Plasma levels of polychlorinated biphenyls and risk of cutaneous malignant melanoma: a preliminary study
Bibliographic record
Abstract
A number of epidemiologic studies have suggested that exposure to polychlorinated biphenyls (PCB) and other organochlorine compounds (OCC) increase risk of cutaneous malignant melanoma (CMM). However, these studies have generally had no biologic measure of OCC exposure, and have been unable to control for sun exposure, the major known environmental risk factor for this disease. This preliminary study examined the relationship between OCC residues in plasma and risk of CMM adjusting for sun sensitivity and sun exposure. A case-control study of 80 CMM patients and 310 control subjects was conducted. Lifetime sun exposure information, along with data on pigmentation variables and sun sensitivity data was collected, along with a blood sample. Cases and controls were assayed for plasma levels of 14 PCB congeners and 11 organochlorine pesticide residues using gas chromatography. Strong associations were seen between risk of CMM and plasma levels of non-dioxin-like PCBs (Adjusted OR = 7.02; 95% CI: 2.30-21.43 for highest quartile) and several PCB congeners, organochlorine pesticides or metabolites. These associations persisted after control for sun sensitivity and sun exposure. Results from this investigation require independent confirmation in larger studies. However, they suggest that environmental factors other than UV radiation may play a role in genesis of CMM, and indicate that it may be productive to search for further agents which might increase risk.
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How this classification was reachedexpand
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".