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Schünemann, Holger J., Mustafa, Reem A., Brozek, Jan, Santesso, Nancy, Bossuyt, Patrick M., Steingart, Karen, Leeflang, Mariska, Lange, Stefan, Trenti, Tommaso, Langendam, Miranda, Scholten, Rob, Hooft, Lotty, Murad, Mohammad Hassan, Jaeschke, Roman, Rutjes, Anne, Singh, Jasvinder, Helfand, Mark, Glasziou, Paul, Rodriguez, Ingrid Arévalo, Akl, Elie A., Deeks, Jonathan J. and Guyatt, Gordon H. (2019) 'GRADE Guidelines: 22. The GRADE approach for tests and strategies - from test accuracy to patient important outcomes and recommendations'. Journal of Clinical Epidemiology, Vol 111, pp. 69-82.
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Abstract
Objectives
This article describes GRADE’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, since resources and time of guideline developers may be limited, we describe alternative, pragmatic strategies for developing recommendations addressing test use.
| Item Type: | Article |
|---|---|
| Subjects: | W General Medicine. Health Professions > Health Services. Patients and Patient Advocacy > W 84.4 Quality of Health Care W General Medicine. Health Professions > Health Services. Patients and Patient Advocacy > W 84 Health services. Delivery of health care WB Practice of Medicine > WB 100 General works WB Practice of Medicine > WB 102 Clinical medicine |
| Faculty: Department: | Clinical Sciences & International Health > Clinical Sciences Department |
| Digital Object Identifer (DOI): | https://doi.org/10.1016/j.jclinepi.2019.02.003 |
| Depositing User: | Stacy Murtagh |
| Date Deposited: | 11 Feb 2019 12:38 |
| Last Modified: | 07 Feb 2020 02:02 |
| URI: | https://archive.lstmed.ac.uk/id/eprint/10144 |
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