Topic Development

The topic of HCV screening was nominated for a comparative effectiveness review (CER) in a public process. The Key Questions were proposed in the public nomination process and developed by investigators from the Evidence-based Practice Center (EPC) with input from expert Key Informants, who helped to refine Key Questions, identify important methodological and clinical issues, and define parameters for the review of evidence. The revised Key Questions were then posted to a public Web site for comment. The Agency for Healthcare Research and Quality (AHRQ) and the EPC agreed upon the final Key Questions after reviewing the public comments and receiving additional input from a Technical Expert Panel (TEP) convened for this report.

Search Strategy

To identify articles relevant to each Key Question, a research librarian searched Ovid® MEDLINE (see Appendix A. Exact Search Strategy), EMBASE, Scopus, and PsycINFO from 1947 to May 2012. Gray literature was identified by searching clinical trial registries (Ovid® EBM Reviews: Cochrane Central Register of Controlled Trials, ClinicalTrials.gov, Current Controlled Trials, Clinical Trial Results, and WHO Trial Registries) and grants databases (NIHRePORTER, HSRProj, and AHRQ GOLD). We supplemented the electronic searches by reviewing the reference lists of retrieved articles.

We updated searches prior to finalization of the report to identify new publications.

Study Selection

We developed criteria for inclusion and exclusion of studies based on the Key Questions and the populations, interventions, comparators, outcomes, timing, and setting (PICOTS) approach. Inclusion and exclusion criteria, summarized below, are described in more detail by Key Question in Appendix B. Papers were selected for full review if they were about chronic HCV infection, were relevant to Key Questions in the analytic framework, and met the predefined inclusion criteria. We restricted inclusion to English language articles since translation of foreign language articles was not feasible due to resource limitations and excluded studies only published as abstracts. Studies of nonhuman subjects were also excluded, and studies had to include original data.

Abstracts and full-text articles were dual reviewed for inclusion or exclusion for each Key Question. Full-text articles were obtained for all studies that either investigator identified as potentially meeting inclusion criteria. Two investigators independently reviewed all full-text articles for final inclusion or exclusion (Appendix C. Included studies list). A list of excluded studies can be found in Appendix D. Discrepancies were resolved through discussion and consensus, and a third investigator was included in the discussion if necessary.

Data Extraction

We extracted the following data from included trials: study design, setting, population characteristics (including sex, age, ethnicity/race, and diagnosis), eligibility and exclusion criteria, HCV infection intervention and comparisons, the method of outcome ascertainment if available, and results for each outcome. Evidence tables with included studies are presented for all Key Questions unless there was only very weak evidence (e.g., because of major methodological shortcomings or study designed without (comparison groups).

For studies reporting the diagnostic yield of different screening strategies, we computed the number needed to screen to identify one case of HCV infection by dividing the number of screening tests performed by the number of HCV cases identified. The proportion screened was the number of patients screened upon application of a particular screening strategy, divided by the total number of patients assessed.

For studies of diagnostic accuracy, we attempted to create 2×2 tables from information provided (usually sample size, prevalence, sensitivity, and specificity) and compared calculated measures of diagnostic accuracy based on the 2×2 tables with reported results. Although we abstracted data for severe fibrosis (defined as biopsy showing METAVIR F3-F4, Ishak 4–6, or equivalent), we summarized results for fibrosis (defined as biopsy showing METAVIR F2-F4, Ishak 3–6, or equivalent) and cirrhosis (defined as biopsy showing METAVIR F4, Ishak 5–6, or equivalent), unless there was insufficient evidence for fibrosis. We also abstracted reported area under the receiver operating characteristic curve (AUROC).^{71, 72} The AUROC, which is based on sensitivities and specificities across a range of test results, is a measure of discrimination, or the ability of a test to distinguish people with a condition from people without. An AUROC of 1.0 indicates perfect discrimination, and an AUROC of 0.5 indicates complete lack of discrimination. Interpretation of AUROC values between 0.5 and 1.0 is somewhat arbitrary, but a value of 0.90 to <1.0 may be classified as excellent, 0.80 to <0.90 good, 0.70 to <0.80 fair, and <0.70 poor. Data abstraction for each study was completed by two investigators: the first abstracted the data, and the second reviewed the abstracted data for accuracy and completeness. See Appendix G for evidence tables of extracted data.

Quality Assessment of Individual Studies

We assessed the quality of each study based on predefined criteria. We adapted criteria from methods proposed by Downs and Black (observational studies),⁷³ the USPSTF,⁷⁴ and the Quality Assessment of Diagnostic Accuracy Studies-2 Group.⁷⁵ The criteria used are consistent with the approach recommended by AHRQ in the Methods Guide for Comparative Effectiveness Reviews.⁷⁶ We used the term “quality” rather than the alternate term “risk of bias”; both refer to internal validity.

