Development and validation of a prognostic score to predict tuberculosis mortality

Duc T. Nguyen, Edward A. Graviss

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

Objective: To develop and validate a simple prognostic scoring system to predict the mortality risk during treatment in tuberculosis patients. Methods: Using data from the CDC's Tuberculosis Genotyping Information Management System of TB patients in Texas reported from 01/2010 to 12/2016, age ≥ 15 years and having an outcome as “completed” or “died” we developed and validated a prognostic mortality scoring system-based logistic regression beta-coefficients. Results: The developmental and validation cohorts consisted of 3378 and 3377 patients, respectively. The score used 9 demographic and clinical characteristics, which are usually available at the patient's initial visits to a healthcare facility. Prognostic scores were categorized into three groups that predicted mortality: low-risk (<15 points), medium-risk (15–18 points), and high-risk (>18 points). The model had excellent discrimination and calibration with an area under the receiver operating characteristic curve of 0.82 and 0.80, and a non-significant Hosmer–Lemeshow test P = 0.514 and P = 0.613 in the developmental and validation cohorts, respectively. Conclusion: Our validated TB prognostic scoring system, which used demographic and clinical characteristics available at the patient's initial visits, can be a practical tool for health care providers to identify TB patients with high mortality risk so that appropriate treatment, medical supports and follow-up resources could be appropriately allocated.

Original languageEnglish (US)
Pages (from-to)283-290
Number of pages8
JournalJournal of Infection
Volume77
Issue number4
Early online dateApr 9 2018
DOIs
StatePublished - Oct 2018

Keywords

  • Elderly
  • HIV infection
  • Meningeal TB
  • Prognosis
  • TB risk score
  • TB-CXR

ASJC Scopus subject areas

  • Microbiology (medical)
  • Infectious Diseases

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