DP01 Survey on the management of dysplastic naevus
Notice bibliographique
Résumé
Abstract Although dysplastic naevus (DN) is a frequent diagnosis, there is significant controversy on its definition and gradation and its relationship to melanoma risk. Therefore, there is no consensus over optimal management, and surveys from Australia, Canada and the USA have shown variation in clinical practice. Dysplastic naevus with involved histological margins has not been shown to progress to melanoma. To assess UK management of DN depending on the grade of atypia and reported excision margin, we circulated a questionnaire via email to dermatologists in Scotland, north Wales, Liverpool and Manchester. Seventy-two responded, of whom 46 (64%) were consultants. The cohort was generally highly experienced, with 10 (14%) responders with 1–5 years’ dermatology experience, 15 (21%) with 6–10 years, 27 (37%) with 11–20 years and 20 (28%) with > 20 years’ experience. Management of DN varied greatly. For mild DN excised with < 1-mm margin, 59 (82%) agreed that no further management was required. Opinions were divided when margins were involved in mild DN, with 14 (19%) agreeing that no further management was required, 42 (58%) choosing to re-excise and six (8%) to re-excising only any residual pigmentation. Most dermatologists reassured patients with moderately DN with margins < 1 mm (49, 68%); 18 (25%) preferred to re-excise. For moderate DN with involved margins, six respondents (8%) felt that no further management was necessary and 54 (75%) would re-excise. For severe DN with margins > 1 mm, 16 (22%) would still re-excise and six (8%) would agree management in the multidisciplinary team meeting (MDT). For severe DN with margins < 1 mm, 41 (57%) would re-excise and seven (10%) would agree management in the MDT. Lastly, for severe DN with involved margins, 62 (86%) would re-excise and seven (10%) would agree management in the MDT. This study has shown comparable results with those from Australia and the USA, whereby most dermatologists would re-excise moderate and severe DN with involved margins. Significant numbers indicated that they would re-excise in the case of close histological margins: this is unnecessary, and more standardized management may reduce expenditure. Limitations of the study include the usual potential sources of bias in a questionnaire survey; it should be noted that reported behaviour may differ from actual practice. However, this is the first UK study on this common clinical scenario. The move to report DN as low- or high-grade may help to reduce variation, but our survey suggests that some patients are currently undergoing unnecessary procedures.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».