Second line drug susceptibility testing to inform the treatment of rifampin-resistant tuberculosis: a quantitative perspective
Author(s) -
Emily A. Kendall,
Ted Cohen,
Carole D. Mitnick,
David W. Dowdy
Publication year - 2016
Publication title -
international journal of infectious diseases
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.278
H-Index - 89
eISSN - 1878-3511
pISSN - 1201-9712
DOI - 10.1016/j.ijid.2016.12.010
Subject(s) - second line , tuberculosis , medicine , drug resistance , drug resistant tuberculosis , perspective (graphical) , first line , intensive care medicine , drug , tb treatment , mycobacterium tuberculosis , pharmacology , pathology , computer science , biology , artificial intelligence , microbiology and biotechnology
Treatment failure and resistance amplification are common among patients with rifampin-resistant tuberculosis (TB). Drug susceptibility testing (DST) for second-line drugs is recommended for these patients, but logistical difficulties have impeded widespread implementation of second-line DST in many settings. To provide a quantitative perspective on the decision to scale up second-line DST, we synthesize literature on the prevalence of second-line drug resistance, the expected clinical and epidemiologic benefits of using second-line DST to ensure that patients with rifampin-resistant TB receive effective regimens, and the costs of implementing (or not implementing) second-line DST for all individuals diagnosed with rifampin-resistant TB. We conclude that, in most settings, second-line DST could substantially improve treatment outcomes for patients with rifampin-resistant TB, reduce transmission of drug-resistant TB, prevent amplification of drug resistance, and be affordable or even cost-saving. Given the large investment made in each patient treated for rifampin-resistant TB, these payoffs would come at relatively small incremental cost. These anticipated benefits likely justify addressing the real challenges faced in implementing second-line DST in most high-burden settings.
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