An overview of the association between allergy and cancer
Bibliographic record
Abstract
Numerous epidemiological studies have evaluated some aspect of the association between a history of allergy and cancer occurrence. In this article, an overview of the epidemiological evidence is presented with a discussion of a number of methodological issues important in this area of study. Literature searches were conducted using the MEDLINE database from 1966 through to August 2005 to identify articles that explored a personal history of allergic disorders as a risk factor for cancer. Although it is difficult to draw conclusions between allergy and cancer at many sites because of insufficient evidence or a lack of consistency both within and among studies completed to date, strong inverse associations have been reported for pancreatic cancer and glioma, whereas lung cancer was positively associated with asthma. Additional studies are needed to confirm these finding and to address the limitations of previous studies, including the validity and reliability of exposure measures and control for confounding. Further, large prospective studies using cancer incidence would be particularly useful, including studies using biological markers of allergic status to reduce potential misclassification and to confirm the results of previous studies based on self-report. There is also a need for further basic research to clarify a potential mechanism, should an association exist.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".