GRADE guidelines: 21 part 1. Study design, risk of bias and indirectness in rating the certainty across a body of evidence for test accuracy

  • Holger J. Schünemann
  • , Reem A. Mustafa
  • , Jan Brozek
  • , Karen Steingart
  • , Mariska Leeflang
  • , Mohammad Hassan Murad
  • , Patrick Bossuyt
  • , Paul Glasziou
  • , Roman Jaeschke
  • , Stefan Lange
  • , Joerg Meerpohl
  • , Miranda Langendam
  • , Monica Hultcrantz
  • , Gunn E. Vist
  • , Elie A. Akl
  • , Mark Helfand
  • , Nancy Santesso
  • , Lotty Hooft
  • , Rob Scholten
  • , Måns Rosen
  • Anne Rutjes, Mark Crowther, Paola Muti, Heike Raatz, Mohammed T. Ansari, John Williams, Regina Kunz, Jeff Harris, Ingrid Arévalo Rodriguez, Mikashmi Kohli, Gordon H. Guyatt

Research output: Contribution to journalArticlepeer-review

264 Citations (Scopus)

Abstract

Objectives

This article provides updated GRADE guidance about how authors of systematic reviews and health technology assessments (HTA) and guideline developers can assess the results and the certainty of evidence (also known as quality of the evidence or confidence in the estimates) of a body of evidence addressing test accuracy (TA).

Study Design and Setting

We present an overview of the GRADE approach and guidance for rating certainty in TA in clinical and public health and review the presentation of results of a body of evidence regarding tests. Part 1 of the two parts in this 21st guidance article about how to apply GRADE focuses on understanding study design issues in test accuracy, provide an overiew of the domains and describe risk of bias and indirectness specifically.

Results

Supplemented by practical examples, we describe how raters of the evidence using GRADE can evaluate study designs focusing on tests and how they apply the GRADE domains risk of bias and indirectness to a body of evidence of TA studies.

Conclusions

Rating the certainty of a body of evidence using GRADE in Cochrane and other reviews and World Health Organization and other guidelines dealing with in TA studies helped refining our approach. The resulting guidance will help applying GRADE successfully for questions and recommendations focusing on tests.

Original languageEnglish
Pages (from-to)129-141
Number of pages13
JournalJournal of Clinical Epidemiology
Volume122
Early online date12 Feb 2020
DOIs
Publication statusPublished - 1 Jun 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Certainty of evidence
  • Diagnosis
  • Diagnostic accuracy
  • GRADE
  • Test accuracy
  • Tests

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