Patient preferences for massively parallel sequencing genetic testing of colorectal cancer risk: a discrete choice experiment
Bibliographic record
Abstract
This study enumerated patients' preference-based personal utility and willingness-to-pay for massively parallel sequencing (MPS) genetic testing of colorectal cancer (CRC) risk. Our setting was the New Exome Technology in (NEXT) Medicine Study, a randomized control trial of usual care genetic testing vs. exome sequencing. Using a discrete choice experiment (DCE), we elicited patient preferences for information on genetic causes of CRC. We estimated personal utility for the following four attributes: proportion of individuals with a genetic cause of CRC who receive a diagnosis, number of tests used, wait time for results, and cost. A total of 122 patients completed our DCE (66% response rate). On average, patients preferred genetic tests identifying more individuals with a diagnosis and involving a shorter wait time. Assuming MPS identifies more individuals with a Mendelian form of CRC risk, involves fewer tests, and results in a shorter wait than traditional diagnostic testing, average willingness-to-pay (WTP) for MPS ranged from US$400 (95% CI: $300, $500) to US$1541 (95% CI: $1224, $1859). These results indicate that patients value information on genetic causes of CRC and replacing traditional diagnostic testing with MPS testing will increase patients' utility. Future research exploring the costs and benefits of MPS for CRC risk is warranted.
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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 | 0.000 | 0.000 |
| 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".