International variations in hepatic tumours incidence in children and adolescents
Notice bibliographique
Résumé
In order to compare the subtype distribution of hepatic tumours in children and adolescents between Japan and other countries, we extracted information on cancer incidence in children and adolescents from the third volume of the International Incidence of Childhood Cancer series (IICC-3) (1). The IICC-3 reports the number or incidence rates of cancers diagnosed in childhood and adolescence from cancer registries (regional or national) worldwide. We analyzed hepatic tumour incidence in four countries in Asia (Japan, China, the Republic of Korea and Thailand), two countries in Africa (Egypt and Uganda), four countries in the Americas (North: The USA and Canada, Latin and Caribbean: Brazil and Colombia), three countries in Europe (the UK, France and Germany) and two countries in Oceania (Australia and New Zealand). Information from the Republic of Korea, USA, UK, Australia and New Zealand were obtained at the national level and those from the other countries were extracted from one or multiple regional cancer registries. The years of incidence included in the analyses varied from country to country, ranging from 1990 to 2014, with the shortest being 12 years (Egypt: 1999–2010, UK: 2000–11) and the longest being 24 years (Japan and China, both: 1990–2013). In this study, we compared the incidence and proportional distribution of hepatic tumour subtype in children (0–14 years old) and adolescents (15–19 years old) between these countries. As shown in Table 1, hepatic tumours incidence rates in children (0–14 years old) were high in Asia, especially in China, followed by North American countries, Oceanian countries and European countries, and were lowest in African countries. The incidence rate in adolescents (15–19 years old) was the highest in Uganda, which was followed by China and Thailand. Other countries had incidence rates ranging from 0.5 to 1.8 cases per 1 000 000 person-years. Incidence rates of hepatic tumours in children and adolescents (per 1 000 000 person-years) Note: Data were extracted from the third volume of the International Incidence of Childhood Cancer series (IICC-3) (1). The table and figures are prepared by the authors of this article, and the responsibility for this presentation and its interpretation lies with the authors of this article. aAge-standardized incidence rate. Figure 1 shows the proportional distribution of subtype of hepatic tumour incidence in children. It is difficult to assess the distribution of subtype when the percentage of unspecified subtype is high: 60.4% in China, 38.0% in Thailand and 29.4% in Uganda. All other countries had the highest percentage of hepatoblastoma, with 90.8% in Japan, 82–89% in Egypt, the two North American countries, the three European countries and Australia; 73–74% in the Republic of Korea, Columbia and New Zealand. Brazil had the same highest percentage of hepatoblastoma, but it was 54.8%, while hepatic carcinoma accounted for 25.8%. Proportional distribution of subtype of hepatic tumours in children (0–14 years old). Proportional distribution of subtype of hepatic tumours in children (15–19 years old). Figure 2 shows the proportional distribution of subtype of hepatic tumours in adolescents. The percentage of unspecifies subtype were high in China, Thailand and Uganda, as was seen in children. Also in Egypt, unspecified accounted for 33.3% of the hepatic tumours, while in children, percentage of unspecified was 17.6%. Unlike in children, hepatic carcinoma accounted for the largest proportion of hepatic tumours in all countries. The percentage of hepatic carcinoma were 100% in New Zealand, 90–95% in Canada and the UK; 82–89% in the Republic of Korea, Brazil, the USA, France, Germany and Australia and 65–77% in Egypt, Uganda and Columbia. None declared.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».