Bibliographic record
Abstract
Epidemiological investigation into a potential relation between a history of allergic disorders, typically characterized by high levels of IgE, and cancer occurrence has been conducted for at least the past five decades. Recently, there is renewed interest in the field, and the literature is expanding rapidly. This chapter summarizes the epidemiological literature examining the potential relation between allergy and cancer, with a particular focus on the most recent contributions to the field. Although the majority of new and previously published studies evaluated self-reported history of specific allergic disorders (asthma, hay fever, eczema), there were also several new studies examining total or allergen-specific IgE antibodies, hospital discharges for allergic conditions, skin prick tested patients, and allergy-related gene polymorphisms in relation to cancer risk. Although there are a number of inverse relations reported, particularly with pancreatic cancer and glioma, there remain a number of methodological considerations. Further research is recommended in order to better understand the nature of a possible inverse relation and possible mechanisms of action with implications for cancer treatment and prevention. Multidisciplinary collaborations between the population and laboratory-based sciences would be particularly useful.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 teacher head, 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".