Development and Internal Validation of a Prediction Model to Estimate the Probability of Needing Aggressive Immunosuppressive Therapy With Cytostatics in de Novo Lupus Nephritis Patients

ABSTRACT: Objective: To develop a multivariable clinical prediction model for the requirement of aggressive immunosuppression with cytostatics, based on simple clinical record data and lab tests. The model is defined in accordance with the result of the kidney biopsies. Methods: Retrospective study...

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Autores:
Restrepo Escobar, Mauricio
Granda Carvajal, Paula Andrea
Jaimes Barragán, Fabian Alberto
Tipo de recurso:
Article of investigation
Fecha de publicación:
2019
Institución:
Universidad de Antioquia
Repositorio:
Repositorio UdeA
Idioma:
eng
OAI Identifier:
oai:bibliotecadigital.udea.edu.co:10495/29831
Acceso en línea:
https://hdl.handle.net/10495/29831
Palabra clave:
Lupus Eritematoso Sistémico
Lupus Erythematosus, Systemic
Técnicas de Apoyo para la Decisión
Decision Support Techniques
Modelos Logísticos
Logistic Models
Nefritis Lúpica
Lupus Nephritis
Análisis Multivariante
Multivariate Analysis
Inmunosupresión
Immunosuppression
Tolerancia Inmunológica
Immune Tolerance
Rights
openAccess
License
http://creativecommons.org/licenses/by/2.5/co/
Description
Summary:ABSTRACT: Objective: To develop a multivariable clinical prediction model for the requirement of aggressive immunosuppression with cytostatics, based on simple clinical record data and lab tests. The model is defined in accordance with the result of the kidney biopsies. Methods: Retrospective study conducted with data from patients 16 years and older, with SLE and nephritis with less than 6 months of evolution. An initial bivariate analysis was conducted to select the variables to be included in a multiple logistic regression model. Goodness of fit was evaluated using a Hosmer–Lemeshow test (H–L) and the discrimination capacity of the model by means of the area under the ROC (AUC) curve. Results Data from 242 patients was gathered; of these, 18.2% (n=44) did not need an addition of cytostatics according to the findings of their kidney biopsies. The variables included in the final model were 24-h proteinuria, diastolic blood pressure, creatinine, C3 complement and the interaction of hematuria with leukocyturia in urinary sediment. The model showed excellent discrimination (AUC=0.929; 95% CI=0.894–0.963) and adequate calibration (H–L, P=.959). Conclusion In recent-onset LN patients, the decision to use or not to use intensive immunosuppressive therapy could be performed based on our prediction model as an alternative to kidney biopsies.