Evaluating the return of additional findings from the 100,000 Genomes Project: A mixed-methods study exploring participant experiences of receiving secondary findings from genomic sequencing
Bibliographic record
Abstract
PURPOSE: The 100,000 Genomes Project participants could consent to receive additional findings (AFs) for variants associated with susceptibility to cancer and familial hypercholesterolemia. Here, we evaluate stakeholder experiences to inform clinical practice. METHODS: Mixed-methods study conducted at 18 sites across England that comprised a cross-sectional survey and interviews with participants who received a positive AF (PAF) and interviews with participants who had no AFs (NAF). RESULTS: There were 146 surveys followed by 35 interviews with PAF participants and 29 interviews with NAF participants. Surveys found that PAF results were seen as useful and would influence health management (82%). Most (90%) had shared their result with family members. Experiences differed by PAF type; cancer PAF participants were often initially shocked and anxious and found telling family members challenging compared with participants with a familial hypercholesterolemia PAF. Although most experiences of NAF results were positive, some misunderstandings were identified. Participants supported returning AFs when offering genome sequencing. CONCLUSION: Patient experiences of receiving AFs were primarily positive, and there is support for offering AFs routinely. Considerations for offering AFs in clinical practice include adapting approaches tailored to individual conditions and greater support for people with a NAF result.
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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 | 0.046 | 0.092 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".