycemia (IH), including impaired fasting glucose and/or impaired glucose tolerance, are at higher risk of developing type 2 diabetes (T2D) than those with normoglycemia. We aimed to evaluate the performance of published T2D risk prediction models in Chinese people with IH to inform them about the choice of primary diabetes prevention measures.
A systematic literature search was conducted to identify Asian-derived T2D risk prediction models, which were eligible if they were built on a prospective cohort of Asian adults without diabetes at baseline and utilized routinely-available variables to predict future risk of T2D. These Asian-derived and five prespecified non-Asian derived T2D risk prediction models were divided into BASIC (clinical variables only) and EXTENDED (plus laboratory variables) versions, with validation performed on them in three prospective Chinese IH cohorts: ACE (n = 3241), Luzhou (n = 1333), and TCLSIH (n = 1702). Model performance was assessed in terms of discrimination (C-statistic) and calibration (Hosmer-Lemeshow test).
Forty-four Asian and five non-Asian studies comprising 21 BASIC and 46 EXTENDED T2D risk prediction models for validation were identified. The majority were at high (n = 43, 87.8%) or unclear (n = 3, 6.1%) risk of bias, while only three studies (6.1%) were scored at low risk of bias. BASIC models showed poor-to-moderate discrimination with C-statistics 0.52-0.60, 0.50-0.59, and 0.50-0.64 in the ACE, Luzhou, and TCLSIH cohorts respectively. EXTENDED models showed poor-to-acceptable discrimination with C-statistics 0.54-0.73, 0.52-0.67, and 0.59-0.78 respectively. Fifteen BASIC and 40 EXTENDED models showed poor calibration (P < 0.05), overpredicting or underestimating the observed diabetes risk. Most recalibrated models showed improved calibration but modestly-to-severely overestimated diabetes risk in the three cohorts. The NAVIGATOR model showed the best discrimination in the three cohorts but had poor calibration (P < 0.05).
In Chinese people with IH, previously published BASIC models to predict T2D did not exhibit good discrimination or calibration. Several EXTENDED models performed better, but a robust Chinese T2D risk prediction tool in people with IH remains a major unmet need.
与血糖正常者相比，具有中间高血糖（IH）的人群，包括空腹血糖受损和/或葡萄糖耐量受损，发生 2 型糖尿病（T2D）的风险更高。我们旨在评估已发表的 T2D 风险预测模型在中国 IH 人群中的表现，为他们提供选择初级糖尿病预防措施的信息。
系统地检索了亚洲人群中 T2D 风险预测模型的文献，这些模型符合以下条件：在没有糖尿病的亚洲成年人前瞻性队列中建立，使用常规可获得的变量来预测 T2D 的未来风险。这些亚洲衍生模型和五个预先指定的非亚洲衍生 T2D 风险预测模型分为 BASIC（仅临床变量）和 EXTENDED（加实验室变量）版本，并在中国三个前瞻性 IH 队列（ACE[3241 例]、泸州[1333 例]和 TCLSIH[1702 例]）中对其进行验证。使用 C 统计量（discrimination）和 Hosmer-Lemeshow 检验（calibration）评估模型性能。
共确定了 44 项亚洲和 5 项非亚洲研究，包括 21 项 BASIC 和 46 项 EXTENDED T2D 风险预测模型用于验证。其中大多数为高（n=43，87.8%）或不明确（n=3，6.1%）偏倚风险，只有 3 项研究（6.1%）为低偏倚风险。BASIC 模型的区分度较差，在 ACE、泸州和 TCLSIH 队列中的 C 统计量分别为 0.52-0.60、0.50-0.59 和 0.50-0.64。EXTENDED 模型的区分度较差至可接受，C 统计量分别为 0.54-0.73、0.52-0.67 和 0.59-0.78。15 项 BASIC 和 40 项 EXTENDED 模型的校准较差（P<0.05），预测的观察到的糖尿病风险过高或过低。在三个队列中，大多数重新校准的模型显示出更好的校准，但仍有适度至严重高估糖尿病风险。NAVIGATOR 模型在三个队列中的区分度最好，但校准较差（P<0.05）。
在中国 IH 人群中，先前发表的用于预测 T2D 的 BASIC 模型并未表现出良好的区分度或校准度。一些 EXTENDED 模型表现更好，但在中国 IH 人群中仍需要一种可靠的 T2D 风险预测工具。
