Genomic sequencing in paediatric oncology: navigating conflicting roles and responsibilities
Bibliographic record
Abstract
BACKGROUND: This study explores the ethical and moral challenges faced by paediatric oncologists when they are informed of patient genomic results, particularly during molecular tumour boards (MTBs), highlighting the interplay between their clinic, research and expert roles. METHODS: This was an explanatory sequential mixed-methods study using a survey distributed to paediatric oncologists in Quebec followed by optional semi-structured interviews. Oncologists' attitudes and comfort levels with six hypothetical germline DNA results identified in a patient from a clinical vignette were assessed using Likert scales. Hypothetical genetic results represented ethical challenges of extended paediatric genomic sequencing. Interviews were conducted with a subgroup of participants to gain insight and context on key survey results. RESULTS: Eighty per cent (n=28) of oncologists in Quebec completed the survey; five participated in the interviews. Comfort levels of oncologists were influenced by the type of genetic result (expected, secondary, incidental finding), whether or not the oncologist was the patient's treating physician, and whether the information disclosed to the patient aligned with the information that they had received. Awareness of a genetic result was sufficient to trigger a feeling of responsibility and liability for that result. CONCLUSION: Oncologists who take part in genomic sequencing initiatives and who attend MTBs have privileged access to genomic results, above what may be accessible to patients. This imbalance in knowledge contributes to moral discomfort experienced by oncologists who feel responsible for genomic information they are aware of. We propose recommendations applicable to consent processes, policies and pipelines for sharing genomic results.
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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 | 0.045 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".