Abstract

BackgroundOver the last 50 years, clinical trials of novel interventions for acute heart failure (AHF) have, with few exceptions, been neutral or shown harm. We hypothesize that this might be related to a differential response to pharmacological therapy.MethodsWe studied the magnitude of treatment effect of rolofylline across clinical characteristics and plasma biomarkers in 2033 AHF patients and derived a biomarker-based responder sum score model. Treatment response was survival from all-cause mortality through day 180.ResultsIn the overall study population, rolofylline had no effect on mortality (HR 1.03, 95% CI 0.82–1.28, p = 0.808). We found no treatment interaction across clinical characteristics, but we found interactions between several biomarkers and rolofylline. The biomarker-based sum score model included TNF-R1α, ST2, WAP four-disulfide core domain protein HE4 (WAP-4C), and total cholesterol, and the score ranged between 0 and 4. In patients with score 4 (those with increased TNF-R1α, ST2, WAP-4C, and low total cholesterol), treatment with rolofylline was beneficial (HR 0.61, 95% CI 0.40–0.92, p = 0.019). In patients with score 0, treatment with rolofylline was harmful (HR 5.52, 95% CI 1.68–18.13, p = 0.005; treatment by score interaction p < 0.001). Internal validation estimated similar hazard ratio estimates (0 points: HR 5.56, 95% CI 5.27–7–5.87; 1 point: HR 1.31, 95% CI 1.25–1.33; 2 points: HR 0.75, 95% CI 0.74–0.76; 3 points: HR 1.13, 95% CI 1.11–1.15; 4 points, HR 0.61, 95% CI 0.61–0.62) compared to the original data.ConclusionBiomarkers are superior to clinical characteristics to study treatment heterogeneity in acute heart failure.

Highlights

  • Acute heart failure is one of the leading causes of hospitalization among patients ≥65 years and carries a dismal prognosis and high economic burden [1, 2]

  • Biomarkers are superior to clinical characteristics to study treatment heterogeneity in acute heart failure

  • To explore treatment heterogeneity across the spectrum of the biomarkers and to establish a clinical relevant cut-point, we studied differential response across the spectrum of biomarkers using the subpopulation treatment effect pattern plot (STEPP) [11, 12]

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Summary

Introduction

Acute heart failure is one of the leading causes of hospitalization among patients ≥65 years and carries a dismal prognosis and high economic burden [1, 2]. The wide variety in the underlying pathophysiological mechanisms and clinical presentations in acute heart failure challenges selection of an appropriate study population and, intuitively, hampers a universal treatment that fits all patients. Based on these factors, acute heart failure might hold a great potential for precision medicine. 50 years, clinical trials of novel interventions for acute heart failure (AHF) have, with few exceptions, been neutral or shown harm. We hypothesize that this might be related to a differential response to pharmacological therapy

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