scholarly journals Supportive–expressive group therapy for primary breast cancer patients: a randomized prospective multicenter trial

2008 ◽  
Vol 17 (5) ◽  
pp. 438-447 ◽  
Author(s):  
Catherine C. Classen ◽  
Helena C. Kraemer ◽  
Christine Blasey ◽  
Janine Giese-Davis ◽  
Cheryl Koopman ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Group Therapy ◽  
Cancer Patients ◽  
Primary Breast Cancer ◽  
Multicenter Trial ◽  
Breast Cancer Patients ◽  
Prospective Multicenter Trial

Clinical relevance of H-RAS, K-RAS and N-RAS in a large cohort of primary breast cancer patients

2018 ◽  
Author(s):  
M Banys-Paluchowski ◽  
K Milde-Langosch ◽  
T Fehm ◽  
I Witzel ◽  
L Oliveira-Ferrer ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Clinical Relevance ◽  
Primary Breast Cancer ◽  
Large Cohort ◽  
Breast Cancer Patients

scholarly journals Prospective comparison of the diagnostic accuracy of 18F-FDG PET/MRI, MRI, CT, and bone scintigraphy for the detection of bone metastases in the initial staging of primary breast cancer patients

2021 ◽  
Author(s):  
Nils Martin Bruckmann ◽  
Julian Kirchner ◽  
Lale Umutlu ◽  
Wolfgang Peter Fendler ◽  
Robert Seifert ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Bone Metastases ◽  
Cancer Patients ◽  
Bone Scintigraphy ◽  
Fdg Pet ◽  
Primary Breast Cancer ◽  
Whole Body ◽  
Newly Diagnosed ◽  
Breast Cancer Patients ◽  
Initial Staging

Abstract Objectives To compare the diagnostic performance of [18F]FDG PET/MRI, MRI, CT, and bone scintigraphy for the detection of bone metastases in the initial staging of primary breast cancer patients. Material and methods A cohort of 154 therapy-naive patients with newly diagnosed, histopathologically proven breast cancer was enrolled in this study prospectively. All patients underwent a whole-body [18F]FDG PET/MRI, computed tomography (CT) scan, and a bone scintigraphy prior to therapy. All datasets were evaluated regarding the presence of bone metastases. McNemar χ2 test was performed to compare sensitivity and specificity between the modalities. Results Forty-one bone metastases were present in 7/154 patients (4.5%). Both [18F]FDG PET/MRI and MRI alone were able to detect all of the patients with histopathologically proven bone metastases (sensitivity 100%; specificity 100%) and did not miss any of the 41 malignant lesions (sensitivity 100%). CT detected 5/7 patients (sensitivity 71.4%; specificity 98.6%) and 23/41 lesions (sensitivity 56.1%). Bone scintigraphy detected only 2/7 patients (sensitivity 28.6%) and 15/41 lesions (sensitivity 36.6%). Furthermore, CT and scintigraphy led to false-positive findings of bone metastases in 2 patients and in 1 patient, respectively. The sensitivity of PET/MRI and MRI alone was significantly better compared with CT (p < 0.01, difference 43.9%) and bone scintigraphy (p < 0.01, difference 63.4%). Conclusion [18F]FDG PET/MRI and MRI are significantly better than CT or bone scintigraphy for the detection of bone metastases in patients with newly diagnosed breast cancer. Both CT and bone scintigraphy show a substantially limited sensitivity in detection of bone metastases. Key Points • [18F]FDG PET/MRI and MRI alone are significantly superior to CT and bone scintigraphy for the detection of bone metastases in patients with newly diagnosed breast cancer. • Radiation-free whole-body MRI might serve as modality of choice in detection of bone metastases in breast cancer patients.

Effects of Supportive-Expressive Group Therapy in Breast Cancer Patients with Affective Disorders: A Pilot Study

2010 ◽  
Vol 79 (1) ◽  
pp. 39-47 ◽  
Author(s):  
Luigi Grassi ◽  
Silvana Sabato ◽  
Elena Rossi ◽  
Luciana Marmai ◽  
Bruno Biancosino
Keyword(s):  
Breast Cancer ◽  
Pilot Study ◽  
Group Therapy ◽  
Cancer Patients ◽  
Affective Disorders ◽  
Breast Cancer Patients

scholarly journals Influence of Covariates on Involved Lymph Nodes in Primary Breast Cancer Patients: Mixture Distribution Zero-Inflated Modeling Methodological Framework

2020 ◽  
Author(s):  
Madiha Liaqat ◽  
Shahid Kamal ◽  
Florian Fischer ◽  
Nadeem Zia
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
Lymph Nodes ◽  
Cancer Patients ◽  
Primary Breast Cancer ◽  
Negative Binomial ◽  
Lymph Node Involvement ◽  
Breast Cancer Patients ◽  
Node Involvement ◽  
Study Population

Abstract Background: Involvement of lymph nodes has been an integral part of breast cancer prognosis and survival. This study aimed to explore factors influencing on the number of auxiliary lymph nodes in women diagnosed with primary breast cancer by choosing an efficient model to assess excess of zeros and over-dispersion presented in the study population. Methods: The study is based on a retrospective analysis of hospital records among 5,196 female breast cancer patients in Pakistan. Zero-inflated Poisson and zero-inflated negative binomial modeling techniques are used to assess the association between under-study factors and the number of involved lymph nodes in breast cancer patients. Results: The most common breast cancer was invasive ductal carcinoma (54.5%). Patients median age was 48 years, from which women aged 46 years and above are the majority of the study population (64.8%). Examination of tumors revealed that over 2,662 (51.2%) women were ER-positive, 2,652 (51.0%) PR-positive, and 2,754 (53.0%) were Her2.neu-positive. The mean tumor size was 3.06 cm and histological grade 1 (n=2021, 38.9%) was most common in this sample. The model performance was best in the zero-inflated negative binomial model. Findings indicate that most factors related to breast cancer have a significant impact on the number of involved lymph nodes. Age is not contributed to lymph node status. Women having a larger tumor size suffered from greater number of involved lymph nodes. Tumor grades 11 and 111 contributed to higher numbers of positive lymph node.Conclusions: Zero-inflated models have successfully demonstrated the advantage of fitting count nodal data when both “at-harm” (lymph node involvement) and “not-at-harm” (no lymph node involvement) groups are important in predicting disease on set and disease progression. Our analysis showed that ZINB is the best model for predicting and describing the number of involved nodes in primary breast cancer, when overdispersion arises due to a large number of patients with no lymph node involvement. This is important for accurate prediction both for therapy and prognosis of breast cancer patients.

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