Original Article

Prediction of pulmonary tuberculosis treatment outcome in a sub‑Saharan African context

Joseph M.F. Mouafo, André N. Yakam, Claude Simo, Jules S. Kamdem, Samuel Bowong, Louis A. Fono, Jürgen Noeske
Journal of Public Health in Africa | Vol 14, No 10 | a68 | DOI: https://doi.org/10.4081/jphia.2023.2694 | © 2024 Joseph M.F. Mouafo, André N. Yakam, Claude Simo, Jules S. Kamdem, Samuel Bowong, Louis A. Fono, Jürgen Noeske | This work is licensed under CC Attribution 4.0
Submitted: 18 March 2024 | Published: 30 October 2023

About the author(s)

Joseph M.F. Mouafo, University of Douala, Cameroon
André N. Yakam, University of Douala, Cameroon
Claude Simo, University of Douala, Cameroon
Jules S. Kamdem, University of Montpellier, France
Samuel Bowong, University of Douala, Cameroon
Louis A. Fono, University of Douala, Cameroon
Jürgen Noeske, Independant Consultant, Yaounde, Cameroon

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Abstract

Failure to treat many pathogens is a concern. Identifying a priori, patients with potential failure treatment outcome of a disease could allow measures to reduce the failure rate. The objectives of this study were to use the Scoring method to identify factors associated with the tuberculosis unsuccessful treatment outcome and to predict the treatment outcome. A total of 1,529 patients with pulmonary tuberculosis were randomly selected in the city of Douala,Cameroon, this sample was randomly split into two parts: one subsample of 1,200 patients (78%) used as the Development sample, and the remaining of 329 patients (22%) used as the Validation sample. Baseline characteristics associated with unsuccessful treatment outcomes were investigated using logistic regression. The optimal score was based on the Youden's index. HIV positive status, active smoker and non‑belief in healing were the factors significantly associated with unsuccessful treatment outcomes (P<0.05). A model used to estimate the risk of unsuccessful treatment outcome was derived. The threshold probability which maximize the area under the ROC curve was 18%. Patients for whom the risk was greater than this threshold were classified as unsuccessful treatment outcome and the others as successful.HIV positive and active smoking status were associated with death; the non-belief in healing, youth and male gender associated with lost-to-follow-up, TB antecedent and not having TB contact associated with therapeutic treatment failure. To increase the tuberculosis treatment success rate, targeted follow-up could be taken during the treatment for TB patients with previous characteristics.

Keywords

scoring method; logistic regression; tuberculosis; treatment failure; Cameroon

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