Accrual Strategies for Cancer Genetics Research: Blurred Boundaries
Bibliographic record
Abstract
and BRCA2 founder mutations in an unselected group of Ashkenazi Jewish women, with an astounding 2,000 women enrolled within 14 days of an article appearing in one of Canada’s most respected newspapers. Given the overwhelming interest among the target population, one might ask exactly what information prompted such an overwhelming response. The article in question was published on the front page of the Toronto Globe and Mail (Saturday May 24, 2008) with a large-font headline reading: “Cancer test a genetic crystal ball for Jewish women.” 2 The first line in the piece stated: “For the first time in Canada, Jewish women will be offered the chance to alter their genetic destiny by taking a test…” a patently untrue and sensationalistic statement, given that presymptomatic BRCA1 and BRCA2 mutation testing, including Ashkenazi Jewish founder mutations, have been available for many years through medical genetics services nationwide. The concept of altering genetic destiny remains a potentially very desirable goal for those at real or perceived risk but is highly problematic in the clinical setting as any involved with the provision of genetic and oncologic care can easily attest. The goal of the test was “to prevent cancer” as elucidated by one of the investigators in the article. Two rabbis were quoted, the first commenting that “The rate of the gene is so high, it will be one of the tests that is normally done,” equatingBRCA1 and-2 testing to screening for Tay-Sachs, a culturally specific heritable disease. The other stated that genetic testing was a no-brainer imputing Halacha (Jewish law) that “insists that one is obligated to take care of oneself” as rationale for testing. Risks of taking the test are described as “primarily psychological, such as depression and stress, or unpredicted implications for obtaining life or critical care insurance.” Although the authors note a number of limitations to their work, the ethical implications are not mentioned. How sensationalistic is a headline allowed to be in order to generate accrual to a research study? How appropriate is it to imbibe the research with culturally and religiously significant implications directly aimed at the ethnic group under investigation? How justified is it to minimize the potential emotional angst and psychological turmoil that genetic testing can engender for subjects and their families? What degree of overstatement can be accepted when describing bothBRCA mutation incidence as well as the evidence of benefit from testing, when approaching a susceptible population for research purposes? With the goal of the research summarized as “to prevent cancer,” along with supporting patient vignettes, religious calls to action, and minimization of the clinical, psychological and emotional dilemmas faced by all those undergoing genetic testing, who could resist making the call to enroll in the study? Although the potential benefits of presymptomatic BRCA1 and -2 mutation detection can be significant, the clinical, ethical, and emotional dilemmas surrounding genetic testing for hereditary cancer syndromes can be even more so. The recent American Society of Clinical Oncology policy statement update regarding genetic and genomic testing for cancer susceptibility 3 elucidates evolving concerns regarding direct-to-consumer genetic testing, which have relevance for both industry and academia.
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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 | 0.351 | 0.387 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.008 | 0.033 |
| Scholarly communication | 0.018 | 0.034 |
| Open science | 0.007 | 0.038 |
| Research integrity | 0.013 | 0.012 |
| Insufficient payload (model declined to judge) | 0.025 | 0.005 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".