Glossary term explanation

p-value

In randomized controlled trials of the efficacy of CoQ10 supplementation, the effect of the CoQ10 supplement is compared with the effect of a placebo supplement on specified outcomes such as mortality, ejection fraction, NYHA class, hospitalizations, health-related quality of life, etc.

The p-value is a measure of the probability that an observed difference between the effect of the CoQ10
supplementation and the effect of the placebo supplementation is a true difference and not a difference
that could be caused just by chance.

The p-value is the probability that the observed difference between the CoQ10 effect and the placebo effect occurs just by chance if, in fact, the hypothesis, called the null hypothesis, is correct that there is no significant difference between the active CoQ10 treatment and the placebo treatment.

P-values can have any value between 0 and 1. If the p-value is close to 0, then the observed difference is unlikely to be due to chance.

If the p-value is close to 1, then the difference between the CoQ10 group and the placebo group is thought to be due to chance and not due to the effect of the CoQ10 supplement.

Typically, clinical trial results are thought to be statistically significant if the p-value is smaller than a
pre-specified confidence level, which is often the 0.05 level but could be the 0.01 level.

A p-value of 0.05 means that one out of 20 studies of the same design and sample size would result, just by chance, in a difference at least as big as the difference observed in the actual study, meaning that would be a 5% chance of calling an observed different significant when it is not significant.

A larger sample size should result in a smaller p-value only if the null hypothesis is false, which is
what we want in trial of CoQ10 efficacy.  We want the CoQ10 effect to be greater than the placebo effect.



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