Recognising Bias in Studies of Diagnostic Tests Part 1: Patient Selection

Emerg Med J. 2019 Jul;36(7):431-434. doi: 10.1136/emermed-2019-208446. Epub 2019 Jul 13.

Abstract

In this two-part series on sources of bias in studies of diagnostic test performance, we outline common errors and optimal conditions during three study phases: patient selection, interpretation of the index test and disease verification by a gold standard. Here in part 1, biases associated with suboptimal participant selection are discussed through the lens of partial verification bias and spectrum bias, both of which increase the proportion of participants who are the 'sickest of the sick' or the 'wellest of the well.' Especially through retrospective methodology, partial verification introduces bias by including patients who are test positive by a gold standard, since patients with a positive index test are more likely to go on to further gold standard testing. Spectrum bias is frequently introduced through case-control design, dropping of indeterminate results or convenience sampling. After reading part 1, the informed clinician should be better able to judge the quality of a diagnostic test study, its inherent limitations and whether its results could be generalisable to their practice. Part 2 will describe how interpretation of the index test and disease verification by a gold standard can contribute to diagnostic test bias.

Keywords: imaging; research, methods; statistics; ultrasound.

Publication types

  • Editorial

MeSH terms

  • Bias*
  • Diagnostic Tests, Routine / methods*
  • Diagnostic Tests, Routine / standards
  • Diagnostic Tests, Routine / statistics & numerical data
  • Humans
  • Patient Selection / ethics*
  • Research Design / standards
  • Research Design / statistics & numerical data
  • Retrospective Studies