ReviewCurrent environmental health reports2025
Comparison of Methods for Analyzing Environmental Mixtures Effects on Survival Outcomes.
Review in Current environmental health reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- A Practical Framework for Incorporating Complex Survey Design in Bayesian Kernel Machine Regression.Stats · 2026Article
- Urinary Metal Levels, Cognitive Test Performance, and Dementia in the Multi-Ethnic Study of Atherosclerosis.JAMA network open · 2024Article
- Association of Urinary Metals With Cardiovascular Disease Incidence and All-Cause Mortality in the Multi-Ethnic Study of Atherosclerosis (MESA).Circulation · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
purpose of reviewEstimating 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
findingsWe 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.