Predicting the outcome of therapy for pulmonary tuberculosis.

TitlePredicting the outcome of therapy for pulmonary tuberculosis.
Publication TypeJournal Article
Year of Publication2000
AuthorsWallis, RS, Perkins, MD, Phillips, M, Joloba, M, Namale, A, Johnson, JL, Whalen, CC, Teixeira, L, Demchuk, B, Dietze, R, Mugerwa, RD, Eisenach, K, Ellner, JJ
JournalAmerican journal of respiratory and critical care medicine
Issue4 Pt 1
Date Published2000 Apr
KeywordsAntitubercular Agents, Brazil, Cohort Studies, Culture Media, Humans, Linear Models, Mycobacterium tuberculosis, Prospective Studies, Recurrence, Sputum, Treatment Outcome, Tuberculosis, Pulmonary, Uganda

Patients vary considerably in their response to treatment of pulmonary tuberculosis. Although several studies have indicated that adverse outcomes are more likely in those patients with delayed sputum sterilization, few tools are available to identify those patients prospectively. In this study, multivariate models were developed to predict the response to therapy in a prospectively recruited cohort of 42 HIV-uninfected subjects with drug-sensitive tuberculosis. The cohort included 2 subjects whose initial response was followed by drug-sensitive relapse. The total duration of culture positivity was best predicted by a model that included sputum M. tuberculosis antigen 85 concentration on Day 14 of therapy, days-to-positive in BACTEC on Day 30, and the baseline radiographic extent of disease (R = 0.63). A model in which quantitative AFB microscopy replaced BACTEC also performed adequately (R = 0.58). Both models predicted delayed clearance of bacilli in both relapses (> 85th percentile of all subjects) using information collected during the first month of therapy. Stratification of patients according to anticipated response to therapy may allow TB treatment to be individualized, potentially offering superior outcomes and greater efficiency in resource utilization, and aiding in the conduct of clinical trials.

Alternate JournalAm. J. Respir. Crit. Care Med.
Full Text
PubMed ID10764293
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