Background: Annual mammography is recommended after breast cancer treatment. However, studies suggest its under-utilization for Medicare patients. Utilization in the broader population is unknown, as is the role of breast magnetic resonance imaging (MRI). Understanding factors associated with imaging use is critical to improvement of adherence to recommendations.
Methods: A random sample of 9835 eligible patients receiving surgery for stages 2 and 3 breast cancer from 2006 to 2007 was selected from the National Cancer Database for primary data collection. Imaging and recurrence data were abstracted from patients 90 days after surgery to 5 years after diagnosis. Factors associated with lack of imaging were assessed using multivariable repeated measures logistic regression with generalized estimating equations. Patients were censored for death, bilateral mastectomy, new cancer, and recurrence.
Results: Of 9835 patients, 9622, 8702, 8021, and 7457 patients were eligible for imaging at surveillance years 1 through 4 respectively. Annual receipt of breast imaging declined from year 1 (69.5%) to year 4 (61.0%), and breast MRI rates decreased from 12.5 to 5.8%. Lack of imaging was associated with age 80 years or older and age younger than 50 years, black race, public or no insurance versus private insurance, greater comorbidity, larger node-positive hormone receptor-negative tumor, excision alone or mastectomy, and no chemotherapy (p < 0.005). Receipt of breast MRI was associated with age younger than 50 years, white race, higher education, private insurance, mastectomy, chemotherapy, care at a teaching/research facility, and MRI 12 months before diagnosis (p < 0.05).
Conclusion: Under-utilization of mammography after breast cancer treatment is associated with sociodemographic and clinical factors, not institutional characteristics. Effective interventions are needed to increase surveillance mammography for at-risk populations. ClinicalTrials.gov Identifier: NCT02171078.
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http://dx.doi.org/10.1245/s10434-018-6359-z | DOI Listing |
FASEB J
January 2025
Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
Milk is a multifaceted biofluid that is essential for infant nutrition and development, yet its cellular and bioactive components, particularly maternal milk cells, remain understudied. Early research on milk cells indicated that they cross the infant's intestinal barrier and accumulate within systemic organs. However, due to the absence of modern analytical techniques, these studies were limited in scope and mechanistic analysis.
View Article and Find Full Text PDFMol Carcinog
January 2025
Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
The standard therapy for locally unresectable advanced non-small cell lung cancer (NSCLC) is comprised of chemoradiotherapy (CRT) before immunotherapy (IO) consolidation. However, how to predict treatment outcomes and recognize patients that will benefit from IO remain unclear. This study aimed to identify prognostic biomarkers by integrating computed tomography (CT)-based radiomics and genomics.
View Article and Find Full Text PDFJpn J Clin Oncol
January 2025
Department of Obstetrics and Gynecology, Tohoku University School of Medicine, 1-1, Seiryo-machi, Aoba-ku, Sendai, Miyagi 980-8574, Japan.
Objectives: To identify a method for breast cancer (BC) surveillance in patients with epithelial ovarian cancer (EOC) with germline BRCA1/2 pathogenic variants (gBRCA1/2m) and the incidence of BC after EOC in the era of broad PARP inhibitors use.
Methods: We retrospectively analyzed the data on EOC patients who had gBRCA1/2m by genetic testing between January 2017 and August 2023 in our single center.
Results: Of 125 patients with EOC, 33 had gBRCA1/2m.
Radiol Case Rep
March 2025
Longstreet Clinic, Breast Surgery, 725 Jesse Jewell Parkway, Gainesville, GA 30501 USA.
Adenoid cystic carcinoma (ACC) of the breast is an exceptionally rare malignancy, accounting for less than 0.1% of all breast cancers. Despite its favorable prognosis, optimal management remains undefined due to its rarity and lack of consensus guidelines.
View Article and Find Full Text PDFFront Neurol
January 2025
Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Objective: To develop a machine learning-based clinical and/or radiomics model for predicting the primary site of brain metastases using multiparametric magnetic resonance imaging (MRI).
Materials And Methods: A total of 202 patients (87 males, 115 females) with 439 brain metastases were retrospectively included, divided into training sets (brain metastases of lung cancer [BMLC] = 194, brain metastases of breast cancer [BMBC] = 108, brain metastases of gastrointestinal tumor [BMGiT] = 48) and test sets (BMLC = 50, BMBC = 27, BMGiT = 12). A total of 3,404 quantitative image features were obtained through semi-automatic segmentation from MRI images (T1WI, T2WI, FLAIR, and T1-CE).
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