P062 A multicentre retrospective observational study reviewing the management of severely dysplastic naevi
Bibliographic record
Abstract
Abstract The aim of this study was to evaluate management of severely dysplastic naevi (SDN) across two NHS trusts over 5 years. A natural language search was performed on the local histopathology system (Copath) to identify all SDN excised between 1 January 2018 and 1 January 2023. Duplicates, cases from external trusts, and histology reports mentioning ‘melanoma in situ’ (MIS) were excluded. Many cases had a spectrum of dysplastic changes mentioned in the report; in such cases the most severe diagnosis was used. Electronic medical records were reviewed to ascertain the surgical excision margin, histological margin, multidisciplinary team (MDT) discussion, management and duration of follow-up. In total, 136 cases were identified, of which 82 met the inclusion criteria. Trust A had 43 included cases and Trust B had 39 included cases. Overall, 58% (n = 25) of Trust A and 97% (n = 38) of Trust B cases were excised with a 2-mm surgical margin, while 81% (n = 35) of Trust A cases and 85% (n = 33) of Trust B cases were excised with at least a 1-mm histological margin. In total, 44% (n = 19) of Trust A and 51% (n = 20) of Trust B cases were discussed at skin cancer MDT. The diagnoses of two cases at Trust A were upgraded to MIS, and one case at Trust B was upgraded to a pT1a melanoma after MDT review. Overall, 74% (n = 32) of cases at Trust A were offered wide local excision (WLE); of these, 78% (n = 25) were to achieve 5-mm clearance. In total, 18% (n = 7) of cases at Trust B were offered WLE; of these, 29% (n = 2) were to achieve 5-mm clearance. Monitoring was recommended in 2% (n = 1) of Trust A cases and 26% (n = 10) of Trust B cases. Our results demonstrate that management of SDN can differ substantially between trusts. Trust A managed the majority (58%) of cases as MIS, whereas Trust B took a more conservative approach. There was no significant difference in outcome. There are currently no consensus guidelines on the management of SDN in the UK or internationally. Surveys from Australia, Canada, the USA and the UK have shown variation in clinical practice. Review of the current literature supports the re-excision of incompletely excised SDN and monitoring (as opposed to re-excision) of completely excised SDN, as the risk of progression to melanoma appears low. Our results highlight the need for consensus guidelines to manage these cases to provide optimal and consistent patient care, as well as minimizing unnecessary and potentially disfiguring surgery.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".