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{"title"=>"Cost-Effectiveness Analysis of Risk-Factor Guided and Birth-Cohort Screening for Chronic Hepatitis C Infection in the United States", "type"=>"journal", "authors"=>[{"first_name"=>"Shan", "last_name"=>"Liu", "scopus_author_id"=>"44861474100"}, {"first_name"=>"Lauren E.", "last_name"=>"Cipriano", "scopus_author_id"=>"16315154700"}, {"first_name"=>"Mark", "last_name"=>"Holodniy", "scopus_author_id"=>"7004800293"}, {"first_name"=>"Jeremy D.", "last_name"=>"Goldhaber-Fiebert", "scopus_author_id"=>"9435535800"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "pui"=>"368580449", "doi"=>"10.1371/journal.pone.0058975", "sgr"=>"84875287973", "isbn"=>"1932-6203", "pmid"=>"23533595", "scopus"=>"2-s2.0-84875287973"}, "id"=>"0c8bf574-ef23-39f7-adf3-4e702686cd5f", "abstract"=>"BACKGROUND: No consensus exists on screening to detect the estimated 2 million Americans unaware of their chronic hepatitis C infections. Advisory groups differ, recommending birth-cohort screening for baby boomers, screening only high-risk individuals, or no screening. We assessed one-time risk assessment and screening to identify previously undiagnosed 40-74 year-olds given newly available hepatitis C treatments.\\n\\nMETHODS AND FINDINGS: A Markov model evaluated alternative risk-factor guided and birth-cohort screening and treatment strategies. Risk factors included drug use history, blood transfusion before 1992, and multiple sexual partners. Analyses of the National Health and Nutrition Examination Survey provided sex-, race-, age-, and risk-factor-specific hepatitis C prevalence and mortality rates. Nine strategies combined screening (no screening, risk-factor guided screening, or birth-cohort screening) and treatment (standard therapy-peginterferon alfa and ribavirin, Interleukin-28B-guided (IL28B) triple-therapy-standard therapy plus a protease inhibitor, or universal triple therapy). Response-guided treatment depended on HCV genotype. Outcomes include discounted lifetime costs (2010 dollars) and quality adjusted life-years (QALYs). Compared to no screening, risk-factor guided and birth-cohort screening for 50 year-olds gained 0.7 to 3.5 quality adjusted life-days and cost $168 to $568 per person. Birth-cohort screening provided more benefit per dollar than risk-factor guided screening and cost $65,749 per QALY if followed by universal triple therapy compared to screening followed by IL28B-guided triple therapy. If only 10% of screen-detected, eligible patients initiate treatment at each opportunity, birth-cohort screening with universal triple therapy costs $241,100 per QALY. Assuming treatment with triple therapy, screening all individuals aged 40-64 years costs less than $100,000 per QALY.\\n\\nCONCLUSIONS: The cost-effectiveness of one-time birth-cohort hepatitis C screening for 40-64 year olds is comparable to other screening programs, provided that the healthcare system has sufficient capacity to deliver prompt treatment and appropriate follow-on care to many newly screen-detected individuals.", "link"=>"http://www.mendeley.com/research/costeffectiveness-analysis-riskfactor-guided-birthcohort-screening-chronic-hepatitis-c-infection-uni-3", "reader_count"=>41, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>4, "Researcher"=>14, "Student > Doctoral Student"=>6, "Student > Ph. D. Student"=>7, "Student > Postgraduate"=>1, "Other"=>2, "Student > Master"=>7}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>4, "Researcher"=>14, "Student > Doctoral Student"=>6, "Student > Ph. D. Student"=>7, "Student > Postgraduate"=>1, "Other"=>2, "Student > Master"=>7}, "reader_count_by_subject_area"=>{"Unspecified"=>3, "Engineering"=>3, "Nursing and Health Professions"=>2, "Mathematics"=>4, "Medicine and Dentistry"=>17, "Agricultural and Biological Sciences"=>3, "Business, Management and Accounting"=>2, "Social Sciences"=>3, "Immunology and Microbiology"=>1, "Economics, Econometrics and Finance"=>3}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>3}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>17}, "Social Sciences"=>{"Social Sciences"=>3}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>3}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>3}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>2}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>2}, "Mathematics"=>{"Mathematics"=>4}, "Unspecified"=>{"Unspecified"=>3}}, "reader_count_by_country"=>{"Canada"=>1, "United States"=>5, "Spain"=>1}, "group_count"=>3}

