Purpose: Current guidelines recommend breast magnetic resonance imaging (MRI) as an adjunct to mammography for breast cancer screening in female cancer survivors treated with chest irradiation at a young age, beginning 8 to 10 years after treatment. Prospective data evaluating its efficacy in female cancer survivors are lacking. This study sought to compare the sensitivity and specificity of breast MRI with those of mammography in women who received chest irradiation for Hodgkin lymphoma (HL).
Patients And Methods: We enrolled 148 women treated with chest irradiation for HL at age ≤ 35 years who were > 8 years beyond treatment. Yearly breast MRI and mammogram were performed over a 3-year period. Sensitivity and specificity of the two screening modalities were compared.
Results: With the screening, 63 biopsies were performed in 45 women; 18 (29%) showed a malignancy. All but one of the screen-detected malignancies were preinvasive or subcentimeter node-negative breast cancers. After excluding first-screen MRI and mammogram, mammogram sensitivity was 68% as compared with 67% for MRI (P = 1.0). Sensitivity increased to 94% using both screening modalities. The specificities of mammogram alone, MRI alone, and both were 93%, 94%, and 90%, respectively.
Conclusion: In contrast to women with genetic or familial risk, in HL survivors breast MRI was not more sensitive than mammogram for breast cancer detection. However, the two screening modalities complement each other in the detection of early cases of disease. Early diagnosis is particularly important in these patients, given the breast cancer treatment challenges in patients who have received prior cancer therapy.
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http://dx.doi.org/10.1200/JCO.2012.46.5732 | DOI Listing |
Pharm Dev Technol
January 2025
Department of Pharmacy, School of Chemistry and Chemical Engineering, Liaoning Normal University, Dalian 116029, China.
In this paper, the pH-sensitive targeting functional material NGR-poly(2-ethyl-2-oxazoline)-cholesteryl methyl carbonate (NGR-PEtOz-CHMC, NPC) modified quercetin (QUE) liposomes (NPC-QUE-L) was constructed. The structure of NPC was confirmed by infrared spectroscopy (IR) and nuclear magnetic resonance hydrogen spectrum (H-NMR). Pharmacokinetic results showed that the accumulation of QUE in plasma of the NPC-QUE-L group was 1.
View Article and Find Full Text PDFJ Med Econ
January 2025
UNESCO-TWAS, The World Academy of Sciences, Trieste, Italy.
Aim: Dynamic cancer control is a current health system priority, yet methods for achieving it are lacking. This study aims to review the application of system dynamics modeling (SDM) on cancer control and evaluate the research quality.
Methods: Articles were searched in PubMed, Web of Science, and Scopus from the inception of the study to November 15th, 2023.
Int J Surg
January 2025
Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China.
Detection of biomarkers of breast cancer incurs additional costs and tissue burden. We propose a deep learning-based algorithm (BBMIL) to predict classical biomarkers, immunotherapy-associated gene signatures, and prognosis-associated subtypes directly from hematoxylin and eosin stained histopathology images. BBMIL showed the best performance among comparative algorithms on the prediction of classical biomarkers, immunotherapy related gene signatures, and subtypes.
View Article and Find Full Text PDFInt J Gen Med
December 2024
Department of Thyroid and Breast Surgery, Quzhou People's Hospital, Quzhou, 324000, People's Republic of China.
Objective: This study aims to demonstrate the impact of sarcopenia on the prognosis of early breast cancer and its role in early multimodal intervention.
Methods: The clinical data of patients (n=285) subjected to chemotherapy for early-stage breast cancer diagnosed pathologically between January 1, 2016, and December 31, 2020, in our hospital were retrospectively analyzed. Accordingly, the recruited subjects were divided into sarcopenia (n=85) and non-sarcopenia (n=200) groups according to CT diagnosis correlating with single-factor and multifactorial logistic regression analyses.
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