How can we better inform our patients about post-heart transplantation survival? A conditional survival analysis.

Background: Conditional survival (CS) is a dynamic method of survival analysis that provides an estimate of how an individual's future survival probability changes based on time post-transplant, individual characteristics, and post-transplant events. This study sought to provide post-transplant CS probabilities for heart transplant recipients based on different prognostic variables and provide a discussion tool for the providers and the patients.
Methods: Adult heart transplant recipients from January 1, 2004, through October 18, 2018, were identified in the UNOS registry. CS probabilities were calculated using data from Kaplan-Meier survival estimates.
Results: CS probability exceeded actuarial survival probability at all times post-transplant. Women had similar short-term, but greater long-term CS than men at all times post-transplant (10-year CS 1.8-11.5% greater [95% CI 1.2-12.9]). Patients with ECMO or a surgical BiVAD had decreased survival at the time of transplant, but their CS was indistinguishable from all others by 1-year post-transplant. Rejection and infection requiring hospitalization during the first year were associated with a persistently decreased CS probability.
Conclusions: In this study, we report differential conditional survival outcomes based on time, patient characteristics, and clinical events post-transplant, providing a dynamic assessment of survival. The survival probabilities will better inform patients and clinicians of future outcomes.
(© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)