Wen-Kai Wong, Fumihiko Takeuchi, Le Thi Phuong Thao, Stephen J Nicholls, Derek P Chew, Karlheinz Peter
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引用次数: 0
Abstract
Aim: To evaluate whether integrating Apolipoprotein B (ApoB) into the SCORE2 cardiovascular risk prediction framework improves its predictive accuracy and clinical applicability within the UK Biobank population.
Method: A 10-year prospective cohort study was conducted with 448,303 UK Biobank participants eligible for SCORE2 calculation. Three approaches were employed: (1) threshold analysis to determine the optimal ApoB cutoff for cardiovascular disease (CVD) risk prediction using Youden's Index, (2) assessment of the synergistic effect of SCORE2 and ApoB through concordant and discordant classifications, and (3) recalibration of the SCORE2 model by incorporating ApoB as an additional predictor.
Results: Each 0.2 g/L increase in ApoB was associated with an increased subdistribution hazard for CVD events (SHR: 1.13; 95% CI: 1.11-1.14, p < 0.001), accounting for non-cardiovascular death as a competing risk. Threshold analysis identified an optimal ApoB cutoff at 1.18 g/L; however, it demonstrated limited discriminatory performance (area under the curve 0.54), with low sensitivity (32.4%) and moderate specificity (74.4%). Individuals with both low ApoB (<1.18 g/L) and low SCORE2 risk (<5%) had a lower CVD incidence rate (232.51 per 100,000 person-years) compared to those identified as low risk by SCORE2 alone (253.69 per 100,000 person-years). Integration of ApoB into the SCORE2 model did not significantly improve the model discrimination, calibration and net reclassification improvement.
Conclusion: ApoB exhibited a dose-response relationship with cardiovascular risk but had limited standalone predictive utility within the UK Biobank population. However, combining ApoB with SCORE2 thresholds improved the identification of low-risk individuals, suggesting a complementary role for ApoB in refining cardiovascular risk stratification.
期刊介绍:
European Journal of Preventive Cardiology (EJPC) is an official journal of the European Society of Cardiology (ESC) and the European Association of Preventive Cardiology (EAPC). The journal covers a wide range of scientific, clinical, and public health disciplines related to cardiovascular disease prevention, risk factor management, cardiovascular rehabilitation, population science and public health, and exercise physiology. The categories covered by the journal include classical risk factors and treatment, lifestyle risk factors, non-modifiable cardiovascular risk factors, cardiovascular conditions, concomitant pathological conditions, sport cardiology, diagnostic tests, care settings, epidemiology, pharmacology and pharmacotherapy, machine learning, and artificial intelligence.