Preferences of Canadian Patients and Physicians for Adjuvant Treatments for Melanoma
Bibliographic record
Abstract
Background: Past research suggests that patients with early- and late-stage melanoma will endure adverse events and inconvenient treatment regimens for improved survival. Evidence about the preferences of Canadian patients and physicians for novel adjuvant treatments for melanoma is unavailable. Methods: Patient and physician preferences for adjuvant treatments for melanoma were assessed in an online discrete choice experiment (dce). Treatment alternatives were characterized by 8 attributes with respect to dosing regimen, efficacy, and toxicities, with levels corresponding to those for dabrafenib-trametinib, nivolumab, pembrolizumab, and interferon. For patients, the effects of melanoma on quality of life and ability to work and perform activities of daily living were also assessed. Patients were recruited by Canadian melanoma patient advocacy groups through e-mail and social media. Physicians were recruited by e-mail. Results: Of 94 patients who started the survey, 51 completed 1 or more dce questions. Of 166 physicians sent the e-mail invitation, 18 completed 1 or more dce questions. For patients, an increased probability of remaining cancer-free over 21 months was the most important attribute. For physicians, an increased chance of the patient's remaining alive over 36 months was the most important attribute. Patients and physicians chose active treatment over no treatment 85% and 86% of the time respectively and a treatment with attributes consistent with dabrafenib-trametinib 71% and 67% of the time respectively. A substantial proportion of patients reported worrying about future diagnostic tests and their cancer coming back. Conclusions: Canadian patients and physicians are generally concordant in their preferences for adjuvant melanoma treatments, preferring active treatment to no treatment and dabrafenib-trametinib to other options.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".