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A Predictive Model for Estimation Risk of Proliferative Lupus Nephritis

摘要Background:Lupus nephritis (LN) is classified by renal biopsy into proliferative and nonproliferative forms,with distinct prognoses,but renal biopsy is not available for every LN patient.The present study aimed to establish an alternate tool by building a predictive model to evaluate the probability of proliferative LN.Methods:In this retrospective cohort with biopsy-proven LN,382 patients in development cohort,193 in intemal validation cohort,and 164 newly diagnosed patients in external validation cohort were selected.Logistic regression model was established,and the concordance statistics (C-statistics),Akaike information criterion (AIC),integrated discrimination improvement,Hosmer-Lemeshow test,and net reclassification improvement were calculated to evaluate the performance and validation of models.Results:The prevalence of proliferative LN was 77.7% in the whole cohort.A model,including age,gender,systolic blood pressure,hemoglobin,proteinuria,hematuria,and serum C3,performed well on good-of-fit and discrimination in the development chohort to predict the risk of proliferative LN (291 for AIC and 0.84 for C-statistics).In the internal and external validation cohorts,this model showed good capability for discrimination and calibration (0.84 and 0.82 for C-statistics,and 0.99 and 0.75 for P values,respectively).Conclusion:This study developed and validated a model including demographic and clinical indices to evaluate the probability of presenting proliferative LN to guide therapeutic decisions and outcomes.

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作者单位 Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510080, China;Key Laboratory of Nephrology, Ministry of Health and Guangdong Province, Guangzhou, Guangdong 510080, China [1] Clinical Trials Unit, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510080, China [2] Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510080, China;Key Laboratory of Nephrology, Ministry of Health and Guangdong Province, Guangzhou, Guangdong 510080, China;Guangdong Medical University, Zhanjiang, Guangdong 524023, China [3]
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DOI 10.4103/0366-6999.232809
发布时间 2018-07-12(万方平台首次上网日期,不代表论文的发表时间)
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中华医学杂志(英文版)

中华医学杂志(英文版)

2018年131卷11期

1275-1281页

SCIMEDLINEISTICCSCDCABP

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