Liver transplantation for primary biliary cirrhosis and primary sclerosing cholangitis: predicting outcomes with natural history models.

Abstract

In patients with primary biliary cirrhosis (PBC) and primary sclerosing cholangitis (PSC), risk score models that reflect disease severity have been developed and can serve as an objective measurement to assess and evaluate the effect of the severity of liver disease on the outcome of liver transplantation. Thus, using the established Mayo risk scores for PBC and PSC, one not only can estimate survival for the individual patient but can measure disease activity as well. Indeed, several studies have suggested that the optimal timing of liver transplantation with use of the Mayo PBC model may be an important tool to improve survival, decrease morbidity, and decrease overall related costs. Likewise, studies in patients with PSC have yielded similar results. This review explores how prognostic mathematical survival models for PBC and PSC might be applied to individual patients in need of liver transplantation. The following question is addressed: How can the timing of liver transplantation be optimized to increase survival, decrease postoperative morbidity, and ultimately, decrease the overall resource utilization involved in this procedure?