Body of Evidence - Explore the Science & Experts | ideXlab

Scan Science and Technology

Contact Leading Edge Experts & Companies

Body of Evidence

The Experts below are selected from a list of 100779 Experts worldwide ranked by ideXlab platform

Reem A Mustafa – 1st expert on this subject based on the ideXlab platform

  • grade guidelines 21 part 1 study design risk of bias and indirectness in rating the certainty across a Body of Evidence for test accuracy
    Journal of Clinical Epidemiology, 2020
    Co-Authors: Holger J Schunemann, Reem A Mustafa, Jan Brozek, Karen R Steingart, Mariska M G Leeflang, Mohammad Hassan Murad, Patrick M M Bossuyt, Paul Glasziou, Roman Jaeschke

    Abstract:

    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.

  • grade guidelines 18 how robins i and other tools to assess risk of bias in nonrandomized studies should be used to rate the certainty of a Body of Evidence
    Journal of Clinical Epidemiology, 2018
    Co-Authors: Holger J Schunemann, Reem A Mustafa, Carlos Cuello, Jorg Meerpohl, Kris Thayer, Rebecca L Morgan, Gerald Gartlehner, Regina Kunz, Vittal S Katikireddi

    Abstract:

    Abstract Objective To provide guidance on how systematic review authors, guideline developers, and health technology assessment practitioners should approach the use of the risk of bias in nonrandomized studies of interventions (ROBINS-I) tool as a part of GRADE’s certainty rating process. Study Design and Setting The study design and setting comprised iterative discussions, testing in systematic reviews, and presentation at GRADE working group meetings with feedback from the GRADE working group. Results We describe where to start the initial assessment of a Body of Evidence with the use of ROBINS-I and where one would anticipate the final rating would end up. The GRADE accounted for issues that mitigate concerns about confounding and selection bias by introducing the upgrading domains: large effects, dose-effect relations, and when plausible residual confounders or other biases increase certainty. They will need to be considered in an assessment of a Body of Evidence when using ROBINS-I. Conclusions The use of ROBINS-I in GRADE assessments may allow for a better comparison of Evidence from randomized controlled trials (RCTs) and nonrandomized studies (NRSs) because they are placed on a common metric for risk of bias. Challenges remain, including appropriate presentation of Evidence from RCTs and NRSs for decision-making and how to optimally integrate RCTs and NRSs in an Evidence assessment.

  • grade guidelines 17 assessing the risk of bias associated with missing participant outcome data in a Body of Evidence
    Journal of Clinical Epidemiology, 2017
    Co-Authors: Gordon H Guyatt, Reem A Mustafa, Shanil Ebrahim, Pablo Alonsocoello, Bradley C Johnston, Alexander G Mathioudakis, Matthias Briel, Stephen D Walter, Diane Heelsansdell, Ignacio Neumann

    Abstract:

    Abstract Objective To provide GRADE guidance for assessing risk of bias across an entire Body of Evidence consequent on missing data for systematic reviews of both binary and continuous outcomes. Study Design and Setting Systematic survey of published methodological research, iterative discussions, testing in systematic reviews, and feedback from the GRADE Working Group. Results Approaches begin with a primary meta-analysis using a complete case analysis followed by sensitivity meta-analyses imputing, in each study, data for those with missing data, and then pooling across studies. For binary outcomes, we suggest use of “plausible worst case” in which review authors assume that those with missing data in treatment arms have proportionally higher event rates than those followed successfully. For continuous outcomes, imputed mean values come from other studies within the systematic review and the standard deviation (SD) from the median SDs of the control arms of all studies. Conclusions If the results of the primary meta-analysis are robust to the most extreme assumptions viewed as plausible, one does not rate down certainty in the Evidence for risk of bias due to missing participant outcome data. If the results prove not robust to plausible assumptions, one would rate down certainty in the Evidence for risk of bias.

