Citations

Abstract Background Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome comprising multiple pathophysiological phenotypes. HFpEF trials have largely enrolled diverse populations and reported average treatment effects, consistently yielding neutral results that may obscure drug-specific benefits within distinct subgroups. To address this issue, we employ an interaction-based that incorporates treatment-by-variable interactions to uncover drug-specific responses. Methods We leveraged four HFpEF clinical trials (TOPCAT, RELAX, NEAT-HFpEF, INDIE-HFpEF) and developed a framework comprising two complementary approaches. The first employed a prognostic responder model to evaluate whether conventional responder definitions reflect treatment-specific benefit or instead capture favorable clinical trajectories common to both treatment and placebo groups. The second used an interaction-based individual treatment effect (ITE) modeling to identify baseline variables that modify therapy effect, distinguishing drug-specific response from prognostic phenotypes. Results Although the prognostic responder model demonstrated good discrimination, further analisys suggested it primarily captured a prognostic signal associated with favorable clinical trajectories common to both treatment and placebo arms. In contrast, the ITE model identified distinct, drug-specific effect modifiers across trials (cardiorenal-inflammatory for spironolactone (TOPCAT), NO-mediated anti-inflammatory for isosorbide mononitrate (NEAT-HFpEF), afterload-reducing for inorganic nitrite (INDIE-HFpEF), and anti–volume-overload for sildenafil (RELAX). Each ITE model demonstrated significance only within its own trial suggesting drug-specific signal. Conclusions The proposed method identifies mechanism-specific effect modifiers, and uncovers clinically meaningful heterogeneity in treatment response, which is not captured by conventional MCID-based approaches. Although exploratory, these findings support phenotype-guided therapy in HFpEF and argue for phenotype-informed trial design to enhance treatment-effect detection and therapy targeting. Graphical Abstract

ImportanceThe advanced ambulatory heart failure (HF) population comprises patients who have progressed beyond the pillars of recommended stage C HF therapies but can still find meaningful life-years ahead. Although these patients are commonly encountered in practice, national databases selectively capture the small groups accepted for heart transplant listing or left ventricular assist devices. The epidemiology, trajectories, and therapies for other ambulatory patients with advanced HF are poorly understood.ObservationsIn December 2022, the National Heart, Lung and Blood Institute convened a team of experts to identify knowledge gaps and research priorities for the ambulatory population with limiting daily symptoms and transition toward refractory end-stage D HF, designated as stage C2D. This article summarizes the findings from that 3-day workshop. Workshop participants surveyed the initial challenges and knowledge gaps for (1) recognition of ambulatory C2D HF, (2) estimation of the magnitude of the affected population and identifiable subpopulations, and (3) physiologic phenotypes, such as low cardiac output, right HF, cardiorenal syndromes, congestive hepatopathy and frailty, which offer distinct targets for existing and emerging therapies. Social drivers of HF and patient preferences for quality/length of survival were highlighted as essential modifiers for personalization of therapies.Conclusions and RelevanceTen key points summarized workshop findings, with target cohorts for study proposed as a crucial next step. This workshop summary is intended as a call for action to address knowledge gaps and develop new strategies to improve outcomes in the large ambulatory population with C2D HF.