Systematic Review and Meta-Analysis on Endocrine Disruptors and Endometrial Cancer Risk
by Lutian Gong·Updated 8d ago
27.5 KB1files
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Description
A systematic review and meta-analysis by Lutian Gong, published on figshare in 2026, evaluates the relationship between environmental endocrine-disrupting chemicals and endometrial cancer risk. It includes 14 studies published up to November 30, 2025, with quantitative meta-analyses for cadmium and polychlorinated biphenyls (PCBs). The work also provides a narrative review of evidence on PFAS, phthalates, and bisphenols.
Use Cases
Assess the association between cadmium exposure and endometrial cancer risk based on the reported meta-analysis results.
Evaluate the evidence for polychlorinated biphenyls (PCBs) as a risk factor for endometrial cancer based on the reported meta-analysis.
Review the current state of evidence on emerging endocrine disruptors like PFAS, phthalates, and bisphenols in relation to endometrial cancer.
Identify gaps in the literature on environmental chemicals and cancer to inform future study designs.
Strengths
Includes a meta-analysis of 14 studies with specific risk ratios and confidence intervals reported.
Provides subgroup analyses for factors like menopausal status and hormone therapy.
Uses a structured narrative review to summarize evidence on PFAS, phthalates, and bisphenols.
Limitations
The dataset is a 27.5 KB DOC file, indicating it is likely a summary document rather than raw data.
Row count and column-level documentation are absent; data structure must be inferred from the text.
Quantitative synthesis was not feasible for PFAS, phthalates, or bisphenols due to a limited number of studies.
Provenance
Source
figshare
Collection Method
Systematic review and meta-analysis of studies from PubMed, Web of Science, EMBASE, and Cochrane Library.
Time Range
Studies published up to November 30, 2025.
Freshness
Last updated 2026-05-28 04:51:55; includes studies up to November 30, 2025.
File format is DOC; data extraction from the document text may be required for computational analysis.