  The current regulatory paradigm is that PM2.5, over time causes lung cancer.
This claim is based on cohort studies and meta-analysis that use cohort studies
as their base studies. There is a need to evaluate the reliability of this
causal claim. Our idea is to examine the base studies with respect to multiple
testing and multiple modeling and to look closer at the meta-analysis using
p-value plots. For two meta-analysis we investigated, some extremely small
p-values were observed in some of the base studies, which we think are due to a
combination of bias and small standard errors. The p-value plot for one
meta-analysis indicates no effect. For the other meta-analysis, we note the
p-value plot is consistent with a two-component mixture. Small p-values might
be real or due to some combination of p-hacking, publication bias, covariate
problems, etc. The large p-values could indicate no real effect, or be wrong
due to low power, missing covariates, etc. We conclude that the results are
ambiguous at best. These meta-analyses do not establish that PM2.5 is causal of
lung tumors.
