Towards complete and accurate reporting of studies of diagnostic accuracy: The STARD Initiative

Ann Intern Med. 2003 Jan 7;138(1):40-4. doi: 10.7326/0003-4819-138-1-200301070-00010.

Abstract

Background: To comprehend the results of diagnostic accuracy studies, readers must understand the design, conduct, analysis, and results of such studies. That goal can be achieved only through complete transparency from authors.

Objective: To improve the accuracy and completeness of reporting of studies of diagnostic accuracy in order to allow readers to assess the potential for bias in the study and to evaluate its generalizability.

Methods: The Standards for Reporting of Diagnostic Accuracy (STARD) steering committee searched the literature to identify publications on the appropriate conduct and reporting of diagnostic studies and extracted potential items into an extensive list. Researchers, editors, methodologists and statisticians, and members of professional organizations shortened this list during a 2-day consensus meeting with the goal of developing a checklist and a generic flow diagram for studies of diagnostic accuracy.

Results: The search for published guidelines on diagnostic research yielded 33 previously published checklists, from which we extracted a list of 75 potential items. The consensus meeting shortened the list to 25 items, using evidence on bias whenever available. A prototypical flow diagram provides information about the method of patient recruitment, the order of test execution, and the numbers of patients undergoing the test under evaluation, the reference standard, or both.

Conclusions: Evaluation of research depends on complete and accurate reporting. If medical journals adopt the checklist and the flow diagram, the quality of reporting of studies of diagnostic accuracy should improve to the advantage of the clinicians, researchers, reviewers, journals, and the public.

Publication types

  • Consensus Development Conference
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Algorithms
  • Bias
  • Clinical Trials as Topic / standards
  • Diagnostic Techniques and Procedures / standards*
  • Guidelines as Topic*
  • Publishing / standards*
  • Research Design / standards*