Holger J Schunemann – 2nd expert on this subject based on the ideXlab platform

  • grade guidelines 21 part 1 study design risk of bias and indirectness in rating the certainty across a Body of Evidence for test accuracy
    Journal of Clinical Epidemiology, 2020
    Co-Authors: Holger J Schunemann, Reem A Mustafa, Jan Brozek, Karen R Steingart, Mariska M G Leeflang, Mohammad Hassan Murad, Patrick M M Bossuyt, Paul Glasziou, Roman Jaeschke

    Abstract:

    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.

  • grade guidelines 18 how robins i and other tools to assess risk of bias in nonrandomized studies should be used to rate the certainty of a Body of Evidence
    Journal of Clinical Epidemiology, 2018
    Co-Authors: Holger J Schunemann, Reem A Mustafa, Carlos Cuello, Jorg Meerpohl, Kris Thayer, Rebecca L Morgan, Gerald Gartlehner, Regina Kunz, Vittal S Katikireddi

    Abstract:

    Abstract Objective To provide guidance on how systematic review authors, guideline developers, and health technology assessment practitioners should approach the use of the risk of bias in nonrandomized studies of interventions (ROBINS-I) tool as a part of GRADE’s certainty rating process. Study Design and Setting The study design and setting comprised iterative discussions, testing in systematic reviews, and presentation at GRADE working group meetings with feedback from the GRADE working group. Results We describe where to start the initial assessment of a Body of Evidence with the use of ROBINS-I and where one would anticipate the final rating would end up. The GRADE accounted for issues that mitigate concerns about confounding and selection bias by introducing the upgrading domains: large effects, dose-effect relations, and when plausible residual confounders or other biases increase certainty. They will need to be considered in an assessment of a Body of Evidence when using ROBINS-I. Conclusions The use of ROBINS-I in GRADE assessments may allow for a better comparison of Evidence from randomized controlled trials (RCTs) and nonrandomized studies (NRSs) because they are placed on a common metric for risk of bias. Challenges remain, including appropriate presentation of Evidence from RCTs and NRSs for decision-making and how to optimally integrate RCTs and NRSs in an Evidence assessment.

Nadja Tschentscher – 3rd expert on this subject based on the ideXlab platform

  • the Body of Evidence what can neuroscience tell us about embodied semantics
    Frontiers in Psychology, 2013
    Co-Authors: Olaf Hauk, Nadja Tschentscher

    Abstract:

    Semantic knowledge is based on the way we perceive and interact with the world. However, the jury is still out on the question: To what degree are neuronal systems that subserve acquisition of semantic knowledge, such as sensory-motor networks, involved in its representation and processing? We will begin with a critical evaluation of the main behavioral and neuroimaging methods with respect to their capability to define the functional roles of specific brain areas. Any behavioral or neuroscientific measure is a conflation of representations and processes. Hence, a combination of behavioral and neurophysiological interactions as well as time-course information is required to define the functional roles of brain areas. This will guide our review of the empirical literature. Most research in this area has been done on semantics of concrete words, where clear theoretical frameworks for an involvement of sensory-motor systems exist. Most of this Evidence still stems from correlational studies that are ambiguous with respect to the behavioral relevance of effects. Evidence for causal effects of sensory-motor systems on semantic processes is still scarce but evolving. Relatively few neuroscientific studies so far have investigated the embodiment of abstract semantics for words, numbers and arithmetic facts. Here, some correlational Evidence exists, but data on causality are mostly absent. We conclude that neuroimaging data, just as behavioral data, have so far not disentangled the fundamental link between process and representation. Future studies should therefore put more emphasis on the effects of task and context on semantic processing. Strong conclusions can only be drawn from a combination of methods that provide time course information, determine the connectivity among poly– or amodal and sensory-motor areas, link behavioral with neuroimaging measures, and allow causal inferences. We will conclude with suggestions on how this could be accomplished in future research.