The current heart transplant allocation system and the newly recommended one prioritizes patients based on waitlist survival and does not take into account risk of death after transplant or likelihood of transplantation. Furthermore, it defines medical urgency for transplantation mainly by use of devices and not by objective evidence of medical illness. Unfortunately, many heart failure patients die on the waitlist, including a disproportionate number of women, Hispanics, and patients with certain heart diseases like restrictive cardiomyopathy. After transplantation there are also survival disparities. The long-term goal of this project is to optimize timing for advanced heart failure therapy in order to improve survival and minimize organ wastage. The objective of this research application is to identify risk factors for disparities in survival among heart transplant candidates and post-transplantation and to create tools that will improve outcome in therapy while minimizing organ wastage. The central hypothesis is that a better heart transplant allocation system requires knowledge of how population differences affect patient selection, waitlist mortality, and post-transplant mortality. The rationale for the proposed research is that there are known disparities (sex, race, and type of heart disease) in survival among advanced heart failure patients (pre- and post-transplantation) and creation of risk prediction models have successfully reduced waitlist mortality for lung, liver, and kidney transplantation.
The specific aims of this research proposal are: 1) to identify risk factors for disparities in survival among heart transplant candidates and post-transplantation using the national transplant database 2) to develop a method to dynamically update risk of waitlist mortality across time using data from multiple transplant centers that includes potential prognistic risk factors not available in our national transplant database and 3) to create a mathematical model that simultaneous estimates waitlist and post-transplant mortality to optimize timing of transplantation. The approach is innovative because it utilizes new mathematical approaches and seeks to shift current heart failure research and clinical practice paradigms by taking into account population differences rather than basing decisions solely on ejection fraction, presence of coronary artery disease, and stages of disease. The proposed research is significant, because few studies have explored population differences in advanced heart failure to determine the factors associated with mortality on the waitlist and poor outcome post-transplantation. This proposal will evaluate the complex interplay of population differences (i.e sex, race, type of heart disease, laboratory measures of organ dysfunction, and influences of co-morbidities) as they relate to mortality on the waitlist, timing of transplantation, and mortality after transplantation. If the aims of our proposal are achieved, our research has the potential to empower clinicians and researchers to provide the right therapies for the right patient at the right time.
There are disparities in survival among patients on the waiting list for a heart transplant, and post-transplantation. These differences are not recognized by the current and newly recommended heart transplant allocation system. Our proposal will identify the factors contributing to these population differences in order to improve survival and minimize organ wastage.
| Ishwaran, Hemant; Lu, Min (2018) Standard errors and confidence intervals for variable importance in random forest regression, classification, and survival. Stat Med : |
| Blackstone, Eugene H; Rajeswaran, Jeevanantham; Cruz, Vincent B et al. (2018) Continuously Updated Estimation of Heart Transplant Waitlist Mortality. J Am Coll Cardiol 72:650-659 |
