Patient-centered benefit-risk analysis of transcatheter aortic valve replacement - Marsh, Kevin (F1000Res, 2021)
Background: Aortic stenosis (AS) treatments include surgical aortic valve replacement (SAVR) and transcatheter aortic valve replacement (TAVR). Choosing between SAVR and TAVR requires patients to trade-off  benefits and risks. The objective of this research was to determine which  TAVR and SAVR outcomes patients consider important, collect quantitative data about how patients weigh benefits and risks, and evaluate patients’ preferences for SAVR or TAVR. Methods: Patients  were recruited from advocacy organization databases. Patients self-reported as being diagnosed with AS, and as either having received AS treatment or as experiencing AS-related physical activity limitations. An online adapted swing weighting (ASW) method – a pairwise comparison of attributes – was used to elicit attribute trade-offs from 219 patients. Survey data were used to estimate patients’ weights for AS treatment attributes, which were incorporated into a quantitative benefit-risk analysis (BRA) to evaluate patients’ preferences for TAVR and SAVR. Results: On average, patients put greater value on attributes that favored TAVR than SAVR. Patients’ valuation of the lower mortality rate, reduced procedural invasiveness, and quicker time to return to normal quality of life associated with TAVR, offset their valuation of the time over which SAVR has been proven to work. There was substantial heterogeneity in patients’ preferences. This was partly explained by age, with differences in preference observed between patients <60 years to those ≥60 years. A Monte Carlo Simulation found that 79.5% of patients prefer TAVR. Conclusions: Most AS patients are willing to tolerate sizable increases in clinical risk in exchange for the benefits of TAVR, resulting in a large proportion of patients preferring TAVR to SAVR. Further work should be undertaken to characterize the heterogeneity in preferences for AS treatment attributes. Shared decision-making tools based on attributes important to patients can support patients’ selection of the procedure that best meets their needs.