Particulate Matter Exposure and Lung Cancer: A Review of two Meta-Analysis Studies

TL;DR

This review critically examines two meta-analyses on PM2.5 and lung cancer, revealing ambiguous results and questioning the causal link due to potential biases and statistical issues.

Contribution

It highlights the limitations of existing meta-analyses and emphasizes the need for more rigorous evaluation of the causal relationship between PM2.5 and lung cancer.

Findings

Some base studies show extremely small p-values, possibly due to bias or small standard errors.

One meta-analysis indicates no effect based on p-value plots.

The other meta-analysis suggests a mixture of effects, but results remain ambiguous.

Abstract

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.