title: Hepatocellular carcinoma in uremic patients: is there evidence for an increased risk of mortality?
abstract: OBJECTIVE
  The clinical aspects of patients with hepatocellular carcinoma (HCC) undergoing maintenance dialysis are largely unknown. We aimed to investigate the long-term survival and prognostic determinants of dialysis patients with HCC.
  
  
  METHODS
  A total of 2502 HCC patients, including 30 dialysis patients and 90 age, sex, and treatment-matched controls were retrospectively analyzed.
  
  
  RESULTS
  Dialysis patients more often had dual viral hepatitis B and C, lower serum α-fetoprotein level, worse performance status, higher model for end-stage liver disease (MELD) score than non-dialysis patients and matched controls (P all < 0.05). There was no significant difference in long-term survival between dialysis and non-dialysis patients and matched controls (P = 0.684 and 0.373, respectively). In the Cox proportional hazards model, duration of dialysis < 40 months (hazard ratio [HR]: 6.67, P = 0.019) and ascites (HR: 5.275, P = 0.019) were independent predictors of poor prognosis for dialysis patients with HCC. Survival analysis disclosed that the Child-Turcotte-Pugh (CTP) provided a better prognostic ability than the MELD system. Among the four currently used staging systems, the Japan Integrated Scoring (JIS) system was a more accurate prognostic model for dialysis patients; a JIS score ≥ 2 significantly predicted a worse survival (P = 0.024).
  
  
  CONCLUSIONS
  Patients with HCC undergoing maintenance dialysis do not have a worse long-term survival. A longer duration of dialysis and absence of ascites formation are associated with a better outcome in dialysis patients. The CTP classification is a more feasible prognostic marker to indicate the severity of cirrhosis, and the JIS system may be a better staging model for outcome prediction.
authors.affiliation: National Yang-Ming University School of Medicine, Taipei, Taiwan.
authors.forename: Yun-Hsuan
authors.initials: YH
authors.lastname: Lee
authors.forename: Chia-Yang
authors.initials: CY
authors.lastname: Hsu
authors.forename: Cheng-Yuan
authors.initials: CY
authors.lastname: Hsia
authors.forename: Yi-Hsiang
authors.initials: YH
authors.lastname: Huang
authors.forename: Chien-Wei
authors.initials: CW
authors.lastname: Su
authors.forename: Han-Chieh
authors.initials: HC
authors.lastname: Lin
authors.forename: Rheun-Chuan
authors.initials: RC
authors.lastname: Lee
authors.forename: Yi-You
authors.initials: YY
authors.lastname: Chiou
authors.forename: Teh-Ia
authors.initials: TI
authors.lastname: Huo
mesh_terms: D000368:Aged; D001201:Ascites / Q000401:mortality; D006528:Carcinoma, Hepatocellular / Q000401:mortality* / Q000473:pathology; D015897:Comorbidity; D005260:Female; D006801:Humans; D053208:Kaplan-Meier Estimate; D007676:Kidney Failure, Chronic / Q000175:diagnosis / Q000401:mortality* / Q000628:therapy; D008103:Liver Cirrhosis / Q000401:mortality; D008113:Liver Neoplasms / Q000401:mortality* / Q000473:pathology; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009367:Neoplasm Staging; D011379:Prognosis; D016016:Proportional Hazards Models; D006435:Renal Dialysis / Q000009:adverse effects / Q000401:mortality*; D012189:Retrospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D013624:Taiwan / Q000453:epidemiology; D013997:Time Factors; D014511:Uremia / Q000175:diagnosis / Q000401:mortality* / Q000628:therapy