ArticleCancer informatics2015
Assessment of weighted quantile sum regression for modeling chemical mixtures and cancer risk.
Article in Cancer informatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 154 papers.
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Who cites it
154 citing papers in PubMed.
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- Environmental Mixture-Health Associations: Current Analytical Practice and Reporting Recommendations.China CDC weekly · 2026Article
- Multi-matrix copper exposure is associated with reduced olfactory bulb volume and odor sensitivity in adolescents.medRxiv : the preprint server for health sciences · 2026Article
- Combined Effects of Metals and PFAS Exposure on Prevalent Diabetes.Journal of xenobiotics · 2026Article
- Magnesium Attenuates the Association Between Mixed Element Exposure and Depressive Symptoms in Older Adults.Toxics · 2026Article
- Exposure to ambient air pollutants and incident chronic kidney disease in patients with hypertension: a CHARLS-based study.International urology and nephrology · 2026Article
- Co-exposure to perchlorate, nitrate, thiocyanate, and per- and polyfluoroalkyl substances (PFAS) mixtures is associated with increased rheumatoid arthritis risk: a population-based cross-sectional study.Clinical rheumatology · 2026Article
- Comparison of environmental mixture methods for estimating the joint effects of environmental mixtures.Environmental research · 2026Article
- Bringing spatial confounding into the causal inferential fold.American journal of epidemiology · 2026Article
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- Genetic and epidemiological insights into the role of neutrophil percentage in heart failure risk: a Mendelian randomization and NHANES study.Molecular and cellular biochemistry · 2026Article
- Prognostic impact of PMiScience · 2026Article
- Review
- Letter to the Editor on "Urinary heavy metal burden and overactive bladder risk: a cross-sectional study based on NHANES 2005-2018".International journal of surgery (London, England) · 2026Article
- The impact of mixed exposure to PMFrontiers in public health · 2026Article
- Distributed lag interaction model with index modification.Biostatistics (Oxford, England) · 2025Article
- Urinary and circulatory levels of plasticizer metabolites and their associations with renal function: a cross-sectional analysis of the NHANES cohort.Annals of medicine · 2025Article
- Associations between phthalate metabolites and two novel systemic inflammatory indexes: a cross-sectional analysis of NHANES data.Annals of medicine · 2025Article
94 more citing papers are in PubMed but not listed here.
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Authors and funding
3 authors.
Funding
Abstract
In evaluation of cancer risk related to environmental chemical exposures, the effect of many chemicals on disease is ultimately of interest. However, because of potentially strong correlations among chemicals that occur together, traditional regression methods suffer from collinearity effects, including regression coefficient sign reversal and variance inflation. In addition, penalized regression methods designed to remediate collinearity may have limitations in selecting the truly bad actors among many correlated components. The recently proposed method of weighted quantile sum (WQS) regression attempts to overcome these problems by estimating a body burden index, which identifies important chemicals in a mixture of correlated environmental chemicals. Our focus was on assessing through simulation studies the accuracy of WQS regression in detecting subsets of chemicals associated with health outcomes (binary and continuous) in site-specific analyses and in non-site-specific analyses. We also evaluated the performance of the penalized regression methods of lasso, adaptive lasso, and elastic net in correctly classifying chemicals as bad actors or unrelated to the outcome. We based the simulation study on data from the National Cancer Institute Surveillance Epidemiology and End Results Program (NCI-SEER) case-control study of non-Hodgkin lymphoma (NHL) to achieve realistic exposure situations. Our results showed that WQS regression had good sensitivity and specificity across a variety of conditions considered in this study. The shrinkage methods had a tendency to incorrectly identify a large number of components, especially in the case of strong association with the outcome.
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