Canadian Melanoma Conference Recommendations on High-Risk Melanoma Surveillance: A Report from the 14th Annual Canadian Melanoma Conference; Banff, Alberta; 20–22 February 2020
Bibliographic record
Abstract
Introduction: There are a lack of established guidelines for the surveillance of high-risk cutaneous melanoma patients following initial therapy. We describe a novel approach to the development of a national expert recommendation statement on high-risk melanoma surveillance (HRS). Methods: A consensus-based, live, online voting process was undertaken at the 13th and 14th annual Canadian Melanoma Conferences (CMC) to collect expert opinions relating to “who, what, where, and when” HRS should be conducted. Initial opinions were gathered via audience participation software and used as the basis for a second iterative questionnaire distributed online to attendees from the 13th CMC and to identified melanoma specialists from across Canada. A third questionnaire was disseminated in a similar fashion to conduct a final vote on HRS that could be implemented. Results: The majority of respondents from the first two iterative surveys agreed on stages IIB to IV as high risk. Surveillance should be conducted by an appropriate specialist, irrespective of association to a cancer centre. Frequency and modality of surveillance favoured biannual visits and Positron Emission Tomography Computed Tomography (PET/CT) with brain magnetic resonance imaging (MRI) among the systemic imaging modalities available. No consensus was initially reached regarding the frequency of systemic imaging and ultrasound of nodal basins (US). The third iterative survey resolved major areas of disagreement. A 5-year surveillance schedule was voted on with 92% of conference members in agreement. Conclusion: This final recommendation was established following 92% overall agreement among the 2020 CMC attendees.
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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 | 0.021 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.008 | 0.003 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.024 | 0.010 |
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".