Abstract B78: Outcomes of mammography in the National Breast and Cervical Cancer Early Detection Program
Notice bibliographique
Résumé
Abstract Background: The National Breast and Cervical Cancer Early Detection Program (NBCCEDP) is a nationwide, comprehensive public health program that provides uninsured, underinsured, and underserved women with access to screening and diagnostic services for breast and cervical cancer. The program enrolls asymptomatic women for cancer screening and symptomatic women for diagnostic services. While the NBCCEDP prioritizes screening for breast cancer to women aged 50 to 64 years, requiring that at least 75% of all program-paid mammograms be provided to this priority population, some women aged 40-49 years also receive services. This study describes the results of mammograms provided by the NBCCEDP, by exam indication (screening or diagnostic) and age group. Methods: For women receiving an NBCCEDP-funded mammogram from 2009 through 2012, we calculated age- specific percentages of abnormal findings, and rates of follow-up testing, biopsy, and invasive and in situ breast cancer diagnosis per 1,000 mammograms. Logistic regression was used to estimate the odds for each of these outcomes by exam indication. The odds ratios (ORs) were adjusted for age, race/ethnicity, rural or urban residence, and region. Results: From 2009 2012, 941,649 screening and 175,310 diagnostic mammograms were provided to women in the NBCCEDP. A small proportion (2.7%; 30,434) of mammograms had unknown indications. Most women were white, non-Hispanic (46.7%), Hispanic (24.4%) or Black, non-Hispanic (18.1%). The percentage of abnormal mammograms was higher for diagnostic mammograms (40.1 %) than screening mammograms (15.5 %). Compared with women aged 40-49 years, fewer women aged 50-64 years had abnormal results for screening (13.7% vs. 19.7%; OR=0.65; 95% confidence interval [CI]: 0.64-0.66) and diagnostic mammograms (37.7% vs, 42.7%; OR=0.82, 95% CI: 0.80-0.83). Overall, the follow-up rates for screening and diagnostic mammograms were 163.1 and 699.7 per 1,000 mammograms; biopsy rates were 26.8 and 168.7, respectively. Follow-up testing rates were lower among women aged 50-64 years compared to those aged 40-49 years (screening: 143.9 vs. 207.5; diagnostic: 645.3 vs. 760.9); biopsy rates exhibited a similar pattern (screening: 24.1 vs. 32.9; diagnostic: 167.7 vs. 169.7). The cancer detection rates for diagnostic mammograms were higher than screening mammograms for invasive (53.1 vs 3.2 per 1,000) and in situ (14.5 vs. 2.2 per 1,000) cancers. For screening mammograms, older women had more cancers detected than younger women (invasive: 3.6 vs. 2.2; in situ: 2.3 vs. 2.0). Similarly, for diagnostic mammograms, cancer detection was higher for older women (invasive: 67.8 vs. 36.6; in situ: 17.4 vs. 11.1). Conclusions: Abnormal mammograms and diagnostic follow-up procedures were less frequent in women aged 50–64 years compared to women aged 40–49 years; however, breast cancer detection was higher for women aged 50-64 years, regardless of indication for the mammogram. Some of these differences between age groups were greater for screening mammograms than for diagnostic mammograms. Cancer detection rates were higher for diagnostic mammograms compared with screening mammograms. These findings support the NBCCEDP's priority of serving women aged 50–64 years. Further, it highlights the need to continue to focus on women at higher risk for developing breast cancer. By providing access to both screening and diagnostic mammograms, NBCCEDP offers much-needed services to this high-risk population. More targeted public health efforts are needed to improve access to screening, timely follow-up and treatment for breast cancer for all women in the United States. Citation Format: Arica White, Jacqueline Miller, Janet Royalty, A. Blythe Ryerson, Vicki Benard. Outcomes of mammography in the National Breast and Cervical Cancer Early Detection Program. [abstract]. In: Proceedings of the Seventh AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 9-12, 2014; San Antonio, TX. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2015;24(10 Suppl):Abstract nr B78.
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 | 0,001 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
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.
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 ».