Development of a multivariate predictive model for dapsone adverse drug events in people with leprosy under standard WHO multidrug therapy

The occurrence of adverse drug events (ADEs) during dapsone (DDS) treatment in patients with leprosy can constitute a significant barrier to the successful completion of the standardized therapeutic regimen for this disease. Well-known DDS-ADEs are hemolytic anemia, methemoglobinemia, hepatotoxicity...

Full description

Saved in:
Bibliographic Details
Published in:PLoS neglected tropical diseases Vol. 18; no. 1; p. e0011901
Main Authors: de Araujo, Ana Carolina Galvão Dos Santos, Hacker, Mariana de Andrea Vilas-Boas, Pinheiro, Roberta Olmo, Illarramendi, Ximena, Durães, Sandra Maria Barbosa, Nobre, Maurício Lisboa, Moraes, Milton Ozório, Sales, Anna Maria, da Silva, Gilberto Marcelo Sperandio
Format: Journal Article
Language:English
Published: United States Public Library of Science 01-01-2024
Public Library of Science (PLoS)
Subjects:
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The occurrence of adverse drug events (ADEs) during dapsone (DDS) treatment in patients with leprosy can constitute a significant barrier to the successful completion of the standardized therapeutic regimen for this disease. Well-known DDS-ADEs are hemolytic anemia, methemoglobinemia, hepatotoxicity, agranulocytosis, and hypersensitivity reactions. Identifying risk factors for ADEs before starting World Health Organization recommended standard multidrug therapy (WHO/MDT) can guide therapeutic planning for the patient. The objective of this study was to develop a predictive model for DDS-ADEs in patients with leprosy receiving standard WHO/MDT. This is a case-control study that involved the review of medical records of adult (≥18 years) patients registered at a Leprosy Reference Center in Rio de Janeiro, Brazil. The cohort included individuals that received standard WHO/MDT between January 2000 to December 2021. A prediction nomogram was developed by means of multivariable logistic regression (LR) using variables. The Hosmer-Lemeshow test was used to determine the model fit. Odds ratios (ORs) and their respective 95% confidence intervals (CIs) were estimated. The predictive ability of the LRM was assessed by the area under the receiver operating characteristic curve (AUC). A total of 329 medical records were assessed, comprising 120 cases and 209 controls. Based on the final LRM analysis, female sex (OR = 3.61; 95% CI: 2.03-6.59), multibacillary classification (OR = 2.5; 95% CI: 1.39-4.66), and higher education level (completed primary education) (OR = 1.97; 95% CI: 1.14-3.47) were considered factors to predict ADEs that caused standard WHO/MDT discontinuation. The prediction model developed had an AUC of 0.7208, that is 72% capable of predicting DDS-ADEs. We propose a clinical model that could become a helpful tool for physicians in predicting ADEs in DDS-treated leprosy patients.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
The authors have declared that no competing interests exist.
ISSN:1935-2735
1935-2727
1935-2735
DOI:10.1371/journal.pntd.0011901