Efficiency Comparison of Analysis Methods for Recurrent Event and Time-to-First Event Endpoints in the Presence of Terminal Events—Application to Clinical Trials in Chronic Heart Failure

References

• Aalen, O. O., Cook, R. J., and Røysland, K. (2015), “Does Cox Analysis of a Randomized Survival Study Yield a Causal Treatment Effect?” Lifetime Data Analysis, 21, 579–593. DOI: 10.1007/s10985-015-9335-y.
   PubMed Web of Science ®Google Scholar
• Andersen, P., and Gill, R. (1982), “Cox’s Regression Model for Counting Processes: A Large Sample Study,” Annals of Statistics, 10, 1100–1120.
   Web of Science ®Google Scholar
• Anker, S. D., and McMurray, J. J. V. (2012), “Time to Move on From Time-to-First: Should All Events Be Included in the Analysis of Clinical Trials?” European Heart Journal, 33, 2764–2765. DOI: 10.1093/eurheartj/ehs277.
   PubMed Web of Science ®Google Scholar
• Bebu, I., and Lachin, J. (2016), “Large Sample Inference for a Win Ratio Analysis of a Composite Outcome Based on Prioritized Components,” Biostatistics, 17, 178–187. DOI: 10.1093/biostatistics/kxv032.
   PubMed Web of Science ®Google Scholar
• CHMP (2017), Committee for Medicinal Products for Human Use: Guideline on Clinical Investigation of Medicinal Products for the Treatment of Chronic Heart Failure, London: European Medicines Agency.
   Google Scholar
• Claggett, B., Pocock, S., Wei, L. J., Pfeffer, M. A., McMurray, J. J. V., and Solomon, S. D. (2018), “Comparison of Time-to-First Event and Recurrent Event Methods in Randomized Clinical Trials,” Circulation, 138, 570–577. DOI: 10.1161/CIRCULATIONAHA.117.033065.
   PubMed Web of Science ®Google Scholar
• Claggett, B., Tian, L., Fu, H., Solomon, S. D., and Wei, L.-J. (2018), “Quantifying the Totality of Treatment Effect With Multiple Event-Time Observations in the Presence of a Terminal Event From a Comparative Clinical Study,” Statistics in Medicine, 37, 3589–3598. DOI: 10.1002/sim.7907.
   PubMed Web of Science ®Google Scholar
• Cohn, J., Tognoni, G., and the Valsartan Heart Failure Trial Investigators. (2001), “A Randomized Trial of the Angiotensin-Receptor Blocker Valsartan in Chronic Heart Failure,” New England Journal of Medicine, 345, 1667–1675. DOI: 10.1056/NEJMoa010713.
   PubMed Web of Science ®Google Scholar
• EMA (2014), Qualification Opinion of MCP-Mod as an Efficient Statistical Methodology for Model-Based Design and Analysis of Phase II Dose Finding Studies Under Model Uncertainty, London: Committee for Medicinal Products for Human Use (CHMP).
   Google Scholar
• EMA (2020), Qualification Opinion of Clinically Interpretable Treatment Effect Measures Based on Recurrent Event Endpoints that Allow for Efficient Statistical Analyses, Committee for Medicinal Products for Human Use (CHMP), available at https://www.ema.europa.eu/en/human-regulatory/research-development/scientific-advice-protocol-assistance/novel-methodologies-biomarkers/opinions-letters-support-qualification-novel-methodologies-medicine-development/#treatment-effect-measures-when-using-recurrent-event-endpoints-section
   Google Scholar
• Fahrmeir, L., Kneib, T., and Lang, S. (2007), Regression, Berlin, Heidelberg, Springer: Springer Science & Business Media.
   Google Scholar
• FDA (2019), Treatment for Heart Failure: Endpoints for Drug Development—Draft Guidance for Industry, Center for Drug Evaluation and Research (CDER), Center for Biologics Evaluation and Research (CBER).
   Google Scholar
• Fletcher, D. (2012), “Estimating Overdispersion When Fitting a Generalized Linear Model to Sparse Data,” Biometrika, 99, 230–237. DOI: 10.1093/biomet/asr083.
