Di Tanna, Gian Luca http://orcid.org/0000-0002-5470-3567
Angell, Blake
Urbich, Michael
Lindgren, Peter
Gaziano, Thomas A.
Globe, Gary
Stollenwerk, Björn
Funding for this research was provided by:
Amgen
Article History
Accepted: 5 July 2022
First Online: 12 August 2022
Declarations
:
: Financial support for this study was provided entirely by Amgen Inc. The funding agreement ensured the authors’ independence in designing the study, interpreting the data, and writing and publishing the report.
: GLDT planned and originally implemented the model proposal and wrote the paper. BA assisted with the analyses and gave writing support. MU and BS implemented the model in Microsoft Excel and gave writing support. PL, TG and GG gave expert opinion support and writing contributions. All authors participated in the critical review of the manuscript and approved the final version submitted for publication
: Björn Stollenwerk is an Amgen employee and Amgen corporate stockholder. Peter Lindgren and Thomas A. Gaziano received Amgen funds and/or honoraria. Gian Luca Di Tanna and Michael Urbich are former Amgen employees. Gian Luca Di Tanna received Amgen honoraria paid to his employer. Gary Globe is a former Amgen employee and remains an Amgen corporate stockholder. Blake Angell is supported by an National Health and Medical Research Council Emerging Leadership Grant (GNT2010055) and declares no other funding or conflicts of interests related to this work.
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: The four models that we have discussed in this manuscript are available at the following Open Science Framework companion repository: ExternalRef removed (Di Tanna, G. L. [2022, July 2]; A Proposal of Cost-effectiveness Modeling Approach for Heart Failure Treatment Assessment: Considering the Short- and Long-Term Impact of Hospitalization on Event Rates). These have been developed using the widely available Microsoft Excel suite (Microsoft Corporation, Redmond, WA, USA) but they can be programmed taking advantage of the increasingly available R packages such as heemod, hesim and mstate (The R Foundation for Statistical Computing, Vienna, Austria), among others.