Mathew Mercuri1,2,3, Brian S Baigrie2. 1. Department of Medicine, Division of Emergency Medicine, McMaster University, Hamilton, Canada. 2. Institute for the History and Philosophy of Science and Technology, University of Toronto, Toronto, Canada. 3. African Centre for Epistemology and Philosophy of Science, University of Johannesburg, Auckland Park, South Africa.
Abstract
RATIONALE, AIMS, AND OBJECTIVES: Confidence (or belief) that a therapy is effective is essential to practicing clinical medicine. GRADE, a popular framework for developing clinical recommendations, provides a means for assigning how much confidence one should have in a therapy's effect estimate. One's level of confidence (or "degree of belief") can also be modelled using Bayes theorem. In this paper, we look through both a GRADE and Bayesian lens to examine how one determines confidence in the effect estimate. METHODS: Philosophical examination. RESULTS: The GRADE framework uses a criteria-based method to assign a quality of evidence level. The criteria pertain mostly to considerations of methodological rigour, derived from a modified evidence-based medicine evidence hierarchy. The four levels of quality relate to the level of confidence one should have in the effect estimate. The Bayesian framework is not bound by a predetermined set of criteria. Bayes theorem shows how a rational agent adjusts confidence (ie, degree of belief) in the effect estimate on the basis of the available evidence. Such adjustments relate to the principles of incremental confirmation and evidence proportionism. Use of the Bayesian framework reveals some potential pitfalls in GRADE's criteria-based thinking on confidence that are out of step with our intuitions on evidence. CONCLUSIONS: A rational thinker uses all available evidence to formulate beliefs. The GRADE criteria seem to suggest that we discard some of that information when other, more favoured information (eg, derived from clinical trials) is available. The GRADE framework should strive to ensure that the whole evidence base is considered when determining confidence in the effect estimate. The incremental value of such evidence on determining confidence in the effect estimate should be assigned in a manner that is theoretically or empirically justified, such that confidence is proportional to the evidence, both for and against it.
RATIONALE, AIMS, AND OBJECTIVES: Confidence (or belief) that a therapy is effective is essential to practicing clinical medicine. GRADE, a popular framework for developing clinical recommendations, provides a means for assigning how much confidence one should have in a therapy's effect estimate. One's level of confidence (or "degree of belief") can also be modelled using Bayes theorem. In this paper, we look through both a GRADE and Bayesian lens to examine how one determines confidence in the effect estimate. METHODS: Philosophical examination. RESULTS: The GRADE framework uses a criteria-based method to assign a quality of evidence level. The criteria pertain mostly to considerations of methodological rigour, derived from a modified evidence-based medicine evidence hierarchy. The four levels of quality relate to the level of confidence one should have in the effect estimate. The Bayesian framework is not bound by a predetermined set of criteria. Bayes theorem shows how a rational agent adjusts confidence (ie, degree of belief) in the effect estimate on the basis of the available evidence. Such adjustments relate to the principles of incremental confirmation and evidence proportionism. Use of the Bayesian framework reveals some potential pitfalls in GRADE's criteria-based thinking on confidence that are out of step with our intuitions on evidence. CONCLUSIONS: A rational thinker uses all available evidence to formulate beliefs. The GRADE criteria seem to suggest that we discard some of that information when other, more favoured information (eg, derived from clinical trials) is available. The GRADE framework should strive to ensure that the whole evidence base is considered when determining confidence in the effect estimate. The incremental value of such evidence on determining confidence in the effect estimate should be assigned in a manner that is theoretically or empirically justified, such that confidence is proportional to the evidence, both for and against it.
Authors: Benjamin Djulbegovic; Muhammad Muneeb Ahmed; Iztok Hozo; Despina Koletsi; Lars Hemkens; Amy Price; Rachel Riera; Paulo Nadanovsky; Ana Paula Pires Dos Santos; Daniela Melo; Ranjan Pathak; Rafael Leite Pacheco; Luis Eduardo Fontes; Enderson Miranda; David Nunan Journal: J Eval Clin Pract Date: 2022-01-28 Impact factor: 2.336