Screening for Breast Cancer in Average-Risk Women
Notice bibliographique
Résumé
Letters17 September 2019Screening for Breast Cancer in Average-Risk WomenJennifer S. Lin, MD, MCR, Reem A. Mustafa, MD, MPH, Timothy J. Wilt, MD, MPH, Carrie A. Horwitch, MD, MPH, and Amir Qaseem, MD, PhD, MHAJennifer S. Lin, MD, MCRKaiser Permanente Northwest, Portland, Oregon (J.S.L.)Search for more papers by this author, Reem A. Mustafa, MD, MPHUniversity of Kansas Medical Center, Kansas City, Kansas (R.A.M.)Search for more papers by this author, Timothy J. Wilt, MD, MPHMinneapolis VA Center for Chronic Disease Outcomes Research and University of Minnesota School of Medicine, Minneapolis, Minnesota (T.J.W.)Search for more papers by this author, Carrie A. Horwitch, MD, MPHVirginia Mason Medical Center, Seattle, Washington (C.A.H.)Search for more papers by this author, and Amir Qaseem, MD, PhD, MHAAmerican College of Physicians, Philadelphia, Pennsylvania (A.Q.)Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/L19-0474 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail IN RESPONSE:We appreciate the comments from Dr. Biggs, Dr. Grimm, Dr. Lenderink-Carpenter, and Dr. Lee and colleagues. We also appreciate the opportunity that our guidance statements provide to engage in robust peer discussion. We emphasize the broad agreement among guideline groups as highlighted by our guidance statement, including for women aged 40 to 49 years (1). None of the guidelines recommends screening in women aged 40 to 45 years; the American Cancer Society suggests that starting screening at age 45 years is a weak recommendation because of the fine balance between benefits and harms and the importance of individual ...References1. Qaseem A, Lin JS, Mustafa RA, et al; Clinical Guidelines Committee of the American College of Physicians. Screening for breast cancer in average-risk women: a guidance statement from the American College of Physicians. Ann Intern Med. 2019. [PMID: 30959525] doi:10.7326/M18-2147 LinkGoogle Scholar2. Redberg RF, Grady D. False information about breast cancer screening-reply. JAMA Intern Med. 2018;178:300. [PMID: 29404614] doi:10.1001/jamainternmed.2017.7090 CrossrefMedlineGoogle Scholar3. Moss SM, Wale C, Smith R, et al. Effect of mammographic screening from age 40 years on breast cancer mortality in the UK Age trial at 17 years' follow-up: a randomised controlled trial. Lancet Oncol. 2015;16:1123-32. [PMID: 26206144] doi:10.1016/S1470-2045(15)00128-X CrossrefMedlineGoogle Scholar4. Miller AB, Wall C, Baines CJ, et al. Twenty five year follow-up for breast cancer incidence and mortality of the Canadian National Breast Screening Study: randomised screening trial. BMJ. 2014;348:g366. [PMID: 24519768] doi:10.1136/bmj.g366 CrossrefMedlineGoogle Scholar5. Nelson HD, Fu R, Cantor A, et al. Effectiveness of breast cancer screening: systematic review and meta-analysis to update the 2009 U.S. Preventive Services Task Force recommendation. Ann Intern Med. 2016;164:244-55. [PMID: 26756588]. doi:10.7326/M15-0969 LinkGoogle Scholar Author, Article, and Disclosure InformationAffiliations: Kaiser Permanente Northwest, Portland, Oregon (J.S.L.)University of Kansas Medical Center, Kansas City, Kansas (R.A.M.)Minneapolis VA Center for Chronic Disease Outcomes Research and University of Minnesota School of Medicine, Minneapolis, Minnesota (T.J.W.)Virginia Mason Medical Center, Seattle, Washington (C.A.H.)American College of Physicians, Philadelphia, Pennsylvania (A.Q.)Disclosures: Authors have disclosed no conflicts of interest. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M18-2147. A record of disclosures of interest and management of conflicts of is kept for each Clinical Guidelines Committee meeting and conference call and can be viewed at www.acponline.org/clinical_information/guidelines/guidelines/conflicts_cgc.htm. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoScreening for Breast Cancer in Average-Risk Women: A Guidance Statement From the American College of Physicians Amir Qaseem , Jennifer S. Lin , Reem A. Mustafa , Carrie A. Horwitch , Timothy J. Wilt , and Screening for Breast Cancer in Average-Risk Women Lars J. Grimm Screening for Breast Cancer in Average-Risk Women Amanda Lenderink-Carpenter Screening for Breast Cancer in Average-Risk Women Michelle V. Lee , Debbie L. Bennett , and Catherine M. Appleton Screening for Breast Cancer in Average-Risk Women Kelly W. Biggs Metrics 17 September 2019Volume 171, Issue 6Page: 451-452KeywordsBreast cancerBreast cancer screeningCancer screeningDisclosureLife expectancyMorbidityMortalityRacial and ethnic issuesRadiation exposureScreening guidelines ePublished: 17 September 2019 Issue Published: 17 September 2019 Copyright & PermissionsCopyright © 2019 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
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 | 0,002 | 0,021 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,062 | 0,011 |
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 ».