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Enregistrement W4213378853 · doi:10.1001/jamaoncol.2021.6204

Breast Cancer Screening Strategies for Women With <i>ATM, CHEK2</i>, and <i>PALB2</i> Pathogenic Variants

2022· article· en· W4213378853 sur OpenAlex
Kathryn P. Lowry, H. Amarens Geuzinge, Natasha K. Stout, Oğuzhan Alagöz, John M. Hampton, Karla Kerlikowske, Harry J. de Koning, Diana L. Miglioretti, Nicolien T. van Ravesteyn, Clyde B. Schechter, Brian L. Sprague, Anna N.A. Tosteson, Amy Trentham‐Dietz, Donald L. Weaver, Martin J. Yaffe, Jennifer M. Yeh, Fergus J. Couch, Chunling Hu, Peter Kraft, Eric C. Polley, Jeanne S. Mandelblatt, Allison W. Kurian, Mark E. Robson, Steven N. Hart, Katherine L. Nathanson, Susan M. Domchek, Christine B. Ambrosone, Hoda Anton‐Culver, Paul L. Auer, Elisa V. Bandera, Leslie Berstein, Kimberly A. Bertrand, Elizabeth S. Burnside, Brian D. Carter, A. Heather Eliassen, Mia M. Gaudet, Christopher Haiman, James M. Hodge, David J. Hunter, Eric J. Jacobs, Esther M. John, Charles Kooperberg, James V. Lacey, Loı̈c Le Marchand, Sara Lindström, Huiyan Ma, Elena Martínez, Susan L. Neuhausen, Polly A. Newcomb, Katie M. O’Brien, Janet E. Olson, Irene M. Ong, Tuya Pal, Julie R. Palmer, Alpa V. Patel, Sonya Reid, Lynn Rosenberg, Dale P. Sandler, Rulla M. Tamimi, Jack A. Taylor, Lauren R. Teras, Celine M. Vachon, Clarice R. Weinberg, Siddhartha Yadav, Song Yao, Argyrios Ziogas, Jeffrey N. Weitzel, David E. Goldgar

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Notice bibliographique

RevueJAMA Oncology · 2022
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueBRCA gene mutations in cancer
Établissements canadiensUniversity of Toronto
Organismes subventionnairesNational Cancer Institute
Mots-clésCHEK2PALB2MedicineBreast cancerMammographyCancerOncologyPopulationBreast cancer screeningInternal medicineGynecologyEnvironmental healthGeneticsBiology

Résumé

récupéré en direct d'OpenAlex

IMPORTANCE: Screening mammography and magnetic resonance imaging (MRI) are recommended for women with ATM, CHEK2, and PALB2 pathogenic variants. However, there are few data to guide screening regimens for these women. OBJECTIVE: To estimate the benefits and harms of breast cancer screening strategies using mammography and MRI at various start ages for women with ATM, CHEK2, and PALB2 pathogenic variants. DESIGN, SETTING, AND PARTICIPANTS: This comparative modeling analysis used 2 established breast cancer microsimulation models from the Cancer Intervention and Surveillance Modeling Network (CISNET) to evaluate different screening strategies. Age-specific breast cancer risks were estimated using aggregated data from the Cancer Risk Estimates Related to Susceptibility (CARRIERS) Consortium for 32 247 cases and 32 544 controls in 12 population-based studies. Data on screening performance for mammography and MRI were estimated from published literature. The models simulated US women with ATM, CHEK2, or PALB2 pathogenic variants born in 1985. INTERVENTIONS: Screening strategies with combinations of annual mammography alone and with MRI starting at age 25, 30, 35, or 40 years until age 74 years. MAIN OUTCOMES AND MEASURES: Estimated lifetime breast cancer mortality reduction, life-years gained, breast cancer deaths averted, total screening examinations, false-positive screenings, and benign biopsies per 1000 women screened. Results are reported as model mean values and ranges. RESULTS: The mean model-estimated lifetime breast cancer risk was 20.9% (18.1%-23.7%) for women with ATM pathogenic variants, 27.6% (23.4%-31.7%) for women with CHEK2 pathogenic variants, and 39.5% (35.6%-43.3%) for women with PALB2 pathogenic variants. Across pathogenic variants, annual mammography alone from 40 to 74 years was estimated to reduce breast cancer mortality by 36.4% (34.6%-38.2%) to 38.5% (37.8%-39.2%) compared with no screening. Screening with annual MRI starting at 35 years followed by annual mammography and MRI at 40 years was estimated to reduce breast cancer mortality by 54.4% (54.2%-54.7%) to 57.6% (57.2%-58.0%), with 4661 (4635-4688) to 5001 (4979-5023) false-positive screenings and 1280 (1272-1287) to 1368 (1362-1374) benign biopsies per 1000 women. Annual MRI starting at 30 years followed by mammography and MRI at 40 years was estimated to reduce mortality by 55.4% (55.3%-55.4%) to 59.5% (58.5%-60.4%), with 5075 (5057-5093) to 5415 (5393-5437) false-positive screenings and 1439 (1429-1449) to 1528 (1517-1538) benign biopsies per 1000 women. When starting MRI at 30 years, initiating annual mammography starting at 30 vs 40 years did not meaningfully reduce mean mortality rates (0.1% [0.1%-0.2%] to 0.3% [0.2%-0.3%]) but was estimated to add 649 (602-695) to 650 (603-696) false-positive screenings and 58 (41-76) to 59 (41-76) benign biopsies per 1000 women. CONCLUSIONS AND RELEVANCE: This analysis suggests that annual MRI screening starting at 30 to 35 years followed by annual MRI and mammography at 40 years may reduce breast cancer mortality by more than 50% for women with ATM, CHEK2, and PALB2 pathogenic variants. In the setting of MRI screening, mammography prior to 40 years may offer little additional benefit.

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.

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: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,902
Score d'incertitude au seuil0,611

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 Opus0,012
Tête enseignante GPT0,276
Écart entre enseignants0,264 · 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