Year: 2025
Type: article
Abstract: PURPOSE OF REVIEW: Estimating the effect of environmental mixtures on survival outcomes is common in epidemiological studies, yet the applicability and performance of advanced mixture modeling methods in this context remains underexplored. In this review, we identify available methods for this context and evaluate their performance via simulations. RECENT FINDINGS: We compared five methods - Cox Proportional Hazards (with/without penalized splines), Cox Elastic Net, Bayesian Additive Regression Trees (BART), and Multivariate Adaptive Regression Splines (MARS). Simulations showed log-linear models achieved low coverage when estimating individual exposure and mixture effects, especially under high exposure correlations and proportional hazards violations. More flexible models exhibited higher variability but improved coverage in effect estimation. While flexible models were better able to estimate mixture effect on survival outcomes compared to more constrained models for most simulation scenarios, they still introduced bias and often had high variability. Given real-world constraints like limited sample sizes and high censoring, there likely remains significant complexities for the application of flexible modeling for environmental mixtures for the survival analysis contexts. We recommend evaluating if findings are consistent across methods.
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,990
Funders: Strong, National Institutes of Health, National Institute on Aging, National Heart, Lung, and Blood Institute, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Environmental Health Sciences, National Center for Advancing Translational Sciences, National Center for Complementary and Integrative Health
Awards: Cardiovascular Disease in Sioux Indians, The Strong Heart Study, Phase V, CVD in American Indians Biomarker lab and Arizona Field Center, G2611541099, Strong Heart Family Study, Cardiovascular Evaluation for the SHS Phase V, Arsenic Exposure, Cardiovascular Disease and Diabetes in Native Americans, CVD in American Indians Genetics Center, CVD in American Indians Study and Data Management Center and OK Field Center, Harvard Chan School NIEHS Center for Environmental Health, Metals in the Trial to Assess Chelation Therapy 2 (TACT2M), CVD in American Indians: Imaging and Cardiovascular Center, Metals and Metal Mixtures: Cognitive Aging, Remediation and Exposure Sources (MEMCARE), CVD in American Indians The Dakota Field Center, G8388944883, Arsenic, Epigenetics and Incident Cardiovascular Disease in American Indians, G867024095, Arsenic Exposure, Genetic Determinants and Diabetes Risk in a Family Study, G8765877990, G8800399531, Cardiovascular Disease in Pima Indians, Clinical and Translational Science Award, The Epitranscriptome as a Novel Mechanism of Arsenic-Induced Diabetes., India - Factors of CKDu in Uddanam Study (India-FOCUS), Metal Exposure and Subclinical Lung Disease in Adult E-cigarette Users, NRSA Training Core, Bayesian Statistical Learning for Robust and Generalizable Causal Inferences in Alzheimer Disease and Related Disorders Research, Columbia University and Northern Plains Partnership for the Superfund Research Program, Center for Environmental Health in Northern Manhattan
OpenAlex ID: W4388444953