   Web of Science ®Google Scholar
• Granger, C. B., McMurray, J. J. V., Yusuf, S., Held, P., Michelson, E. L., Olofson, B., Östergren, J., Pfeffer, M. A., and Swedberg, K. (2003), “Effects of Candesartan in Patients With Chronic Heart Failure and Reduced Left-Ventricular Systolic Function Intolerant to Angiotensin-Converting-Enzyme Inhibitors: The CHARM-Alternative Trial,” Lancet, 362, 772–776. DOI: 10.1016/S0140-6736(03)14284-5.
   PubMed Web of Science ®Google Scholar
• Jahn-Eimermacher, A. (2008), “Comparison of the Andersen–Gill Model With Poisson and Negative Binomial Regression on Recurrent Event Data,” Computational Statistics and Data Analysis, 52, 4989–4997. DOI: 10.1016/j.csda.2008.04.009.
   Web of Science ®Google Scholar
• Lin, D., Wei, L., Yang, I., and Ying, Z. (2000), “Semiparametric Regression for the Mean and Rate Functions of Recurrent Events,” Journal of Royal Statistical Society, Series B, 62, 711–730. DOI: 10.1111/1467-9868.00259.
   Google Scholar
• Luo, X. (2017), WWR: Weighted Win Loss Statistics and their Variances. R package version 1.2.2, available at https://CRAN.R-project.org/package=WWR
   Google Scholar
• Mao, L., and Lin, D. (2016), “Semiparametric Regression for the Weighted Composite Endpoint of Recurrent and Terminal Events,” Biostatistics, 17, 390–403. DOI: 10.1093/biostatistics/kxv050.
   PubMed Web of Science ®Google Scholar
• McMurray, J. J., Packer, M., Desai, A. S., Gong, J., Lefkowitz, M. P., Rizkala, A. R., Rouleau, J. L., Shi, V. C., Solomon, S. D., Swedberg, K., and Zile, M. R., for the PARADIGM-HF Investigators and Committees. (2014), “Angiotensin–Neprilysin Inhibition Versus Enalapril in Heart Failure,” New England Journal of Medicine, 371, 993–1004. DOI: 10.1056/NEJMoa1409077.
   PubMed Web of Science ®Google Scholar
• McMurray, J. J., Packer, M., Desai, A. S., Gong, J., Lefkowitz, M. P., Rizkala, A. R., Rouleau, J., Shi, V. C., Solomon, S. D., Swedberg, K., Zile, M. R., PARADIGM-HF Committees and Investigators. (2013), “Dual Angiotensin Receptor and Neprilysin Inhibition as an Alternative to Angiotensin-Converting Enzyme Inhibition in Patients With Chronic Systolic Heart Failure: Rationale for and Design of the Prospective Comparison of ARNI With ACEI to Determine Impact on Global Mortality and Morbidity in Heart Failure Trial (PARADIGM-HF),” European Journal of Heart Failure, 15, 1062–1073. DOI: 10.1093/eurjhf/hft052.
   PubMed Web of Science ®Google Scholar
• McMurray, J. J. V., Östergren, J., Swedberg, K., Granger, C. B., Held, P., Michelson, E. L., Olofsson, B., Yusuf, S., and Pfeffer, M. A. (2003), “Effects of Candesartan in Patients With Chronic Heart Failure and Reduced Left-Ventricular Systolic Function Taking Angiotensin Converting-Enzyme Inhibitors: The CHARM-Added Trial,” Lancet, 362, 767–771. DOI: 10.1016/S0140-6736(03)14283-3.
   PubMed Web of Science ®Google Scholar
• Metcalfe, C., and Thompson, S. G. (2006), “The Importance of Varying the Event Generation Process in Simulation Studies of Statistical Methods for Recurrent Events,” Statistics in Medicine, 25, 165–179. DOI: 10.1002/sim.2310.
   PubMed Web of Science ®Google Scholar
• Mogensen, U. M., Gong, J., Jhund, P. S., Li, S., Køber, L., Desai, A. S., Lefkowitz, M. P., Packer, M., Rouleau, J. L., Solomon, S. D., Claggett, B., Swedberg, K., Zile, M. R., Mueller-Velten, G., and McMurray, J. J. V. (2018), “Effect of Sacubitril/Valsartan on Recurrent Events in the Prospective Comparison of ARNI with ACEI to Determine Impact on Global Mortality and Morbidity in Heart Failure Trial (PARADIGM-HF),” European Journal of Heart Failure, 20, 760–768. DOI: 10.1002/ejhf.1139.
