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

Abstract

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.