Validation of 10-Year Stroke Prediction Scores in a Community-Based Cohort of Chinese Older Adults - Zhang, Yanlei; Fang, Xianghua; Guan, Shaochen; Wu, Xiaoguang; Liu, Hongjun; Wang, Chunxiu; Zhang, Zhongying; Gu, Xiang; Liu, Chunxiao; Cheng, Jianhua (Frontiers in Neurology, 2020)
A stroke prediction model based on the Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR) project was developed. We compared its predictive ability with the revised Framingham Stroke Risk Score (R-FSRS) for 5-year stroke incidence in a community cohort of Chinese adults, namely the Beijing Longitudinal Study of Aging (BLSA). Calibration, discrimination and recalibration were used to compare the predictive ability between the two prediction models. Category-less net reclassification improvement (NRI) and integrated discrimination improvement (IDI) values were also assessed. During a mean follow-up duration of 5.1 years, 106 incident fatal or non-fatal strokes occurred among 1203 participants aged 55 to 84 years. The R-FSRS applied to our cohort underestimated the 5-year risk for stroke in men and women. China-PAR performed better than the R-FSRS in terms of calibration (men, R-FSRS: χ2-value 144.2 [P < 0.001], China-PAR: 10.4 [P = 0.238]; women, R-FSRS: 280.1 [P<0.001], China-PAR: 12.5 [P = 0.129]). In terms of discrimination, R-FSRS and China-PAR models performed modestly in our cohort (C-statistic 0.603 [95% CI: 0.560-0.644] for men using China-PAR and 0.568 [95% CI: 0.524-0.610] using the R-FSRS; the corresponding numbers for women were 0.602 [95% CI: 0.564-0.639] and 0.575 [95% CI: 0.537-0.613). The recalibrated China-PAR model significantly improved the discrimination in C statistics and produced higher category-less NRI and IDI for stroke incidence than the R-FSRS. Although China-PAR fairly estimated stroke risk in our cohort, it did not sufficiently identify adults at high risk of stroke. Caution would be exercised by practitioners in applying the original China-PAR to Chinese older adults. Further studies are needed to develop an adequate prediction model based on the recalibrated China-PAR or to find new risk markers which could upgrade this model.