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Integrating Quality of Life and Survival Outcomes Cardiovascular Clinical Trials: Results from the PARTNER Trial

Jacob V. Spertus, View ORCID ProfileLaura A. Hatfield, David J. Cohen, Suzanne V. Arnold, Martin Ho, Philip G. Jones, Martin Leon, Bram Zuckerman, John A. Spertus
doi: https://doi.org/10.1101/513895
Jacob V. Spertus
1Department of Statistics, University of California, Berkeley CA
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Laura A. Hatfield
2Department of Health Care Policy, Harvard Medical School, Boston, MA
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David J. Cohen
3Saint Luke’s Mid America Heart Institute, Kansas City MO
4University of Missouri – Kansas City, Kansas City MO
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Suzanne V. Arnold
3Saint Luke’s Mid America Heart Institute, Kansas City MO
4University of Missouri – Kansas City, Kansas City MO
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Martin Ho
5Center for Devices and Radiologic Health, Food and Drug Administration, Bethesda MD
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Philip G. Jones
3Saint Luke’s Mid America Heart Institute, Kansas City MO
4University of Missouri – Kansas City, Kansas City MO
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Martin Leon
6Columbia University, New York, NY
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Bram Zuckerman
5Center for Devices and Radiologic Health, Food and Drug Administration, Bethesda MD
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John A. Spertus
3Saint Luke’s Mid America Heart Institute, Kansas City MO
4University of Missouri – Kansas City, Kansas City MO
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ABSTRACT

Background Survival and health status (e.g., symptoms and quality of life) are key outcomes in clinical trials of heart failure treatment. However, health status can only be recorded on survivors, potentially biasing treatment effect estimates when there is differential survival across treatment groups. Joint modeling of survival and health status can address this bias.

Methods and Results We analyzed patient-level data from the PARTNER 1B trial of transcatheter aortic valve replacement (TAVR) versus standard care. Health status was quantified with the Kansas City Cardiomyopathy Questionnaire (KCCQ) at randomization, 1, 6, and 12 months. We compared hazard ratios for survival and mean differences in KCCQ scores at 12 months using several models: the original growth curve model for KCCQ scores (ignoring death), separate Bayesian models for survival and KCCQ scores, and a Bayesian joint longitudinal-survival model fit to either 12 or 30 months of survival follow-up. The benefit of TAVR on 12-month KCCQ scores was greatest in the joint model fit to all survival data (mean difference = 33.7 points; 95% CrI: 24.2, 42.4), followed by the joint model fit to 12 months of survival follow-up (32.3 points; 95% CrI: 22.5, 41.5), a Bayesian model without integrating death (30.4 points; 95% CrI: 21.4, 39.3), and the original growth curve model (26.0 points; 95% CI: 18.7, 33.3). At 12 months, the survival benefit of TAVR was also greater in the joint model (hazard ratio = 0.50; 95% CrI: 0.32, 0.73) than in the non-joint Bayesian model (0.54; 95% CrI: 0.37, 0.75) or the original Kaplan-Meier estimate (0.55; 95% CI: 0.40, 0.74).

Conclusions In patients with severe symptomatic aortic stenosis and prohibitive surgical risk, the estimated benefits of TAVR on survival and health status compared with standard care were greater in joint Bayesian models than other approaches.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted January 12, 2019.
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Integrating Quality of Life and Survival Outcomes Cardiovascular Clinical Trials: Results from the PARTNER Trial
Jacob V. Spertus, Laura A. Hatfield, David J. Cohen, Suzanne V. Arnold, Martin Ho, Philip G. Jones, Martin Leon, Bram Zuckerman, John A. Spertus
bioRxiv 513895; doi: https://doi.org/10.1101/513895
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Integrating Quality of Life and Survival Outcomes Cardiovascular Clinical Trials: Results from the PARTNER Trial
Jacob V. Spertus, Laura A. Hatfield, David J. Cohen, Suzanne V. Arnold, Martin Ho, Philip G. Jones, Martin Leon, Bram Zuckerman, John A. Spertus
bioRxiv 513895; doi: https://doi.org/10.1101/513895

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