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Background: This study aimed to evaluate the performance of a modified U.S. (MUS) model for risk prediction of cardiovascular (CV) events in Asian patients and compare it to European and Japanese models., Methods: The MUS model, based on the US ACC/AHA 2018 lipid treatment guideline, was employed to stratify patients under primary or secondary prevention. Two multi-center prospective observational registry cohorts, T-SPARCLE and T-PPARCLE, were used to validate the scoring system, and the primary outcome was the time to first occurrence/recurrence of major adverse cardiac events (MACEs). The MUS model's performance was compared to other models from Europe and Japan., Results: A total of 10,733 patients with the mean age of 64.2 (SD: 11.9) and 36.5% female were followed up for a median of 5.4 years. The MUS model was validated, with an AUC score of 0.73 (95% CI 0.68-0.78). The European and Japanese models had AUC scores ranging from 0.6 to 0.7. The MUS model categorized patients into four distinct CV risk groups, with hazard ratios (HRs) as follows: very high- vs. high-risk group (HR = 1.91, 95% CI 1.53-2.39), high- vs. moderate-risk group (HR = 2.08, 95% CI 1.60-2.69), and moderate- vs. low-risk group (HR = 3.14, 95% CI 1.63-6.03). After adjusting for the MUS model, a history of atherosclerotic vascular disease (ASCVD) was not a significant predictor of adverse cardiovascular outcomes within each risk group., Conclusion: The MUS model is an effective tool for risk stratification in Asian patients with and without ASCVD, accurately predicting MACEs and performing comparably or better than other established risk models. Our findings suggest that patient management should focus on background risk factors instead of solely on primary or secondary prevention., Competing Interests: Conflicts of interest The authors declared no conflicts of interest., (© 2023 The Authors. Published by Elsevier B.V. on behalf of Chang Gung University. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)