Cargando…

T-BACCO SCORE: A predictive scoring tool for tuberculosis (TB) loss to follow-up among TB smokers

INTRODUCTION: Loss to follow-up (LTFU) and smoking during TB treatment are major challenges for TB control programs. Smoking increases the severity and prolongs TB treatment duration, which lead to a higher rate of LTFU. We aim to develop a prognostic scoring tool to predict LTFU among TB patients w...

Descripción completa

Detalles Bibliográficos
Autores principales: Sharani, Zatil Zahidah, Ismail, Nurhuda, Yasin, Siti Munira, Isa, Muhamad Rodi, Razali, Asmah, Sherzkawee, Mas Ahmad, Ismail, Ahmad Izuanuddin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10270618/
https://www.ncbi.nlm.nih.gov/pubmed/37319310
http://dx.doi.org/10.1371/journal.pone.0287374
_version_ 1785059352829231104
author Sharani, Zatil Zahidah
Ismail, Nurhuda
Yasin, Siti Munira
Isa, Muhamad Rodi
Razali, Asmah
Sherzkawee, Mas Ahmad
Ismail, Ahmad Izuanuddin
author_facet Sharani, Zatil Zahidah
Ismail, Nurhuda
Yasin, Siti Munira
Isa, Muhamad Rodi
Razali, Asmah
Sherzkawee, Mas Ahmad
Ismail, Ahmad Izuanuddin
author_sort Sharani, Zatil Zahidah
collection PubMed
description INTRODUCTION: Loss to follow-up (LTFU) and smoking during TB treatment are major challenges for TB control programs. Smoking increases the severity and prolongs TB treatment duration, which lead to a higher rate of LTFU. We aim to develop a prognostic scoring tool to predict LTFU among TB patients who smoke to improve successful TB treatment outcomes. MATERIALS AND METHODS: The development of the prognostic model utilized prospectively collected longitudinal data of adult TB patients who smoked in the state of Selangor between 2013 until 2017, which were obtained from the Malaysian Tuberculosis Information System (MyTB) database. Data were randomly split into development and internal validation cohorts. A simple prognostic score (T-BACCO SCORE) was constructed based on the regression coefficients of predictors in the final logistic model of the development cohort. Estimated missing data was 2.8% from the development cohort and was completely at random. Model discrimination was determined using c-statistics (AUCs), and calibration was based on the Hosmer and Lemeshow goodness of fit test and calibration plot. RESULTS: The model highlights several variables with different T-BACCO SCORE values as predictors for LTFU among TB patients who smoke (e.g., age group, ethnicity, locality, nationality, educational level, monthly income level, employment status, TB case category, TB detection methods, X-ray categories, HIV status, and sputum status). The prognostic scores were categorized into three groups that predict the risk for LTFU: low-risk (<15 points), medium-risk (15 to 25 points) and high-risk (> 25 points). The model exhibited fair discrimination with a c-statistic of 0.681 (95% CI 0.627–0.710) and good calibration with a nonsignificant chi-square Hosmer‒Lemeshow’s goodness of fit test χ2 = 4.893 and accompanying p value of 0.769. CONCLUSION: Predicting LTFU among TB patients who smoke in the early phase of TB treatment is achievable using this simple T-BACCO SCORE. The applicability of the tool in clinical settings helps health care professionals manage TB smokers based on their risk scores. Further external validation should be carried out prior to use.
format Online
Article
Text
id pubmed-10270618
