Abstract 847: Human papillomavirus (HPV) type distribution in multi-ethnic cohort of women: Implications for vaccination programs
Notice bibliographique
Résumé
Abstract Introduction: HPV is linked to many genital and oropharyngeal cancers, and current HPV vaccines target 2 oncogenic HPV types (16 and 18), which are estimated to account for 70% of cervical cancer cases. We sought to determine type distributions among a multi-ethnic cohort of women to understand what proportion of infections are covered by current and proposed vaccines. Methods: We analyzed cervical specimens from a cohort of 536 non-pregnant women from four clinical centers in the United States and Canada. HPV genotyping was performed using the Linear Array® HPV Genotyping Test (Roche), which detects 37 HPV types. We calculated prevalence of HPV types (individually and grouped by those types included in the currently approved bivalent and quadrivalent vaccines and the nonavalent vaccine currently being developed) by age, race/ethnicity, and histology. Results: Overall the prevalence of any HPV type in the entire cohort was 57%. More than a quarter of all specimens showed infection with multiple HPV infections with 6 types being the most detected in a single specimen. The prevalence of oncogenic types on the array ranged from 36% among women with normal histology to 88% and 92% among those with low-grade and high-grade lesions, respectively. Among women with high-grade lesions the prevalence of types 16/18 was only 45% while the prevalence of types in the nonavalent vaccine was 85%. Prevalence of oncogenic types decreased by age group with women less than 30 having a prevalence of 63%, while in those over age 50 it was 34%. HPV16 was the most prevalent type among non-Hispanic white women (19%), but not among African-American (0%) or Hispanic (2%) women. HPV58 and HPV58/59 were the most common types among African-American and Hispanic women, respectively. Among non-Hispanic whites, 50% of prevalent oncogenic types were covered by current vaccines, while 81% would be covered by the nonavalent vaccine. In comparison, only 32% of infections among African-American and 29% among Hispanic women were covered by current vaccines, compared to 86% and 75%, respectively, for the nonavalent vaccine. In fact, African American women had 2.5-fold higher prevalence of HPV 58 compared to non-Hispanic white women. Of note, Asian women were more than four-times as likely to be infected with multiple HPV genotypes compared to non-Hispanic white women. Conclusions: Our findings suggest that a nonavalent vaccine would cover more of the prevalent HPV genotypes present across racial/ethnic groups when compared to current vaccines. These results also suggest that even though more infections occur among younger women (<30), a significant proportion of older women (>50) are also infected. Further, 14-25% of currently prevalent HPV types would still not be covered by next generation vaccines. Citation Format: Michael E. Scheurer, Hung N. Luu, Martial Guillaud, Jane Montealegre, Laura M. Dillon, Michele Follen, Karen Adler-Storthz. Human papillomavirus (HPV) type distribution in multi-ethnic cohort of women: Implications for vaccination programs. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 847. doi:10.1158/1538-7445.AM2015-847
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».