A Bayesian approach to estimate the probability of resistance to bedaquiline in the presence of a genomic variant

ABSTRACTBackgroundBedaquiline is a core drug for treatment of rifampicin-resistant tuberculosis. Few genomic variants have been statistically associated with bedaquiline resistance. Alternative approaches for determining the genotypic-phenotypic association are needed to guide clinical care.MethodsUsing published phenotype data for variants inRv0678, atpE, pepQandRv1979cgenes in 756Mycobacterium tuberculosisisolates and survey data of the opinion of 33 experts, we applied Bayesian methods to estimate the posterior probability of bedaquiline resistance and corresponding 95% credible intervals.ResultsExperts agreed on the role ofRv0678, andatpE, were uncertain about the role ofpepQandRv1979cvariants and overestimated the probability of bedaquiline resistance for most variant types, resulting in lower posterior probabilities compared to prior estimates. The posterior median probability of bedaquiline resistance was low for synonymous mutations inatpE(0.1%) andRv0678(3.3%), high for missense mutations inatpE(60.8%) and nonsense mutations inRv0678(55.1%), relatively low for missense (31.5%) mutations and frameshift (30.0%) inRv0678and low for missense mutations inpepQ(2.6%) andRv1979c(2.9%), but 95% credible intervals were wide.ConclusionsBayesian probability estimates of bedaquiline resistance given the presence of a specific mutation could be useful for clinical decision-making as it presents interpretable probabilities compared to standard odds ratios. For a newly emerging variant, the probability of resistance for the variant type and gene can still be used to guide clinical decision-making. Future studies should investigate the feasibility of using Bayesian probabilities for bedaquiline resistance in clinical practice.