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• {"files"=>["https://ndownloader.figshare.com/files/995863"], "description"=>"<p>Small squares represent decisions. For the screening policy decision we considered the alternatives of implementing a policy of no screening, risk-factor guided screening, and birth-cohort screening. For the HCV genotype 1 treatment policy decision we considered the alternatives of standard therapy, in which patients receive pegylated interferon with ribavirin; IL-28B-guided triple therapy, in which after IL-28B genotyping patients with non-CC types receive triple therapy and patients with CC types receive standard therapy; and universal triple therapy, in which patients receive pegylated interferon with ribavirin and a protease inhibitor. In all strategies patients diagnosed with genotypes 2 and 3 receive 24 weeks of standard therapy. We considered all possible combinations of the screening policy decision and the genotype 1 treatment policy decision for a total of 9 policy alternatives. Small circles indicate chance events. Upon entering the model the cohort is stratified by true health state of risk-factor status (high risk or low risk), HCV-status (positive or negative), among HCV-positive individuals by HCV genotype (genotype 1 or other), and among HCV-positive genotype 1 individuals by IL-28B genotype (CC or non-CC type). Depending on the screening strategy, individuals may be imperfectly identified as “high-risk” or “low-risk”, may be screened for HCV, and may be imperfectly identified as “HCV+” and “HCV–”. Once individuals are classified with a diagnosis they enter one of two Markov models based on their true health state. The Markov model of HCV is shown. The Markov model of individuals who do not have HCV has only two health states, No HCV and Dead. We assume no HCV incidence in the model. HCC = hepatocellular carcinoma; HCV = hepatitis C virus; IL-28B = interleukin-28B; PEG-IFN = pegylated interferon; PI = protease inhibitor; Rb = ribavirin.</p>", "links"=>[], "tags"=>["Infectious diseases", "public health and epidemiology", "Gastroenterology and hepatology", "Non-clinical medicine"], "article_id"=>658572, "categories"=>["Biotechnology", "Chemistry", "Medicine", "Infectious Diseases"], "users"=>["Shan Liu", "Lauren E. Cipriano", "Mark Holodniy", "Jeremy D. Goldhaber-Fiebert"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0058975.g001", "stats"=>{"downloads"=>4, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Model_schematics_/658572", "title"=>"Model schematics.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-23 02:49:22"}
• {"files"=>["https://ndownloader.figshare.com/files/1008021"], "description"=>"*<p>Population weighted average (white male 44%, white female 45%, black male 5%, black female 6%). Each strategy is compared to the next-best strategy on the efficient frontier. Risk factors were considered for all of these scenario analyses but are dominated in all cases.</p>**<p>Prevalence based on 1962–1971 cohort.</p>&<p>Adherence is defined as patients taking ≥80% of their HCV medications.</p><p>“Dominated” indicates that the strategy costs more and provides fewer benefits than another strategy or a combination of two strategies.</p>", "links"=>[], "tags"=>["cohort"], "article_id"=>668648, "categories"=>["Biotechnology", "Chemistry", "Medicine", "Infectious Diseases"], "users"=>["Shan Liu", "Lauren E. Cipriano", "Mark Holodniy", "Jeremy D. Goldhaber-Fiebert"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0058975.t004", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Deterministic_sensitivity_analysis_of_cohort_and_treatment_factors_/668648", "title"=>"Deterministic sensitivity analysis of cohort and treatment factors.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-03-22 02:24:08"}
• {"files"=>["https://ndownloader.figshare.com/files/1008038"], "description"=>"*<p>Population weighted average (white male 44%, white female 45%, black male 5%, black female 6%) for fibrosis distribution: F0 13%, F1 51%, F2 13%, F3 10%, and F4 13%. All incremental cost and QALY are compared to the reference. Eligible screening population in the 40–64 year-old cohort is assumed at 83.5 million.</p><p>ICER = incremental cost-effectiveness ratio; IL-28B = interleukin-28B; QALY = quality-adjusted life-year.</p><p>“Dominated” indicates that the strategy costs more and provides fewer benefits than another strategy or a combination of two strategies.