The problem with hospitalization endpoints in heart failure trials

Abstract

Most early trials for heart failure (HF) assessed the effect of therapies on haemodynamic parameters, functional capacity and symptoms. Methodological limitations of these trials, as well the discovery that improvements in symptoms do not always correlate with better outcomes, 1 resulted in the inclusion of cardiovascu-lar safety as a mandated trial endpoint. The near parallel discovery that neurohormonal blockade could improve survival led to a paradigm in which new treatments received regulatory approval on this basis. As prognosis improved with successive therapies, event rates in clinical trials declined, meaning ever-larger sample sizes were required (Figure 1). Further confounding the situation, participant profiles have shifted from a population of younger people with a single condition, to one which is older and increasingly multimorbid. With this has come an increasing contribution of non-cardiovascular events, which dilute the treatment effect of HF specific therapies. 2 Why hospitalizations matter A hospitalization for HF is a significant event, commonly followed by a permanent decline in quality of life, functional status, and independence. This might result from direct harms of the hospitalization itself or simply reflect the progression of the underlying HF syndrome. Hospitalizations are not only the costliest component of HF care but, given its high and increasing prevalence , also form a large proportion of overall healthcare expenditure. Regulatory bodies and guideline committees now consider reducing hospitalizations a valid reason to recommend treatments , and so capturing and reporting these data in HF trials is essential. So, what's the problem? Problem 1: Hospitalizations are different from other endpoints Whilst hospitalizations (and their causes) are more difficult to assess than total mortality, preventing both death and hospitalization are important to patients. Including hospitalization events within composite endpoints is, therefore, a legitimate strategy to provide a broader assessment of treatment effects, whilst also having the advantage of increasing statistical power. Nevertheless , in time-to-first or first-and-recurrent event analyses, hospitalization events are regarded as being equally important to death although intuitively, this makes no sense. Whilst balancing the relative importance of mortality and hospitalization endpoints is challenging, this conflict is limited if the direction of the effect is concordant. Discordant endpoints complicate trial interpretation. In FINEARTS-HF (Finerenone Trial to Investigate Efficacy and Safety Superior to Placebo in Patients with Heart Failure), reductions in worsening HF events were not corroborated by reductions in cardiovascular death or total mortality. 3 Whilst this trial is widely viewed as 'positive' and potentially practice changing , comparable reductions in HF hospitalizations in DIG (Digi-talis Investigation Group) have been largely forgotten, perhaps in part due to the choice of all-cause mortality as this trial's primary endpoint. 4 Hierarchical clinical composite endpoints attempt to take account of how mortality, hospitalization and patient-reported outcomes differ in their relative importance, whilst also increasing statistical power and including more information relevant to patients. 5 However, subjective endpoints may dominate where event rates are low. In trials assessing tricuspid transcatheter edge-to-edge repair for right HF adverse clinical events were uncommon, and so the positive results were driven by unblinded quality-of-life assessments, which are challenging to assess since most scoring systems are influenced by comorbidities in this population. 6,7 The conflation of surrogate markers with mortality