Impact of rapid genetic counselling and testing on the decision to undergo immediate or delayed prophylactic mastectomy in newly diagnosed breast cancer patients: findings from a randomised controlled trial
Bibliographic record
Abstract
BACKGROUND: Female breast cancer patients with a BRCA1/2 mutation have an increased risk of contralateral breast cancer. We investigated the effect of rapid genetic counselling and testing (RGCT) on choice of surgery. METHODS: Newly diagnosed breast cancer patients with at least a 10% risk of a BRCA1/2 mutation were randomised to an intervention group (offer of RGCT) or a control group (usual care; ratio 2 : 1). Primary study outcomes were uptake of direct bilateral mastectomy (BLM) and delayed contralateral prophylactic mastectomy (CPM). RESULTS: Between 2008 and 2010, we recruited 265 women. On the basis of intention-to-treat analyses, no significant group differences were observed in percentage of patients opting for a direct BLM (14.6% for the RGCT group vs 9.2% for the control group; odds ratio (OR) 2.31; confidence interval (CI) 0.92-5.81; P=0.08) or for a delayed CPM (4.5% for the RGCT group vs 5.7% for the control group; OR 0.89; CI 0.27-2.90; P=0.84). Per-protocol analysis indicated that patients who received DNA test results before surgery (59 out of 178 women in the RGCT group) opted for direct BLM significantly more often than patients who received usual care (22% vs 9.2%; OR 3.09, CI 1.15-8.31, P=0.03). INTERPRETATION: Although the large majority of patients in the intervention group underwent rapid genetic counselling, only a minority received DNA test results before surgery. This may explain why offering RGCT yielded only marginally significant differences in uptake of BLM. As patients who received DNA test results before surgery were more likely to undergo BLM, we hypothesise that when DNA test results are made routinely available pre-surgery, they will have a more significant role in surgical treatment decisions.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".