</p>", "links"=>[], "tags"=>["hcv", "aged", "incremental", "costs"], "article_id"=>668661, "categories"=>["Biotechnology", "Chemistry", "Medicine", "Infectious Diseases"], "users"=>["Shan Liu", "Lauren E. Cipriano", "Mark Holodniy", "Jeremy D. Goldhaber-Fiebert"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0058975.t005", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Population_impact_of_HCV_screening_aged_40_64_years_total_lifetime_costs_health_benefits_and_incremental_costs_effectiveness_ratio_of_combined_screening_and_treatment_strategies_/668661", "title"=>"Population impact of HCV screening aged 40–64 years, total lifetime costs, health benefits, and incremental costs effectiveness ratio of combined screening and treatment strategies<b>.</b>", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-03-22 02:24:21"}
• {"files"=>["https://ndownloader.figshare.com/files/1008054"], "description"=>"<p>HCC = hepatocellular carcinoma; HCV = hepatitis C virus; IL-28B = interleukin-28B; NHANES III = Third National Health and Nutrition Examination Survey; PEG-IFN = pegylated interferon; PI = protease inhibitor; Rb = ribavirin; SVR = sustained virologic response; AE = adverse event; QALY = quality-adjusted life-year; CMS =  Center for Medicare & Medicaid Services. For further details on parameter generation and the uncertainty distribution of parameters see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0058975#pone.0058975.s001\" target=\"_blank\">Appendix S1</a> I; <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0058975#pone.0058975.s001\" target=\"_blank\">Appendix S1</a> I Table S2; <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0058975#pone.0058975.s001\" target=\"_blank\">Appendix S1</a> Table S3.</p>*<p>A high-risk individual is someone having a history of injection drug use, transfusion prior to 1992, or greater than 20 lifetime sex partners. The reported prevalence is estimated for the 1952–1961 birth cohort and include individuals both aware and unaware of their HCV infection status. We adjusted the prevalence to only include individuals unaware of their infection status in the cost-effectiveness analyses.</p><p>& The mortality rates for people who recovered from HCV are adjusted by a linear combination of their mortality rates with HCV and mortality rates without HCV using a factor of 0.7.</p>**<p>The reported triple therapy effectiveness in the base-case is similar to boceprevir.</p>***<p>The total quality-of-life weight for a given age and HCV disease state is computed as the product of the mean age-specific quality weight obtained from published data <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0058975#pone.0058975-Nyman1\" target=\"_blank\">[28]</a>, <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0058975#pone.0058975-Sullivan1\" target=\"_blank\">[29]</a> and the utility associated with the HCV disease state minus any utility decrements for events that occurred during the cycle such as receiving treatment or a liver transplant.</p>†<p>Unlike other utilities in this table, these utility decrements are for short-term states (that is, receiving HCV treatment or a liver transplant). The QALY decrement for receiving HCV treatment involves multiplying the annual utility decrement by the time on treatment, which can vary given the response-guided therapy rules of each strategy. ˆOne time disutility applied in a 12 weeks period.</p>‡<p>The PI cost is added to the standard therapy cost while receiving triple therapy.</p><p>|| The total costs for a given age and HCV disease state is computed as the sum of the mean age-specific health care costs <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0058975#pone.0058975-Meara1\" target=\"_blank\">[36]</a> and the HCV-specific health state plus any costs of testing, treatment, or liver transplant that occurred in the cycle.</p>¶<p>We assumed costs in the recovered states are 50% of the hepatitis C–related care costs in the year before diagnosis of the corresponding unaware states <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0058975#pone.0058975-Poret1\" target=\"_blank\">[37]</a>.</p>", "links"=>[], "tags"=>["parameter"], "article_id"=>668678, "categories"=>["Biotechnology", "Chemistry", "Medicine", "Infectious Diseases"], "users"=>["Shan Liu", "Lauren E. Cipriano", "Mark Holodniy", "Jeremy D. Goldhaber-Fiebert"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0058975.t001", "stats"=>{"downloads"=>1, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Model_Parameter_Values_and_Ranges_/668678", "title"=>"Model Parameter Values and Ranges.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-03-22 02:24:38"}
