Knowledge, views and expectations for cancer polygenic risk testing in clinical practice: A cross‐sectional survey of health professionals
Bibliographic record
Abstract
Polygenic risk scores (PRS) are becoming increasingly available in clinical practice to evaluate cancer risk. However, little is known about health professionals' knowledge, attitudes, and expectations of PRS. An online questionnaire was distributed by relevant health professional organisations predominately in Australia, Canada and the US to evaluate health professionals' knowledge, views and expectations of PRS. Eligible participants were health professionals who provide cancer risk assessments. Results from the questionnaire were analysed descriptively and content analysis was undertaken of free-text responses. In total, 105 health professionals completed the questionnaire (genetic counsellors 84%; oncologists 6%; clinical geneticists 4%; other 7%). Although responses differed between countries, most participants (61%) had discussed PRS with patients, 20% had ordered a test and 14% had returned test results to a patient. Confidence and knowledge around interpreting PRS were low. Although 69% reported that polygenic testing will certainly or likely influence patient care in the future, most felt unprepared for this. If scaled up to the population, 49% expect that general practitioners would have a primary role in the provision of PRS, supported by genetic health professionals. These findings will inform the development of resources to support health professionals offering polygenic testing, currently and in the future.
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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 | 0.004 | 0.020 |
| 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".