Future Economics of Liver Transplantation: A 20-Year Cost Modeling Forecast and the Prospect of Bioengineering Autologous Liver Grafts

Abstract

During the past 20 years liver transplantation has become the definitive treatment for most severe types of liver failure and hepatocellular carcinoma, in both children and adults. In the U.S., roughly 16,000 individuals are on the liver transplant waiting list. Only 38% of them will receive a transplant due to the organ shortage. This paper explores another option: bioengineering an autologous liver graft. We developed a 20-year model projecting future demand for liver transplants, along with costs based on current technology. We compared these cost projections against projected costs to bioengineer autologous liver grafts. The model was divided into: 1) the epidemiology model forecasting the number of wait-listed patients, operated patients and postoperative patients; and 2) the treatment model forecasting costs (pre-transplant-related costs; transplant (admission)-related costs; and 10-year post-transplant-related costs) during the simulation period. The patient population was categorized using the Model for End-Stage Liver Disease score. The number of patients on the waiting list was projected to increase 23% over 20 years while the weighted average treatment costs in the pre-liver transplantation phase were forecast to increase 83% in Year 20. Projected demand for livers will increase 10% in 10 years and 23% in 20 years. Total costs of liver transplantation are forecast to increase 33% in 10 years and 81% in 20 years. By comparison, the projected cost to bioengineer autologous liver grafts is $9.7M based on current catalog prices for iPS-derived liver cells. The model projects a persistent increase in need and cost of donor livers over the next 20 years that's constrained by a limited supply of donor livers. The number of patients who die while on the waiting list will reflect this ever-growing disparity. Currently, bioengineering autologous liver grafts is cost prohibitive. However, costs will decline rapidly with the introduction of new manufacturing strategies and economies of scale.

Fig 1. Model Scheme.

Blue and green rectangles represent, respectively, the forecast outputs of the Epidemiology Model and the Treatment Costs Model. Data used to perform the forecasts are shown in red square (refer to Table 1 for further details on data source).

Fig 2. Number of New Patients per MELD score.

(A) Metric evolution over 20-years. (B) Metric forecasts at Years 1, 10 and 20.

Fig 3. Percent of theoretic patients that would die per liver transplantation phase.

The figure shows the predicted mortality percentages. A lower proportion of patients with a high MELD scores (>30), compared to those with a MELD score < 30, are predicted to die due to the significantly shorter wait-time for an organ for sicker patients compared to those in better health.

Fig 4. Discounted costs (per theoretical patient and per liver transplantation phase) and total discounted costs of liver transplantation (per theoretical patient) at Years 1, 10 and 20.

The total weighted treatment costs of a liver transplantation will increase from $1,427,805 per patient in Year 1 to $2,093,789 per patient in Year 20.

Fig 5. Potential U.S. liver transplant demand and potential U.S. liver transplant medical expenses at Years 1, 10 and 20.

The demand for liver organs will increase by 10% in 10 years and by 23% in 20 years.