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      Analysis of recurrent events with an associated informative dropout time: Application of the joint frailty model

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          Abstract

          This paper considers the analysis of a repeat event outcome in clinical trials of chronic diseases in the context of dependent censoring (e.g. mortality). It has particular application in the context of recurrent heart failure hospitalisations in trials of heart failure. Semi‐parametric joint frailty models (JFMs) simultaneously analyse recurrent heart failure hospitalisations and time to cardiovascular death, estimating distinct hazard ratios whilst individual‐specific latent variables induce associations between the two processes. A simulation study was carried out to assess the suitability of the JFM versus marginal analyses of recurrent events and cardiovascular death using standard methods. Hazard ratios were consistently overestimated when marginal models were used, whilst the JFM produced good, well‐estimated results. An application to the Candesartan in Heart failure: Assessment of Reduction in Mortality and morbidity programme was considered. The JFM gave unbiased estimates of treatment effects in the presence of dependent censoring. We advocate the use of the JFM for future trials that consider recurrent events as the primary outcome. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

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          Most cited references12

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          Calcium Upregulation by Percutaneous Administration of Gene Therapy in Cardiac Disease (CUPID): a phase 2 trial of intracoronary gene therapy of sarcoplasmic reticulum Ca2+-ATPase in patients with advanced heart failure.

          Adeno-associated virus type 1/sarcoplasmic reticulum Ca(2+)-ATPase was assessed in a randomized, double-blind, placebo-controlled, phase 2 study in patients with advanced heart failure. Thirty-nine patients received intracoronary adeno-associated virus type 1/sarcoplasmic reticulum Ca(2+)-ATPase or placebo. Seven efficacy parameters were assessed in 4 domains: symptoms (New York Heart Association class, Minnesota Living With Heart Failure Questionnaire), functional status (6-minute walk test, peak maximum oxygen consumption), biomarker (N-terminal prohormone brain natriuretic peptide), and left ventricular function/remodeling (left ventricular ejection fraction, left ventricular end-systolic volume), plus clinical outcomes. The primary end point success criteria were prospectively defined as achieving efficacy at 6 months in the group-level (concordant improvement in 7 efficacy parameters and no clinically significant worsening in any parameter), individual-level (total score for predefined clinically meaningful changes in 7 efficacy parameters), or outcome end points (cardiovascular hospitalizations and time to terminal events). Efficacy in 1 analysis had to be associated with at least a positive trend in the other 2 analyses. This combination of requirements resulted in a probability of success by chance alone of 2.7%. The high-dose group versus placebo met the prespecified criteria for success at the group-level, individual-level, and outcome analyses (cardiovascular hospitalizations) at 6 months (confirmed at 12 months) and demonstrated improvement or stabilization in New York Heart Association class, Minnesota Living With Heart Failure Questionnaire, 6-minute walk test, peak maximum oxygen consumption, N-terminal prohormone brain natriuretic peptide levels, and left ventricular end-systolic volume. Significant increases in time to clinical events and decreased frequency of cardiovascular events were observed at 12 months (hazard ratio=0.12; P=0.003), and mean duration of cardiovascular hospitalizations over 12 months was substantially decreased (0.4 versus 4.5 days; P=0.05) on high-dose treatment versus placebo. There were no untoward safety findings. The Calcium Upregulation by Percutaneous Administration of Gene Therapy in Cardiac Disease (CUPID) study demonstrated safety and suggested benefit of adeno-associated virus type 1/sarcoplasmic reticulum Ca(2+)-ATPase in advanced heart failure, supporting larger confirmatory trials. http://www.clinicaltrials.gov. Unique identifier: NCT00454818.
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            Repeated hospitalizations predict mortality in the community population with heart failure.

            Identification of patients at high risk of death is critical for appropriate management of patients and health care resources. The impact of repeated heart failure (HF) hospitalization on mortality has not been studied for a large community population with HF. We aimed to characterize survival of patients in relation to the number of HF hospitalizations. Using the health care utilization databases, we identified a cohort of patients with a first hospitalization for HF among all residents of British Columbia between 2000 and 2004. Survival time was measured after patients' first and each subsequent HF hospitalization. Kaplan-Meier cumulative mortality curves were constructed after each subsequent HF hospitalization. Hazard ratios for the number of HF hospitalizations were estimated using a multivariate Cox regression adjusting for major comorbidities. Of 14,374 patients hospitalized for HF, 7401 died during the 24,766 person-years of follow-up. Mortality significantly increased after each HF hospitalization. After adjusting for age, sex, and major comorbidities, the number of HF hospitalizations was a strong predictor of all-cause death. Median survival after the first, second, third, and fourth hospitalization was 2.4, 1.4, 1.0, and 0.6 years. Advanced age, renal disease, and history of cardiac arrest attenuated the impact of the number of HF hospitalizations. The number of HF hospitalizations is a strong predictor of mortality in community HF patients. This simple predictor of mortality in HF patients should help triage management and resources for HF and trigger patient planning for prognosis.
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              Analysing recurrent hospitalizations in heart failure: a review of statistical methodology, with application to CHARM-Preserved.

              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.

                Author and article information

                Journal
                Stat Med
                Stat Med
                10.1002/(ISSN)1097-0258
                SIM
                Statistics in Medicine
                John Wiley and Sons Inc. (Hoboken )
                0277-6715
                1097-0258
                10 January 2016
                15 June 2016
                : 35
                : 13 ( doiID: 10.1002/sim.v35.13 )
                : 2195-2205
                Affiliations
                [ 1 ]University of Oxford OxfordU.K.
                [ 2 ]Vital Systems, Inc Rolling MeadowsU.S.A.
                [ 3 ]London School of Hygiene and Tropical Medicine LondonU.K.
                [ 4 ]Mesoblast New YorkU.S.A.
                [ 5 ]Celladon San DiegoU.S.A.
                Author notes
                [*] [* ] Correspondence to: Jennifer K. Rogers, University of Oxford, Oxford, U.K.

                E‐mail: j.rogers@ 123456stats.ox.ac.uk

                Article
                SIM6853 sim.6853
                10.1002/sim.6853
                5019155
                26751714
                4f7733c6-4e87-4b65-8a58-a3a837fdfb59
                © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 21 October 2014
                : 06 October 2015
                : 26 November 2015
                Page count
                Pages: 11
                Funding
                Funded by: National Institute for Health Research
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                sim6853
                sim6853-hdr-0001
                15 June 2016
                Converter:WILEY_ML3GV2_TO_NLMPMC version:4.9.4 mode:remove_FC converted:12.09.2016

                Biostatistics
                recurrent events,dependent censoring,joint frailty models,heart failure
                Biostatistics
                recurrent events, dependent censoring, joint frailty models, heart failure

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