A Comprehensive Study of the Effect on Colorectal Cancer Survival of Common Germline Genetic Variation Previously Linked with Cancer Prognosis
Bibliographic record
Abstract
BACKGROUND: Germline genetic variants may influence pathways of tumor progression common to multiple cancer types. Here, we investigated the association between survival after colorectal cancer diagnosis and 128 common genetic variants previously associated with prognosis in genome-wide association studies in different cancer types. METHODS: We studied survival outcomes in a large well-documented, prospective, population-based cohort (5,675 patients with colorectal cancer) with up to 20 years' follow-up. RESULTS: < 0.05) for eight variants (rs17026425, rs17057166, rs6854845, rs1728400, rs17693104, rs202280, rs6797464, and rs823920) in all colorectal cancer and two variants (rs17026425 and rs6854845) in rectal cancer that were concordant with previous reports. CONCLUSIONS: Given good statistical power (>0.80 for 75% of variants), this study indicates that most previously reported variants associated with cancer survival have limited influence on colorectal cancer prognosis. IMPACT: Although small effects cannot be excluded, clinically meaningful germline influences on patients with colorectal cancer as a group are unlikely.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".