Prediction Models for Adverse Drug Reactions During Tuberculosis Treatment in Brazil.

ABSTRACT:

Background

Tuberculosis (TB) treatment-related adverse drug reactions (TB-ADRs) can negatively affect adherence and treatment success rates.

Methods

We developed prediction models for TB-ADRs, considering participants with drug-susceptible pulmonary TB who initiated standard TB therapy. TB-ADRs were determined by the physician attending the participant, assessing causality to TB drugs, the affected organ system, and grade. Potential baseline predictors of TB-ADR included concomitant medication (CM) use, human immunodeficiency virus (HIV) status, glycated hemoglobin (HbA1c), age, body mass index (BMI), sex, substance use, and TB drug metabolism variables (NAT2 acetylator profiles). The models were developed through bootstrapped backward selection. Cox regression was used to e

SUBMITTER: Ridolfi F 

PROVIDER: S-EPMC10938211 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature