Journal of clinical epidemiology
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Evidence-based medicine (EBM) has experienced numerous advances since its inception over 2 decades ago. Yet a persistent gulf remains between how medicine is actually practiced and the goal of providing care based on best available research evidence integrated with patient perspective and clinical expertise. A primary source of challenge for EBM is induced by inefficiencies in the generation, synthesis, and translation of evidence. ⋯ Based on the features of a natural ecosystem, the ecosystem of evidence is influenced by living organisms: stakeholders replete with competition and collaboration among and between them, as well as their conflicts of interest; the environment: social, cultural, economic, and/or political contexts; and nonliving components: scientific evidence, influenced by the rules, standards, and frameworks associated with evidence generation, synthesis, and translation. This article provides an analysis of the strengths and weaknesses of this ecosystem with a focus on nonliving components, specifically evidence generation, synthesis, and translation. Specific suggestions are outlined for building a stable and resilient ecosystem of evidence.
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To determine which systematic review characteristics are needed to estimate the risk of conclusion change in systematic review updates. ⋯ When estimating the risk of conclusion change in systematic review updates, information about the sizes of trials that will be added in an update are most useful. Future tools aimed at signaling conclusion change risks would benefit from complementary tools that automate screening of relevant trials.
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To investigate whether comparing observed with expected P-value distributions for baseline continuous variables in randomized controlled trials (RCTs) might be limited by randomization methods, normality and correlation of variables, or calculation of P-values from rounded summary statistics. ⋯ Randomization methods, non-normality, and strength of correlation of baseline variables did not have important effects on baseline P-value distribution or AUC-CDF, but baseline P-values calculated from rounded summary statistics are non-uniformly distributed.
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The determinants of guideline panels' recommendations remain uncertain. The objective of this study was to investigate factors considered by members of 8 panels convened by the American Society of Hematology (ASH) to develop guidelines using Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system. ⋯ GRADE's conceptual framework proved, in general, to be highly associated with SOR. Failure of certainty of evidence to be associated with SOR against an intervention, suggest the need for improvements in the process.