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Background: The use of the Model for End-Stage Liver Disease (MELD) score to prioritize patients on liver waiting lists must take the bias of different laboratories into account., Methods: We evaluated the outcome of 418 patients listed during 1 year whose MELD score was computed by two laboratories (lab 1 and lab 2). The two labs had different normality ranges for bilirubin (maximal normal value [Vmax]: 1.1 for lab 1 and 1.2 for lab 2) and creatinine (Vmax: 1.2 for lab 1 and 1.4 for lab 2). The outcome during the waiting time was evaluated by considering the liver transplantations and the dropouts, which included deaths on the list, tumor progression, and patients who were too sick., Results: Although the clinical features of patients were similar between the two laboratories, 36 (13.1%) out of 275 were dropped from the list in lab 1, compared to 5 (3.5%) out of 143 in lab 2 (P<0.01). The differences were mainly due to the deaths on the list (8% lab 1 vs. 2.1% lab 2, P<0.05). The competing risk analysis confirmed the different risk of dropout between the two labs independently of the MELD score, blood group, and preoperative diagnosis. The bias on MELD calculation was considered and bilirubin and creatinine values were "normalized" to Vmax of lab 1 (corrected value=measured value x Vmax lab 1/Vmax lab 2). By comparing receiver operating characteristic curves, the ability of MELD to predict the 6-month dropouts significantly increased from an area under the curve of 0.703 to 0.716 after "normalization" (P<0.05)., Conclusions: Normalization of MELD is a correct and good compromise to avoid systematic bias due to different laboratory methods.

Background: Policies to decrease dropout during waiting time for liver transplantation (LT) are under debate., Methods: We evaluated the allocation system from 1996 to 2003, when recipients had priority related to Child-Pugh score and donors >60 years were mainly offered to recipients with hepatocellular carcinoma (HCC). The outcomes of 656 patients with chronic liver disease (142 HCC and 514 non-HCC) listed for LT were prospectively evaluated, considering recipient and donor features., Results: Transplantation and dropout rates were similar between HCC and non-HCC patients: 64.1% vs. 70.6% and 26% vs. 22.6%. Multivariate analysis showed the probability of being transplanted within 3 months was related to Child-Pugh score >10 and to HCC, whereas the probability of being removed from the list within 3 months was only related to Child-Pugh score >10. HCC patients had a lower median waiting time (97 vs. 197 days, P<0.001), a higher rate of donors > 60 years (50.5% vs. 33.5%, P<0.005) and with steatosis (31.6% vs. 14.3%, P<0.01), but a lower Child-Pugh score (9.1+/-2.1 vs. 9.6+/-1.7, P<0.05) than non-HCC patients. The 5-year patient survival was comparable since registration on the list and since LT: 56.9% and 77% in the HCC group vs. 61.4% and 79% in the non-HCC patients. Donors > 60 years affected outcome after LT in the non-HCC group, but not in the HCC patients., Conclusion: By allocating donors >60 years mainly to HCC patients, we controlled dropout without affecting their survival and the outcome of non-HCC patients.

Background/Aims: Debate continues on whether serum and intrahepatic HCV viral loads are correlated and if HCV viral load correlates with the severity of liver disease. These difficulties may at least in part be linked to liver cell heterogeneity, when total liver extracts from HCV-infected individuals are tested for HCV RNA quantification. We have therefore investigated the feasibility of quantifying HCV replication using a laser-based microdissection technique.Methods: We compared the results with those obtained for serum HCV RNA quantification and immunochemistry in the case of HCV antigen detection in the liver. Twenty-one HCV-positive patients with chronic active hepatitis (n=10) or cirrhosis (n=11) were analyzed.Results: A positive correlation (P=0.0019) was observed between HCV RNA quantifications in sera and microdissected cells. Immunohistochemistry demonstrated that HCV antigen hepatocytes were randomly distributed within liver lobules. Their percentage varied in different patients (0–40%), but did not correlate with the HCV viral load.Conclusions: We have designed a sensitive methodology to evaluate the intrahepatic HCV viral load by combining a standardized RNA quantification method with microdissected hepatocytes from frozen liver needle biopsies. Our results directly demonstrate a positive correlation between serum and intrahepatic viral loads, which therefore provides a reliable reflection of intrahepatic HCV replication. [Copyright &y& Elsevier]