Childhood, adolescent, and young adulthood cancer risk in <i>BRCA1</i> or <i>BRCA2</i> pathogenic variant carriers
Bibliographic record
Abstract
BACKGROUND: Whether carriers of BRCA1 or BRCA2 pathogenic variants have increased risks of childhood, adolescent, and young adult cancers is controversial. We aimed to evaluate this risk and to inform clinical care of young BRCA1 and BRCA2 pathogenic variant carriers and genetic testing for childhood, adolescent, and young adult cancer patients. METHODS: Using data from 47 117 individuals from 3086 BRCA1 or BRCA2 families, we conducted pedigree analysis to estimate relative risks (RRs) for cancers diagnosed before age 30 years. RESULTS: Our data included 274 cancers diagnosed before age 30 years: 139 breast cancers, 10 ovarian cancers, and 125 nonbreast nonovarian cancers. Associations for breast cancer in young adulthood (aged 20-29 years) were found with relative risks of 11.4 (95% confidence interval [CI] = 5.5 to 23.7) and 5.2 (95% CI = 1.6 to 17.7) for BRCA1 and BRCA2 pathogenic variant carriers, respectively. No association was found for any other investigated childhood, adolescent, and young adult cancer or for all nonbreast nonovarian cancers combined; the relative risks were 0.4 (95% CI = 0.1 to 1.4) and 1.4 (95% CI = 0.7 to 3.0) in BRCA1 and BRCA2 pathogenic variant carriers, respectively. CONCLUSION: We found no evidence that BRCA1 and BRCA2 pathogenic variant carriers have an increased childhood, adolescent, and young adult cancer risk aside from breast cancer in women aged between 20 and 30 years. Our results, along with a critical evaluation of previous germline sequencing studies, suggest that the childhood and adolescent cancer risk conferred by BRCA1 and BRCA2 pathogenic variant would be low (ie, RR < 2) if it existed. Our findings do not support pathogenic variant testing for offspring of BRCA1 and BRCA2 pathogenic variant carriers at ages younger than 18 years or for conducting BRCA1 and BRCA2 pathogenic variant testing for childhood and adolescent cancer patients.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".