School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
HKU Business School, The University of Hong Kong, Hong Kong SAR, China.
Diabetes Obes Metab. 2024 May;26(5):1697-1705. doi: 10.1111/dom.15474. Epub 2024 Jan 31.
To validate cardiovascular risk prediction models for individuals with diabetes using the UK Biobank in order to assess their applicability.
We externally validated 19 cardiovascular risk scores from seven risk prediction models (Chang et al., Framingham, University of Hong Kong-Singapore [HKU-SG], Li et al, RECODe [risk equations for complications of type 2 diabetes], SCORE [Systematic Coronary Risk Evaluation] and the UK Prospective Diabetes Study Outcomes Model 2 [UKPDS OM2]), identified from systematic reviews, using UK Biobank data from 2006 to 2021 (n = 23 685; participant age 40-71 years, 63.5% male). We evaluated performance by assessing the discrimination and calibration of the models for the endpoints of mortality, cardiovascular mortality, congestive heart failure, myocardial infarction, stroke, and ischaemic heart disease.
Over a total of 269 430 person-years of follow-up (median 11.89 years), the models showed low-to-moderate discrimination performance on external validation (concordance indices [c-indices] 0.50-0.71). Most models had low calibration with overprediction of the observed risk. RECODe outperformed other models across four comparable endpoints for discrimination: all-cause mortality (c-index 0.67, 95% confidence interval [CI] 0.65-0.69), congestive heart failure (c-index 0.71, 95% CI 0.69-0.72), myocardial infarction (c-index 0.67, 95% CI 0.65-0.68); and stroke (c-index 0.65, 95% CI 0.62-0.68), and for calibration (except for all-cause mortality). The UKPDS OM2 had comparable performance to RECODe for all-cause mortality (c-index 0.67, 95% CI 0.66-0.69) and cardiovascular mortality (c-index 0.71, 95% CI 0.70-0.73), but worse performance for other outcomes. The models performed better for younger participants and somewhat better for non-White ethnicities. Models developed from non-Western datasets showed worse performance in our UK-based validation set.
The RECODe model led to better risk estimations in this predominantly White European population. Further validation is needed in non-Western populations to assess generalizability to other populations.
利用英国生物库验证适用于糖尿病患者的心血管风险预测模型，以评估其适用性。
我们使用 2006 年至 2021 年英国生物库的数据（n=23685；参与者年龄 40-71 岁，63.5%为男性），对系统评价中确定的来自七个风险预测模型的 19 个心血管风险评分（Chang 等人、Framingham、香港大学-新加坡[HKU-SG]、Li 等人、RECODe[2 型糖尿病并发症风险方程]、SCORE[系统冠状动脉风险评估]和英国前瞻性糖尿病研究结局模型 2[UKPDS OM2]）进行外部验证。我们通过评估模型在终点（死亡率、心血管死亡率、充血性心力衰竭、心肌梗死、卒中和缺血性心脏病）的区分度和校准度来评估模型的性能。
在总计 269430 人年的随访期间（中位数 11.89 年），模型在外部验证中的区分度表现为低到中等（一致性指数[c-index]0.50-0.71）。大多数模型的校准度较低，观察到的风险存在高估。RECODe 在四个可比终点的区分度方面优于其他模型：全因死亡率（c-index0.67，95%置信区间[CI]0.65-0.69）、充血性心力衰竭（c-index0.71，95%CI0.69-0.72）、心肌梗死（c-index0.67，95%CI0.65-0.68）和卒中等（c-index0.65，95%CI0.62-0.68），以及校准度（除全因死亡率外）。UKPDS OM2 在全因死亡率（c-index0.67，95%CI0.66-0.69）和心血管死亡率（c-index0.71，95%CI0.70-0.73）方面与 RECODe 具有相当的性能，但在其他结局方面表现稍差。该模型在年轻参与者中的表现更好，在非白种人群体中的表现稍好。来自非西方数据集的模型在我们基于英国的验证集中表现不佳。
RECODe 模型在以白种欧洲人为主的人群中产生了更好的风险估计。需要在非西方人群中进一步验证，以评估其在其他人群中的普遍性。
