Parent and Patient Proxies’ Preferences on Whole-body MRI Techniques for Cancer Predisposition Syndromes’ Surveillance
Bibliographic record
Abstract
PURPOSE: Given trade-offs between whole-body MRI(WBMRI) techniques' attributes for cancer predisposition syndromes (CPS) surveillance, we determined the strength of preferences of adolescents with no cancer history (group 1) and their parents (group 2) (proxies) for different WBMRI surveillance approaches in CPS. METHODS: A proxy cohort of adolescents without cancer history (group 1) and their parents (group 2) completed a discrete choice experiment (DCE) survey on hypothetical situations of cancer surveillance imaging as if they or their children had a CPS. Five attributes (diagnostic accuracy; examination length; radiation exposure; intravenous access discomfort; and contrast extravasation risk) and 3 WBMRI techniques (inversion recovery [IR]; diffusion-weighted [DW]+IR; positron-emission tomography [PET]-MRI) were assessed in association with respondents' age, sex, education level, and prior MRI history. RESULTS: There were 86 of 342 (25.1%) participants; N=71 (83%) females; 21 (24%) adolescents 12 years or older and 18 years or younger, and 65 (76%) parents. Diagnostic accuracy was ranked highest for importance for groups 1 (47.6%) and 2 (55.3%). Group 1 ranked examination length and risk of radiation exposure as second (23.8%) and third (19.0%) preferred attributes, respectively; group 2 ranked these attributes reversely (15.3% and 18.4%). Group 1 ranked intravenous access discomfort and radionuclide extravasation risk as the fourth preferred attribute, 4.8% each, while they were ranked fourth (7.7%) and fifth (3.7%) for group 2. No agreement was reached for aggregated responses (kappa coefficient=0 or McNemar test P >0.05), or any predictors(multinomial logistic regression) between groups 1 and 2. CONCLUSION: Although both adolescents and parents agreed on diagnostic accuracy as the most important attribute in CPS imaging surveillance, other preferences were discordant, opening up discussions about whom the clinical decision-making process should align with.
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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 | 0.004 | 0.012 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".