• {"files"=>["https://ndownloader.figshare.com/files/995866"], "description"=>"<p>(A) The graph plots the incremental discounted QALYs (<i>y</i>-axis) and incremental discounted lifetime costs (<i>x</i>-axis) for each combined screening and treatment strategy. The solid line represents the cost-effectiveness frontier, those strategies that are potentially economically efficient depending on one’s willingness-to-pay per unit of health benefit gained. (B) The bar graph shows the incremental cost-effectiveness ratios of each combined screening and treatment strategy at different levels of treatment uptake at each opportunity (varied over the range 0–50%). The asterisk denotes that, at 5% uptake, birth-cohort screening followed by universal triple therapy for screen-detected, treatment-eligible individuals is dominated. For both panels, IL-28B = interleukin-28B; QALY = quality-adjusted life-year.</p>", "links"=>[], "tags"=>["Infectious diseases", "public health and epidemiology", "Gastroenterology and hepatology", "Non-clinical medicine"], "article_id"=>658575, "categories"=>["Biotechnology", "Chemistry", "Medicine", "Infectious Diseases"], "users"=>["Shan Liu", "Lauren E. Cipriano", "Mark Holodniy", "Jeremy D. Goldhaber-Fiebert"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0058975.g002", "stats"=>{"downloads"=>3, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Cost_effectiveness_analysis_/658575", "title"=>"Cost-effectiveness analysis.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-23 02:50:08"}
• {"files"=>["https://ndownloader.figshare.com/files/1008076"], "description"=>"*<p>Population weighted average (white male 44%, white female 45%, black male 5%, black female 6%) for fibrosis distribution: F0 13%, F1 51%, F2 13%, F3 10%, and F4 13%. All incremental cost and QALY are compared to the reference.</p><p>ICER = incremental cost-effectiveness ratio; IL-28B = interleukin-28B; QALY = quality-adjusted life-year.</p><p>“Dominated” indicates that the strategy costs more and provides fewer benefits than another strategy or a combination of two strategies.</p>", "links"=>[], "tags"=>["benefits", "incremental", "costs", "strategies", "cohort", "individuals", "50", "years"], "article_id"=>668697, "categories"=>["Biotechnology", "Chemistry", "Medicine", "Infectious Diseases"], "users"=>["Shan Liu", "Lauren E. Cipriano", "Mark Holodniy", "Jeremy D. Goldhaber-Fiebert"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0058975.t002", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Base_case_lifetime_costs_health_benefits_per_100_000_and_incremental_costs_effectiveness_ratio_of_combined_screening_and_treatment_strategies_for_a_cohort_of_individuals_who_are_currently_50_years_of_age_/668697", "title"=>"Base case lifetime costs, health benefits (per 100,000), and incremental costs effectiveness ratio of combined screening and treatment strategies for a cohort of individuals who are currently 50 years of age.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-03-22 02:24:57"}
• {"files"=>["https://ndownloader.figshare.com/files/1008094"], "description"=>"*<p>Population weighted average (white male 44%, white female 45%, black male 5%, black female 6%) for fibrosis distribution: F0 13%, F1 51%, F2 13%, F3 10%, and F4 13%. All incremental cost and QALY are compared to the reference.</p><p>ICER = incremental cost-effectiveness ratio; IL-28B = interleukin-28B; QALY = quality-adjusted life-year.</p><p>“Dominated” indicates that the strategy costs more and provides fewer benefits than another strategy or a combination of two strategies.</p>", "links"=>[], "tags"=>["benefits", "incremental", "costs", "strategies"], "article_id"=>668716, "categories"=>["Biotechnology", "Chemistry", "Medicine", "Infectious Diseases"], "users"=>["Shan Liu", "Lauren E. Cipriano", "Mark Holodniy", "Jeremy D. Goldhaber-Fiebert"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0058975.t003", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Lifetime_costs_health_benefits_per_100_000_and_incremental_costs_effectiveness_ratio_of_combined_screening_and_treatment_strategies_for_various_patient_ages_/668716", "title"=>"Lifetime costs, health benefits (per 100,000), and incremental costs effectiveness ratio of combined screening and treatment strategies for various patient ages.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-03-22 02:25:16"}
