Dichlorodiphenyltrichloroethane and risk of hepatocellular carcinoma
Bibliographic record
Abstract
Dichlorodiphenyltrichloroethane (p,p'-DDT), an organochlorine pesticide known to have deleterious health effects in humans, has been linked to hepatocellular carcinoma (HCC) in rodents. A recent study has reported that p,p'-DDT and its most persistent metabolite, dichlorodiphenyldichloroethylene (p,p'-DDE), may also be associated with HCC in humans. To examine whether there is an association between p,p'-DDT and/or p,p'-DDE in a population at high-risk of developing HCC, a nested case-control study was conducted within the 83,794 person Haimen City Cohort in China. Sera and questionnaire data were collected from all participants between 1992 and 1993. This study included 473 persons who developed HCC and 492 who did not, frequency matched on sex, age and area of residence. p,p'-DDT and p,p'-DDE levels were determined by mass spectrometry. Hepatitis B viral infection status (based on hepatitis B virus surface antigen; HBsAg) was also determined. p,p'-DDT and/or p,p'-DDE serum levels were significantly associated with sex, area of residence, occupation, alcohol consumption and cigarette smoking. Adjusting for age, sex, area of residence, HBsAg, family history of HCC, history of acute hepatitis, smoking, alcohol, occupation (farmer vs. other) and levels of p,p'-DDT or p,p'-DDE, odds ratios (OR) and 95% confidence intervals (CI) were calculated via unconditional logistic regression. Overall, the highest quintile of p,p'-DDT was associated with an increased risk of HCC, OR = 2.96 95% CI; 1.19-7.40. There were no statistically significant associations with p,p'-DDE. Overall, these results suggest that recent exposure to p,p'-DDT may increase risk of HCC.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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, 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".