A Case Study Addressing the Reliability of Polychlorinated Biphenyl Levels Measured at the Time of Breast Cancer Diagnosis in Representing Early-Life Exposure
Bibliographic record
Abstract
BACKGROUND: To date, breast cancer epidemiologic studies have relied on blood or tissue specimens sampled at the time of diagnosis or a few years prior to assess lifetime exposure to polychlorinated biphenyls (PCB). In this study, we evaluated whether such PCB measurements are indicative of early-life levels by reconstructing lifetime toxicokinetic profiles for women included in the CECILE case-control study, using a physiologically based pharmacokinetic (PBPK) model. METHODS: We simulated lifetime toxicokinetic profiles of PCB-153 for 2,134 French women by incorporating information on body weight history, height, pregnancies, and breast-feeding in the PBPK model. Oral dose was calculated by considering measured blood PCB-153 and the temporal trend of environmental contamination. Area under the concentration versus time curve (AUC) for each decade of life and maximum blood concentration (C(max)) were compiled and compared with measured levels, using Pearson partial correlation analyses adjusting for age at diagnosis. RESULTS: When considering all individuals, simulated AUCs correlated with measured PCBs, with coefficients ranging from 0.735 to 0.981. The weakest correlations were obtained with AUCs for the first decades of life. Stratified analyses suggested that breast-feeding reduces the reliability of late-life blood levels in representing lifetime exposure. CONCLUSION: Results of this study suggest that PCB levels measured at the time of diagnosis do not fully represent early-life exposures. IMPACT: PBPK-derived estimates of early-life levels circumvent the limitations of current approaches in assessing PCB lifetime exposure and may be used to address hypothesized windows of breast vulnerability (e.g., puberty) in this population.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
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".