TY - JOUR
T1 - GRADE guidelines: 22. The GRADE approach for tests and strategies—from test accuracy to patient-important outcomes and recommendations
AU - the GRADE Working Group
AU - Schünemann, Holger J.
AU - Mustafa, Reem A.
AU - Brozek, Jan
AU - Santesso, Nancy
AU - Bossuyt, Patrick M.
AU - Steingart, Karen R.
AU - Leeflang, Mariska
AU - Lange, Stefan
AU - Trenti, Tommaso
AU - Langendam, Miranda
AU - Scholten, Rob
AU - Hooft, Lotty
AU - Murad, Mohammad Hassan
AU - Jaeschke, Roman
AU - Rutjes, Anne
AU - Singh, Jasvinder
AU - Helfand, Mark
AU - Glasziou, Paul
AU - Arevalo-Rodriguez, Ingrid
AU - Akl, Elie A.
AU - Deeks, Jonathan J.
AU - Guyatt, Gordon H.
PY - 2019/7
Y1 - 2019/7
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85062971920&partnerID=8YFLogxK
U2 - 10.1016/j.jclinepi.2019.02.003
DO - 10.1016/j.jclinepi.2019.02.003
M3 - Article
C2 - 30738926
AN - SCOPUS:85062971920
SN - 0895-4356
VL - 111
SP - 69
EP - 82
JO - Journal of Clinical Epidemiology
JF - Journal of Clinical Epidemiology
ER -