Development of prognostic scoring system for predicting 1-year mortality among pulmonary tuberculosis patients in South India.
India
mortality
nomograms
prognosis
tuberculosis
Journal
Journal of public health (Oxford, England)
ISSN: 1741-3850
Titre abrégé: J Public Health (Oxf)
Pays: England
ID NLM: 101188638
Informations de publication
Date de publication:
14 Jun 2023
14 Jun 2023
Historique:
received:
28
10
2021
revised:
13
05
2022
medline:
19
6
2023
pubmed:
30
8
2022
entrez:
29
8
2022
Statut:
ppublish
Résumé
Development of a prediction model using baseline characteristics of tuberculosis (TB) patients at the time of diagnosis will aid us in early identification of the high-risk groups and devise pertinent strategies accordingly. Hence, we did this study to develop a prognostic-scoring model for predicting the death among newly diagnosed drug sensitive pulmonary TB patients in South India. We undertook a longitudinal analysis of cohort data under the Regional Prospective Observational Research for Tuberculosis India consortium. Multivariable cox regression using the stepwise backward elimination procedure was used to select variables for the model building and the nomogram-scoring system was developed with the final selected model. In total, 54 (4.6%) out of the 1181 patients had died during the 1-year follow-up period. The TB mortality rate was 0.20 per 1000 person-days. Eight variables (age, gender, functional limitation, anemia, leukopenia, thrombocytopenia, diabetes, neutrophil-lymphocyte ratio) were selected and a nomogram was built using these variables. The discriminatory power was 0.81 (95% confidence interval: 0.75-0.86) and this model was well-calibrated. Decision curve analysis showed that the model is beneficial at a threshold probability ~15-65%. This scoring system could help the clinicians and policy makers to devise targeted interventions and in turn reduce the TB mortality in India.
Sections du résumé
BACKGROUND
BACKGROUND
Development of a prediction model using baseline characteristics of tuberculosis (TB) patients at the time of diagnosis will aid us in early identification of the high-risk groups and devise pertinent strategies accordingly. Hence, we did this study to develop a prognostic-scoring model for predicting the death among newly diagnosed drug sensitive pulmonary TB patients in South India.
METHODS
METHODS
We undertook a longitudinal analysis of cohort data under the Regional Prospective Observational Research for Tuberculosis India consortium. Multivariable cox regression using the stepwise backward elimination procedure was used to select variables for the model building and the nomogram-scoring system was developed with the final selected model.
RESULTS
RESULTS
In total, 54 (4.6%) out of the 1181 patients had died during the 1-year follow-up period. The TB mortality rate was 0.20 per 1000 person-days. Eight variables (age, gender, functional limitation, anemia, leukopenia, thrombocytopenia, diabetes, neutrophil-lymphocyte ratio) were selected and a nomogram was built using these variables. The discriminatory power was 0.81 (95% confidence interval: 0.75-0.86) and this model was well-calibrated. Decision curve analysis showed that the model is beneficial at a threshold probability ~15-65%.
CONCLUSIONS
CONCLUSIONS
This scoring system could help the clinicians and policy makers to devise targeted interventions and in turn reduce the TB mortality in India.
Identifiants
pubmed: 36038507
pii: 6678104
doi: 10.1093/pubmed/fdac087
pmc: PMC10273380
doi:
Types de publication
Observational Study
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e184-e195Subventions
Organisme : NIH HHS
Pays : United States
Organisme : NIH HHS
Pays : United States
Informations de copyright
© The Author(s) 2022. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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