• {"files"=>["https://ndownloader.figshare.com/files/995873"], "description"=>"<div><p>Background</p><p>No consensus exists on screening to detect the estimated 2 million Americans unaware of their chronic hepatitis C infections. Advisory groups differ, recommending birth-cohort screening for baby boomers, screening only high-risk individuals, or no screening. We assessed one-time risk assessment and screening to identify previously undiagnosed 40–74 year-olds given newly available hepatitis C treatments.</p> <p>Methods and Findings</p><p>A Markov model evaluated alternative risk-factor guided and birth-cohort screening and treatment strategies. Risk factors included drug use history, blood transfusion before 1992, and multiple sexual partners. Analyses of the National Health and Nutrition Examination Survey provided sex-, race-, age-, and risk-factor-specific hepatitis C prevalence and mortality rates. Nine strategies combined screening (no screening, risk-factor guided screening, or birth-cohort screening) and treatment (standard therapy–peginterferon alfa and ribavirin, Interleukin-28B-guided (IL28B) triple-therapy–standard therapy plus a protease inhibitor, or universal triple therapy). Response-guided treatment depended on HCV genotype. Outcomes include discounted lifetime costs (2010 dollars) and quality adjusted life-years (QALYs).</p> <p>Compared to no screening, risk-factor guided and birth-cohort screening for 50 year-olds gained 0.7 to 3.5 quality adjusted life-days and cost $168 to $568 per person. Birth-cohort screening provided more benefit per dollar than risk-factor guided screening and cost $65,749 per QALY if followed by universal triple therapy compared to screening followed by IL28B-guided triple therapy. If only 10% of screen-detected, eligible patients initiate treatment at each opportunity, birth-cohort screening with universal triple therapy costs $241,100 per QALY. Assuming treatment with triple therapy, screening all individuals aged 40–64 years costs less than $100,000 per QALY.</p> <p>Conclusions</p><p>The cost-effectiveness of one-time birth-cohort hepatitis C screening for 40–64 year olds is comparable to other screening programs, provided that the healthcare system has sufficient capacity to deliver prompt treatment and appropriate follow-on care to many newly screen-detected individuals.</p> </div>", "links"=>[], "tags"=>["cost-effectiveness", "risk-factor", "guided", "birth-cohort", "hepatitis", "united", "states"], "article_id"=>658582, "categories"=>["Biotechnology", "Chemistry", "Medicine", "Infectious Diseases"], "users"=>["Shan Liu", "Lauren E. Cipriano", "Mark Holodniy", "Jeremy D. Goldhaber-Fiebert"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0058975", "stats"=>{"downloads"=>2, "page_views"=>16, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Cost_Effectiveness_Analysis_of_Risk_Factor_Guided_and_Birth_Cohort_Screening_for_Chronic_Hepatitis_C_Infection_in_the_United_States__/658582", "title"=>"Cost-Effectiveness Analysis of Risk-Factor Guided and Birth-Cohort Screening for Chronic Hepatitis C Infection in the United States", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-03-23 02:52:03"}
• {"files"=>["https://ndownloader.figshare.com/files/995870"], "description"=>"<p>The graph plots the incremental discounted QALYs and incremental discounted lifetime costs for screening various birth cohorts. The analysis shown in the graph assumes that the treatment strategy used is universal triple therapy. For clarity, the graph shows only those strategies on the cost-effectiveness frontier (i.e., those that are not dominated) although all combinations of birth-cohort groups (40–44, 45–49, 50–54, 55–59, 60–64, 65–69, 70–74 years of age) were considered in the analysis.</p>", "links"=>[], "tags"=>["birth-cohort"], "article_id"=>658579, "categories"=>["Biotechnology", "Chemistry", "Medicine", "Infectious Diseases"], "users"=>["Shan Liu", "Lauren E. Cipriano", "Mark Holodniy", "Jeremy D. Goldhaber-Fiebert"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0058975.g003", "stats"=>{"downloads"=>4, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Cost_effectiveness_of_birth_cohort_screening_by_age_group_/658579", "title"=>"Cost-effectiveness of birth-cohort screening by age group.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-03-23 02:50:53"}

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Relative Metric

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F1000Prime