Background: Core patient characteristic sets (CPCS) are increasingly developed to identify variables that should be reported to describe the target population of epidemiological studies in the same medical area, while keeping the additional burden on the data collection acceptable. Methods: We conduct a systematic review of primary studies/ protocols published aiming to develop CPCS, using the PubMed database. We particularly focus on the study design and the characteristics of the proposed CPCS. Quality of Delphi studies was assessed by a tool prosposed in the literatue. All results are reported descriptively. Results: Among 23 eligible studies, Delphi survey is the most frequently used technique to obtain consensus in CPCS development (69.6%, n=16). Most studies do not include patients as stakeholders. The final CPCS rarely include socioeconomic factors. 60.9% (n=14) and 31.6% (n=6) of studies provide definition and recommend measurement methods for items, respectively. Conclusion: This study identified a considerable variation and suboptimality in many methodological aspects of CPCS studies. To enhance the credibility and adoption of CPCS, a standard for conducting and reporting CPCS studies is warranted.
Background: Bedaquiline 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. Methods: Using published phenotype data for variants in Rv0678, atpE, pepQ and Rv1979c genes in 756 Mycobacterium tuberculosis isolates 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. Results: Experts agreed on the role of Rv0678, and atpE, were uncertain about the role of pepQ and Rv1979c variants 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 in atpE (0.1%) and Rv0678 (3.3%), high for missense mutations in atpE (60.8%) and nonsense mutations in Rv0678 (55.1%), relatively low for missense (31.5%) mutations and frameshift (30.0%) in Rv0678 and low for missense mutations in pepQ (2.6%) and Rv1979c (2.9%), but 95% credible intervals were wide. Conclusions: Bayesian 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.
Background Bedaquiline (BDQ) is a core drug for rifampicin-resistant tuberculosis (RR-TB) treatment. Accurate prediction of a BDQ-resistant phenotype from genomic data is not yet possible. A Bayesian method to predict BDQ resistance probability from next-generation sequencing data has been proposed as an alternative. Methods We performed a qualitative study to investigate the decision-making of physicians when facing different levels of BDQ resistance probability. Fourteen semi-structured interviews were conducted with physicians experienced in treating RR-TB, sampled purposefully from eight countries with varying income levels and burden of RR-TB. Five simulated patient scenarios were used as a trigger for discussion. Factors influencing the decision of physicians to prescribe BDQ at macro-, meso- and micro levels were explored using thematic analysis. Results The perception and interpretation of BDQ resistance probability values varied widely between physicians. The limited availability of other RR-TB drugs and the high cost of BDQ hindered physicians from altering the BDQ-containing regimen and incorporating BDQ resistance probability in their decision-making. The little experience with BDQ susceptibility testing and whole-genome sequencing results, and the discordance between phenotypic susceptibility and resistance probability were other barriers for physicians to interpret the resistance probability estimates. Especially for BDQ resistance probabilities between 25% and 70%, physicians interpreted the resistance probability value dynamically, and other factors such as clinical and bacteriological treatment response, history of exposure to BDQ, and resistance profile were often considered more important than the BDQ probability value for the decision to continue or stop BDQ. In this grey zone, some physicians opted to continue BDQ but added other drugs to strengthen the regimen. Conclusions This study highlights the complexity of physicians' decision-making regarding the use of BDQ in RR-TB regimens for different levels of BDQ resistance probability.. Ensuring sufficient access to BDQ and companion drugs, improving knowledge of the genotype–phenotype association for BDQ resistance, availability of a rapid molecular test, building next-generation sequencing capacity, and developing a clinical decision support system incorporating BDQ resistance probability will all be essential to facilitate the implementation of BDQ resistance probability in personalizing treatment for patients with RR-TB.
Background Bedaquiline (BDQ) is a core drug for rifampicin-resistant tuberculosis (RR-TB) treatment. Accurate prediction of a BDQ-resistant phenotype from genomic data is not yet possible. A Bayesian method to predict BDQ resistance probability from next-generation sequencing data has been proposed as an alternative. Methods We performed a qualitative study to investigate the decision-making of physicians when facing different levels of BDQ resistance probability. Fourteen semi-structured interviews were conducted with physicians experienced in treating RR-TB, sampled purposefully from eight countries with varying income levels and burden of RR-TB. Five simulated patient scenarios were used as a trigger for discussion. Factors influencing the decision of physicians to prescribe BDQ at macro-, meso- and micro levels were explored using thematic analysis. Results The availability of BDQ and companion RR-TB drugs, the cost of BDQ, and the need for consultation with the clinical advisory committee shaped physicians' view on BDQ use and how they weighed BDQ resistance probability in their decision-making. Physicians’ view on the role of BDQ and accuracy of drug susceptibility testing impacted their perception of the BDQ resistance probability estimate. Physicians’ interpretation of BDQ resistance probability values varied widely. Probabilities between 25% and 70% were often seen as a grey zone, where physicians interpret the BDQ resistance probability dynamically, considering patient characteristics, including treatment response, history of exposure to BDQ, and resistance profile. In the grey zone, some physicians opted to continue BDQ but added other drugs to strengthen the regimen. Conclusions This study highlights the complexity of physicians' decision-making regarding the use of BDQ in RR-TB regimens for different levels of BDQ resistance probability. Structural barriers, physicians’ views on accuracy of drug susceptibility testing and patient characteristics influenced BDQ prescription and interpretation of the BDQ resistance probability. The development of a clinical decision support system incorporating BDQ resistance probability could facilitate the use of next generation sequencing and implementation of BDQ resistance probability in personalizing treatment for patients with RR-TB.
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