Waiting time predicts survival after liver transplantation for hepatocellular carcinoma: a cohort study using the United Network for Organ Sharing registry.

Recipients of liver transplantation (LT) for hepatocellular carcinoma (HCC) have an 8% to 20% risk of HCC recurrence. Single-center studies suggest that a period of waiting after HCC therapy may facilitate the selection of patients at low risk for post-LT HCC recurrence and mortality. We evaluated whether a longer waiting time after Model for End-Stage Liver Disease (MELD) prioritization for HCC predicts longer post-LT survival. From the United Network for Organ Sharing registry, we selected 2 groups registered for LT between March 2005 and March 2009: (1) HCC patients receiving MELD prioritization and (2) non-HCC patients. Patients were stratified by their MELD status at LT (a marker of time on the wait list after HCC MELD prioritization) and were followed from LT until death or censoring through October 2012. By comparing post-LT survival to intention-to-treat (ITT) survival from registration, we assessed predictors of post-LT survival and estimated the benefit of LT. The median MELD scores at LT were 22 (HCC) and 24 (non-HCC). A higher MELD score at LT was independently associated with lower post-LT mortality in the HCC group [hazard ratio (HR) = 0.84, 95% confidence interval (CI) = 0.73-0.98] and higher post-LT mortality in the non-HCC group (HR = 1.20, 95% CI = 1.15-1.25). Compared with the HCC group, the non-HCC group had lower post-LT mortality [relative risk (RR) = 0.85, log-rank P < 0.01] but higher ITT mortality (RR = 1.25, log-rank P < 0.01) because of a 33 percentage point lower probability of undergoing LT. In conclusion, a longer waiting time before LT for HCC predicted longer post-LT survival in a national transplant registry. Delaying LT for HCC may reduce disparities in ITT survival and access to LT among different indications and thereby improve system utility and organ allocation equity for the overall pool of LT candidates.

Survival and cost-effectiveness analysis of competing strategies in the management of small hepatocellular carcinoma.

The aim of the present study is to compare the survival rates and cost-effectiveness of different treatment strategies for small (<2 cm) hepatocellular carcinoma (HCC). Markov chains are developed to model different management strategies for patients with compensated cirrhosis and small HCC. Probabilities of progression and survival and the likelihood of orthotopic liver transplantation are taken from the literature and incorporated into the models. As a starting population, 1000 patients are followed over a period of 10 years. Patients treated immediately with transarterial chemoembolization (TACE) or radiofrequency ablation (RFA) live as long as or longer than patients who are monitored expectantly with the intention of liver transplantation once the HCC has grown larger than 2 cm and a higher transplant priority score becomes available. With TACE, immediate treatment results in an average survival time of 4.269 years versus 4.324 years with the monitoring strategy. With RFA, immediate treatment results in an average survival time of 5.273 years versus 5.236 years with the monitoring strategy. In addition, the cost analysis shows that immediate treatment with either TACE or RFA is less expensive than monitoring. The better cost-effectiveness of immediate therapy versus the monitoring strategy remains robust and unaffected by variations of the assumptions built into the model. In conclusion, in patients with compensated cirrhosis and small HCC, a strategy of immediate treatment with either TACE or RFA prevails over a strategy of expectant monitoring with the intention of transplantation.

Models of influence in chronic liver disease.

BACKGROUND & AIMS: Liver disease is often characterized by an intricate network of multiple, simultaneously interacting factors with organ-specific, as well as systemic effects. The aim of the present study is to introduce a new mathematical model on how to weigh a variety of factors contributing to chronic liver disease by the relevance of their influence on the overall disease processes. METHODS: Liver disease is modelled as the interaction of multiple internal and external factors. Each factor can potentially interact with any of the other factors in the model. The strength of interactions is expressed as per cent. The sum of all interactions contributing to each individual factor adds up to 100%. This model corresponds mathematically to a transposed Markov matrix. The analysis uses the two examples of hepatitis C virus (HCV) and autoimmune hepatitis (AIH). RESULTS: Impaired liver function is the most influential factor and increases in relevance as the degree of hepatic fibrosis increases. The relative importance of treating the primary disease process (HCV or AIH) diminishes as fibrosis develops. Similarly, psychosocial factors become less important with disease progression. Liver transplant is most important for Child's C cirrhosis. It is relatively influential for the early phase of AIH but not HCV, reflecting the fact that some cases of non-cirrhotic AIH can progress rapidly to acute liver failure. CONCLUSION: In a disease process characterized by a large array of multiple interacting factors, the decision tool of a transposed Markov chain helps to sort the contributing factors by the magnitude of their influence.