Li Miaohong, Lin Yifen, Zhong Xiangbin, Huang Rihua, Zhang Shaozhao, Liu Menghui, Liu Sen, Ye Xiaomin, Xu Xinghao, Huang Yiquan, Xiong Zhenyu, Guo Yue, Liao Xinxue, Zhuang Xiaodong
Cardiology Department, The First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan 2nd Road, Guangzhou 510080, China.
NHC Key Laboratory of Assisted Circulation, Sun Yat-sen University, 58 Zhongshan 2nd Road, Guangzhou 510080, China.
Eur J Prev Cardiol. 2023 Oct 10;30(14):1427-1438. doi: 10.1093/eurjpc/zwad106.
Prediabetes is a highly heterogenous metabolic state with increased risk of cardiovascular disease (CVD). Current guidelines raised the necessity of CVD risk scoring for prediabetes without clear recommendations. Thus, this study aimed to systematically assess the performance of 11 models, including five general population-based and six diabetes-specific CVD risk scores, in prediabetes.
A cohort of individuals aged 40-69 years with prediabetes (HbA1c ≥ 5.7 and <6.5%) and without baseline CVD or known diabetes was identified from the UK Biobank, which was used to validate 11 prediction models for estimating 10- or 5-year risk of CVD. Model discrimination and calibration were evaluated by Harrell's C-statistic and calibration plots, respectively. We further performed decision curve analyses to assess the clinical usefulness.Overall, 56 831 prediabetic individuals were included, of which 4303 incident CVD events occurred within a median follow-up of 8.9 years. All the 11 risk scores assessed had modest C-statistics for discrimination ranging from 0.647 to 0.680 in prediabetes. Scores developed in the general population did not outperform those diabetes-specific models (C-statistics, 0.647-0.675 vs. 0.647-0.680), while the PREDICT-1° Diabetes equation developed for Type 2 diabetes performed best [0.680 (95% confidence interval, 0.672-0.689)]. The calibration plots suggested overall poor calibration except that the PREDICT-1° Diabetes equation calibrated well after recalibration. The decision curves generally indicated moderate clinical usefulness of each model, especially worse within high threshold probabilities.
Neither risk stratification schemes for the general population nor those specific for Type 2 diabetes performed well in the prediabetic population. The PREDICT-1° Diabetes equation could be a substitute in the absence of better alternatives, rather than the general population-based scores. More precise and targeted risk assessment tools for this population remain to be established.
糖尿病前期是一种高度异质性的代谢状态，心血管疾病（CVD）风险增加。当前指南提出了对糖尿病前期进行CVD风险评分的必要性，但没有明确建议。因此，本研究旨在系统评估11种模型在糖尿病前期的表现，包括5种基于普通人群的模型和6种糖尿病特异性CVD风险评分。
从英国生物银行中识别出一组年龄在40 - 69岁之间、患有糖尿病前期（糖化血红蛋白[HbA1c]≥5.7%且<6.5%）且无基线CVD或已知糖尿病的个体，用于验证11种预测模型，以估计10年或5年的CVD风险。分别通过Harrell C统计量和校准图评估模型的区分度和校准情况。我们进一步进行决策曲线分析以评估临床实用性。总体而言，纳入了56831名糖尿病前期个体，其中4303例发生CVD事件，中位随访时间为8.9年。所有评估的11种风险评分在糖尿病前期的区分度C统计量适中，范围为0.647至0.680。在普通人群中开发的评分并不优于糖尿病特异性模型（C统计量，0.647 - 0.675对0.647 - 0.680），而针对2型糖尿病开发的PREDICT - 1°糖尿病方程表现最佳[0.680（95%置信区间，0.672 - 0.689）]。校准图显示除PREDICT - 1°糖尿病方程重新校准后校准良好外，总体校准较差。决策曲线总体表明每个模型的临床实用性中等，特别是在高阈值概率范围内更差。
普通人群的风险分层方案和2型糖尿病特异性方案在糖尿病前期人群中表现均不佳。在没有更好选择的情况下，PREDICT - 1°糖尿病方程可以作为替代，而不是基于普通人群的评分。针对该人群更精确和有针对性的风险评估工具仍有待建立。
