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Summarizing Studies of Diagnostic Test Performance

¹ Department of Medicine, Mayo Clinic, Rochester, MN 55905

² Departments of Clinical Epidemiology, and, Biostatistics and Medicine, McMaster University, Hamilton, Ontario L8N 3Z5, Canada

^aAuthor for correspondence.

The first 300 words of the full text of this article appear below.

In this issue of Clinical Chemistry, Brown et al. (1) report a metaanalysis of studies of the test characteristics of the latex turbidimetric D-dimer test for the diagnosis of pulmonary embolism. In this editorial, we will discuss the importance of conducting systematic reviews of diagnostic evidence and their contribution to the practice of evidence-based laboratory medicine.

Evidence-based practitioners complement, or at times substitute, diagnostic intuition with the explicit use of the best available quantitative evidence about the power of symptoms, signs, and laboratory tests to increase or decrease the probabilities associated with alternative diagnoses. Summarizing studies that have high validity will yield unbiased results, and pooling across studies will reduce the random error associated with individual smaller studies. In addition to generating more precise, accurate summaries, pooling across different patient groups will, if tests perform similarly in those groups, yield results that apply to a broader population than the individual studies. Thus, systematic summaries of valid diagnostic evidence are at the top of the hierarchy of diagnostic evidence.

Summaries of evidence will yield misleading results if they try to combine results across patient groups or test methods that are too heterogeneous; if they assemble an incomplete, biased sample of potentially available studies; or if they use results from studies that are themselves methodologically weak and very susceptible to bias. To avoid these sources of error, authors of systematic reviews should (a) ask a sensible question; (b) conduct a detailed and exhaustive search for relevant studies; (c) if possible, focus on studies of high methodologic quality; and (d) use reproducible approaches to assess the limitations in the methodologic quality of the studies on which they focus (2).

Brown et al. (1) asked a narrowly focused and sensible question and translated their review question into . . . [Full Text of this Article]

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