Impact of bedaquiline resistance probability on treatment decision for rifampicin-resistant TB

BACKGROUND Accurate diagnosis of bedaquiline (BDQ) resistance remains challenging. A Bayesian approach expresses this uncertainty as a probability of BDQ resistance (prBDQ R ) with a 95% credible interval. We investigated how prBDQ R information influences BDQ prescribing decisions. METHOD We performed a discrete choice experiment with 55 international rifampicin-resistant tuberculosis physicians. We employed mixed-effects multinomial logistic regression to quantify the effect of prBDQ R , patient attributes, and contextual factors on the decision to continue BDQ or not when sequencing results become available. RESULTS PrBDQ R was the most influential factor for BDQ decision-making, three times greater than treatment response. Each percentage point increase in prBDQ R resulted in 8.2% lower odds (OR 0.92, 95% CI 0.90–0.93) of continuing BDQ as a fully effective drug and 5.0% lower odds (OR 0.95, 95% CI 0.94–0.96) of continuing it but not counting it as an effective drug. The most favourable patient profile for prescribing BDQ as a fully effective drug was a patient receiving the BPaLM regimen (BDQ, pretomanid, linezolid and moxifloxacin) with low prBDQ R , good 1-month treatment response, fluoroquinolone-susceptible TB, and no prior BDQ treatment. Physicians with higher discomfort with uncertainty and more years of experience with BDQ were more inclined to stop BDQ. CONCLUSION Given the uncertainty of genotype-phenotype associations, physicians valued prBDQ R for BDQ decision-making in rifampicin-resistant TB treatment.