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

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.

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Can primary breast cancer patients sense the presence of lymph node metastasis? An unexpected research finding

Psychiatry and Clinical Neurosciences ◽

10.1046/j.1440-1819.1998.00389.x ◽

1998 ◽

Vol 52 (3) ◽

pp. 363-364 ◽

Cited By ~ 2

Author(s):

Bert De Brabander ◽

Pol Gerits ◽

Robert Sacré ◽

Jan Lamote

Keyword(s):

Breast Cancer ◽

Lymph Node ◽

Lymph Node Metastasis ◽

Cancer Patients ◽

Primary Breast Cancer ◽

Research Finding ◽

Breast Cancer Patients ◽

Node Metastasis

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The Effect of Psychological Intervention on Personality Change, Coping, and Psychological Distress of Japanese Primary Breast Cancer Patients

Cancer Nursing ◽

10.1097/01.ncc.0000305746.49205.f8 ◽

2008 ◽

Vol 31 (4) ◽

pp. E27-E35 ◽

Cited By ~ 14

Author(s):

Takako Maeda ◽

Hiroko Kurihara ◽

Isamu Morishima ◽

Tsunetsugu Munakata

Keyword(s):

Breast Cancer ◽

Psychological Distress ◽

Cancer Patients ◽

Primary Breast Cancer ◽

Psychological Intervention ◽

Personality Change ◽

Breast Cancer Patients

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201TiP Evaluation of the feasibility of ultrasound-guided clipping of suspicious intramammary lesions in primary breast cancer patients receiving neoadjuvant therapy (Ultra3Detect)

Annals of Oncology ◽

10.1016/j.annonc.2021.08.482 ◽

2021 ◽

Vol 32 ◽

pp. S445

Author(s):

E. Vlachou ◽

S. Kümmel ◽

N. Künzel ◽

E. Breit ◽

D. Schindowski ◽

...

Keyword(s):

Breast Cancer ◽

Neoadjuvant Therapy ◽

Cancer Patients ◽

Primary Breast Cancer ◽

Breast Cancer Patients ◽

Ultrasound Guided

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

10.21203/rs.3.rs-62928/v1 ◽

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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