Timing of genetic testing in BRCA1/2 and PALB2-Associated breast cancer: Preoperative result disclosure increases uptake of risk-reducing mastectomy and reduces unnecessary exposure to radiotherapy
Bibliographic record
Abstract
INTRODUCTION: The impact of timing of genetic testing on uptake of risk reducing mastectomy (RRM) in affected female BRCA1/2 or PALB2 carriers remains an area of evolving interest, particularly with the introduction of mainstream genetic testing initiatives. METHODS: Women with stage I-III breast cancer and a confirmed germline pathogenic variant in BRCA1/2 or PALB2 between 2000 and 2023 were identified from an institutional genetics database. Uptake of RRM was evaluated according to disclosure of genetic testing results before or after index surgery for a first diagnosis of breast cancer. RESULTS: The cohort included 287 female BRCA1/2 or PALB2 carriers with a median age of 44 years (IQR, 36-52). Overall, 155 (54 %) carriers received genetic testing results before and 132 (46 %) after index breast surgery. Receipt of genetic testing results before surgery was associated with a higher rate of index bilateral mastectomy (58.7 % vs. 7.6 %, p < 0.001) and a commensurate decrease in adjuvant radiation (41.9 % vs. 74.2 %, p < 0.001). At a median follow up of 4.4 years after genetic testing, 219 (76.3 %) affected carriers had undergone bilateral RRM, including 83.9 % with preoperative knowledge and 67.4 % of patients with postoperative knowledge of their germline pathogenic variant (log rank, p < 0.001). On multivariate regression, disclosure of genetic testing results before index breast surgery was independently associated with long-term uptake of bilateral mastectomy (HR 1.69, 95 % CI 1.21-2.38). CONCLUSION: Genetic testing results delivered prior to index breast surgery increase uptake of bilateral RRM in affected BRCA1/2 and PALB2 carriers. Efforts to mainstream genetic testing would help optimize surgical decision-making.
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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 | 0.008 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".