Search published articles


Showing 4 results for Neoplasms.
Androgen receptor expression on breast cancer cells: a clinicopathologic and survival study
Sanambar Sadighi, Hosein Kamranzadeh, Easa Jahanzad , Saghi Vaziri ,
Volume 73, Issue 8 (11-2015)
Abstract

Background: Breast cancer is the most common cancer in women around the world. It has been known for over a century that androgens and androgen receptor (AR) play a role in normal and neoplastic breast cells. The aim of this study was to determined the AR expression on tumor cells and its correlation with other prognostic and predictive factors as well as contribution of AR in patients overall survival (OS) and disease- free survival (DFS). Methods: This retrospective cross-sectional study performed on 189 patients who referred to Medical Oncology Ward of Cancer Institute, Tehran University of Medical Sciences, from April 2007 to February 2010. We performed an immunohistochemistry study for AR (AR441 clone, Dako, Germany) (10% cut-off point) and Ki-67 MIB-1 clone, Dako, Germany) on paraffin embedded blocks. Other data were extracted from patients’ documents. Results: Overall, AR expression was 49.1%. Mean age of the patients with and without AR was 47.86 and 48.49 years, respectively. AR positive tumors presented more in stage I/II than III/IV (P=0.02) and AR were more positive for estrogen receptor positive, lower grade of tumor (grade I/II versus III) and lower Ki-67 (P=0.01). AR positivity had neither correlation with progesterone receptor, HER2/neu, P53 expression or menopausal status. OS and DFS were higher in AR positive patients but did not reach statistical significance. In triple-negative breast cancer (TNBC) group, 25% of tumors showed AR expression. AR had non-significant positive correlation with OS in TNBC cancer patients. OS and DFS had significant statistic positive correlation with ER, PR and stage regardless of AR status. Conclusion: Based on this study, although androgen receptor expression showed correlation with other prognostic factors for survival in patients, we didn’t find statistically significant independent relationship between AR and overall survival in patients. As far as there isn’t any targeted therapy for triple-negative breast cancer (TNBC), prospective basic and clinical studies regarding AR inhibitors in the treatment of TNBC seems to be logical and valuable.


Non-melanoma skin cancer diagnosis with a convolutional neural network
Ali Ameri,
Volume 78, Issue 4 (7-2020)
Abstract
Background: The most common types of non-melanoma skin cancer are basal cell carcinoma (BCC), and squamous cell carcinoma (SCC). AKIEC -Actinic keratoses (Solar keratoses) and intraepithelial carcinoma (Bowen’s disease)- are common non-invasive precursors of SCC, which may progress to invasive SCC, if left untreated. Due to the importance of early detection in cancer treatment, this study aimed to propose a computer-based model for identification non-melanoma malignancies.
Methods: In this analytic study, 327 AKIEC, 513 BCC, and 840 benign keratosis images from human against machine with 10000 training dermoscopy images (HAM10000) were extracted. From each of these three types, 90% of the images were designated as the training set and the remaining images were considered as the test set. A deep learning convolutional neural network (CNN) was developed for skin cancer detection by using AlexNet (Krizhevsky, et al., 2012) as a pretrained network. First, the model was trained on the training images to discriminate between benign and malignant lesions. In comparison with conventional methods, the main advantage of the proposed approach is that it does not need cumbersome and time-consuming procedures of lesion segmentation and feature extraction. This is because CNNs have the capability of learning useful features from the raw images. Once the system was trained, it was validated with test data to assess the performance. Study was carried out at Shahid Beheshti University of Medical Sciences, Tehran, Iran, in January and February, 2020.
Results: The proposed deep learning network achieved an AUC (area under the ROC curve) of 0.97. Using a confidence score threshold of 0.5, a classification accuracy of 90% was attained in the classification of images into malignant and benign lesions. Moreover, a sensitivity of 94% and specificity of 86% were obtained. It should be noted that the user can change the threshold to adjust the model performance based on preference. For example, reducing the threshold increase sensitivity while decreasing specificity.
Conclusion: The results highlight the efficacy of deep learning models in detecting non-melanoma skin cancer. This approach can be employed in computer-aided detection systems to assist dermatologists in identification of malignant lesions.
 

