Last Revision Date: Friday, 13-Apr-2001 16:32:20 EDT
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This is a response to a question about the meaning of the term "p value" in
statistical analysis.
Question:

While researching my diagnosis I have come across the term "p value" quite
often. What does this mean?
Thank you,
MH
Todd Doyle, MD, OncoLink Editorial Assistant, responds:
Dear OncoLink readers:
Thank you very much for your interest and questions regarding the meaning of
the term "p value".
The "p value" is a statistical term found in almost all scientific papers in
which two or more outcomes are compared. By definition, a p value is the
probability that a given outcome, or one more extreme than that outcome
could have occurred by chance alone.
Research papers often state that one treatment was better than another and
that the difference in outcome for example was statistically significant
with a p value <0.05. This means that there was a less than 5% probability
of the observed difference occurring between the outcomes of the two
different groups of patients who got the different treatments. It is very
unlikely that some fluke caused the difference in survival and alternatively
the difference is likely secondary to a better treatment, all other things
being equal.
The actual significance level is somewhat arbitrarily chosen, but the lower
the value, the less likely it is that the difference between the two
outcomes occurred by chance alone. Most investigators agree that p>0.05 is
not significant, p<0.05 is significant, and p<0.01 is highly significant.
Some experts would consider p<0.10 to be marginally significant and would
leave it up to the reader to decide whether the information is sufficient to
conclude that the difference is not simply due to chance alone.
One important thing to keep in mind is that just because the difference
between two treatments is not statistically significant (p>0.05), does not
mean that the two treatments are the same. Rather, there may be insufficient
evidence to be certain the differences are "real" and not due to chance. One
reason that this sometimes happens is that the number of patients enrolled
in the particular study was not large enough to show the difference.
Furthermore, a statistically significant difference does not mean that the
difference is clinically significant. A comparison between toxicity of
treatment X = 10.1% and treatment Y = 10.2% may be statistically
significant, but may also be so small as to have little practical, impact.
For a more detailed description of the statistics regarding p values and
tests of significance the reader is referred to any number of medical
statistics texts including the following:
1. Kuzma JW. Basic Statistics for the Health Sciences, 3rd Edition, Mayfield
Publishing Company, 1998.

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