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Enregistrement W2401611683 · doi:10.1158/2159-8290.cd-nd2012-007

Breast Cancer Screening Goes Personalized

2012· article· en· W2401611683 sur OpenAlexaboutno aff
Charles Schmidt

Notice bibliographique

RevueCancer Discovery · 2012
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueNutrition, Genetics, and Disease
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCancerComputational biologyBreast cancerMedicineBioinformaticsComputer scienceBiologyInternal medicine

Résumé

récupéré en direct d'OpenAlex

Research on individual risk will point to better decisions about who gets mammography tests and when they should get themIn 2009, the U.S. Preventive Services Task Force (PSTF) created a controversy with its revised guidelines for screening mammography, which asserted that women between the ages of 50 and 74 should undergo routine biannual screening, while younger women could choose to be screened based on how they valued mammography's possible benefits and harms.The previous guidelines had recommended screening for all women older than 40 years, and critics attacked the updates as vague and disparaging of mammography's life-saving payback. But the task force cited clinical data and models showing that, for younger women, the small mortality reductions from mammography do not justify the unnecessary treatments resulting from false-positive findings.Fueled by a seemingly endless series of studies, the same controversy simmers today. In November 2011, Canada's Task Force on Preventive Health Care issued guidelines that essentially mirror the PSTF's position: no screening until age 50, and then mammograms every 2 to 3 years until age 74.The American Cancer Society (ACS), meanwhile, recommends annual screening for all women starting at age 40 until they reach 10 years of life expectancy (typically 74 years). “The ACS's position is that all women between the ages of 40 and 50 should be told that mammography isn't a good test, but they should get it anyway, while the PSTF recommends these women should be told mammography isn't a good test, but they can get it if they want it,” explains ACS chief medical officer, Otis Brawley, MD.Now the debate is shifting toward individual risk factors.Karla Kerlikowske, MD, a professor at the University of California's Helen Diller Comprehensive Cancer Center in San Francisco, says older studies behind the 2009 guidelines considered mammography outcomes only in relation to age.Studies conducted more recently also looked at other risk factors; those factors evaluated in a screening context so far include breast density, family history, and the history of prior biopsies. According to Kerlikowske, those studies are shaping a more personalized landscape for determining who should be screened with mammography and when they should be screened. “We want to maximize the benefits from screening by focusing it on the women who really need it,” she says.In July 2011, Kerlikowske and colleagues reported analyses showing that biannual mammograms make sense mainly for women in their 40s who have high breast density and at least one other cancer risk factor (Ann Intern Med 2011;155:10–20). Women aged 50 to 79 with no additional risk factors apart from age need only be screened every 3 to 4 years, the authors concluded. “I know of at least 2 other studies slated to come out soon that support the same concept,” Kerlikowske remarks.Diana Pettiti, MD, MPH, a professor in the department of biomedical informatics at Arizona State University in Metro Phoenix, who was vice chair on the PSTF task force, feels that Kerlikowske's data provide a useful step in the right direction. “We need screening recommendations tailored to each woman's individual risk profile,” Pettiti says. “These results are excellent on a population basis, but they still need to be validated for individual predictive value.”Validation efforts are ongoing through a 5-year, multicenter, prospective study funded last September by NCI's Division of Cancer Control and Population Sciences (DCCPS). Codirected by Kerlikowske and Diana Miglioretti, PhD, a senior investigator at Group Health Research Institute, in Seattle, WA, the study will compare age- to risk-based screening according to factors including breast density, family history, results of prior biopsy, hormonal status, and genetic variations.“The study aims to determine if a risk-based approach detects more invasive breast cancers while also reducing false-positive findings compared with age-based screening alone,” says Stephen Taplin, MD, PhD, acting chief in the DCCPS's Process of Care Research Branch.Pettiti says it will not be easy to replace mammography, which has 40 years of data and clinical history behind it. But alternatives that address its chief drawbacks—a limited ability to detect tumors in dense-breasted women (who make up 25% of the female population) and excessive biopsies for findings that turn out to be benign—are making progress.Film-screen mammography has been largely replaced with digital mammography, which does a moderately better job on dense breast tissue, says Kerlikowske.Other promising techniques include tomosynthesis, which takes 3-dimensional pictures of the breast using X-rays; ultrasound; MRI; and an early-stage technology called molecular breast imaging (MBI) geared specifically for dense tissue.“Tomosynthesis seems to be making the most headway,” comments Kerlikowske. “But we're not going to get to where we need to be just with fancy imaging modalities. The real issue now is defining who meets a high enough threshold to get a screening test in the first place.”For more news on cancer research, visit Cancer Discovery online at www.AACR.org/CDnews.

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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,244
Score d'incertitude au seuil0,599

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
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 Opus0,015
Tête enseignante GPT0,279
Écart entre enseignants0,265 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

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

En bref

Citations0
Publié2012
Routes d'admission1
Résumé présentoui

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