Predictors of long-term cancer-related distress among female BRCA1 and BRCA2 mutation carriers without a cancer diagnosis: an international analysis
Bibliographic record
Abstract
BACKGROUND: Women with a BRCA1 or BRCA2 mutation have high lifetime risks of developing breast and ovarian cancers. We sought to estimate the prevalence of cancer-related distress and to identify predictors of distress in an international sample of unaffected women with a BRCA mutation. METHODS: Women with a BRCA1/2 mutation and no previous cancer diagnosis were recruited from the United States, Canada, the United Kingdom, Australia and from a national advocacy group. Using an online survey, we asked about cancer risk reduction options and screening, and we measured cancer-related distress using the Impact of Event Scale. RESULTS: Among 576 respondents, mean age was 40.8 years (SD = 8.1). On average 4.9 years after a positive test result, 16.3% of women reported moderate-to-severe cancer-related distress. Women who had undergone risk-reducing breast and ovarian surgery were less likely to have (moderate or severe) cancer-related distress compared to other women (22.0% versus 11.4%, P value = 0.007). Women recruited from the advocacy group were more likely to have cancer-related distress than other women (21.6% versus 5.3%, P value = 0.002). CONCLUSIONS: Approximately 16% of women with a BRCA1 or BRCA2 mutation experience distress levels comparable to those of women after a cancer diagnosis. Distress was lower for women who had risk-reducing surgery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".