title: Hepatocellular carcinoma screening in patients waiting for liver transplantation: a decision analytic model.
abstract: De novo hepatocellular carcinoma (HCC) may have a large impact on patients waiting for liver transplantation. The presence of HCC can lead to a status upgrade or removal from the waitlist. Our aim is to compare costs and outcomes of different liver cancer surveillance strategies. A Markov-based decision analytic model is created to simulate costs and health outcomes for a hypothetical cohort awaiting liver transplantation undergoing HCC screening. Three strategies of HCC screening are compared with the referent strategy of using alphafetaprotein (AFP) level alone: (1) ultrasound (U/S), (2) AFP plus U/S, and (3) computed tomography (CT). Screening is performed for all strategies at 6-month intervals. Selected tumors are treated locally. Costs and clinical outcomes are discounted. Using baseline assumptions, incremental cost-effectiveness ratios (ICERs) for U/S, U/S plus AFP, and CT are $60,300/life-year saved (LY), $74,000/LY, and $101,100/LY, respectively. The most cost-effective strategy was dependent on the relative costs of each screening modality. U/S screening becomes the dominant strategy when the cost of an AFP test is decreased. Our results show that screening with CT is associated the greatest gain in life expectancy and greatest costs. U/S screening strategy is the preferred screening strategy based on the lowest ICER. Ultimately, costs of the screening modalities determine the most cost-effective strategy.
authors.affiliation: Department of Medicine, Dumont-UCLA Liver Transplant Center, University of California Los Angeles, USA. Ssaab@mednet.ucla.edu
authors.forename: Sammy
authors.initials: S
authors.lastname: Saab
authors.forename: David
authors.initials: D
authors.lastname: Ly
authors.forename: Jose
authors.initials: J
authors.lastname: Nieto
authors.forename: Fasiha
authors.initials: F
authors.lastname: Kanwal
authors.forename: David
authors.initials: D
authors.lastname: Lu
authors.forename: Steven
authors.initials: S
authors.lastname: Raman
authors.forename: Rafael
authors.initials: R
authors.lastname: Amado
authors.forename: Barbara
authors.initials: B
authors.lastname: Nuesse
authors.forename: Francisco
authors.initials: F
authors.lastname: Durazo
authors.forename: Steven
authors.initials: S
authors.lastname: Han
authors.forename: Douglas G
authors.initials: DG
authors.lastname: Farmer
authors.forename: Rafik M
authors.initials: RM
authors.lastname: Ghobrial
authors.forename: Hasan
authors.initials: H
authors.lastname: Yersiz
authors.forename: Pauline
authors.initials: P
authors.lastname: Chen
authors.forename: Kathy
authors.initials: K
authors.lastname: Schwegel
authors.forename: Leonard I
authors.initials: LI
authors.lastname: Goldstein
authors.forename: Myron
authors.initials: M
authors.lastname: Tong
authors.forename: Ronald W
authors.initials: RW
authors.lastname: Busuttil
mesh_terms: D006528:Carcinoma, Hepatocellular / Q000175:diagnosis* / Q000601:surgery; D003362:Cost-Benefit Analysis; D003658:Decision Making, Computer-Assisted; D003663:Decision Trees; D017048:Health Care Costs; D006801:Humans; D008107:Liver Diseases / Q000601:surgery; D008113:Liver Neoplasms / Q000175:diagnosis* / Q000601:surgery; D016031:Liver Transplantation / Q000191:economics / Q000379:methods; D008403:Mass Screening / Q000191:economics; D010043:Outcome and Process Assessment, Health Care; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed; D014463:Ultrasonography; D014850:Waiting Lists; D000509:alpha-Fetoproteins / Q000032:analysis
chemical_list: D000509:alpha-Fetoproteins