Objective To highlight the main demographic characteristics and clinical profiles of female patients registered with breast cancer in Iraq; focusing on the impact of age.Methods This retrospective study enrolled 1172 female patients who were diagnosed with breast cancer at the Main Center for Early Detection of Breast Cancer/Medical City Teaching Hospital in Baghdad. Data were extracted from an established information system, developed by the principal author under supervision of WHO, that was based on valid clinical records of Iraqi patients affected by breast cancer. The recorded information regarding clinical examination comprised positive palpable lumps, bloody nipple discharge, skin changes, bilateral breast involvement, tumor size, lymph node status, and the stage of the disease.Results The mean age at the presentation was 51 years; patients under the age of 50 constituted 46.8%. Overall 9.8% were not married, 22.4% were illiterate whereas 19.2% graduated from universities. About 72% of the patients had more than two children, merely 7.5% delivered their first child after the age of 35 years and only 11% were nulliparous. History of lactation and hormonal therapy was recorded in 57.6% and 19.4% respectively. Family history of cancer was positive in 28.8% and breast cancer specifically in 18.7%. Clinically, the most common presenting symptom was breast lumps (95%) followed by skin changes/ulcerations (6.7%) and bloody nipple discharge (4.3%).Bilateral breast involvement was encountered in 4.7%. More than two-thirds of the patients (68.2%) had palpable axillary lymph nodes; classifying 40.5% into advanced stages III and IV. In general stages I–IV comprised 12%, 47.5%, 31.9%, and 8.6% respectively. Upon stratifying the studied sample with respect to age at diagnosis, it was observed that the frequency of unmarried patients was significantly higher among younger women under the age of 50 years, whereas illiteracy and nulliparity features were statistically lower (p < 0.05).Conclusion A considerable proportion of breast cancer patients in Iraq still present with locally advanced disease at the time of diagnosis. That justifies the necessity to promote public awareness educational campaigns to strengthen our national early detection program. Excluding the marital status, level of education and number of parity, there was no statistical difference regarding the impact of age on the demographic and clinical profiles of breast cancer among premenopausal versus postmenopausal Iraqi patients.
BACKGROUND: HLA-B27 can effect clinical presentation and course of ankylosing spondylitis. Different detection techniques of HLA-B27 are available with variable sensitivities and specificities. OBJECTIVE: To compare serologic and molecular diagnostic techniques of detecting HLA-B27 status and to correlate it with some clinical variables among ankylosing spondylitis patients. PATIENTS AND METHODS: A cross-sectional study was conducted on 83 Iraqi patients with ankylosing spondylitis. Clinical and laboratory evaluations were reported. HLA-B27 status was determined in all patients by real-time PCR using HLA-B27 RealFast™ kit; ELISA method was used as well to detect soluble serum HLA-B27 antigens using Human Leukocyte Antigen® kit. RESULTS:
... Show MoreKE Sharquie, AA Noaimi, AH Muhammad Ali, 2008 - Cited by 3
Background: Diabetic patients have been reported to be more susceptible to gingivitis and periodontitis than healthy subjects. Many intracellular enzymes like (alkaline phosphatase- (ALP), aspartate aminotransferase- (AST) and alanine aminotransferase- (ALT) that are released outside cells into the gingival crevicular fluid (GCF) and saliva after destruction of periodontal tissue during periodontitis. This study was conducted to determine the periodontal health status and the levels of salivary enzymes (ALP, AST and ALT) of the study and control groups and to correlate the levels of these enzymes with clinical periodontal parameters in each study group. Subjects, Materials and Methods: One hundred subjects were enrolled in the study, with a
... Show MoreDisease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature
... Show MoreContracting cancer typically induces a state of terror among the individuals who are affected. Exploring how glucose excess, estrogen excess, and anxiety work together to affect the speed at which breast cancer cells multiply and the immune system’s response model is necessary to conceive of ways to stop the spread of cancer. This paper proposes a mathematical model to investigate the impact of psychological panic, glucose excess, and estrogen excess on the interaction of cancer and immunity. The proposed model is precisely described. The focus of the model’s dynamic analysis is to identify the potential equilibrium locations. According to the analysis, it is possible to establish four equilibrium positions. The stability analys
... Show MoreChronic inflammation can induce proliferative events and posttranslational DNA modifications in prostate tissue through oxidative stress. The present study was designed to evaluate the changes in serum levels of TNF-α, malomdialdehyde (MDA) and total antioxidant status (TAS) patients with different stages of malignant prostatic cancer (PCa) and benign prostatic hyperplasia (BPH). One hundred males (age range of 58-72 years) with different stages of malignant PCa were recruited from the Radiotherapy and Nuclear Medicine Teaching Hospital in Baghdad during the period from September 2010 to April 2011. The patients were categorized according to the 4 disease stages (I, II, III, and IV); 25 patients with benign prostatic hyperplasia (BPH)
... Show MoreAbstract
Prescribing drugs to patients to treat ailments or reducing their morbidity may not be enough, even if the drugs were all indicated and in the right dose. Clinical pharmacists play a pivotal role in conducting information and instruction to patients and conveying feedback to treating physician when appropriate, and the final goal is in the interest of the patient. Identification and classification of drug related problems and discussing them with the health care providers. Prospective, interventional, clinical study for 180 hemodialysis patients, and was designed as two phases, an observational phase to identify drug related problems and classifying them according to the latest Pharmaceutical
... Show MoreUrine proteomics have been an area of interest and recently in Kala-azar as an alternative sample type for serum or plasma. Because of simplicity, noninvasiveness of collection and simpler matrix. Many studies had detected an increased protein excretion in the urine of patients with active Kala-azar due to renal involvement particularly by an immunological related mechanism(s). This study have demonstrated the presence of three different protein profiles in Iraqi children (Patients: including 60 children aged 4-60 months) with defined Kala-azar using the conventional SDS-PAGE on urine samples. Urine protein profile in Kala-azar patients revealed three groups of banding patterns: group-1(33.4)% of the patients show the pattern of 5
... Show MoreThe last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of
... Show More