Utility of the China-PAR Score in Predicting Secondary Events Among Patients Undergoing Percutaneous Coronary Intervention
Coronary artery disease (CAD) remains the leading cause of global mortality, despite advancements in treatments like percutaneous coronary intervention (PCI), which have significantly reduced acute-phase mortality and transitioned patients into chronic cardiovascular disease (CVD) management. This shift underscores the critical need for effective secondary prevention strategies to mitigate long-term adverse outcomes. Current risk assessment tools for secondary prevention, such as the Global Registry of Acute Coronary Events (GRACE) and Patterns of Non-Adherence to Anti-Platelet Regimen in Stented Patients (PARIS) scores, face limitations in applicability to Chinese populations due to their reliance on clinical parameters unfamiliar to the general public and suboptimal performance in this demographic. In contrast, the China-PAR (Prediction for Atherosclerotic Cardiovascular Disease Risk in China) score, a guideline-endorsed tool for primary prevention, utilizes conventional risk factors and demonstrates potential for broader utility. This study investigates the adaptability of the China-PAR score for predicting secondary events in CAD patients post-PCI, offering a pragmatic tool for risk stratification and personalized prevention.
Study Design and Methodology
The study enrolled 10,724 CAD patients who underwent PCI at Fuwai Hospital (Beijing, China) in 2013. After excluding 482 patients with incomplete data, 9,361 individuals were included in the final analysis. Follow-up continued until 2019, with 9,843 patients (91.8%) completing a 5-year follow-up. Endpoints included all-cause death and major adverse cardiovascular and cerebrovascular events (MACCEs), defined as myocardial infarction (MI), stroke, stent thrombosis, or cardiac death. Data were collected from medical records, telephone interviews, and standardized follow-up protocols, with endpoints adjudicated by independent cardiologists.
The China-PAR score, originally designed for primary prevention, was adapted to accommodate data limitations in the study cohort. Waist circumference and family history of CVD in the original score were replaced with body mass index (BMI) and family history of CAD, respectively. Validation using the China-PAR derivation cohort confirmed comparable discrimination capacity between the revised and original scores, with C-indices of 0.792 (95% CI: 0.772–0.812) for males and 0.807 (95% CI: 0.783–0.832) for females. Patients were stratified into four risk categories based on the revised score: low (<5.0%), moderate (5.0–<10.0%), high (10.0–<20.0%), and very high (≥20.0%).
Key Findings
During a median follow-up of 4.9 years, 365 all-cause deaths and 1,048 MACCEs were recorded, corresponding to event rates of 7.9 and 23.7 per 1,000 person-years, respectively. The revised China-PAR score demonstrated a strong, graded association with secondary events:
- All-Cause Death: Compared to the low-risk group, hazard ratios (HRs) for all-cause death were 1.39 (95% CI: 0.96–2.01), 2.44 (95% CI: 1.74–3.41), and 4.95 (95% CI: 3.46–7.07) for moderate-, high-, and very high-risk groups, respectively.
- MACCEs: Similarly, MACCE risks increased across risk categories, with HRs of 1.25 (95% CI: 1.03–1.50), 1.78 (95% CI: 1.49–2.12), and 2.28 (95% CI: 1.85–2.82) for moderate-, high-, and very high-risk groups.
- MACCE Subtypes: The score significantly predicted stroke (HR for very high risk: 2.46; 95% CI: 1.71–3.55), stent thrombosis (HR: 2.20; 95% CI: 1.22–3.97), and cardiac death (HR: 5.12; 95% CI: 3.21–8.18), but not myocardial infarction.
Dose-response analyses revealed linear relationships between the revised China-PAR score and risks of all-cause death, MACCEs, stent thrombosis, and cardiac death. A non-linear association was observed for stroke, particularly in females.
Discrimination Performance
The revised China-PAR score exhibited moderate discrimination for all-cause death (C-index: 0.661; 95% CI: 0.632–0.689), comparable to the GRACE score (0.671) and superior to the PARIS score (0.598). For MACCEs, discrimination was modest (C-index: 0.588) but slightly better than GRACE (0.572) and PARIS (0.570). Subgroup analyses indicated consistent performance across sexes, though males showed marginally higher HRs and C-indices.
Subgroup and Sensitivity Analyses
Stratification by prior CAD history (MI, PCI, or coronary artery bypass grafting) revealed no significant interaction effects, though risk estimates were slightly higher in patients without prior CAD. Sensitivity analyses excluding events occurring within 1 or 3 months post-PCI confirmed the robustness of associations, affirming the score’s utility for long-term risk prediction.
Clinical and Public Health Implications
The China-PAR score’s strength lies in its simplicity and accessibility, using routinely collected risk factors without requiring specialized clinical parameters. This facilitates its adoption as a self-assessment tool for patients and a decision aid for clinicians, particularly in resource-limited settings. By identifying high-risk individuals, the score enables targeted intensification of secondary prevention measures, such as lifestyle modifications, lipid-lowering therapies, and antiplatelet regimens.
However, the score’s moderate discrimination highlights areas for improvement. The exclusion of treatment-related factors (e.g., statin use or antiplatelet adherence) likely limits its precision, suggesting future iterations could integrate therapeutic variables to enhance predictive accuracy. Additionally, the single-center design and lack of waist circumference data necessitate validation in multicenter cohorts and diverse populations.
Conclusion
This study demonstrates the China-PAR score’s potential as a pragmatic tool for secondary prevention in CAD patients post-PCI. Its ability to stratify long-term risks of death and MACCEs using accessible risk factors bridges a critical gap between primary and secondary prevention, empowering patients and clinicians to make informed, risk-based decisions. Future research should focus on refining the score with treatment-related variables and validating its applicability across broader populations and CVD subtypes.
doi.org/10.1097/CM9.0000000000003467
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