Does salmon calcitonin cause cancer? A review and meta-analysis
Bibliographic record
Abstract
Recently an association between the use of calcitonin and cancer has been postulated. We reviewed the biological rationale and performed an additional analysis of historical data with respect to the possibility. An association cannot be excluded, but the relationship is weak and causality is unlikely. The purpose of the present study is to review the strength of association and likelihood of a causal relationship between use of calcitonin and cancer. We reviewed the evidence for this association, including the molecular signaling mechanisms of calcitonin, preclinical data, an "experiment of nature," and the results of a previous meta-analysis which showed a weak association. We performed an additional meta-analysis to incorporate the data from a novel investigational oral formulation of salmon calcitonin. Review of the literature did not identify a cellular signaling mechanism of action which might account for a causal relationship or toxicologic or postmarketing data to support the thesis. Additional clinical results incorporated into previous meta-analyses weakened but did not completely negate the possibility of association. A causal association between calcitonin use and malignancy is unlikely, as there is little biological plausibility. The preponderance of nonclinical and clinical evidence also does not favor a causal relationship.
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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.017 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".