Cost-effectiveness of screening for hepatitis C virus: a systematic review of economic evaluations
Bibliographic record
Abstract
OBJECTIVES: With 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. SETTING: A systematic review was completed. 5 databases were searched until May 2016 (NHSEED, MEDLINE, the HTA Health Technology Assessment Database, EMBASE, EconLit). PARTICIPANTS: Any 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. RESULTS: 2305 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. CONCLUSIONS: Economic 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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".