Cost evaluation of chemotherapy and epidemiology of five most common cancers in Isfahan Province in Iran
Mohammadreza Amirsadri , Amir Houshang Zargarzadeh , Farimah Rahimi, Fatemeh Jahani,
Volume 78, Issue 4 (7-2020)
Abstract
Background: Cancer is the third leading cause of death in Iran. Cancer treatment is very costly and chemotherapy drugs are one of the main causes of the high cost of cancer treatment. The purpose of this study was to evaluate the cost of chemotherapy drugs of five most common cancers and identifying the factors might affect the costs of chemotherapy drugs in a one of the large provinces of Iran, located in the center of the country.
Methods: In a cross-sectional study, the data of all patients with five common cancer diagnosed from March 2015 to March 2016 in Isfahan Province in Iran were collected from the Cancer Registry Center of Isfahan, as well as the pharmacies which distribute chemotherapy drugs. The required information (including, patient characteristics, type of cancer, and the costs of chemotherapy) of patients was obtained by linking the information of patients registered in the distributor pharmacies with the patients registered at the Isfahan Cancer Registry Center through the national code of the patients.
Results: Breast, skin, colorectal, stomach and thyroid cancers were the most common cancers within the evaluated period of time in Isfahan Province. Colorectal cancer with an annual average total cost of 110,510,720 IRR (Rials) per patient was the most expensive cancer during the evaluated time period while thyroid cancer with an annual average total cost of 40,791,123 IRR per patient was the least costly cancer within the evaluated time period in Isfahan among the five most common cancers, considering the chemotherapy medicines cost. The highest cost in the colorectal cancer was due to the drug cetuximab distributed under the trade name Erbitux®. Regardless of the cancer type, the mean annual total cost of chemotherapy drugs per patient within the considered period of time calculated to be 96,307,145 IRR.
Conclusion: The chemotherapy cost of the common cancers was high with an annual average of more than 96 million IRR (Rials) per patient, within the considered time period. This was particularly true for colorectal cancer with an annual average cost of more than 110 million Rials.

Cutaneous granular cell tumor: case report
Mahdi Ghoncheh, Narges Nazeri ,
Volume 78, Issue 10 (1-2021)
Abstract
Background: Granular cell tumor (Abrikossoff’s tumor) is a rare and slow-growing tumor of the soft tissue. Originated from the Schwann cells, it is often a benign tumor, but it can be malignant in 1-3% of the cases. Malignant cases can cause significant morbidity and mortality. It may develop in many anatomic locations, especially in the head and neck region, and also in skin and subcutaneous tissue.
Case Presentation: The patient was a 27 years old female who was referred to the Imam-Reza Hospital of Birjand because of a subcutaneous mass in the left inguinal region. The tumor was appeared six months ago as a painless slow-growing nodule. In physical examination, there was a 3×4 cm subcutaneous tumor in the left inguinal region. The tumor was attached to the skin but not to the deep and surrounding tissues. There was not any evidence of lymphadenopathy or distant metastasis.  The patient was admitted in September 2017. The tumor was excised surgically with a one cm safe margin. The post-operative course was uneventful. In histopathology examination, there was a non-encapsulated neoplasm containing polygonal cells with round to oval nuclei and abundant fine pas-positive granules in the eosinophilic cytoplasm. There were fibrous bands between the tumoral cells. Overlying epithelium shows foci of pseudoepitheliomatous hyperplasia. This finding was compatible with granular cell tumor. Immunohistochemistry (IHC) staining of the cytoplasm and the nucleus for s-100 protein and cytoplasm for CD68 was also positive. The patient is symptom-free and without any sign of local recurrence or distant metastasis for 1.5 years post-operation.
Conclusion: Although it’s a rare tumor, the granular cell tumor must be considered in the differential diagnosis of soft tissue tumors. Surgical excision with a safe margin is the treatment of choice for the tumor. It is recommended that the patients must be observed for two years postoperatively.

Page 1 from 1     

© 2024 , Tehran University of Medical Sciences, CC BY-NC 4.0

Designed & Developed by : Yektaweb