What is the true worth of a P-value? Time for a change

Bayesian statistics in anesthesia practice: a tutorial for anesthesiologists

This narrative review intends to provide the anesthesiologist with the basic knowledge of the Bayesian concepts and should be considered as a tutorial for anesthesiologists in the concept of Bayesian statistics. The Bayesian approach represents the mathematical formulation of the idea that we can update our initial belief about data with the evidence obtained from any kind of acquired data. It provides a theoretical framework and a statistical method to use pre-existing information within the context of new evidence. Several authors have described the Bayesian approach as capable of dealing with uncertainty in medical decision-making. This review describes the Bayes theorem and how it is used in clinical studies in anesthesia and critical care. It starts with a general introduction to the theorem and its related concepts of prior and posterior probabilities. Second, there is an explanation of the basic concepts of the Bayesian statistical inference. Last, a summary of the applicability of some of the Bayesian statistics in current literature is provided, such as Bayesian analysis of clinical trials and PKPD modeling.

Potential effects of lowering the threshold of statistical significance in the field of chronic rhinosinusitis - A meta-research on published randomized controlled trials over last decade

OBJECTIVE

To evaluate the impact of change in p-value threshold from 0.05 to 0.005, on published Randomized Controlled Trials (RCTs) over the last ten years in the field of chronic rhinosinusitis.

METHODS

A search of the PubMed database from 1st January 2011 to 31st December 2020 was conducted to include all RCTs that used p-value to determine the effects of an intervention. Data extracted included p-values, type of intervention, publishing journal with indexing, registration, funding, and multi- or single center status. The proportion of primary endpoints having p < 0.005 was determined first, followed by those with p > 0.005 but <0.05. Logistic regression analysis was used to determine if any trial characteristic was associated with reporting of significant p-values.

RESULTS

In total, 168 primary endpoints were identified from 123 RCTs. On analysis, 80 had a p-value <0.05, i.e., statistically significant on conventional parameter. Out of these, 53.75% had a p-value <0.005, which would retain significance under the proposed threshold, and the remaining 46.25% to be reclassified as "suggestive". None of the trial characteristics were contributing to reporting of conventional or proposed p-values on logistic regression analysis.

CONCLUSION

Lowering the p-value threshold would render 46.25% of a decade of published RCTs results (in the field of CRS) to be reclassified as merely "suggestive" and not significant. Trial characteristics were not found contributing to reporting of p-value <0.005 or even <0.05.

LEVEL OF EVIDENCE

II.