ABSTRACT
BACKGROUND/AIMS: Selection of patients for hepatectomy for hepatocellular carcinoma conventionally has been based upon Child-Pugh grading. However, postoperative liver failure after hepatectomy is a major cause of hospital mortality. A new predictor of postoperative liver failure is required. The objective of this study was to identify risk factors for postoperative liver failure after hepatectomy. METHODOLOGY: Perioperative risk factors for liver failure after hepatectomy were analyzed in 112 patients with hepatocellular carcinoma Eight of these patients died of liver failure. Stepwise multivariate logistic regression was performed to investigate significant independent factors among 17 variables, including the serum alkaline phosphatase ratio (ALPR) on the first day after hepatectomy. ALPR was calculated as the postoperative ALP level divided by the ALP level before surgery. RESULTS: Significant risk factors of postoperative liver failure were ALPR on postoperative day 1 (ALPR1), sex, operative blood loss, and operative procedure. As an indicator of liver failure, the diagnostic accuracy of the ALPR1 was 93.7% when the ALPR was less than 0.4 on the first postoperative day. The ALPR and the serum total bilirubin concentration after hepatectomy were uncorrelated. CONCLUSIONS: ALPR1 is a useful predictor of liver failure after hepatectomy.
Subject(s)
Alkaline Phosphatase/metabolism , Carcinoma, Hepatocellular/surgery , Hepatectomy/adverse effects , Hospital Mortality/trends , Liver Failure, Acute/diagnosis , Liver Neoplasms/surgery , Aged , Alkaline Phosphatase/analysis , Biomarkers/blood , Carcinoma, Hepatocellular/diagnosis , Carcinoma, Hepatocellular/mortality , Chi-Square Distribution , Cohort Studies , Female , Follow-Up Studies , Hepatectomy/methods , Humans , Liver Failure, Acute/etiology , Liver Failure, Acute/mortality , Liver Function Tests , Liver Neoplasms/diagnosis , Liver Neoplasms/mortality , Logistic Models , Male , Middle Aged , Neoplasm Staging , Postoperative Complications/mortality , Predictive Value of Tests , Retrospective Studies , Risk Factors , Severity of Illness Index , Statistics, Nonparametric , Survival AnalysisABSTRACT
BACKGROUND: Hepatocellular carcinoma has a poor prognosis because of the high intrahepatic recurrence rate. There are technological limitations to traditional methods such as TNM staging for accurate prediction of recurrence, suggesting that new techniques are needed. METHODS: We investigated mRNA expression profiles in tissue specimens from a training set, comprising 33 patients with hepatocellular carcinoma, with high-density oligonucleotide microarrays representing about 6000 genes. We used this training set in a supervised learning manner to construct a predictive system, consisting of 12 genes, with the Fisher linear classifier. We then compared the predictive performance of our system with that of a predictive system with a support vector machine (SVM-based system) on a blinded set of samples from 27 newly enrolled patients. FINDINGS: Early intrahepatic recurrence within 1 year after curative surgery occurred in 12 (36%) and eight (30%) patients in the training and blinded sets, respectively. Our system correctly predicted early intrahepatic recurrence or non-recurrence in 25 (93%) of 27 samples in the blinded set and had a positive predictive value of 88% and a negative predictive value of 95%. By contrast, the SVM-based system predicted early intrahepatic recurrence or non-recurrence correctly in only 16 (60%) individuals in the blinded set, and the result yielded a positive predictive value of only 38% and a negative predictive value of 79%. INTERPRETATION: Our system predicted early intrahepatic recurrence or non-recurrence for patients with hepatocellular carcinoma much more accurately than the SVM-based system, suggesting that our system could serve as a new method for characterising the metastatic potential of hepatocellular carcinoma.