   PubMed Web of Science ®Google Scholar
• Pfeffer, M. A., Claggett, B., Assmann, S. F., Boineau, R., Anand, I. S., Clausell, N., Desai, A. S., Diaz, R., Fleg, J. L., Gordeev, I., Heitner, J. F., Lewis, E. F., O’Meara, E., Rouleau, J.-L., Probstfield, J. L., Shaburishvili, T., Shah, S. J., Solomon, S. D., Sweitzer, N. K., McKinlay, S. M., and Pitt, B. (2015), “Regional Variation in Patients and Outcomes in the Treatment of Preserved Cardiac Function Heart Failure With an Aldosterone Antagonist (TOPCAT) Trial,” Circulation, 131, 34–42. DOI: 10.1161/CIRCULATIONAHA.114.013255.
   PubMed Web of Science ®Google Scholar
• Pitt, B., Pfeffer, M. A., Assmann, S. F., Boineau, R., Anand, I. S., Claggett, B., Clausell, N., Desai, A. S., Diaz, R., Fleg, J. L., Gordeev, I., Harty, B., Heitner, J. F., Kenwood, C. T., Lewis, E. F., O’Meara, E., Probstfield, J. L., Shaburishvili, T., Shah, S. J., Solomon, S. D., Sweitzer, N. K., Yang, S., and McKinlay, S. M. (2014), “Spironolactone for Heart Failure With Preserved Ejection Fraction,” New England Journal of Medicine, 370, 1383–1392. DOI: 10.1056/NEJMoa1313731.
   PubMed Web of Science ®Google Scholar
• Pocock, S. J., Ariti, C. A., Collier, T. J., and Wang, D. (2011), “The Win Ratio: A New Approach to the Analysis of Composite Endpoints in Clinical Trials Based on Clinical Priorities,” European Heart Journal, 33, 176–182. DOI: 10.1093/eurheartj/ehr352.
   PubMed Web of Science ®Google Scholar
• Ponikowski, P., Voors, A. A., Anker, S. D., Bueno, H., Cleland, J. G. F., Coats, A. J. S., Falk, V., González-Juanatey, J. R., Harjola, V.-P., Jankowska, E. A., Jessup, M., Linde, C., Nihoyannopoulos, P., Parissis, J. T., Pieske, B., Riley, J. P., Rosano, G. M. C., Ruilope, L. M., Ruschitzka, F., Rutten, F. H., and van der Meer, P. (2016), “2016 ESC Guidelines for The Diagnosis and Treatment of Acute and Chronic Heart Failure,” European Journal of Heart Failure, 18, 891–975. DOI: 10.1002/ejhf.592.
   PubMed Web of Science ®Google Scholar
• Prentice, R., Williams, B., and Peterson, A. (1981), “On the Regression Analysis of Multivariate Failure Time Data,” Biometrika, 68, 373–379. DOI: 10.1093/biomet/68.2.373.
   Web of Science ®Google Scholar
• Rogers, J. K., McMurray, J. J. V., Pocock, S. J., Zannad, F., Krum, H., Van Veldhuisen, D. J., Swedberg, K., Shi, H., Vincent, J., and Pitt, B. (2012), “Eplerenone in Patients With Systolic Heart Failure and Mild Symptoms: Analysis of Repeat Hospitalizations,” Circulation, 126, 2317–2323. DOI: 10.1161/CIRCULATIONAHA.112.110536.
   PubMed Web of Science ®Google Scholar
• Rogers, J. K., Pocock, S. J., McMurray, J. J., Granger, C. B., Michelson, E. L., Östergren, J., Pfeffer, M. A., Solomon, S. D., Swedberg, K., and Yusuf, S. (2014), “Analysing Recurrent Hospitalizations in Heart Failure: A Review of Statistical Methodology, With Application to CHARM-Preserved,” European Journal of Heart Failure, 16, 33–40. DOI: 10.1002/ejhf.29.
