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Qiuyue Zhang,1– 5,* Qi Zhang,6,* Zhiyu Duan,2– 5,7 Pu Chen,2– 5 Jing-jing Chen,2– 5 Ming-xv Li,8 Jing-jie Zhang,9 Yan-hong Huo,10 Wu-xing Zhang,11 Chen Yang,12 Yu Zhang,12 Xiangmei Chen,2– 5 Guangyan Cai2– 5 1Chinese PLA Medical School, Beijing, People’s Republic of China; 2Department of Nephrology, First Medical Center of Chinese PLA General Hospital, Beijing, People’s Republic of China; 3National Key Laboratory of Kidney Diseases, Beijing, People’s Republic of China; 4National Clinical Research Center for Kidney Diseases, Beijing, People’s Republic of China; 5Beijing Key Laboratory of Kidney Diseases Research, Beijing, People’s Republic of China; 6Department of Nephrology, Capital Medical University Electric Power Teaching Hospital, Beijing, People’s Republic of China; 7Department of Nephrology, Fourth Medical Center of Chinese PLA General Hospital, Beijing, People’s Republic of China; 8Department of Nephrology, Sixth Medical Center of Chinese PLA General Hospital, Beijing, People’s Republic of China; 9Department of Nephrology, Third Medical Center of Chinese PLA General Hospital, Beijing, People’s Republic of China; 10Department of Nephrology, Seventh Medical Center of Chinese PLA General Hospital, Beijing, People’s Republic of China; 11Department of Nephrology, Eighth Medical Center of Chinese PLA General Hospital, Beijing, People’s Republic of China; 12School of Medicine, Nankai University, Tianjin, People’s Republic of China*These authors contributed equally to this workCorrespondence: Guangyan Cai, Department of Nephrology, First Medical Center of Chinese PLA General Hospital, Hospital 28 Fuxing Road, Beijing, 100853, People’s Republic of China, Email caiguangyan@sina.comPurpose: The International IgA Nephropathy Prediction Tool (IIgAN-PT) can predict the risk of End-stage renal disease (ESRD) or estimated glomerular filtration rate (eGFR) decline ≥ 50% for adult IgAN patients. Considering the differential progression between older adult and adult patients, this study aims to externally validate its performance in the older adult cohort.Patients and Methods: We analyzed 165 IgAN patients aged 60 and above from six medical centers, categorizing them by their predicted risk. The primary outcome was a ≥ 50% reduction in estimated glomerular filtration rate (eGFR) or kidney failure. Evaluation of both models involved concordance statistics (C-statistics), time-dependent receiver operating characteristic (ROC) curves, Kaplan–Meier survival curves, and calibration plots. Comparative reclassification was conducted using net reclassification improvement (NRI) and integrated discrimination improvement (IDI).Results: The study included 165 Chinese patients (median age 64, 60% male), with a median follow-up of 5.1 years. Of these, 21% reached the primary outcome. Both models with or without race demonstrated good discrimination (C-statistics 0.788 and 0.790, respectively). Survival curves for risk groups were well-separated. The full model without race more accurately predicted 5-year risks, whereas the full model with race tended to overestimate risks after 3 years. No significant reclassification improvement was noted in the full model without race (NRI 0.09, 95% CI: − 0.27 to 0.34; IDI 0.003, 95% CI: − 0.009 to 0.019).Conclusion: : Both models exhibited excellent discrimination among older adult IgAN patients. The full model without race demonstrated superior calibration in predicting the 5-year risk.Keywords: IgAN Progression, statistical validation, risk analysis, progression risk, prediction models, older adults |
