Heterogeneous Treatment Effects in HFpEF: Distinguishing Drug-Specific Response from Prognostic Phenotypes Across...

Area of Science:

• Cardiovascular Medicine
• Clinical Pharmacology
• Biostatistics

Background:

• Heart failure with preserved ejection fraction (HFpEF) is a complex syndrome with diverse underlying pathophysiological phenotypes.
• Previous HFpEF clinical trials often included heterogeneous populations, leading to neutral average treatment effects that may mask benefits in specific patient subgroups.
• Current approaches may obscure drug-specific benefits by failing to account for distinct patient phenotypes within HFpEF.

Purpose of the Study:

• To develop and apply a novel analytical framework to uncover drug-specific treatment responses in HFpEF.
• To identify baseline variables that modify treatment effects, distinguishing true drug-specific benefits from general prognostic trajectories.
• To support the development of phenotype-guided therapeutic strategies for HFpEF.

Main Methods:

• Leveraged data from four HFpEF clinical trials (TOPCAT, RELAX, NEAT-HFpEF, INDIE-HFpEF).
• Employed a prognostic responder model to assess if responder definitions reflect treatment-specific benefits or common favorable clinical trajectories.
• Utilized interaction-based individual treatment effect (ITE) modeling to identify baseline variables that modify therapy effects.

Main Results:

• The prognostic responder model primarily captured a general prognostic signal, not treatment-specific benefits.
• ITE modeling identified distinct, drug-specific effect modifiers for different HFpEF medications: spironolactone (cardiorenal-inflammatory), isosorbide mononitrate (NO-mediated anti-inflammatory), inorganic nitrite (afterload-reducing), and sildenafil (anti-volume-overload).
• The significance of each ITE model was trial-specific, reinforcing the drug-specific nature of the identified signals.

Conclusions:

• The proposed interaction-based method effectively identifies mechanism-specific effect modifiers in HFpEF.
• This approach uncovers clinically significant heterogeneity in treatment response, surpassing conventional methods.
• Findings support phenotype-guided therapy and advocate for phenotype-informed trial design to enhance treatment efficacy detection in HFpEF.