   PubMed Web of Science ®Google Scholar
• Rogers, J. K., Yaroshinsky, A., Pocock, S. J., Stokar, D., and Pogoda, J. (2016), “Analysis of Recurrent Events With an Associated Informative Dropout Time: Application of The Joint Frailty Model,” Statistics in Medicine, 35, 2195–205. DOI: 10.1002/sim.6853.
   PubMed Web of Science ®Google Scholar
• Rondeau, V., Mazroui, Y., and Gonzales, J. R. (2012), “An R Package for the Analysis of Correlated Survival Data With Frailty Models Using Penalized Likelihood Estimation or Parametric Estimation,” Journal of Statistical Software, 47, 1–28. DOI: 10.18637/jss.v047.i04.
   Web of Science ®Google Scholar
• Schmidli, H., Roger, J. H., Akacha, M., and on behalf of the Recurrent Event Qualification Opinion Consortium (2021), “Estimands for Recurrent Event Endpoints in the Presence of a Terminal Event,” Statistics in Biopharmaceutical Research.
   Google Scholar
• Setoguchi, S., Stevenson, L. W., and Schneeweiss, S. (2007), “Repeated Hospitalizations Predict Mortality in The Community Population With Heart Failure,” American Heart Journal, 154, 260–266. DOI: 10.1016/j.ahj.2007.01.041.
   PubMed Web of Science ®Google Scholar
• Solomon, S. D., McMurray, J. J. V., Anand, I. S., Ge, J., Lam, C. S. P., Maggioni, A. P., Martinez, F., Packer, M., Pfeffer, M. A., Pieske, B., Redfield, M. M., Rouleau, J. L., van Veldhuisen, D. J., Zannad, F., Zile, M. R., Desai, A. S., Claggett, B., Jhund, P. S., Boytsov, S. A., Comin-Colet, J., Cleland, J., Düngen, H.-D., Goncalvesova, E., Katova, T. Kerr Saraiva, J. F., Lelonek, M., Merkely, B., Senni, M., Shah, S. J., Zhou, J., Rizkala, A. R., Gong, J., Shi, V. C., and Lefkowitz, M. P. (2019), “Angiotensin–Neprilysin Inhibition in Heart Failure With Preserved Ejection Fraction,” New England Journal of Medicine, 381, 1609–1620. DOI: 10.1056/NEJMoa1908655.
   PubMed Web of Science ®Google Scholar
• Toenges, G., and Jahn-Eimermacher, A. (2019), “Marginal Hazard Ration Estimates in Joint Frailty Models for Heart Failure Trials,” Biometrical Journal, 61, 1385–1401. DOI: 10.1002/bimj.201800133.
   PubMed Web of Science ®Google Scholar
• Toenges, G., and Jahn-Eimermacher, A. (2020), “Computational Issues in Fitting Joint Frailty Models for Recurrent Events With an Associated Terminal Event,” Computer Methods and Programs in Biomedicine, 188, 1–13.
   Web of Science ®Google Scholar
• Wei, J., Mütze, T., Jahn-Eimermacher, A., Roger, J. H., and on Behalf of the Recurrent Event Qualification Opinion Consortium (2021), “Properties of While-Alive Estimands for Recurrent Event Endpoints Truncated by Death,” Statistics in Biopharmaceutical Research ’, accepted.
   Google Scholar
• Wei, L., Lin, D., and Weissfeld, L. (1989), “Regression Analysis of Multivariate Incomplete Failure Time Data by Modeling Marginal Distributions,” Journal of the American Statistical Association, 84, 1065–1073. DOI: 10.1080/01621459.1989.10478873.
   Web of Science ®Google Scholar
• Wood, S. N. (2017), Generalized Additive Models—An introduction With R (2nd ed), Boca Raton, FL: Chapman & Hall/CRC.
   Google Scholar
• Yusuf, S., Pfeffer, M. A., Swedberg, K., Granger, C. B., Held, P., McMurray, J. J. V., Michelson, E. L., Olofsson, B., and Östergren, J. (2003), “Effects of Candesartan in Patients With Chronic Heart Failure and Preserved Left-Ventricular Ejection Fraction: The CHARM-Preserved Trial,” The Lancet, 362, 777–781. DOI: 10.1016/S0140-6736(03)14285-7.
   PubMed Web of Science ®Google Scholar