End stage liver disease (ESLD) is a problem of major proportions in the United States, and liver transplantation is an effective but expensive therapy for this disease. Recent publicity surrounding organ allocation and waiting times has brought the question of the optimal selection of candidates and timing of transplantation under significant public scrutiny. Therefore, the specific aim of this project is to construct a complex, realistic mathematical simulation model of ESLD that is sufficiently detailed to determine the optimal timing of transplantation during the natural course of disease. Because these methods have the ability to evaluate models across several dimensions simultaneously, the model will integrate natural history, survival, costs, and quality of life into a single decision analytic framework. Although such models have substantial data requirements, the recent development and availability of several large series of liver transplantation candidates such as the NIDDK Liver Transplantation Registry) make the detailed calibration of such models possible. This project is an example of health services research designed to utilize existing registries and databases to the extent possible. The work is divided into three separate tasks: 1) By using techniques and the basic model structure developed under prior work by the PI, we will create disease specific simulation models of ESLD. The effort will be enhanced through the use of better supported modeling software, and the extensive transplantation expertise of the University of Pittsburgh and the Deaconess Hospital. 2) The model will be calibrated with time-varying estimates of expected survival, resource use, and quality of life both before and after transplantation. Data for various portions of these estimates will come from several large existing datasets (Pittsburgh and NIDDK) augmented with judicious primary data collection to fill certain gaps in existing data. 3) Once built and calibrated, the simulation model will be used to investigate several questions about the effect of selection criteria on survival, quality of life and costs in the use of transplantation in ESLD, and the effect of various criteria on organ wasting and transplant waiting times. This work will create, for the first time, a complete model that will allow for the evaluation of the cost-effectiveness of different timing and allocation strategies.
| Stahl, James E; Kreke, Jennifer E; Malek, Fawaz Ali Abdul et al. (2008) Consequences of cold-ischemia time on primary nonfunction and patient and graft survival in liver transplantation: a meta-analysis. PLoS One 3:e2468 |
| Shechter, Steven M; Schaefer, Andrew J; Braithwaite, R Scott et al. (2006) Increasing the efficiency of Monte Carlo cohort simulations with variance reduction techniques. Med Decis Making 26:550-3 |
| Bryce, Cindy L; Angus, Derek C; Switala, JoAnn et al. (2004) Health status versus utilities of patients with end-stage liver disease. Qual Life Res 13:773-82 |
| Mendeloff, John; Ko, Kilkon; Roberts, Mark S et al. (2004) Procuring organ donors as a health investment: how much should we be willing to spend? Transplantation 78:1704-10 |
