<i>CHEK</i><i>2</i>mutations and the risk of papillary thyroid cancer
Bibliographic record
Abstract
Mutations in the cell cycle checkpoint kinase 2 (CHEK2) tumor suppressor gene are associated with multi-organ cancer susceptibility including cancers of the breast and prostate. A genetic association between thyroid and breast cancer has been suggested, however little is known about the determinants of this association. To characterize the association of CHEK2 mutations with thyroid cancer, we genotyped 468 unselected patients with papillary thyroid cancer and 468 (matched) cancer-free controls for four founder mutations of CHEK2 (1100delC, IVS2 + 1G>A, del5395 and I157T). We compared the family histories reported by patients with a CHEK2 mutation to those of non-carriers. A CHEK2 mutation was seen in 73 of 468 (15.6%) unselected patients with papillary thyroid cancer, compared to 28 of 460 (6.0%) age- and sex-matched controls (OR 3.3; p < 0.0001). A truncating mutation (IVS2 + 1G>A, 1100delC or del5395) was associated with a higher risk of thyroid cancer (OR = 5.7; p = 0.006), than was the missense mutation I157T (OR = 2.8; p = 0.0001). CHEK2 mutation carriers reported a family history of breast cancer 2.2 times more commonly than non-carriers (16.4% vs.8.1%; p = 0.05). A CHEK2 mutation was found in seven of 11 women (63%) with multiple primary cancers of the breast and thyroid (OR = 10; p = 0.0004). These results suggest that CHEK2 mutations predispose to thyroid cancer, familial aggregations of breast and thyroid cancer and to double primary cancers of the breast and thyroid.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".