SynthesisBMJ open2016
Cost-effectiveness of screening for hepatitis C virus: a systematic review of economic evaluations.
Synthesis in BMJ open, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
29 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Pooled it
- Population-Based Testing for Undiagnosed Hepatitis C: A Systematic Review of Economic Evaluations.Applied health economics and health policy · 2022Pooled it
- Is the universal population Hepatitis C virus screening a cost-effective strategy? A systematic review of the economic evidence.Revista espanola de quimioterapia : publicacion oficial de la Sociedad Espanola de Quimioterapia · 2020Pooled it
- Hepatitis B/C in the countries of the EU/EEA: a systematic review of the prevalence among at-risk groups.BMC infectious diseases · 2018Pooled it
- Universal screening for HCV infection in China: An effectiveness and cost-effectiveness analysis.JHEP reports : innovation in hepatology · 2024Article
- A province-by-province cost-effectiveness analysis and budget impact analysis of one-time birth cohort screening of hepatitis C virus (HCV) infection in Canada.Scientific reports · 2023Article
- Finding undiagnosed patients with hepatitis C virus: an application of machine learning to US ambulatory electronic medical records.BMJ health & care informatics · 2023Article
- Country versus pharmaceutical company interests for hepatitis C treatment.Health care management science · 2022Article
- Hepatitis C Antibody Screening Among Baby Boomers by a Community-Based Health Insurance Company.Population health management · 2021Article
- Screening for hepatitis C in an outpatient endoscopy unit.Canadian liver journal · 2021Article
- Social values for health technology assessment in Canada: a scoping review of hepatitis C screening, diagnosis and treatment.BMC public health · 2020Article
- Article
- Elimination of hepatitis C virus in Germany: modelling the cost-effectiveness of HCV screening strategies.BMC infectious diseases · 2019Article
- Hepatitis C screening in hospitals: find the missing patients.Virology journal · 2019Article
- Screening for hepatitis C in a general adult population in a low-prevalence area: the Tromsø study.BMC infectious diseases · 2019Article
- The role of insurance providers in supporting treatment and management of hepatitis C patients.BMC health services research · 2019Article
- Article
- Article
- Streamlining the screening cascade for active Hepatitis C in Russia: A cost-effectiveness analysis.PloS one · 2019Article
- Associating conditional cash transfer to universal access to treatment could be the solution to the HCV epidemic among drug users (DUs).Harm reduction journal · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesWith the developments of near-cures for hepatitis C virus (HCV), who to screen has become a high-priority policy issue in many western countries. Cost-effectiveness of screening programmes should be one consideration when developing policy. The objective of this work is to synthesise the cost-effectiveness of HCV screening programmes.
settingA systematic review was completed. 5 databases were searched until May 2016 (NHSEED, MEDLINE, the HTA Health Technology Assessment Database, EMBASE, EconLit).
participantsAny study reporting an economic evaluation (any type) of screening compared with opportunistic or no screening for HCV was included. Exclusion criteria were: (1) abstracts or commentaries, (2) economic evaluations of other interventions for HCV, including blood donors screening, diagnosis tests for HCV, screening for concurrent disease or medications for treatment. PRIMARY AND SECONDARY OUTCOME MEASURES: Data extraction included type of model, target population, perspective, comparators, time horizon, discount rate, clinical inputs, cost inputs and outcome. Quality was evaluated using the Consolidated Health Economic Evaluation Reporting Standards checklist. Data are summarised using narrative synthesis by population.
results2305 abstracts were identified with 52 undergoing full-text review. 30 papers met inclusion criteria addressing 7 populations: drug users (n=6), high risk (n=5), pregnant (n=4), prison (n=3), birth cohort (n=8), general population (n=5) and other (n=6). The majority (77%) of the studies were high quality. Drug users, birth cohort and high-risk populations were associated with cost-effectiveness ratios of under £30 000 per quality-adjusted-life-year (QALY). The remaining populations were associated with cost-effectiveness ratios that exceeded £30 000 per QALY.
conclusionsEconomic evidence for screening populations is robust. If a cost per QALY of £30 000 is considered reasonable value for money, then screening birth cohorts, drug users and high-risk populations are policy options that should be considered.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.