Prediction of pulmonary tuberculosis treatment outcome in a sub‑Saharan African context
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 unsucce...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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AOSIS
2023-10-01
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| Series: | Journal of Public Health in Africa |
| Subjects: | |
| Online Access: | https://publichealthinafrica.org/index.php/jphia/article/view/68 |
| _version_ | 1827160131213721600 |
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| author | Joseph M.F. Mouafo André N. Yakam Claude Simo Jules S. Kamdem Samuel Bowong Louis A. Fono Jürgen Noeske |
| author_facet | Joseph M.F. Mouafo André N. Yakam Claude Simo Jules S. Kamdem Samuel Bowong Louis A. Fono Jürgen Noeske |
| author_sort | Joseph M.F. Mouafo |
| collection | DOAJ |
| description | 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 (P0.05). 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. |
| first_indexed | 2024-03-10T03:55:16Z |
| format | Article |
| id | doaj.art-7abcace57e224ec7adbea869a115cc99 |
| institution | Directory Open Access Journal |
| issn | 2038-9922 2038-9930 |
| language | English |
| last_indexed | 2025-03-21T00:08:09Z |
| publishDate | 2023-10-01 |
| publisher | AOSIS |
| record_format | Article |
| series | Journal of Public Health in Africa |
| spelling | doaj.art-7abcace57e224ec7adbea869a115cc992024-08-03T10:01:11ZengAOSISJournal of Public Health in Africa2038-99222038-99302023-10-01141010.4081/jphia.2023.269468Prediction of pulmonary tuberculosis treatment outcome in a sub‑Saharan African contextJoseph M.F. Mouafo0André N. Yakam1Claude Simo2Jules S. Kamdem3Samuel Bowong4Louis A. Fono5Jürgen Noeske6University of Douala, CameroonUniversity of Douala, CameroonUniversity of Douala, CameroonUniversity of Montpellier, FranceUniversity of Douala, CameroonUniversity of Douala, CameroonIndependant Consultant, Yaounde, CameroonFailure 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 (P0.05). 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.https://publichealthinafrica.org/index.php/jphia/article/view/68scoring methodlogistic regressiontuberculosistreatment failurecameroon |
| spellingShingle | Joseph M.F. Mouafo André N. Yakam Claude Simo Jules S. Kamdem Samuel Bowong Louis A. Fono Jürgen Noeske Prediction of pulmonary tuberculosis treatment outcome in a sub‑Saharan African context Journal of Public Health in Africa scoring method logistic regression tuberculosis treatment failure cameroon |
| title | Prediction of pulmonary tuberculosis treatment outcome in a sub‑Saharan African context |
| title_full | Prediction of pulmonary tuberculosis treatment outcome in a sub‑Saharan African context |
| title_fullStr | Prediction of pulmonary tuberculosis treatment outcome in a sub‑Saharan African context |
| title_full_unstemmed | Prediction of pulmonary tuberculosis treatment outcome in a sub‑Saharan African context |
| title_short | Prediction of pulmonary tuberculosis treatment outcome in a sub‑Saharan African context |
| title_sort | prediction of pulmonary tuberculosis treatment outcome in a sub saharan african context |
| topic | scoring method logistic regression tuberculosis treatment failure cameroon |
| url | https://publichealthinafrica.org/index.php/jphia/article/view/68 |
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