ArticlePLoS neglected tropical diseases2024
Development of a multivariate predictive model for dapsone adverse drug events in people with leprosy under standard WHO multidrug therapy.
Article in PLoS neglected tropical diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- TSC22 domain family member 3 links natural killer cells to CD8+ T cell-mediated drug hypersensitivity.Signal transduction and targeted therapy · 2025Article
- Challenges associated with dapsone for leprosy treatment in Indonesia - urgent need for access to alternative antimicrobial drugs.The Lancet regional health. Southeast Asia · 2025Review
- Aortic dissection type A, common carotid artery occlusion, and stroke after dapsone for 20 years.Journal of family medicine and primary care · 2025Article
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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. METHODOLOGY: 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).
resultsA 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.
conclusionWe propose a clinical model that could become a helpful tool for physicians in predicting ADEs in DDS-treated leprosy patients.
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