Qiuyue Zhang, Qi Zhang, Zhi-juan Duan, Pu Chen, Jing-jing Chen, Ming-xv Li, Jing-jie Zhang, Yan-hong Huo, Wu-xing Zhang, Chen Yang, Yu Zhang, Xiangmei Chen, G. Cai
{"title":"国际 IgA 肾病预测工具在老年患者中的外部验证","authors":"Qiuyue Zhang, Qi Zhang, Zhi-juan Duan, Pu Chen, Jing-jing Chen, Ming-xv Li, Jing-jie Zhang, Yan-hong Huo, Wu-xing Zhang, Chen Yang, Yu Zhang, Xiangmei Chen, G. Cai","doi":"10.2147/cia.s455115","DOIUrl":null,"url":null,"abstract":"Purpose: 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.","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":" 44","pages":""},"PeriodicalIF":4.3000,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"External Validation of the International IgA Nephropathy Prediction Tool in Older Adult Patients\",\"authors\":\"Qiuyue Zhang, Qi Zhang, Zhi-juan Duan, Pu Chen, Jing-jing Chen, Ming-xv Li, Jing-jie Zhang, Yan-hong Huo, Wu-xing Zhang, Chen Yang, Yu Zhang, Xiangmei Chen, G. Cai\",\"doi\":\"10.2147/cia.s455115\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Purpose: 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.\",\"PeriodicalId\":3,\"journal\":{\"name\":\"ACS Applied Electronic Materials\",\"volume\":\" 44\",\"pages\":\"\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Electronic Materials\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2147/cia.s455115\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/cia.s455115","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
External Validation of the International IgA Nephropathy Prediction Tool in Older Adult Patients
Purpose: 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.
期刊介绍:
ACS Applied Electronic Materials is an interdisciplinary journal publishing original research covering all aspects of electronic materials. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials science, engineering, optics, physics, and chemistry into important applications of electronic materials. Sample research topics that span the journal's scope are inorganic, organic, ionic and polymeric materials with properties that include conducting, semiconducting, superconducting, insulating, dielectric, magnetic, optoelectronic, piezoelectric, ferroelectric and thermoelectric.
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