Ling Pan , Jinwei Wang , Yang Deng , Yexiang Sun , Zhenyu Nie , Xiaoyu Sun , Chao Yang , Guohui Ding , Ming-Hui Zhao , Yunhua Liao , Luxia Zhang
{"title":"中国城市社区慢性肾病患者肾衰竭风险方程的外部验证","authors":"Ling Pan , Jinwei Wang , Yang Deng , Yexiang Sun , Zhenyu Nie , Xiaoyu Sun , Chao Yang , Guohui Ding , Ming-Hui Zhao , Yunhua Liao , Luxia Zhang","doi":"10.1016/j.xkme.2024.100817","DOIUrl":null,"url":null,"abstract":"<div><h3>Rationale & Objective</h3><p>The Kidney Failure Risk Equations have been proven to perform well in multinational databases, whereas validation in Asian populations is lacking. This study sought to externally validate the equations in a community-based chronic kidney disease cohort in China.</p></div><div><h3>Study Design</h3><p>A retrospective cohort study.</p></div><div><h3>Setting & Participants</h3><p>Patients with and estimated glomerular filtration rate (eGFR) < 60<!--> <!-->mL/min/1.73<!--> <!-->m<sup>2</sup> dwelling in an industrialized coastal city of China.</p></div><div><h3>Exposure</h3><p>Age, sex, eGFR, and albuminuria were included in the 4-variable model, whereas serum calcium, phosphate, bicarbonate, and albumin levels were added to the previously noted variables in the 8-variable model.</p></div><div><h3>Outcome</h3><p>Initiation of long-term dialysis treatment.</p></div><div><h3>Analytical Approach</h3><p>Model discrimination, calibration, and clinical utility were evaluated by Harrell’s C statistic, calibration plots, and decision curve analysis, respectively.</p></div><div><h3>Results</h3><p>A total of 4,587 participants were enrolled for validation of the 4-variable model, whereas 1,414 were enrolled for the 8-variable model. The median times of follow-up were 4.0 (interquartile range: 2.6-6.3) years for the 4-variable model and 3.4 (2.2-5.6) years for the 8-variable model. For the 4-variable model, the C statistics were 0.750 (95% CI: 0.615-0.885) for the 2-year model and 0.766 (0.625-0.907) for the 5-year model, whereas the values were 0.756 (0.629-0.883) and 0.774 (0.641-0.907), respectively, for the 8-variable model. Calibration was acceptable for both the 4-variable and 8-variable models. Decision curve analysis for the models at the 5-year scale performed better throughout different net benefit thresholds than the eGFR-based (<30<!--> <!-->mL/min/1.73<!--> <!-->m<sup>2</sup>) strategy.</p></div><div><h3>Limitations</h3><p>A large proportion of patients lack albuminuria measurements, and only a subset of population could provide complete data for the 8-variable equation.</p></div><div><h3>Conclusions</h3><p>The kidney failure risk equations showed acceptable discrimination and calibration and better clinical utility than the eGFR-based strategy for incidence of kidney failure among community-based urban Chinese patients with chronic kidney disease.</p></div><div><h3>Plain-Language Summary</h3><p>Accurate and reliable risk evaluation of chronic kidney disease (CKD) prognosis can be helpful for physicians to make decisions concerning treatment opportunity and therapeutic strategy. The kidney failure risk equation is an outstanding model for predicting risk of kidney failure among patients with CKD. However, the equation is lacking validation among Chinese populations. In the current study, we demonstrated that the equation had good discrimination among an urban community-based cohort of patients with CKD in China. The calibration was also acceptable. Decision curve analysis also showed that the equation performed better than a traditional kidney function-based strategy. The results provide the basis for using predictions derived from the kidney failure risk equation to improve the management of patients with CKD in community settings in China.</p></div>","PeriodicalId":17885,"journal":{"name":"Kidney Medicine","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2590059524000281/pdfft?md5=e3746bf0072de8cf7641cb8f9de6a004&pid=1-s2.0-S2590059524000281-main.pdf","citationCount":"0","resultStr":"{\"title\":\"External Validation of the Kidney Failure Risk Equation Among Urban Community-Based Chinese Patients With CKD\",\"authors\":\"Ling Pan , Jinwei Wang , Yang Deng , Yexiang Sun , Zhenyu Nie , Xiaoyu Sun , Chao Yang , Guohui Ding , Ming-Hui Zhao , Yunhua Liao , Luxia Zhang\",\"doi\":\"10.1016/j.xkme.2024.100817\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Rationale & Objective</h3><p>The Kidney Failure Risk Equations have been proven to perform well in multinational databases, whereas validation in Asian populations is lacking. This study sought to externally validate the equations in a community-based chronic kidney disease cohort in China.</p></div><div><h3>Study Design</h3><p>A retrospective cohort study.</p></div><div><h3>Setting & Participants</h3><p>Patients with and estimated glomerular filtration rate (eGFR) < 60<!--> <!-->mL/min/1.73<!--> <!-->m<sup>2</sup> dwelling in an industrialized coastal city of China.</p></div><div><h3>Exposure</h3><p>Age, sex, eGFR, and albuminuria were included in the 4-variable model, whereas serum calcium, phosphate, bicarbonate, and albumin levels were added to the previously noted variables in the 8-variable model.</p></div><div><h3>Outcome</h3><p>Initiation of long-term dialysis treatment.</p></div><div><h3>Analytical Approach</h3><p>Model discrimination, calibration, and clinical utility were evaluated by Harrell’s C statistic, calibration plots, and decision curve analysis, respectively.