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-102706182023-06-16 T-BACCO SCORE: A predictive scoring tool for tuberculosis (TB) loss to follow-up among TB smokers Sharani, Zatil Zahidah Ismail, Nurhuda Yasin, Siti Munira Isa, Muhamad Rodi Razali, Asmah Sherzkawee, Mas Ahmad Ismail, Ahmad Izuanuddin PLoS One Research Article INTRODUCTION: Loss to follow-up (LTFU) and smoking during TB treatment are major challenges for TB control programs. Smoking increases the severity and prolongs TB treatment duration, which lead to a higher rate of LTFU. We aim to develop a prognostic scoring tool to predict LTFU among TB patients who smoke to improve successful TB treatment outcomes. MATERIALS AND METHODS: The development of the prognostic model utilized prospectively collected longitudinal data of adult TB patients who smoked in the state of Selangor between 2013 until 2017, which were obtained from the Malaysian Tuberculosis Information System (MyTB) database. Data were randomly split into development and internal validation cohorts. A simple prognostic score (T-BACCO SCORE) was constructed based on the regression coefficients of predictors in the final logistic model of the development cohort. Estimated missing data was 2.8% from the development cohort and was completely at random. Model discrimination was determined using c-statistics (AUCs), and calibration was based on the Hosmer and Lemeshow goodness of fit test and calibration plot. RESULTS: The model highlights several variables with different T-BACCO SCORE values as predictors for LTFU among TB patients who smoke (e.g., age group, ethnicity, locality, nationality, educational level, monthly income level, employment status, TB case category, TB detection methods, X-ray categories, HIV status, and sputum status). The prognostic scores were categorized into three groups that predict the risk for LTFU: low-risk (<15 points), medium-risk (15 to 25 points) and high-risk (> 25 points). The model exhibited fair discrimination with a c-statistic of 0.681 (95% CI 0.627–0.710) and good calibration with a nonsignificant chi-square Hosmer‒Lemeshow’s goodness of fit test χ2 = 4.893 and accompanying p value of 0.769. CONCLUSION: Predicting LTFU among TB patients who smoke in the early phase of TB treatment is achievable using this simple T-BACCO SCORE. The applicability of the tool in clinical settings helps health care professionals manage TB smokers based on their risk scores. Further external validation should be carried out prior to use. Public Library of Science 2023-06-15 /pmc/articles/PMC10270618/ /pubmed/37319310 http://dx.doi.org/10.1371/journal.pone.0287374 Text en © 2023 Sharani et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://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
Sharani, Zatil Zahidah
Ismail, Nurhuda
Yasin, Siti Munira
Isa, Muhamad Rodi
Razali, Asmah
Sherzkawee, Mas Ahmad
Ismail, Ahmad Izuanuddin
T-BACCO SCORE: A predictive scoring tool for tuberculosis (TB) loss to follow-up among TB smokers
title T-BACCO SCORE: A predictive scoring tool for tuberculosis (TB) loss to follow-up among TB smokers
title_full T-BACCO SCORE: A predictive scoring tool for tuberculosis (TB) loss to follow-up among TB smokers
title_fullStr T-BACCO SCORE: A predictive scoring tool for tuberculosis (TB) loss to follow-up among TB smokers
title_full_unstemmed T-BACCO SCORE: A predictive scoring tool for tuberculosis (TB) loss to follow-up among TB smokers
title_short T-BACCO SCORE: A predictive scoring tool for tuberculosis (TB) loss to follow-up among TB smokers
title_sort t-bacco score: a predictive scoring tool for tuberculosis (tb) loss to follow-up among tb smokers
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10270618/
https://www.ncbi.nlm.nih.gov/pubmed/37319310
http://dx.doi.org/10.1371/journal.pone.0287374
work_keys_str_mv AT sharanizatilzahidah tbaccoscoreapredictivescoringtoolfortuberculosistblosstofollowupamongtbsmokers
AT ismailnurhuda tbaccoscoreapredictivescoringtoolfortuberculosistblosstofollowupamongtbsmokers
AT yasinsitimunira tbaccoscoreapredictivescoringtoolfortuberculosistblosstofollowupamongtbsmokers
AT isamuhamadrodi tbaccoscoreapredictivescoringtoolfortuberculosistblosstofollowupamongtbsmokers
AT razaliasmah tbaccoscoreapredictivescoringtoolfortuberculosistblosstofollowupamongtbsmokers
AT sherzkaweemasahmad tbaccoscoreapredictivescoringtoolfortuberculosistblosstofollowupamongtbsmokers
AT ismailahmadizuanuddin tbaccoscoreapredictivescoringtoolfortuberculosistblosstofollowupamongtbsmokers