Evaluation of clinical research outcomes must rely upon both the clinical meaningfulness of the findings and their statistical precision.
We want to make it mandatory to state the researchers' clinical relevance levels ahead of the trial, mentioning what they will consider clinically relevant when they pre-register their research on the clinicaltrials.gov website or similar websites. They then need to compare their findings in both the paper and abstract when publishing data from the study. #clinicalrelevance
The most common method to prove the significance of a trial's discovery is to use the p-value. The p-value is, in short, a mathematical calculation of the probability (hence the "p") for the presented findings (or something more extreme) to be due to pure chance. The p-value is a calculated probability for the findings or even more extreme results being due to chance. The p-value does not relate directly to the research question but to the data collected – or better analyzed – and is not a measure of relevant differences between groups in a trial of the findings' power.
The p-value refers to the analyzed data, cannot distinguish between "true or false," and does not say anything about the results' clinical meaningfulness.
In contrast to evaluating outcomes by statistical significance, we talk about clinical relevance, clinical meaningfulness, or clinical significance, all of which relate to something relevant, meaningful, or significant to a patient. Examples of that could be reducing pain enough to be felt like a change and not just statistically significant. Other examples are reducing the risk of complications, risk of death, improvement in Quality of Life, or chance of cure.
Researchers most often present data about their trials before starting data collection. They do that on websites and databases like clinicaltrials.gov and others. It may be mandatory to provide that information; otherwise, researchers are encouraged to present it
So if the researchers stated - or better even had to state - when they made this preregistration WHAT they would consider clinically relevant, it would significantly improve healthcare. It would come from focusing on using the provided information to help patients and improve healthcare.
And not just publishing a paper
The use of p-value to define results as "statistically significant" is purely arbitrary and goes 100 years back to 1925 when Sir Ronald A. Fischer presented the idea and definition in his book" Statistical Methods for Research Workers." He suggested p=0.05 as the limit to judge whether a deviation should be considered significant or not. See more on our blog.
Listen to Precision Evidence episode #10, where we discuss this and remember to always
ASK FOR A CLINICAL RELEVANCE EVALUATION OF THE RESULTS - Every Time.
All of us, whatever relation we have to produce, read, and use clinical research information.