Analysing recurrent hospitalizations in heart failure: a review of statistical methodology, with application to CHARM-Preserved
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Aims: Heart failure is characterized by recurrent hospitalizations, but often only the first event is considered in clinical trial reports. In chronic diseases, such as heart failure, analysing all events gives a more complete picture of treatment benefit. We describe methods of analysing repeat hospitalizations, and illustrate their value in one major trial. Methods and results: The Candesartan in Heart failure Assessment of Reduction in Mortality and morbidity (CHARM)-Preserved study compared candesartan with placebo in 3023 patients with heart failure and preserved systolic function. The heart failure hospitalization rates were 12.5 and 8.9 per 100 patient-years in the placebo and candesartan groups, respectively. The repeat hospitalizations were analysed using the Andersen–Gill, Poisson, and negative binomial methods. Death was incorporated into analyses by treating it as an additional event. The win ratio method and a method that jointly models hospitalizations and mortality were also considered. Using repeat events gave larger treatment benefits than time to first event analysis. The negative binomial method for the composite of recurrent heart failure hospitalizations and cardiovascular death gave a rate ratio of 0.75 [95% confidence interval (CI) 0.62–0.91, P = 0.003], whereas the hazard ratio for time to first heart failure hospitalization or cardiovascular death was 0.86 (95% CI 0.74–1.00, P = 0.050). Conclusions: In patients with preserved EF, candesartan reduces the rate of admissions for worsening heart failure, to a greater extent than apparent from analysing only first hospitalizations. Recurrent events should be routinely incorporated into the analysis of future clinical trials in heart failure.
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As a pre-specified statistical method, negative binomial regression was used to calculate rates and rate ratios for total cardiovascular events.
“As a pre-specified statistical method, we used the negative binomial regression model to calculate rates and rate ratios for total cardiovascular events, which accounts for the variability in each patient's risk of events (45-47).”
From Effects of Icosapent Ethyl on Total Ischemic Events (2019) · cites this paper as [46]
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- Authors
- Rogers, J. K., Pocock, S. J., McMurray, J. J. V., Granger, C. B., Michelson, E. L., Östergren, J., Pfeffer, M. A., Solomon, S. D., Swedberg, K., & Yusuf, S.
- Affiliations
- London School of Hygiene & Tropical Medicine (GB)
- University of Glasgow (GB)
- Duke University (US)
- AstraZeneca (United States) (US)
- Karolinska University Hospital (SE)
- Brigham and Women's Hospital (US)
- Imperial College London (GB)
- Hamilton Health Sciences (CA)
- Corresponding author
- Rogers, Jennifer K.
- ORCID
- Venue
- European Journal of Heart Failure
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-12-18
- Volume
- 16
- Issue
- 1
- Pages
- 33-40
- ISSN
- 1388-9842 (ISSN-L)
- 1879-0844
- PMC
- PMC4822681
- OpenAlex
- W1870916828
- Cited by
- 226
- References
- 26
- Citations by year
- 2026: 7 · 2025: 9 · 2024: 15 · 2023: 20 · 2022: 23 · 2021: 28 · 2020: 11 · 2019: 20 · 2018: 21 · 2017: 26 · 2016: 23 · 2015: 13 · 2014: 8 · 2013: 2
- FWCI
- 10.43
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- European Journal of Heart Failure (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Research Bank (Australian Catholic University) (submittedVersion)
- ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- AstraZeneca
- National Institute for Health and Care Research (PDF-2013-06-024)
- Medical Research Council (MC_EX_G0800814)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Failure Treatment and Management
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- heart failure, recurrent hospitalization, heart failure with preserved ejection fraction, candesartan, Andersen-Gill model, negative binomial regression, Poisson regression, win ratio, treatment benefit, cardiovascular mortality
- MeSH terms
- Data Interpretation, Statistical, Heart Failure, Hospitalization, Humans, Morbidity, Global Health, Survival Rate, Risk Assessment
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