The Impact of Angelina Jolie (AJ)'s Story on Genetic Referral and Testing at an Academic Cancer Centre in Canada
Bibliographic record
Abstract
In May 2013, Angelina Jolie revealed to the media that she had undergone preventive double mastectomy after testing positive for a BRCA1 gene mutation. Media coverage has been extensive, but it is not clear how such a personal story affected the public and cancer genetics clinics. We conducted a retrospective review using data from the clinical database of the Familial Cancer Program at our centre. The impact of Ms. Jolie's story on genetic counseling referrals and the appropriateness of such referrals were assessed and reported. The number of women referred for genetic counseling increased by 90 % after 6 months and remained high one year after AJ's story with an increase of 88 % from baseline. The number of women who qualified for genetic testing increased by 105 % after 6 months; this increase persisted but was somewhat lower after one year with an increase of 68 % from baseline. Furthermore the number of BRCA1/2 carriers identified increased by 110 % after 6 months and by 42 % after one year.The effect of Mrs. Jolie's story persisted one year after its release; however in the latter half of the year, the hereditary cancer risk of referred women was significantly lower than initially observed. The next challenge for our health care system will not only be to meet the increased demand for cancer genetic services in our region, but also to ensure that referrals and hence use of genetic counseling resources are appropriate.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".