No evidence of bias in the process of publication of diagnostic accuracy studies in stroke submitted as abstracts

Miriam Brazzelli, Stephanie C Lewis, Jonathan J Deeks, Peter A G Sandercock

Research output: Contribution to journalArticle

27 Citations (Scopus)

Abstract

Objective
There is little empirical evidence on publication bias in diagnostic test accuracy studies. We evaluated the proportion of abstracts presented at international stroke meetings, which were later published in full, and investigated which study features characterized publication.

Methods
We reviewed all diagnostic abstracts presented at two international stroke conferences between 1995 and 2004. We assessed the characteristics and findings of the identified abstracts. We identified full publications through electronic databases and by contacting the authors. Determinants of publication were assessed by Cox regression.

Results
Seventy-six percent (121 out of 160) of identified abstracts were subsequently published in full. Sixty-two percent were published within 24 months of presentation. The median time to publication was 16 months. Assessment of interobserver agreement between test readers was a significant predictor of full publication (P = 0.02). No other study characteristic (including clinical utility of results, multicenter status, or Youden's index) was predictive.

Conclusions
We found no clear evidence of bias in the publication process that occurs after abstract acceptance. We were unable to assess bias in abstract submission or acceptance. “Interobserver agreement” was the only characteristic statistically associated with publication. Clinical utility of results and other study characteristics did not predict publication. Diagnostic abstracts often did not report many relevant methodological aspects.
Original languageEnglish
Pages (from-to)425-430
Number of pages6
JournalJournal of Clinical Epidemiology
Volume62
Issue number4
DOIs
Publication statusPublished - Apr 2009

Keywords

  • diagnosis
  • diagnostic accuracy studies
  • stroke
  • publication bias
  • survival analysis
  • regression analysis

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