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Comprehensive Overview of Methods and Reporting of Meta-Analyses of Test Accuracy

Methods Research Reports

Investigators: , MD, MS, , PhD, MPH, , MD, PhD, MS, , MD, PhD, , MD, MS, , MD, PhD, , MD, MS, , MD, , MD, PhD, and , PhD.

Tufts Evidence-based Practice Center
Rockville (MD): Agency for Healthcare Research and Quality (US); .
Report No.: 12-EHC044-EF

Structured Abstract

Background:

Medical tests play a critical role in disease screening, diagnosis, and prediction of future outcomes. Meta-analyses of diagnostic or predictive test accuracy are increasingly performed and the relevant methods are continuously evolving.

Methods:

We identified systematic reviews including quantitative synthesis (meta-analysis) of test accuracy for diagnostic or predictive medical tests through MEDLINE searches (1966 to December 2009) and perusal of reference lists of eligible articles and relevant reviews. We extracted information on topics and test types covered, methods for literature synthesis and quality assessment, availability of data, and statistical analyses performed.

Results:

Our searches retrieved 1,225 potentially eligible reviews of which 760 (published from 1987 to 2009) were finally considered eligible for inclusion. Eligible reviews included a median of 18 primary studies and typically examined a single index test against a single reference standard. The number of publications increased per calendar year (P < 0.001). Most meta-analyses pertained to cardiovascular disease (21 percent) and oncology (25 percent); the most common test categories were imaging (44 percent) and biomarker tests (28 percent). Meta-analyses used multiple electronic databases (62 percent used at least one electronic database in addition to MEDLINE; P for trend over time < 0.001) to identify eligible studies. There was a striking increase in the proportion of systematic reviews that reported assessing verification bias (P for trend < 0.001), spectrum bias (P for trend = 0.007), blinding (P for trend < 0.001), prospective study design (P for trend < 0.001), or consecutive patient recruitment (P for trend < 0.001), over time. Improvements were associated with reporting of using quality-item checklists to guide assessment of methodological quality. In statistical analyses, sensitivity (in 77 percent), specificity (in 74 percent) and diagnostic/predictive odds ratios (in 34 percent) were the most commonly used metrics. Heterogeneity tests were used in 58 percent, and subgroup or regression analyses were used in 57 percent of meta-analyses. Random effects models were employed in 57 percent of the reviews and increasingly over time (P for trend < 0.001). Theoretically motivated methods that model sensitivity and specificity simultaneously, while accounting for between-study heterogeneity, were used in a minority of reviews (11 percent) but increasingly over time (P for trend < 0.001).

Conclusion:

Meta-analyses of diagnostic or predictive tests are increasingly performed. Over time there have been substantial improvements in the literature review, quality assessment and statistical analysis methods employed. Much of the improvement in quality assessment is associated with the use of quality item checklists. Advanced statistical methods have been increasingly adopted over time but their use still remains limited.

540 Gaither Road, Rockville, MD 20850; www​.ahrq.gov

Prepared for: Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services1, Contract No. 290-2007-10055-I. Prepared by: Tufts Evidence-based Practice Center, Boston, MA

Suggested citation:

Dahabreh IJ, Chung M, Kitsios GD, Terasawa T, Raman G, Tatsioni A, Tobar A, Lau J, Trikalinos TA, Schmid CH. Comprehensive Overview of Methods and Reporting of Meta-Analyses of Test Accuracy. Methods Research Report. (Prepared by the Tufts Evidence-based Practice Center under Contract No. 290-2007-10055-I.) AHRQ Publication No. 12-EHC044-EF. Rockville, MD: Agency for Healthcare Research and Quality; March 2012. www.effectivehealthcare.ahrq.gov/reports/final.cfm.

This report is based on research conducted by the Tufts Evidence-based Practice Center under contract to the Agency for Healthcare Research and Quality (AHRQ), Rockville, MD (Contract No. 290-2007-10055-I). The findings and conclusions in this document are those of the author(s), who are responsible for its contents; the findings and conclusions do not necessarily represent the views of AHRQ. Therefore, no statement in this report should be construed as an official position of AHRQ or of the U.S. Department of Health and Human Services.

The information in this report is intended to help health care decisionmakers—patients and clinicians, health system leaders, and policymakers, among others—make well-informed decisions and thereby improve the quality of health care services. This report is not intended to be a substitute for the application of clinical judgment. Anyone who makes decisions concerning the provision of clinical care should consider this report in the same way as any medical reference and in conjunction with all other pertinent information, i.e., in the context of available resources and circumstances presented by individual patients.

This report may be used, in whole or in part, as the basis for development of clinical practice guidelines and other quality enhancement tools, or as a basis for reimbursement and coverage policies. AHRQ or U.S. Department of Health and Human Services endorsement of such derivative products may not be stated or implied.

The investigators have no relevant financial interests in the report. The investigators have no employment, consultancies, honoraria, or stock ownership or options, or royalties from any organization or entity with a financial interest or financial conflict with the subject matter discussed in the report.

1

540 Gaither Road, Rockville, MD 20850; www​.ahrq.gov

Bookshelf ID: NBK92422PMID: 22553887
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