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Record W4409626849 · doi:10.1158/1538-7445.am2025-4945

Abstract 4945: Exposure to per and poly fluoroalkyl substances and cancer risk: A systematic review and meta-analysis

2025· review· en· W4409626849 on OpenAlexaboutno aff
Monireh Sadat Seyyedsalehi, Paolo Boffetta

Bibliographic record

VenueCancer Research · 2025
Typereview
Languageen
FieldMedicine
TopicCardiovascular and Diving-Related Complications
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisCancerMedicineOncologyInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Abstract Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals that humans can encounter through occupational or environmental exposure. Recent evidence suggests that exposure to PFAS may increase the risk of different types of cancer. In our comprehensive review and meta-analysis, we investigated the association between PFAS exposure and the risks of breast, female genital, bladder, kidney, prostate, testis, liver, esophageal, gastric, colorectal, pancreatic, head and neck, lung, thyroid, and lymphatic cancers. We systematically reviewed literature from IARC Monographs, ATSDR Reports, PubMed, and Scopus (up to January 2024) for cohort, case-control, and ecological studies. Four reviewers independently screened studies, and data extraction included study design, patient characteristics, and effect size measures. The quality of studies was assessed using the modified version of the Newcastle-Ottawa Scale (NOS). We constructed forest plots and random-effects meta-analyses of relative risks (RR) for PFAS-cancer associations with at least 3 independent risk estimates and conducted stratified, dose-response, and publication bias analyses. A total of 41 articles reported results on PFAS exposure and cancer. The pooled RR for the associations between exposure to different types of PFAS and cancer incidence and mortality are reported in Table 1 Table 1: The combined relative risk (RR) of occupational and environmental PFAS exposure and various types of cancer. Cancer type PFAS type RR (95%CI), I2, p value Number of risk estimates Publication bias Breast PFOA 1.08(0.97-1.20), I2=85.2%, p<0.001 21 0.30 PFOS 1.00(0.85-1.18), I2=0.81.5%, p<0.001 12 PFNA 0.95(0.81-1.12), I2=83%, p<0.001 10 PFDA 1.29(0.73- 2.25), I2=91.3%, p<0.001 6 Cervix PFAS overall 0.94(0.79-1.12), I2=0.0%, p=86 3 0.55 PFOA 1.00(0.90-1.11), I2=0.0%, p=0.58 4 Ovary PFAS overall 1.07(1.04-1.09), I2=99.3%, p<0.001 12 PFOA 1.05(0.89-1.24), I2=22.6%, p=0.27 4 Kidney PFAS overall 1.18(1.05-1.32), I2=52.6%, p=0.02 11 0.31 Bladder PFOA 0.93(0.86- 1.01), I2=1%, p=0.43 11 0.79 PFOS 0.94(0.78- 1.13), I2=45.1%, p=0.14 4 Prostate PFOA 0.95(0.91-1.00), I2=34%, p=0.08 17 0.71 PFOS 1.04(0.98-1.11), I2=34.4%, p=0.14 9 PFNA 0.96(0.83-1.12), I2=92.7%, p<0.001 6 Testis PFAS overall 1.12(0.94-1.34), I2=0.0%, p=0.52 8 0.53 Colorectal PFOA 0.83(0.65-1.06), I2=81.6%, p<0.001 6 0.37 PFOS 0.71(0.22-2.27), I2=81.5%, p<0.001 4 Liver PFAS overall 1.03(0.91-1.16), I2=47.9%, p=0.02 16 0.51 Pancreas PFOA 1.01(0.89-1.15), I2=0.0%, p=0.79 9 0.44 Lung PFAS overall 1.20 (1.12-1.28), I2=0.0%, p=0.95 9 0.57 Head and neck PFAS overall 1.15 (0.96-1.37), I2=0.0%, p=0.72 3 0.79 Thyroid PFAS overall 1.54 (0.86-2.78), I2=69.0%, p=0.02 4 0.08 Hodgkin lymphoma PFAS overall 1.23(0.90-1.70), I2=0.0%, p=0.38 3 0.47 Non-Hodgkin lymphoma PFAS overall 1.01(0.90-1.13), I2=31.8%, p=0.19 6 0.64 . Our findings suggest that overall PFAS exposure may be associated with kidney, ovary, and lung cancer and high doses of PFAS with testicular cancer. Further prospective studies with an appropriate assessment of co-exposure with other carcinogens and detailed exposure assessment among study participants are needed to establish causality of observed associations. Citation Format: Monireh Sadat Seyyedsalehi, Paolo Boffetta. Exposure to per and poly fluoroalkyl substances and cancer risk: A systematic review and meta-analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4945.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.717
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0070.002
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.165
GPT teacher head0.469
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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