Commentary: Why is genetic testing underutilized worldwide? The case for hereditary breast cancer
Bibliographic record
Abstract
It is thirty years since the BRCA1 and BRCA2 genes were discovered and genetic testing for BRCA1 and BRCA2 was introduced. Despite increasing awareness of the genetic basis of cancer and our evolving knowledge of effective means of prevention, screening, and treatment for hereditary breast and ovarian cancers, genetic testing is underutilized, and most mutation carriers remain unidentified. In this commentary, we explore possible reasons for why this might be so. Our focus is on factors that may influence or deter a patient from pursuing testing, rather than discussing the implications of receiving a positive test result. Issues of concern include an inadequate number of genetic counselors, restrictive (and conflicting) eligibility criteria for testing, the cost of the test, health insurance coverage, fear of future insurance discrimination, privacy issues, lack of familiarity with the testing process in primary care and gaps in both patient and provider knowledge about the impact and the value of testing. We discuss how these factors may lead to the underutilization of genetic testing in North America and throughout the world and discuss alternative models of genetic healthcare delivery. We have invited leaders in cancer genetic from around the world to tell us what they think are the barriers to testing in their host countries.
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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) | 0.001 | 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".