Mechanistic evidence in evidence-based medicine a conceptual framework

RESULTS: The final version of the framework for evaluation of mechanistic evidence incorporates an evaluation of the strength of evidence for the: 1. Intervention's target effect in nonhuman models.2. Clinical impact of target effect in nonhuman models.3. Predictive power of nonhuman model for...

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Bibliographic Details
Main Authors: Goodman, Steven N., Gerson, Jason (Author)
Corporate Authors: United States Agency for Healthcare Research and Quality, Johns Hopkins University Evidence-based Practice Center
Format: eBook
Language:English
Published: Rockville (MD) Agency for Healthcare Research and Quality (US) 2013, June 2013
Series:Research white papers
Subjects:
Online Access:
Collection: National Center for Biotechnology Information - Collection details see MPG.ReNa
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245 0 0 |a Mechanistic evidence in evidence-based medicine  |h Elektronische Ressource  |b a conceptual framework  |c investigators, Steven N. Goodman, Jason Gerson 
260 |a Rockville (MD)  |b Agency for Healthcare Research and Quality (US)  |c 2013, June 2013 
300 |a 1 PDF file various pagings 
505 0 |a Includes bibliographical references 
653 |a Research Design 
653 |a Technology Assessment, Biomedical 
653 |a Evidence-Based Medicine 
700 1 |a Gerson, Jason  |e [author] 
710 2 |a United States  |b Agency for Healthcare Research and Quality 
710 2 |a Johns Hopkins University  |b Evidence-based Practice Center 
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989 |b NCBI  |a National Center for Biotechnology Information 
490 0 |a Research white papers 
500 |a Title from PDF title page 
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520 |a RESULTS: The final version of the framework for evaluation of mechanistic evidence incorporates an evaluation of the strength of evidence for the: 1. Intervention's target effect in nonhuman models.2. Clinical impact of target effect in nonhuman models.3. Predictive power of nonhuman model for an effect in humans3t The predictive power of the target effect model3c The predictive power of the clinical effect model4. Intervention's target effect in human disease states.5. Clinical impact of the target effect in human disease states.A graphic representation is included in the full report. CONCLUSION: This framework has several features combining work from a variety of fields that represent an important step forward in the rigorous assessment of such evidence. 1. It uses a definition of evidence based on inferential effect, not study design.2. It separates evidence based on mechanistic knowledge from that based on direct evidence linking the intervention to a given clinical outcome.3.  
520 |a BACKGROUND: Virtually all current frameworks for the evaluation of the strength of evidence for an intervention's effect focus on the quality of the design linking the intervention to a given outcome. Knowledge of biological mechanism plays no formal role. In none of the evidence grading schemas, new statistical methodologies or other technology assessment guidelines is there a formal language and structure for how knowledge of how an intervention works. OBJECTIVES: The objective was to identify and pilot test a framework for the evaluation of the evidential weight of mechanistic knowledge in evidence-based medicine and technology assessment. METHODS: Six steps were used to develop a framework for the evaluation of the evidential weight of mechanistic knowledge: (1) Focused literature review, (2) Development of draft framework, (3) Workshop with technical experts, (4) Refinement of framework, (5) Development of two case studies, (6) Pilot test of framework on case studies.  
520 |a It represents the minimum sufficient set of steps for building an indirect chain of mechanistic evidence.4. It is adaptable and generalizable to all forms of interventions and health outcomes.It mirrors in the evidential framework the conceptual framework for translational medicine, thus linking the fields of basic science, evidence-based medicine and comparative effectiveness research