P125 International incidence trends for melanoma in children, teenagers and young adults: a systematic review
Notice bibliographique
Résumé
Abstract Globally the incidence rates of melanoma have been increasing; however, knowledge of the incidence in children, teenagers and young adults (CTYA) is limited due to the low prevalence. Several risk factors for melanoma exist such as ultraviolet exposure, sex, skin type and genetic predisposition. However, the impacts of these risk factors vary by genetics, age and episodes of severe sunburn, and are more relevant to younger individuals. For this study we undertook a systematic review to investigate the incidence trends and patient characteristics of melanoma in patients aged < 25 years. Currently, there is a gap in the literature for systematic reviews exploring trends in melanoma in CTYA. On 18 October 2024, a search was completed using CINAHL, EBSCO, PubMed, Scopus and Web of Science, where 236 papers were identified from 1980 to 2024. Studies were excluded with data recorded prior to 1980 along with any that solely focused on basal or squamous cell carcinomas. The Newcastle–Ottawa Scale was used to assess the risk of bias, with results graded as ‘good’, ‘fair’ or ‘poor’ based on Agency for Healthcare Research and Quality standards. Thirty-three studies were included from 16 countries across 6 continents, with 1 study reporting global burden of disease using a dataset from 204 countries. Through the decades, the general trends of melanoma varied depending on the years and geographical location. Most countries observed a female predominance in CTYA with melanoma. This was recorded in 12 out of 19 papers (63%). In the USA, from seven studies, all cases were observed in those of a White non-Hispanic background. More cases were recorded as age increased, even in patients aged ≤ 12 years. Over various time periods, studies reported a general decrease in CTYA with melanoma from the years of 2000 to 2010 in North America and Australasia. However, some studies in Europe noted an increase in melanoma, including countries such as Finland and Denmark. Trends in Iran vary as there was a decrease from 2004 to 2012, but this was then followed by an increase up until 2019. International trends varied with no unifying trend; however, there was evidence to suggest reducing trends in countries where incidence rates were higher (Australia and the USA). A greater understanding of trends by ethnicity, sun safety behaviour and the impact of public health campaigns is needed to better understand the trends, and a greater representation of developing countries is needed to understand the global burden.
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 | 0,004 | 0,026 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,008 | 0,009 |
| Bibliométrie | 0,016 | 0,020 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,000 |
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 ».