Cancer Risk from Exposure to Low to Moderate Level of Arsenic Using Meta-Analysis of Flexible Regression Models

Abstract

These meta-analysis studies on arsenic exposure and disease risk assume linear exposure-response models. The linearity assumption for the logarithm of relative risks and levels of exposure to arsenic is overly simplified and is not adequate to capture the local structure accurately. This article applies fractional polynomial and cubic spline regression models in order to capture the shapes of the exposure-response relationships between both bladder and lung cancer risk and exposure to low to moderate dose arsenic. We consider low to moderate dose levels with concentrations from near 0 to 300µg/l. We also consider more recent studies on low to moderate dose exposure to arsenic and the risk of bladder and lung cancer. These flexible models are used to identify a combined general exposure-response relationship for the logarithm of relative risk and the levels of exposure to arsenic. The primary objective of this study is to predict overall risks of bladder and lung cancers by combining findings from systematically selected studies on these cancers under both linear and non-linear modeling assumptions. We predict overall risks of bladder and lung cancers for a series of exposure levels from the best fitting models.