We rated the quality of each randomized trial based on the methods used for randomization, allocation concealment, and blinding; the similarity of compared groups at baseline; maintenance of comparable groups; adequate reporting of dropouts, attrition, crossover, adherence, and contamination; loss to followup; the use of intent-to-treat analysis; and ascertainment of outcomes.⁷⁴

We rated the quality of each cohort study based on whether it used nonbiased selection methods to create an inception cohort; whether it evaluated comparable groups; whether rates of loss to followup were reported and acceptable; whether it used accurate methods for ascertaining exposures, potential confounders, and outcomes; and whether it performed appropriate statistical analyses of potential confounders.⁷⁴ For assessing quality of each case-control study, we evaluated whether similar inclusion and exclusion criteria were applied to select cases and controls, whether it used accurate methods to identify cases, whether it used accurate methods for ascertaining exposures and potential confounders, and whether it performed appropriate statistical analyses of potential confounders.⁷⁴

We rated the quality of each diagnostic accuracy study based on whether it evaluated a representative spectrum of patients, whether it enrolled a random or consecutive sample of patients meeting predefined criteria, whether it used a credible reference standard, whether the same reference standard was applied to all patients, whether the reference standard was interpreted independently from the test under evaluation, and whether thresholds were predefined.^{74, 75}

Following assessment of individual quality criteria, individual studies were rated as “good,” “fair,” or “poor” quality, as defined below.⁷⁶

Good-quality studies are considered likely to be valid. Good-quality studies clearly describe the population, setting, interventions, and comparison groups; use a valid method for allocation of patients to interventions; clearly report dropouts and have low dropout rates; use appropriate methods for preventing bias; and appropriately measure outcomes and fully report results.

Fair-quality studies have some methodological deficiencies, but no flaw or combination of flaws judged likely to cause major bias. The study may be missing information, making it difficult to assess its methods or assess limitations and potential problems. The fair-quality category is broad, and studies with this rating vary in their strengths and weaknesses: the results of some fair-quality studies are likely to be valid, while others are only probably valid.

Poor-quality studies have significant flaws that may invalidate the results. They have a serious or “fatal” flaw in design, analysis, or reporting; large amounts of missing information; or discrepancies in reporting. The results of these studies are judged to be at least as likely to reflect flaws in the study design as true effects of the interventions under investigation. We did not exclude studies rated poor quality a priori, but they were considered to be the least reliable studies when synthesizing the evidence, particularly when discrepancies between studies were present. For detailed quality assessment methods see Appendix E.

Assessing Research Applicability

We recorded factors important for understanding the applicability of studies, such as whether the publication adequately described the study population, how similar patients were to populations likely to be targeted by screening, whether differences in outcomes were clinically (as well as statistically) significant, and whether the interventions and tests evaluated were reasonably representative of standard practice.⁷⁷ We also recorded the funding source and role of the sponsor. We did not assign a rating of applicability (such as “high” or “low”) because applicability may differ based on the user of this report.

Evidence Synthesis and Rating the Body of Evidence

We did not attempt to pool studies of screening or treatments quantitatively due to small numbers of studies, lack of randomized trials, and substantial clinical diversity with respect to the populations, settings, and comparisons evaluated. We also did not quantitatively pool results on diagnostic accuracy (such as creating summary receiver operating characteristic curves) due to differences across those studies in populations evaluated, differences in how fibrosis or cirrhosis were defined, and methodological limitations in the studies. Instead, we created descriptive statistics with the median sensitivity and specificity at specific cutoffs and reported AUROCs, along with associated ranges. The total range, rather than the interquartile range, was chosen because certain outcomes were only reported by a few studies and the summary range highlighted the greater variability (and uncertainty) in the estimates.

We assessed the overall strength of evidence for each body of evidence in accordance with the AHRQ Methods Guide for Comparative Effectiveness Reviews.⁷⁶ We synthesized the quality of the studies; the consistency of results within and between study designs; the directness of the evidence linking the intervention and health outcomes; the precision of the estimate of effect (based on the number and size of studies and confidence intervals for the estimates); and strength of association (magnitude of effect). We were not able to formally assess for publication bias in studies of interventions due to small number of studies, methodological shortcomings, or differences across studies in designs, measured outcomes, and other factors. We rated the strength of evidence for each Key Question using the four categories recommended in the AHRQ Methods Guide:⁷⁶ A “high” grade indicates high confidence that the evidence reflects the true effect and that further research is very unlikely to change our confidence in the estimate of effect. A “moderate” grade indicates moderate confidence that the evidence reflects the true effect and further research may change our confidence in the estimate of effect and may change the estimate. A “low” grade indicates low confidence that the evidence reflects the true effect and further research is likely to change the confidence in the estimate of effect and is likely to change the estimate. An “insufficient” grade indicates evidence either is unavailable or does not permit a conclusion. See Appendix F for strength of evidence tables.

Peer Review

Experts in gastroenterology, hepatology, and infectious disease fields and individuals representing stakeholder and user communities were invited to provide external peer review of this CER; AHRQ and an associate editor also provided comments. The draft report was posted on the AHRQ Web site for 4 weeks to elicit public comment. We addressed all reviewer comments, revising the text as appropriate, and documented everything in a disposition of comments report that will be made available 3 months after the Agency posts the final CER on the AHRQ Web site.