Sharma, Kavita

Abstract Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous entity with complex pathophysiology and manifestations. Phenomapping is the process of applying statistical learning techniques to patient data to identify distinct subgroups based on patterns in the data. Phenomapping has emerged as a technique with potential to improve the understanding of different HFpEF phenotypes. Phenomapping efforts have been increasing in HFpEF over the past several years using a variety of data sources, clinical variables, and statistical techniques. This review summarizes methodologies and key takeaways from these studies, including consistent discriminating factors and conserved HFpEF phenotypes. We argue that phenomapping results to date have had limited implications for clinical care and clinical trials, given that the phenotypes, as currently described, are not reliably identified in each study population and may have significant overlap. We review the inherent limitations of aggregating and utilizing phenomapping results. Lastly, we discuss potential future directions, including using phenomapping to optimize the likelihood of clinical trial success or to drive discovery in mechanisms of the disease process of HFpEF.

Abstract Clinical trial Data and Safety Monitoring Boards (DSMBs) have a primary obligation of ensuring study participant safety, while maintaining trial integrity. The role of DSMBs is expanding, and ideally should include post-hoc reporting of deliberative processes related to clinically important safety issues or factors that could impact on future trial designs. We describe how the TOPCAT DSMB detected, investigated, and adjudicated an unexpectedly large renal adverse event signal midway through the trial, and offer general guidelines for dealing with similar unanticipated occurrences in future trials. The detection of a greater than expected incidence of deterioration in renal function, occurring in 6.1% of patients in the spironolactone arm compared with 3.9% in the placebo arm (P = 0.009), led to an in-depth DSMB review of associated study medication withdrawals and adverse events. The trial continued uninterrupted throughout the review, which reached the conclusions that spironolactone-associated renal dysfunction did not compromise overall patient safety or interfere with a perceived efficacy signal. Although no discrete mechanism for the spironolactone-associated renal adverse event signal was identified, likely possibilities are discussed. In clinical trials, DSMBs and co-ordinating centres should have the resources to detect, investigate, and adjudicate unexpected safety issues, with goals of ensuring patient safety and preserving the potential for detection of therapeutic effectiveness. In TOPCAT, spironolactone-associated renal dysfunction emerged as a potentially trial-threatening adverse event and, although clinically important, did not lead to compromise of patient safety, trial interruption, termination, or apparent loss of treatment effectiveness.