The Methods Guide to Medical Test Reviews (also referred to as the Medical Test Methods Guide) highlights common challenges in systematic reviews of medical tests and outlines their mitigation, as perceived by researchers partaking in the Agency for Healthcare Research and Quality (AHRQ) Effective Healthcare Program.
This can be performed in the context of proper (multivariate) meta-regressions. At the same time, quantitative analyses are used to explore and explain any observed dissimilarity (heterogeneity) in the results of the examined studies. More complex analyses are needed if studies report results at multiple thresholds for positive tests. Because sensitivity and specificity are not independent across studies, the meta-analysis of medical tests is fundamentally a multivariate problem, and should be addressed with multivariate methods. The choice of the most helpful summary is subjective, and in some cases both summaries provide meaningful and complementary information. Other times, when the sensitivity or specificity estimates vary widely or when the test threshold varies, it is more helpful to synthesize data using a "summary line" that describes how the average sensitivity changes with the average specificity. Sometimes, a helpful way to summarize medical test studies is to provide a "summary point," a summary sensitivity and a summary specificity. Because many metrics of test performance are of interest, the meta-analysis of medical tests is more complex than the meta-analysis of interventions or associations.
Synthesizing information on test performance metrics, such as sensitivity, specificity, predictive values and likelihood ratios, is often an important part of a systematic review of a medical test. This is a chapter from AHRQ's Methods Guide for Medical Test Reviews.
0 kommentar(er)
