Development and Validation of a Risk Prediction Model for Adverse Outcomes in Patients with Suspected Coronary Artery Disease and No Significant Stenosis on Angiography: a Retrospective Cohort Study

Lei Zhu,Zheng-Kai Xue, Xue Wu,JingKun Zhang,Su-Tao Hu,Yu-Kun Zhang, Tian-Shu Gu,Tong Liu,Seung-Woon Rha,Kang-Yin Chen

BMJ open（2025）

3 Department of Anaesthesiology | Cardiovascular Center | 1Korea University Guro Hospital

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Abstract

OBJECTIVES:To develop and validate a risk prediction model for adverse outcomes in patients with angina with non-obstructive coronary arteries (ANOCA) confirmed by invasive coronary angiography. DESIGN:Retrospective cohort study. SETTING:A tertiary cardiovascular care centre in China. PARTICIPANTS:From 17 816 consecutive patients undergoing coronary angiography for suspected coronary artery disease, 5934 met ANOCA criteria after rigorous exclusion: (1) significant stenosis (≥50% luminal narrowing), (2) established coronary artery disease history, (3) incomplete baseline/follow-up data, (4) non-cardiovascular life-limiting conditions. PRIMARY AND SECONDARY OUTCOME MEASURES:The primary outcome was a composite of all-cause death, non-fatal myocardial infarction (MI), stroke and repeat percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG). The secondary outcome was major adverse cardiovascular events, defined as cardiac-related death, non-fatal MI, non-fatal stroke, repeat PCI and CABG. RESULTS:The derivation cohort (n=4452) and validation cohort (n=1482) demonstrated comparable baseline characteristics. The nomogram incorporated eight prognosticators: age, haemoglobin, serum urea, serum sodium, alanine aminotransferase/aspartate aminotransferase ratio, N-terminal pro-B-type natriuretic peptide (NT-proBNP), left atrial diameter and left ventricular ejection fraction. The prediction model showed robust discrimination for primary endpoint, achieving area under the curve (AUC) values of 0.82 (1 year), 0.90 (2 years) and 0.89 (3 years) in the derivation cohort, with corresponding validation cohort AUCs of 0.75, 0.77 and 0.78. Calibration plots revealed close alignment between predicted and actual event-free survival probabilities in both cohorts. Risk stratification identified two distinct prognostic groups with significant survival differences (log-rank p<0.0001). CONCLUSIONS:This predictive model integrates routinely available clinical parameters to accurately stratify mortality and cardiovascular risk in ANOCA patients, providing a potential valuable decision-support tool for personalised therapeutic strategies.

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【要点】：本研究开发并验证了一种用于预测无显著冠状动脉狭窄的疑似冠心病患者不良结局的风险预测模型，该模型具有良好的区分度和校准度，可用于指导个性化治疗方案。

【方法】：通过回顾性队列研究，对经冠状动脉造影确认的无显著狭窄的冠心病患者（ANOCA）进行了风险预测模型的开发与验证。

【实验】：研究纳入了17,816例行冠状动脉造影的患者，其中5,934名符合ANOCA标准。实验分为 derivation cohort（n=4452）和validation cohort（n=1482），使用13个临床参数最终筛选出8个预后因素构建列线图模型。模型在 derivation cohort 中展现了良好的区分度，AUC值分别为1年时0.82、2年时0.90和3年时0.89，而在 validation cohort 中AUC值分别为0.75、0.77和0.78，校准图显示预测与实际事件无生存率之间有很好的吻合度。