Corrections: Breast cancer screening guidelines for young women of color
Notice bibliographique
Résumé
We enjoyed reading Hendrick et al's important article entitled “Age Distributions of Breast Cancer Diagnosis and Mortality by Race and Ethnicity in US Women”1 and the accompanying editorial by Yaffe.2 We write, however, to point out several important errors in the editorial by Seewaldt and Bernstein.3 They incorrectly cite Stapleton et al4 as stating that “for Black, Asian, and Hispanic/Latina women, the diagnosis of invasive breast cancer peaked at the age of 40 years (vs the mid-60s for NH-White women).” The actual statement is that “the median age at diagnosis was 59 years for White (IQR, 51-67 years), 56 years for Black (IQR, 49-65 years), 55 years for Hispanic (IQR, 48-64 years), and 56 years for Asian patients (IQR, 48-64 years) (Figure 1).” Figure 1 shows that the “peak” is in the mid to late 40s for Women of Color. Citing an advocacy website,5 they also incorrectly state that “all 50 states in the United States have enacted legislation requiring radiologists to inform women of all races and ethnicities who have high breast density that they 1) are at increased breast cancer risk and 2) may benefit from supplemental breast cancer screening modalities, such as whole breast screening ultrasound.” The federal law passed in 2019 ensured that the Food and Drug Administration process of updating postmammography reporting requirements for both patients and referring physicians would move forward. To date, the Food and Drug Administration has not introduced a federal standard.6 Individual state “inform” requirements are still accomplished through individual state laws. Currently, 38 states and the District of Columbia7 have active density inform laws, but they vary in the depth and breadth of information required to be provided to women. For instance, not all mention increased risk or supplemental screening or even require mammography facilities to inform a given woman that she has dense breasts. The outcomes of breast cancer in women with dense breasts are, in fact, worse in the cited analysis of Gierach et al8 with an excess of late-stage (II and III) disease. The relatively short mean follow-up of 6.6 years was insufficient for an accurate analysis of mortality after screening. The primary intent of dense breast notification is to address the risk of underdiagnosis from mammography: cancer, if present, could be masked. This information is intended to allow shared decision-making with a woman's health care provider regarding possible supplemental screening with magnetic resonance imaging (MRI) or ultrasound. The added yield from MRI, averaging 10 to 16 cancers per 1000 women screened,8-10 far exceeds that from ultrasound at 2 to 3 per 1000,11-13 but MRI is not available for all women with dense breasts at this time. As Monticciolo et al14 have pointed out, a risk assessment should be performed for all women by the age of 30 years so that women at high risk can begin screening with MRI if that is appropriate. Women of Ashkenazi Jewish heritage and Women of Color are especially encouraged to seek a formal risk assessment by the age of 30 years, possibly including testing for pathogenic mutations. No specific funding was disclosed. Paula B. Gordon has received honoraria for speaking at university-sponsored and society continuing medical education events but always donates them to Dense Breasts Canada; she previously served as a secretary/treasurer for the Society of Breast Imaging, volunteers on the medical advisory boards of Dense Breasts Canada and DenseBreast-info.org, and is a stockholder of Volpara Solutions.
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 | 0,010 | 0,143 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,005 | 0,003 |
| Science ouverte | 0,004 | 0,002 |
| Intégrité de la recherche | 0,015 | 0,023 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,032 | 0,034 |
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 ».