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...

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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
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Language:English
Published: United States Public Library of Science 01-01-2024
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Abstract 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.
AbstractList 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.METHODOLOGYThis 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.
Background 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. Methodology This is a case-control study that involved the review of medical records of adult ([greater than or equal to]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). Results 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. Conclusion We propose a clinical model that could become a helpful tool for physicians in predicting ADEs in DDS-treated leprosy patients.
Background 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. 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). Results 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. Conclusion We propose a clinical model that could become a helpful tool for physicians in predicting ADEs in DDS-treated leprosy patients.
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.
Adverse events (AE) produced by the drugs used to treat leprosy can hinder the successful completion of the therapeutic regimen. Well-known AE produced by dapsone (DDS) are related to liver problems, allergic reactions, or to the destruction of red and/or white blood cells, causing anemia. Helping the physician to recognize a patient that may develop these adverse reactions can be useful. Thus, we developed a model to predict AE in patients with leprosy receiving standard World Health Organization-recommended multidrug therapy (WHO/MDT). Our question was whether we could use sociodemographic and clinical variables to generate a predictive model for DDS-ADEs. The model developed in this study could be a useful tool to assist physicians in predicting DDS-ADEs when treating patients with standard WHO/MDT for leprosy, and thus, establish a safer therapeutic plan for patients with a greater ADE risk.
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 ([greater than or equal to]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.
Audience Academic
Author Hacker, Mariana de Andrea Vilas-Boas
Durães, Sandra Maria Barbosa
Sales, Anna Maria
de Araujo, Ana Carolina Galvão Dos Santos
Pinheiro, Roberta Olmo
Illarramendi, Ximena
Moraes, Milton Ozório
Nobre, Maurício Lisboa
da Silva, Gilberto Marcelo Sperandio
AuthorAffiliation Federal University of Ceará, Fortaleza, Brazil, BRAZIL
2 Oswaldo Cruz Institute, Oswaldo Cruz Foundation (IOC/Fiocruz), Rio de Janeiro, RJ, Brazil
4 Giselda Trigueiro Hospital, Rio Grande do Norte Federal State Public Health department (SESAP-RN), Natal, RN, Brazil
1 Evandro Chagas National Institute of Infectious Diseases, Oswaldo Cruz Foundation (INI/Fiocruz), Rio de Janeiro, RJ, Brazil
3 Dermatology Department, Fluminense Federal University (UFF), Niterói, RJ, Brazil
AuthorAffiliation_xml – name: 4 Giselda Trigueiro Hospital, Rio Grande do Norte Federal State Public Health department (SESAP-RN), Natal, RN, Brazil
– name: Federal University of Ceará, Fortaleza, Brazil, BRAZIL
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– name: 3 Dermatology Department, Fluminense Federal University (UFF), Niterói, RJ, Brazil
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/38271456$$D View this record in MEDLINE/PubMed
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Copyright Copyright: © 2024 de Araujo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
COPYRIGHT 2024 Public Library of Science
2024 de Araujo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
2024 de Araujo et al 2024 de Araujo et al
2024 de Araujo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
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– notice: 2024 de Araujo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
– notice: 2024 de Araujo et al 2024 de Araujo et al
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Snippet The occurrence of adverse drug events (ADEs) during dapsone (DDS) treatment in patients with leprosy can constitute a significant barrier to the successful...
Background The occurrence of adverse drug events (ADEs) during dapsone (DDS) treatment in patients with leprosy can constitute a significant barrier to the...
BackgroundThe occurrence of adverse drug events (ADEs) during dapsone (DDS) treatment in patients with leprosy can constitute a significant barrier to the...
BACKGROUNDThe occurrence of adverse drug events (ADEs) during dapsone (DDS) treatment in patients with leprosy can constitute a significant barrier to the...
Adverse events (AE) produced by the drugs used to treat leprosy can hinder the successful completion of the therapeutic regimen. Well-known AE produced by...
Background The occurrence of adverse drug events (ADEs) during dapsone (DDS) treatment in patients with leprosy can constitute a significant barrier to the...
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SubjectTerms Adult
Adverse and side effects
Anaemia
Anemia
Brazil - epidemiology
Care and treatment
Case-Control Studies
Classification
Clofazimine - therapeutic use
Complications and side effects
Confidence intervals
Dapsone
Dapsone - adverse effects
Diagnosis
Diaminodiphenylsulfone
DNA methylation
Dosage and administration
Drug Therapy, Combination
Drug-Related Side Effects and Adverse Reactions
Drugs
Education
Female
Females
Hemoglobin
Hemolytic anemia
Hepatotoxicity
Humans
Hypersensitivity
Infectious diseases
Leprostatic Agents - adverse effects
Leprosy
Leprosy - drug therapy
Medical records
Medicine and Health Sciences
Methemoglobinemia
Neutropenia
Nomograms
Outpatient care facilities
Patients
Physical Sciences
Prediction models
Research and Analysis Methods
Rifampin - therapeutic use
Risk factors
Sociodemographics
Statistical analysis
World Health Organization
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Title Development of a multivariate predictive model for dapsone adverse drug events in people with leprosy under standard WHO multidrug therapy
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