Pharmacodynamic Modeling of Bacillary Elimination Rates and Detection of Bacterial Lipid Bodies in Sputum to Predict and Understand Outcomes in Treatment of Pulmonary Tuberculosis..pdf (309.88 kB)Download file
Pharmacodynamic Modeling of Bacillary Elimination Rates and Detection of Bacterial Lipid Bodies in Sputum to Predict and Understand Outcomes in Treatment of Pulmonary Tuberculosis
journal contributionposted on 2016-02-17, 10:53 authored by D. J. Sloan, H. C. Mwandumba, Natalie J. Garton, S. H. Khoo, A. E. Butterworth, T. J. Allain, R. S. Heyderman, E. L. Corbett, Michael Richard Barer, G. R. Davies
BACKGROUND: Antibiotic-tolerant bacterial persistence prevents treatment shortening in drug-susceptible tuberculosis, and accumulation of intracellular lipid bodies has been proposed to identify a persister phenotype of Mycobacterium tuberculosis cells. In Malawi, we modeled bacillary elimination rates (BERs) from sputum cultures and calculated the percentage of lipid body-positive acid-fast bacilli (%LB + AFB) on sputum smears. We assessed whether these putative measurements of persistence predict unfavorable outcomes (treatment failure/relapse). METHODS: Adults with pulmonary tuberculosis received standard 6-month therapy. Sputum samples were collected during the first 8 weeks for serial sputum colony counting (SSCC) on agar and time-to positivity (TTP) measurement in mycobacterial growth indicator tubes. BERs were extracted from nonlinear and linear mixed-effects models, respectively, fitted to these datasets. The %LB + AFB counts were assessed by fluorescence microscopy. Patients were followed until 1 year posttreatment. Individual BERs and %LB + AFB counts were related to final outcomes. RESULTS: One hundred and thirty-three patients (56% HIV coinfected) participated, and 15 unfavorable outcomes were reported. These were inversely associated with faster sterilization phase bacillary elimination from the SSCC model (odds ratio [OR], 0.39; 95% confidence interval [CI], .22-.70) and a faster BER from the TTP model (OR, 0.71; 95% CI, .55-.94). Higher %LB + AFB counts on day 21-28 were recorded in patients who suffered unfavorable final outcomes compared with those who achieved stable cure (P = .008). CONCLUSIONS: Modeling BERs predicts final outcome, and high %LB + AFB counts 3-4 weeks into therapy may identify a persister bacterial phenotype. These methods deserve further evaluation as surrogate endpoints for clinical trials.
CitationClinical Infectious Diseases, 2015, 61 (1), pp. 1-8
Author affiliation/Organisation/COLLEGE OF MEDICINE, BIOLOGICAL SCIENCES AND PSYCHOLOGY/School of Medicine/Department of Infection, Immunity and Inflammation
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