RE: Population-Level Impact of the Bivalent, Quadrivalent, and Candidate Nonavalent Human Papillomavirus Vaccines: A Comparative Model-Based Analysis
Notice bibliographique
Résumé
In a recent article in the Journal, Van de Velde et al. ( 1 ) assume that human papillomavirus (HPV) vaccines “prevent infection but do not alter the natural history of disease in individuals already infected by a vaccine type.” We question whether this assumption is correct. In 2006, the US Food and Drug Administration (FDA) expressed concerns about “the potential for Gardasil to enhance disease among a subgroup of subjects who had evidence of persistent infection with vaccine-relevant HPV types at baseline” ( 2 ). The increase in high-grade cervical disease rates among a subgroup of vaccinated girls and women noted by the FDA was not statistically significant. However, a subsequent ecological study of approximately 2.9 million Australian girls and women ( 3 ) documented that the introduction of Gardasil was associated with statistically significant increases in high-grade cervical disease rates among women aged more than 21 years but with statistically significant decreases in high-grade cervical disease rates among girls and women aged less than 18 years. Decreases in high-grade cervical disease rates among Australian girls and women aged less than 18 years were considered evidence of beneficial effect from Australia’s HPV vaccination program ( 3 ). However, to our knowledge, no explanations have been offered for the increases in high-grade cervical disease rates reported from the same study among Australian women aged more than 21 years. We ask Van de Velde et al. to consider whether the ecological observations from Australia suggest that Gardasil may in fact be enhancing disease among a subgroup of vaccinated individuals. In an accompanying editorial, Sahasra buddhe and Sherman ( 4 ) claim that “HPV vaccination provides the scientific and public health community an unprecedented opportunity to reduce the burden of cervical cancer.” We question the scientific accuracy of this claim. Should perfect HPV vaccine efficacy last less than 15 to 20 years, HPV vaccination will prove to have been a “costly failed public health experiment in cancer control” ( 5 ). The best-case scenario modelled by Van de Velde et al., which includes an assumption of lifelong, perfect HPV vaccine efficacy, predicts that HPV vaccination will reduce cervical cancer rates by approximately 30% over 70 years ( 1 ). In contrast, the US Preventive Services Task Force has determined that Papanicolaou cytology screening reduces cervical cancer rates by 60% to 90% within 3 years of its introduction to populations naive to screening and that these reductions of disease burden are “‘consistent and equally dramatic across populations”‘ ( 6 ). Even if HPV vaccines eventually prove to confer lifelong perfect efficacy, we question whether the introduction of HPV vaccines to resource-constrained settings will decelerate coverage of target demographic groups by cervical screening services and thereby decelerate rather than accelerate global reductions in cervical cancer–related mortality ( 7 ).
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 | 0,015 | 0,052 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,004 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,019 | 0,002 |
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 ».