GRADE guidelines: 22. The GRADE approach for tests and strategies-from test accuracy to patient-important outcomes and recommendations

Holger J Schünemann; Reem A Mustafa; Jan Brozek; Nancy Santesso; Patrick M Bossuyt; Karen R Steingart; Mariska Leeflang; Stefan Lange; Tommaso Trenti; Miranda Langendam; Rob Scholten; Lotty Hooft; Mohammad Hassan Murad; Roman Jaeschke; Anne Rutjes; Jasvinder Singh; Mark Helfand; Paul Glasziou; Ingrid Arevalo-Rodriguez; Elie A Akl; Jonathan J Deeks; Gordon H Guyatt; GRADE Working Group

doi:10.1016/j.jclinepi.2019.02.003

GRADE guidelines: 22. The GRADE approach for tests and strategies-from test accuracy to patient-important outcomes and recommendations

J Clin Epidemiol. 2019 Jul:111:69-82. doi: 10.1016/j.jclinepi.2019.02.003. Epub 2019 Feb 7.

Authors

Holger J Schünemann¹, Reem A Mustafa², Jan Brozek³, Nancy Santesso⁴, Patrick M Bossuyt⁵, Karen R Steingart⁶, Mariska Leeflang⁵, Stefan Lange⁷, Tommaso Trenti⁸, Miranda Langendam⁵, Rob Scholten⁹, Lotty Hooft⁹, Mohammad Hassan Murad¹⁰, Roman Jaeschke¹¹, Anne Rutjes¹², Jasvinder Singh¹³, Mark Helfand¹⁴, Paul Glasziou¹⁵, Ingrid Arevalo-Rodriguez¹⁶, Elie A Akl¹⁷, Jonathan J Deeks¹⁸, Gordon H Guyatt¹¹; GRADE Working Group

Affiliations

¹ Department of Health Research Methods, Evidence, and Impact, McMaster University, 1280 Main Street West, Hamilton, Ontario L8S4K1, Canada; Department of Medicine, McMaster University, 1280 Main Street West, Hamilton, Ontario L8S4K1, Canada; McMaster GRADE Centre, Michael DeGroote Cochrane Canada Centre, McMaster University, 1280 Main Street West, Hamilton, Ontario L8S4K1, Canada. Electronic address: schuneh@mcmaster.ca.
² Department of Health Research Methods, Evidence, and Impact, McMaster University, 1280 Main Street West, Hamilton, Ontario L8S4K1, Canada; Department of Medicine, University of Kansas Medical Center, Kansas City, KS, USA.
³ Department of Health Research Methods, Evidence, and Impact, McMaster University, 1280 Main Street West, Hamilton, Ontario L8S4K1, Canada; Department of Medicine, McMaster University, 1280 Main Street West, Hamilton, Ontario L8S4K1, Canada; McMaster GRADE Centre, Michael DeGroote Cochrane Canada Centre, McMaster University, 1280 Main Street West, Hamilton, Ontario L8S4K1, Canada.
⁴ Department of Health Research Methods, Evidence, and Impact, McMaster University, 1280 Main Street West, Hamilton, Ontario L8S4K1, Canada; McMaster GRADE Centre, Michael DeGroote Cochrane Canada Centre, McMaster University, 1280 Main Street West, Hamilton, Ontario L8S4K1, Canada.
⁵ Clinical Epidemiology and Biostatistics and Bioinformatics Academic Medical Center, University of Amsterdam, Meibergdreef 9, P.O.Box 227001100 DE, Amsterdam, The Netherlands.
⁶ Cochrane Infectious Diseases Group, Liverpool School of Tropical Medicine, Liverpool, L3 5QA UK.
⁷ Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen/Institute for Quality and Efficiency in Health Care (IQWiG), Im Mediapark 8, Köln, 50670 Cologne, Germany.
⁸ Azienda Ospedaliera Universitaria e Azienda USL di Modena, Nuovo Ospedale S. Agostino Estense, Via Giardini 1355, Modena, 41126 Italy.
⁹ Cochrane Netherlands/Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, P.O. Box 85500, Utrecht, 3508 GA The Netherlands.
¹⁰ Division of Preventive Medicine, Mayo Clinic, 200 1st, ST, SW, Rochester, MN 55902, USA.
¹¹ Department of Health Research Methods, Evidence, and Impact, McMaster University, 1280 Main Street West, Hamilton, Ontario L8S4K1, Canada; Department of Medicine, McMaster University, 1280 Main Street West, Hamilton, Ontario L8S4K1, Canada.
¹² Clinical Trial Unit (CTU) Bern, Institute of Primary Health Care; Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland.
¹³ Medicine Service, VA Medical Center, Birmingham, AL, USA; Department of Medicine, University of Alabama at Birmingham, 510, 20th Street South, Birmingham, FOT805B AL, USA.
¹⁴ Oregon Evidence-based Practice Center, Oregon Health & Science University, Portland VA Medical Center, Portland, OR, USA.
¹⁵ CREBP, Faculty Health Science & Medicine, Bond University, Gold Coast, Queensland 4229, Australia.
¹⁶ Clinical Biostatistics Unit, Ramón y Cajal Hospital (IRYCIS), Madrid, Spain; Division of Research, Fundación Universitaria de Ciencias de la Salud, Hospital de San José, Hospital Infantil de San José, Bogotá, Colombia.
¹⁷ Department of Internal Medicine, American University of Beirut, Riad-El-Solh Beirut, Beirut, 1107 2020 Lebanon.
¹⁸ Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Edgbaston, Birmingham, B15 2TT UK.

PMID: 30738926
DOI: 10.1016/j.jclinepi.2019.02.003

Abstract

Objectives: This article describes the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Working Group's framework of moving from test accuracy to patient or population-important outcomes. We focus on the common scenario when studies directly evaluating the effect of diagnostic and other tests or strategies on health outcomes are not available or are not providing the best available evidence.

Study design and setting: Using practical examples, we explored how guideline developers and other decision makers can use information from test accuracy to develop a recommendation by linking evidence that addresses downstream consequences. Guideline panels should develop an analytic framework that summarizes the actions that follow from applying a test and the consequences.

Results: We describe GRADE's current thinking about the overall certainty of the evidence (also known as quality of the evidence or confidence in the estimates) arising from consideration of the often complex pathways that involve multiple tests and management options. Each link in the evidence can-and often does-lower the overall certainty of the evidence required to formulate recommendations and make decisions about tests. The frequency with which an outcome occurs and its importance will influence whether or not a particular step in the linked evidence is critical to decision-making.

Conclusions: Overall certainty may be expressed by the weakest critical step in the linked evidence. The linked approach to addressing optimal testing will often require the use of decision analytic approaches. We present an example that involves decision modeling in a GRADE Evidence to Decision framework for cervical cancer screening. However, because resources and time of guideline developers may be limited, we describe alternative, pragmatic strategies for developing recommendations addressing test use.

Keywords: Diagnosis; Frameworks; GRADE; Guidelines; Recommendations; Systematic reviews; Tests.

Publication types

Practice Guideline
Research Support, Non-U.S. Gov't

MeSH terms

GRADE Approach*
Humans
Outcome Assessment, Health Care / methods*
Outcome Assessment, Health Care / standards*