title: Prognostic Scoring Models for Patients Undergoing Sorafenib Treatment for Advanced Stage Hepatocellular Carcinoma in Real-Life Practice.
abstract: BACKGROUND
  The purpose of this study was to build prognostic models capable of estimating the outcomes of individual sorafenib-treated advanced stage hepatocellular carcinoma (HCC) patients based on specific patient and tumor factors.
  
  
  METHODS
  A parametric model for time-to-event data was used to construct scoring systems based on the intent-to-treat data set from 480 sorafenib-treated patients with advanced stage HCC: 356 for derivation and 124 for validation. Clinical parameters included in the models were based on importance variable scores generated by a random forest approach and bootstrap resampling. The model's accuracy was internally and externally assessed using the time-dependent C-index of discrimination and a Hosmer-Lemeshow type test for calibration.
  
  
  RESULTS
  The models generated for time-to-progression and overall survival based on Child-Pugh score, serum α-fetoprotein, tumor morphology, and vascular invasion and/or extrahepatic involvement had good calibration and discrimination abilities, with C-indexes of 0.669 (3 mo progression) and 0.809 (6 mo survival), respectively. External validation results also showed that these models performed well in terms of goodness-of-fit and discrimination (C-index: 0.746 for 3 mo progression and 0.875 for 6 mo survival). Receiver operating characteristic curve analysis in the validation patients indicated that these models have better predictive power than Child-Pugh scores (C-index: 0.686 for 3 mo progression and 0.777 for 6 mo survival).
  
  
  CONCLUSIONS
  The prognostic tools developed to quantify the potential outcomes for progression and survival expected from sorafenib treatment can serve as useful clinical aids in personalized decision making regarding treatment in advanced stage HCC patients.
authors.affiliation: Departments of *Gastroenterology ‡Oncology, Asan Liver Center, Asan Medical Center †Department of Biostatistics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
authors.forename: Gwang Hyeon
authors.initials: GH
authors.lastname: Choi
authors.forename: Seungbong
authors.initials: S
authors.lastname: Han
authors.forename: Ju Hyun
authors.initials: JH
authors.lastname: Shim
authors.forename: Min-Hee
authors.initials: MH
authors.lastname: Ryu
authors.forename: Baek-Yeol
authors.initials: BY
authors.lastname: Ryoo
authors.forename: Yoon-Koo
authors.initials: YK
authors.lastname: Kang
authors.forename: Kang Mo
authors.initials: KM
authors.lastname: Kim
authors.forename: Young-Suk
authors.initials: YS
authors.lastname: Lim
authors.forename: Han Chu
authors.initials: HC
authors.lastname: Lee
mesh_terms: D000970:Antineoplastic Agents / Q000627:therapeutic use*; D006528:Carcinoma, Hepatocellular / Q000188:drug therapy* / Q000401:mortality / Q000473:pathology; D018450:Disease Progression; D005260:Female; D006801:Humans; D008113:Liver Neoplasms / Q000188:drug therapy* / Q000401:mortality / Q000473:pathology; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009367:Neoplasm Staging; D009536:Niacinamide / Q000031:analogs & derivatives* / Q000627:therapeutic use; D010671:Phenylurea Compounds / Q000627:therapeutic use*; D011379:Prognosis; D018570:Risk Assessment; D000077157:Sorafenib; D015996:Survival Rate
chemical_list: D000970:Antineoplastic Agents; D010671:Phenylurea Compounds; D009536:Niacinamide; D000077157:Sorafenib