A Predictive Model for Estimation Risk of Proliferative Lupus Nephritis
Autor: | Li Fan, Yu-Xi Wu, Qian Zhou, Wei Chen, Xueqing Yu, Dongni Chen |
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Rok vydání: | 2018 |
Předmět: |
Adult
Male 0301 basic medicine Oncology medicine.medical_specialty Biopsy Concordance Lupus nephritis lcsh:Medicine Lupus Nephritis Nomogram Predictive Value of Tests Risk Factors Logistic regression Young Adult 03 medical and health sciences 0302 clinical medicine Internal medicine medicine Humans Retrospective Studies 030203 arthritis & rheumatology medicine.diagnostic_test business.industry lcsh:R Retrospective cohort study General Medicine Prognosis medicine.disease Nomograms 030104 developmental biology Predictive value of tests Cohort Female Original Article business |
Zdroj: | Chinese Medical Journal Chinese Medical Journal, Vol 131, Iss 11, Pp 1275-1281 (2018) |
ISSN: | 0366-6999 |
Popis: | 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 internal 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 Pvalues, 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. Key words: Biopsy; Lupus Nephritis; Nomogram; Predictive Value of Tests; Risk Factors |
Databáze: | OpenAIRE |
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