A Proposal of a Cost-Effectiveness Modeling Approach for Heart Failure Treatment Assessment: Considering the Short- and Long-Term Impact of Hospitalization on Event Rates

Gian Luca Di Tanna (), Blake Angell, Michael Urbich, Peter Lindgren, Thomas A. Gaziano, Gary Globe and Björn Stollenwerk
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Gian Luca Di Tanna: University of New South Wales
Blake Angell: The George Institute for Global Health
Michael Urbich: Biogen International GmbH
Peter Lindgren: Karolinska Institutet
Thomas A. Gaziano: Brigham and Women’s Hospital, Harvard Medical School
Gary Globe: Cerevel Therapeutics
Björn Stollenwerk: Amgen (Europe) GmbH, Economic Modeling Center of Excellence

PharmacoEconomics, 2022, vol. 40, issue 11, No 6, 1095-1105

Abstract: Abstract Background The rate of events such as recurrent heart failure (HF) hospitalization and death are known to dramatically increase directly after HF hospitalization. Furthermore, the number of HF hospitalizations is associated with irreversible long-term disease progression, which is in turn associated with increased event rates. However, cost-effectiveness models of HF treatments commonly fail to capture both the short- and long-term association between HF hospitalization and events. Objective The aim of this study was to provide a decision-analytic model that reflects the short- and long-term association between HF hospitalization and event rates. Furthermore, we assess the impact of omitting these associations. Methods We developed a life-time Markov cohort model to evaluate HF treatments, and modeled the short-term impact of HF hospitalization on event rates via a sequence of tunnel states, with transition probabilities following a parametric survival curve. The corresponding long-term impact was modeled via hazard ratios per HF hospitalization. We obtained baseline event rates and utilities from published literature. Subsequently, we assessed, for a hypothetical HF treatment, how omitting the modeled associations (through a simple two-state model) affects incremental quality-adjusted life-years (QALYs). Results We developed a model that incorporates both short- and long-term impacts of HF hospitalizations. Based on an assumed treatment effect of a 20% risk reduction for HF hospitalization (and associated reductions in all-cause mortality of 15%), omitting the short-term, the long-term, or both associations resulted in a 5%, 1%, and 22% decrease in QALYs gained, respectively. Conclusion For both modeling components, i.e., the short- and long-term implications of HF hospitalization, the impact on incremental outcomes associated with treatment was substantial. Considering these aspects as proposed within this modeling approach better reflects the natural course of this progressive condition and will enhance the evaluation of future HF treatments.

Date: 2022
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DOI: 10.1007/s40273-022-01174-2

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