Breast cancer has got much attention in the recent years as it is a one of the complex diseases that can threaten people lives. It can be determined from the levels of secreted proteins in the blood. In this project, we developed a method of finding a threshold to classify the probability of being affected by it in a population based on the levels of the related proteins in relatively small case-control samples. We applied our method to simulated and real data. The results showed that the method we used was accurate in estimating the probability of being diseased in both simulation and real data. Moreover, we were able to calculate the sensitivity and specificity under the null hypothesis of our research question of being diseased or not.
With the increasing prevalence of breast cancer among female internationally, occupies about 25% of all cases of cancer, with a measured 1.57 million up to date cases in 2012. Breast cancer has turn a most warning to health of female in Iraq, where it is the major cause of death among women after cardiovascular diseases, with a mortality rate of 23% related cancer. Recently there is a crucial requirement to include community pharmacists in health elevation activities to support awareness and early diagnosis of cancer, specially breast cancer. The aim of this study is to assess knowledge, attitude and perceived barriers amongst Iraqi community pharmacists towards health promotion of breast cancer. This study is cross sectional research. A
... Show MoreConsidering the expanding frequency of breast cancer and high incidence of vitamin D3 [25(OH)D3] insufficiently, this investigate pointed to explain a relation between serum [25(OH)D3] (the sunshine vitamin) level and breast cancer hazard. The current study aimed to see how serum levels of each [25(OH)D3], HbA1c%, total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), and triglyceride (TG) were affected a woman’s risk of getting breast cancer. In 40 healthy volunteers and 69 untreated breast cancer patients with clinical and histological evidence which include outpatients and hospitalized admissions patients at the Oncology Center, Medical City / Baghdad - Iraq. Venous blood samp
... Show MoreData mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the most effective parameter, particularly when Age<49.5. Whereas Ki67 appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu
... Show MoreA new synthesis of Schiff (K) 6 and Mannich bases (Q) 7 had formed compound (Q) 7 by reacting compound (K) with N-methylaniline at the presence of formalin 35% to given Mannich base (Q). Additionally, new complexes were formed by reacting Schiff base (K) with metal salts CuCl2·2H2O, PdCl2·2H2O, and PtCl6·6H2O by 2:1 of M:L ratio. New ligands and their complexes were characterized, exanimated, and confirmed through several techniques, including FTIR, UV-visible, 1H-NMR, 13C-NMR spectroscopy, CHN analysis, FAA, TG, molar conductivity, and magnetic susceptibility. These compounds and their complexes were screened against breast cancer cells. It was determined that several of these compounds had a significant anti-breast cancer effec
... Show MoreBackground: While two-thirds of breast cancers express hormone receptors for either estrogen (ER) and/or progesterone (PR) , genetically altered PI3K pathway was found in more than 70% of ER-positive breast cancers.An aberrant activity of cyclin-dependent kinase 1 (CDK1) in a wide variety of human cancers has selectively constituted an attractive pharmacological targets in MYC-dependent human breast cancer cells.
Aim of the study: Role of p110-beta as well as and CDK 1 in the pathogenesis of subset of breast cancers and contribution in their carcinogenesis.
Type of the study: is a retrospective study
Methods: This retr
... Show MoreColorectal cancer is the world's 3rd most frequent malignant neoplasm and the 4th most common cancer in Iraq. Leptin and Adiponectin are two major Adipocytokines produced by adipose cells that have opposite effects on the formation of colorectal tumors. Leptin induces tumor growth and metastasis, whereas Adiponectin inhibits it. 1,25-Dihydroxyvitamin D controls and limits cancer cell proliferation, differentiation, and survival. Vitamin C deficiency, on the other hand, has been regularly detected in cancer tissues and has potent anti-cancer properties. The purpose of this study was to look at the biochemical role of circulatory Adipocytokine levels (Adiponectin and Leptin) as well as the anti-cancer potentials of Vi
... Show MoreBackground: Breast Cancer is the most common malignancy among the Iraqi population; the majority of cases are still diagnosed at advanced stages with poor prospects of cure. Early detection through promoting public awareness is one of the promising tools in its control. Objectives: To evaluate the baseline needs for breast cancer awareness in Iraq through exploring level of knowledge, beliefs and behavior towards the disease and highlighting barriers to screening among a sample of Iraqi women complaining of breast cancer. Methodology: Two-hundred samples were enrolled in this study; gathered from the National
Objective This research investigates Breast Cancer real data for Iraqi women, these data are acquired manually from several Iraqi Hospitals of early detection for Breast Cancer. Data mining techniques are used to discover the hidden knowledge, unexpected patterns, and new rules from the dataset, which implies a large number of attributes. Methods Data mining techniques manipulate the redundant or simply irrelevant attributes to discover interesting patterns. However, the dataset is processed via Weka (The Waikato Environment for Knowledge Analysis) platform. The OneR technique is used as a machine learning classifier to evaluate the attribute worthy according to the class value. Results The evaluation is performed using
... Show MoreBreast cancer is the most diagnosed form of malignant tumour in Iraqi women. Tamoxifen and trastuzumab are highly effective adjuvant therapy for breast cancer.
This study's objectives were to define the patient's belief in tamoxifen or trastuzumab when used as adjuvant therapy and to determine the variation in belief between the two medications in a sample of Iraqi breast cancer patients.
The cross-section survey was conducted using the BMQ-Specific questionnaire. Ninety-seven participants (sixty-seven tamoxifen, thirty trastuzumab) participated in this study.
The mean of specific-necessity scale for tamoxifen was (3.7) and for trastuzumab (4). The findings showed a high necessity for both medicines, and there wer
... Show MoreStatisticians often use regression models like parametric, nonparametric, and semi-parametric models to represent economic and social phenomena. These models explain the relationships between different variables in these phenomena. One of the parametric model techniques is conic projection regression. It helps to find the most important slopes for multidimensional data using prior information about the regression's parameters to estimate the most efficient estimator. R algorithms, written in the R language, simplify this complex method. These algorithms are based on quadratic programming, which makes the estimations more accurate.