</p></div><div><h3>Results</h3><p>A total of 4,587 participants were enrolled for validation of the 4-variable model, whereas 1,414 were enrolled for the 8-variable model. The median times of follow-up were 4.0 (interquartile range: 2.6-6.3) years for the 4-variable model and 3.4 (2.2-5.6) years for the 8-variable model. For the 4-variable model, the C statistics were 0.750 (95% CI: 0.615-0.885) for the 2-year model and 0.766 (0.625-0.907) for the 5-year model, whereas the values were 0.756 (0.629-0.883) and 0.774 (0.641-0.907), respectively, for the 8-variable model. Calibration was acceptable for both the 4-variable and 8-variable models. Decision curve analysis for the models at the 5-year scale performed better throughout different net benefit thresholds than the eGFR-based (<30<!--> <!-->mL/min/1.73<!--> <!-->m<sup>2</sup>) strategy.</p></div><div><h3>Limitations</h3><p>A large proportion of patients lack albuminuria measurements, and only a subset of population could provide complete data for the 8-variable equation.</p></div><div><h3>Conclusions</h3><p>The kidney failure risk equations showed acceptable discrimination and calibration and better clinical utility than the eGFR-based strategy for incidence of kidney failure among community-based urban Chinese patients with chronic kidney disease.</p></div><div><h3>Plain-Language Summary</h3><p>Accurate and reliable risk evaluation of chronic kidney disease (CKD) prognosis can be helpful for physicians to make decisions concerning treatment opportunity and therapeutic strategy. The kidney failure risk equation is an outstanding model for predicting risk of kidney failure among patients with CKD. However, the equation is lacking validation among Chinese populations. In the current study, we demonstrated that the equation had good discrimination among an urban community-based cohort of patients with CKD in China. The calibration was also acceptable. Decision curve analysis also showed that the equation performed better than a traditional kidney function-based strategy. The results provide the basis for using predictions derived from the kidney failure risk equation to improve the management of patients with CKD in community settings in China.</p></div>\",\"PeriodicalId\":17885,\"journal\":{\"name\":\"Kidney Medicine\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-03-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2590059524000281/pdfft?md5=e3746bf0072de8cf7641cb8f9de6a004&pid=1-s2.0-S2590059524000281-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Kidney Medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2590059524000281\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"UROLOGY & NEPHROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Kidney Medicine","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2590059524000281","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"UROLOGY & NEPHROLOGY","Score":null,"Total":0}
External Validation of the Kidney Failure Risk Equation Among Urban Community-Based Chinese Patients With CKD
Rationale & Objective
The Kidney Failure Risk Equations have been proven to perform well in multinational databases, whereas validation in Asian populations is lacking. This study sought to externally validate the equations in a community-based chronic kidney disease cohort in China.
Study Design
A retrospective cohort study.
Setting & Participants
Patients with and estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2 dwelling in an industrialized coastal city of China.
Exposure
Age, sex, eGFR, and albuminuria were included in the 4-variable model, whereas serum calcium, phosphate, bicarbonate, and albumin levels were added to the previously noted variables in the 8-variable model.
Outcome
Initiation of long-term dialysis treatment.
Analytical Approach
Model discrimination, calibration, and clinical utility were evaluated by Harrell’s C statistic, calibration plots, and decision curve analysis, respectively.
Results
A total of 4,587 participants were enrolled for validation of the 4-variable model, whereas 1,414 were enrolled for the 8-variable model. The median times of follow-up were 4.0 (interquartile range: 2.6-6.3) years for the 4-variable model and 3.4 (2.2-5.6) years for the 8-variable model. For the 4-variable model, the C statistics were 0.750 (95% CI: 0.615-0.885) for the 2-year model and 0.766 (0.625-0.907) for the 5-year model, whereas the values were 0.756 (0.629-0.883) and 0.774 (0.641-0.907), respectively, for the 8-variable model. Calibration was acceptable for both the 4-variable and 8-variable models. Decision curve analysis for the models at the 5-year scale performed better throughout different net benefit thresholds than the eGFR-based (<30 mL/min/1.73 m2) strategy.
Limitations
A large proportion of patients lack albuminuria measurements, and only a subset of population could provide complete data for the 8-variable equation.
Conclusions
The kidney failure risk equations showed acceptable discrimination and calibration and better clinical utility than the eGFR-based strategy for incidence of kidney failure among community-based urban Chinese patients with chronic kidney disease.
Plain-Language Summary
Accurate and reliable risk evaluation of chronic kidney disease (CKD) prognosis can be helpful for physicians to make decisions concerning treatment opportunity and therapeutic strategy. The kidney failure risk equation is an outstanding model for predicting risk of kidney failure among patients with CKD. However, the equation is lacking validation among Chinese populations. In the current study, we demonstrated that the equation had good discrimination among an urban community-based cohort of patients with CKD in China. The calibration was also acceptable. Decision curve analysis also showed that the equation performed better than a traditional kidney function-based strategy. The results provide the basis for using predictions derived from the kidney failure risk equation to improve the management of patients with CKD in community settings in China.