Cargando…
Development of a risk score for prediction of poor treatment outcomes among patients with multidrug-resistant tuberculosis
BACKGROUND: Treatment outcomes among patients treated for multidrug-resistant tuberculosis (MDR-TB) are often sub-optimal. Therefore, the early prediction of poor treatment outcomes may be useful in patient care, especially for clinicians when they have the ability to make treatment decisions or off...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6941813/ https://www.ncbi.nlm.nih.gov/pubmed/31899769 http://dx.doi.org/10.1371/journal.pone.0227100 |
_version_ | 1783484601332662272 |
---|---|
author | Alene, Kefyalew Addis Viney, Kerri Gray, Darren J. McBryde, Emma S. Xu, Zuhui Clements, Archie C. A. |
author_facet | Alene, Kefyalew Addis Viney, Kerri Gray, Darren J. McBryde, Emma S. Xu, Zuhui Clements, Archie C. A. |
author_sort | Alene, Kefyalew Addis |
collection | PubMed |
description | BACKGROUND: Treatment outcomes among patients treated for multidrug-resistant tuberculosis (MDR-TB) are often sub-optimal. Therefore, the early prediction of poor treatment outcomes may be useful in patient care, especially for clinicians when they have the ability to make treatment decisions or offer counselling or additional support to patients. The aim of this study was to develop a simple clinical risk score to predict poor treatment outcomes in patients with MDR-TB, using routinely collected data from two large countries in geographically distinct regions. METHODS: We used MDR-TB data collected from Hunan Chest Hospital, China and Gondar University Hospital, Ethiopia. The data were divided into derivation (n = 343; 60%) and validation groups (n = 227; 40%). A poor treatment outcome was defined as treatment failure, lost to follow up or death. A risk score for poor treatment outcomes was derived using a Cox proportional hazard model in the derivation group. The model was then validated in the validation group. RESULTS: The overall rate of poor treatment outcome was 39.5% (n = 225); 37.9% (n = 86) in the derivation group and 40.5% (n = 139) in the validation group. Three variables were identified as predictors of poor treatment outcomes, and each was assigned a number of points proportional to its regression coefficient. These predictors and their points were: 1) history of taking second-line TB treatment (2 points), 2) resistance to any fluoroquinolones (3 points), and 3) smear did not convert from positive to negative at two months (4 points). We summed these points to calculate the risk score for each patient; three risk groups were defined: low risk (0 to 2 points), medium risk (3 to 5 points), and high risk (6 to 9 points). In the derivation group, poor treatment outcomes were reported for these three groups as 14%, 27%, and 71%, respectively. The area under the receiver operating characteristic curve for the point system in the derivation group was 0.69 (95% CI 0.60 to 0.77) and was similar to that in the validation group (0.67; 95% CI 0.56 to 0.78; p = 0.82). CONCLUSION: History of second-line TB treatment, resistance to any fluoroquinolones, and smear non-conversion at two months can be used to estimate the risk of poor treatment outcome in patients with MDR-TB with a moderate degree of accuracy (AUROC = 0.69). |
format | Online Article Text |
id | pubmed-6941813 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-69418132020-01-10 Development of a risk score for prediction of poor treatment outcomes among patients with multidrug-resistant tuberculosis Alene, Kefyalew Addis Viney, Kerri Gray, Darren J. McBryde, Emma S. Xu, Zuhui Clements, Archie C. A. PLoS One Research Article BACKGROUND: Treatment outcomes among patients treated for multidrug-resistant tuberculosis (MDR-TB) are often sub-optimal. Therefore, the early prediction of poor treatment outcomes may be useful in patient care, especially for clinicians when they have the ability to make treatment decisions or offer counselling or additional support to patients. The aim of this study was to develop a simple clinical risk score to predict poor treatment outcomes in patients with MDR-TB, using routinely collected data from two large countries in geographically distinct regions. METHODS: We used MDR-TB data collected from Hunan Chest Hospital, China and Gondar University Hospital, Ethiopia. The data were divided into derivation (n = 343; 60%) and validation groups (n = 227; 40%). A poor treatment outcome was defined as treatment failure, lost to follow up or death. A risk score for poor treatment outcomes was derived using a Cox proportional hazard model in the derivation group. The model was then validated in the validation group. RESULTS: The overall rate of poor treatment outcome was 39.5% (n = 225); 37.9% (n = 86) in the derivation group and 40.5% (n = 139) in the validation group. Three variables were identified as predictors of poor treatment outcomes, and each was assigned a number of points proportional to its regression coefficient. These predictors and their points were: 1) history of taking second-line TB treatment (2 points), 2) resistance to any fluoroquinolones (3 points), and 3) smear did not convert from positive to negative at two months (4 points). We summed these points to calculate the risk score for each patient; three risk groups were defined: low risk (0 to 2 points), medium risk (3 to 5 points), and high risk (6 to 9 points). In the derivation group, poor treatment outcomes were reported for these three groups as 14%, 27%, and 71%, respectively. The area under the receiver operating characteristic curve for the point system in the derivation group was 0.69 (95% CI 0.60 to 0.77) and was similar to that in the validation group (0.67; 95% CI 0.56 to 0.78; p = 0.82). CONCLUSION: History of second-line TB treatment, resistance to any fluoroquinolones, and smear non-conversion at two months can be used to estimate the risk of poor treatment outcome in patients with MDR-TB with a moderate degree of accuracy (AUROC = 0.69). Public Library of Science 2020-01-03 /pmc/articles/PMC6941813/ /pubmed/31899769 http://dx.doi.org/10.1371/journal.pone.0227100 Text en © 2020 Alene et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Alene, Kefyalew Addis Viney, Kerri Gray, Darren J. McBryde, Emma S. Xu, Zuhui Clements, Archie C. A. Development of a risk score for prediction of poor treatment outcomes among patients with multidrug-resistant tuberculosis |
title | Development of a risk score for prediction of poor treatment outcomes among patients with multidrug-resistant tuberculosis |
title_full | Development of a risk score for prediction of poor treatment outcomes among patients with multidrug-resistant tuberculosis |
title_fullStr | Development of a risk score for prediction of poor treatment outcomes among patients with multidrug-resistant tuberculosis |
title_full_unstemmed | Development of a risk score for prediction of poor treatment outcomes among patients with multidrug-resistant tuberculosis |
title_short | Development of a risk score for prediction of poor treatment outcomes among patients with multidrug-resistant tuberculosis |
title_sort | development of a risk score for prediction of poor treatment outcomes among patients with multidrug-resistant tuberculosis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6941813/ https://www.ncbi.nlm.nih.gov/pubmed/31899769 http://dx.doi.org/10.1371/journal.pone.0227100 |
work_keys_str_mv | AT alenekefyalewaddis developmentofariskscoreforpredictionofpoortreatmentoutcomesamongpatientswithmultidrugresistanttuberculosis AT vineykerri developmentofariskscoreforpredictionofpoortreatmentoutcomesamongpatientswithmultidrugresistanttuberculosis AT graydarrenj developmentofariskscoreforpredictionofpoortreatmentoutcomesamongpatientswithmultidrugresistanttuberculosis AT mcbrydeemmas developmentofariskscoreforpredictionofpoortreatmentoutcomesamongpatientswithmultidrugresistanttuberculosis AT xuzuhui developmentofariskscoreforpredictionofpoortreatmentoutcomesamongpatientswithmultidrugresistanttuberculosis AT clementsarchieca developmentofariskscoreforpredictionofpoortreatmentoutcomesamongpatientswithmultidrugresistanttuberculosis |