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Enregistrement W2223162680 · doi:10.6004/jnccn.2010.0100

The Changing Face of Cervical Cancer Screening in the United States

2010· editorial· en· W2223162680 sur OpenAlexaboutno aff
Warner K. Huh

Notice bibliographique

RevueJournal of the National Comprehensive Cancer Network · 2010
Typeeditorial
Langueen
DomaineMedicine
ThématiqueCervical Cancer and HPV Research
Établissements canadiensnon disponible
Organismes subventionnairesNational Cancer Institute
Mots-clésMedicineFace (sociological concept)Cervical cancerCervical cancer screeningCancerInternal medicine

Résumé

récupéré en direct d'OpenAlex

With the introduction of widespread Pap smear screening starting in the 1940s, the United States has seen at least a 50% reduction in the incidence and mortality of invasive cervical cancer. In light of the ease of sampling, the long pre-malignant phase of cervical cancer, and well-tolerated treatment options for pre-invasive disease, cervical cancer screening has served as a model for screening for other malignancies. For some women, it also serves as the cornerstone for annual routine visits with gynecologists. Both patients and gynecologists have been taught that a yearly Pap test is important, and it can serve as the backbone of care. Unfortunately, however, access to screening and treatment for cervical cancer continues to be an issue for some women in the United States. Approximately 60% of women with invasive cancer had not undergone a Pap test in the 5 years preceding their diagnosis or have never undergone a Pap test. 1 The long history of Pap tests has also taught us a number of lessons. We have learned that cytologic screening is hardly perfect. In a study by Nanda et al. 2 the sensitivity of a single test was 51%, and this was subsequently confirmed in a pooled analysis of European and Canadian studies by Cuzick et al. 3 One way to compensate for this poor sensitivity is by using serial screening; the sensitivity of cytology increases to 76% with 2 consecutive annual Pap tests and 88% with 3 consecutive tests. Just adding tests and procedures, however, is not always the answer, and most recently the pendulum has swung in the other direction. We now understand the risk of overtreating pre-invasive disease and the potential impact of overtreatment on preterm labor and neonatal morbidity and mortality. In many adolescents and young women, abnormal Pap tests and underlying disease will resolve spontaneously. Therefore, in 2009, the American College of Obstetricians and Gynecologists recommended that screening for cervical cancer start at age 21. 4 Another lesson learned is the role of human papillomavirus (HPV) in cervical cancer. High-risk (HR) HPV DNA testing has become a mainstay of cervical cancer screening over the past 10 years. Experts now recognize that more than 99% of all invasive cervical cancers are associated with 14 different HR HPV types. Currently, HR HPV testing is recommended for women with equivocal Pap tests (ASC-US) and atypical glandular Pap tests (AGC). Most importantly, it is also widely recommended in conjunction with Pap testing in women older than 30 years of age. In keeping with the lesson of not overtreating and overscreening, after negative Pap and HPV test results, an individual woman can increase her screening interval to every 3 years. Another benefit of HR HPV testing is its much higher sensitivity than Pap testing (96% vs. 53% in pooled estimates). Since 2005, 7 randomized controlled trials 5–11 have been published that evaluated HPV testing in the screening setting. These studies have largely shown improvements in the detection of pre-invasive lesions either alone or in conjunction with Pap testing. Of particular note, a recently published trial from Finland showed

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesIntégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,095
Score d'incertitude au seuil0,998

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,002
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,005
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,051
Tête enseignante GPT0,388
Écart entre enseignants0,337 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations7
Publié2010
Routes d'admission1
Résumé présentoui

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