Parental smoking and alcohol consumption and risk of neuroblastoma.
Bibliographic record
Abstract
Previous studies and animal evidence have suggested a relationship between parental tobacco or alcohol use and the risk of some childhood cancers, including neuroblastoma. A case-control study was conducted to investigate the relationship between parental tobacco smoking, alcohol consumption, and risk of neuroblastoma. Cases were children diagnosed with neuroblastoma over the period 1992-1994 at Children's Cancer Group and Pediatric Oncology Group institutions throughout the United States and Canada. One matched control was selected using random-digit dialing. Information on parental smoking and drinking history was obtained from 504 case and 504 control parents by telephone interview. Overall, there was no consistent pattern of association with parental smoking and alcohol consumption. For example, both maternal smoking and drinking during the period from 1 month before pregnancy through breastfeeding had adjusted odds ratios (ORs) of 1.1 [95% confidence interval (CI), 0.8-1.4]. There was no association with paternal smoking (OR, 1.2; 95% CI, 0.8-1.6) or paternal drinking 1 month before conception (OR, 1.0; 95% CI, 0.7-1.4). There was no consistent increase in risk by the amount of smoking or drinking during any time period relative to pregnancy. There was no suggestion of an increased risk when only one parent smoked. Smoking or drinking among both parents did not jointly increase the risk of neuroblastoma in their offspring. The child's age at diagnosis, stage, or MYCN oncogene amplification status did not materially alter the OR estimates. It is concluded that the results from this study do not indicate any evidence for a relationship between neuroblastoma and parental tobacco or alcohol use.
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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) | 0.000 | 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".