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 (prBDQR) 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 prBDQR, 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.

Keywords

• discrete choice experiment
• clinical decision-making
• treatment uncertainty