title: Validation of the Hong Kong Liver Cancer Staging System in Determining Prognosis of the North American Patients Following Intra-arterial Therapy.
abstract: OBJECTIVE
  There is debate over the best way to stage hepatocellular carcinoma (HCC). We attempted to validate the prognostic and clinical utility of the recently developed Hong Kong Liver Cancer (HKLC) staging system, a hepatitis B-based model, and compared data with that from the Barcelona Clinic Liver Cancer (BCLC) staging system in a North American population that underwent intra-arterial therapy (IAT).
  
  
  METHODS
  We performed a retrospective analysis of data from 1009 patients with HCC who underwent IAT from 2000 through 2014. Most patients had hepatitis C or unresectable tumors; all patients underwent IAT, with or without resection, transplantation, and/or systemic chemotherapy. We calculated HCC stage for each patient using 5-stage HKLC (HKLC-5) and 9-stage HKLC (HKLC-9) system classifications, and the BCLC system. Survival information was collected up until the end of 2014 at which point living or unconfirmed patients were censored. We compared performance of the BCLC, HKLC-5, and HKLC-9 systems in predicting patient outcomes using Kaplan-Meier estimates, calibration plots, C statistic, Akaike information criterion, and the likelihood ratio test.
  
  
  RESULTS
  Median overall survival time, calculated from first IAT until date of death or censorship, for the entire cohort (all stages) was 9.8 months. The BCLC and HKLC staging systems predicted patient survival times with significance (P < .001). HKLC-5 and HKLC-9 each demonstrated good calibration. The HKLC-5 system outperformed the BCLC system in predicting patient survival times (HKLC C = 0.71, Akaike information criterion = 6242; BCLC C = 0.64, Akaike information criterion = 6320), reducing error in predicting survival time (HKLC reduced error by 14%, BCLC reduced error by 12%), and homogeneity (HKLC chi-square = 201, P < .001; BCLC chi-square = 119, P < .001) and monotonicity (HKLC linear trend chi-square = 193, P < .001; BCLC linear trend chi-square = 111, P < .001). Small proportions of patients with HCC of stages IV or V, according to the HKLC system, survived for 6 months and 4 months, respectively.
  
  
  CONCLUSIONS
  In a retrospective analysis of patients who underwent IAT for unresectable HCC, we found the HKLC-5 staging system to have the best combination of performances in survival separation, calibration, and discrimination; it consistently outperformed the BCLC system in predicting survival times of patients. The HKLC system identified patients with HCC of stages IV and V who are unlikely to benefit from IAT.
authors.affiliation: Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut.
authors.forename: Jae Ho
authors.initials: JH
authors.lastname: Sohn
authors.affiliation: Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut.
authors.forename: Rafael
authors.initials: R
authors.lastname: Duran
authors.affiliation: Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut.
authors.forename: Yan
authors.initials: Y
authors.lastname: Zhao
authors.affiliation: Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut.
authors.forename: Florian
authors.initials: F
authors.lastname: Fleckenstein
authors.affiliation: Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut.
authors.forename: Julius
authors.initials: J
authors.lastname: Chapiro
authors.affiliation: Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut.
authors.forename: Sonia
authors.initials: S
authors.lastname: Sahu
authors.affiliation: Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut.
authors.forename: Rüdiger E
authors.initials: RE
authors.lastname: Schernthaner
authors.affiliation: Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
authors.forename: Tianchen
authors.initials: T
authors.lastname: Qian
authors.affiliation: Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut.
authors.forename: Howard
authors.initials: H
authors.lastname: Lee
authors.affiliation: Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut.
authors.forename: Li
authors.initials: L
authors.lastname: Zhao
authors.affiliation: Division of Gastroenterology and Hepatology, Department of Medicine, The Johns Hopkins Hospital, Baltimore, Maryland.
authors.forename: James
authors.initials: J
authors.lastname: Hamilton
authors.affiliation: Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
authors.forename: Constantine
authors.initials: C
authors.lastname: Frangakis
authors.affiliation: Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut; U/S Imaging and Interventions (UII), Philips Research North America, Cambridge, Massachusetts.
authors.forename: MingDe
authors.initials: M
authors.lastname: Lin
authors.affiliation: Department of Radiology, Section of Interventional Radiology, Northwestern University, Chicago, Illinois.
authors.forename: Riad
authors.initials: R
authors.lastname: Salem
authors.affiliation: Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut. Electronic address: jeff.geschwind@yale.edu.
authors.forename: Jean-Francois
authors.initials: JF
authors.lastname: Geschwind
mesh_terms: D000368:Aged; D004621:Embolization, Therapeutic; D005260:Female; D006801:Humans; D008113:Liver Neoplasms / Q000175:diagnosis* / Q000473:pathology* / Q000628:therapy; D008297:Male; D008875:Middle Aged; D009656:North America; D011379:Prognosis; D012189:Retrospective Studies; D012720:Severity of Illness Index
keywords: Liver Cancer; Predicted Outcome; Prognosis; Risk Factors