An international survey of predictive genetic testing in young people for adult onset conditions
Bibliographic record
Abstract
Purpose: Predictive genetic testing is offered to asymptomatic adults even when there is no effective prophylaxis or treatment. Testing of young people in similar circumstances is controversial, and guidelines recommend against it. We sought to document descriptive examples of the occurrence of genetic testing in young people for nonmedical reasons, in the countries where guidelines exist. Methods: Clinical geneticists in the USA, Canada, UK, Australia, and New Zealand were surveyed about the occurrence and outcomes of testing in asymptomatic young people for conditions where no prophylaxis or treatment exists and onset is usually in adulthood. Results: Of 301 responses, details were provided of 49 cases where such testing had occurred. The most common condition tested for was Huntington Disease. In 22 cases (45%), the young person tested was immature, defined as under the age of 14 years. Results were disclosed to only two immature minors and in three cases parents experienced clinically significant anxiety related to how they would pass on information to their gene positive child. In 27 cases (55%), the young person tested was mature. Results were disclosed to 26 mature minors and it was reported that two individuals experienced an adverse event. Consistent follow-up did not take place and findings represent the minimum frequency of adverse events. The majority of respondents agree with existing guidelines but many believe each case must be considered individually. Conclusion: Clinicians agree with existing guidelines regarding predictive testing in young people, but choose to provide tests for nonmedical reasons in specific cases.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".