Inherited NBN Mutations and Prostate Cancer Risk and Survival
Bibliographic record
Abstract
PURPOSE: To establish the contribution of four founder alleles of NBN to prostate cancer risk and cancer survival. MATERIALS AND METHODS: Five thousand one hundred eighty-nine men with prostate cancer and 6,152 controls were genotyped for four recurrent variants of NBN (657del5, R215W, I171V, and E185Q). RESULTS: The NBN 657del5 mutation was detected in 74 of 5,189 unselected cases and in 35 of 6,152 controls (odds ratio [OR], 2.5; p < 0.001). In carriers of 657del5 deletion, the cancer risk was restricted to men with the GG genotype of the E185Q variant of the same gene. Among men with the GG genotype, the OR associated with 657del5 was 4.4 (95% confidence interval [CI], 2.4 to 8.0). Among men with other E185Q genotypes, the OR associated with 657del5 was 1.4 (95% CI, 0.8 to 2.4) and the interaction was significant (homogeneity p=0.006). After a median follow-up of 109 months, mortality was worse for 657del5 mutation carriers than for non-carriers (hazard ratio [HR], 1.6; p=0.001). The adverse effect of 657del5 on survival was only seen on the background of the GG genotype of E185Q (HR, 1.9; p=0.0004). CONCLUSION: The NBN 657del5 mutation predisposes to poor prognosis prostate cancer. The pathogenicity of this mutation, with regards to both prostate cancer risk and survival, is modified by a missense variant of the same gene (E185Q).
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".