Assessment of Lipid peroxidation and total antioxidant capacity in patients with breast carcinoma

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Oxidative stress has been implicated in the development and progression of various cancers, including BC. Assessing lipid peroxidation and overall antioxidant status in breast cancer offers valuable information regarding the advancement, prognosis, and effectiveness of treatment options. Methods: A total of one hundred and fifty women, categorized into three groups Normal, Benign BC, and Malignant BC cases. Patients were selected and examined in the oncology clinic, fasting blood samples were collected and measurements of Total Antioxidant Capacity (TAC), Ox-LDL, CA 15.3, and CEA were performed. Then statistical analysis was done to compare the levels of these parameters in different groups and measure the analytical performance of TAC and Ox-LDL in BC. Results: The serum level of TAC in malignant cases was significantly decreased compared to benign group, 8.3 U/ml and 16.04 U/ml (P<0.001) respectively. Healthy controls show higher levels of TAC (43.4 U/ml). The levels of Ox-LDL in BC was significantly increased in malignant cases and benign group, 3831, and 1234 pg/ml, respectively compared to normal controls (682 pg/ml) (P<0.001). CEA and CA15-3 sharply increased in BC groups compared to control group. A significant area under the curve (AUC) for TAC (0.975, P<0.001), and Ox-LDL (0.986, P<0.001) was observed in ROC curve analysis. Conclusion: The present study revealed that breast cancer patients had lower TAC and higher Ox-LDL serum levels, indicating elevated oxidative stress. Additionally, TAC and Ox-LDL levels may serve as promising monitoring parameters in BC. Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Breast cancer is a prevalent and life-threatening disease that affects millions of women worldwide [ 1 ]. Studies exploring the mechanisms underlying breast cancer progression and treatment is crucial for developing effective therapies. One area of interest in breast cancer research is the evaluation of lipid peroxidation and total antioxidant status in patients with breast cancer. Lipid peroxidation is a process that involves the oxidative modification of lipids, especially low density lipoproteins, caused by reactive oxygen species (ROS) that can damage cells and tissues leading to serious pathologies [ 2 ]. On the other hand, dietary antioxidants and/or antioxidant defense system in the body play a vital role in protecting cells from oxidative stress [ 3 , 4 ]. Understanding the balance between lipid peroxidation and antioxidant status in breast cancer patients can provide valuable insights into disease progression, potential therapeutic strategies, and management options to increase the patient outcomes. The evaluation of lipid peroxidation and total antioxidant status in patients with breast cancer has garnered significant attention in the medical community as researchers strive to better understand the underlying mechanisms of this disease. Parisa Kangar et al found that levels of malondialdehyde (MDA), a marker of lipid peroxidation, were significantly higher in breast cancer patients compared to healthy controls [ 5 ]. This increase in MDA levels was associated with tumor size and stage, suggesting a link between lipid peroxidation and disease severity. Didžiapetrienė and colleagues investigate the oxidative stress biomarkers in breast cancer patients in pre-and post-operative periods and report the significance of these biomarkers to evaluate oxidative stress in breast cancer patients [ 6 ]. Moreover, Ioannis et al suggest a possible involvement of Ox-LDL in the process of malignancy in 32 patients diagnosed with breast or ovarian cancer [ 7 ]. In addition to lipid peroxidation, a considerable body of research has also explored total antioxidant status in breast cancer patients. A study by Khalaf et al. (2021) demonstrated that breast cancer patients had lower levels of antioxidants such as glutathione and ceruloplasmin compared to healthy individuals [ 8 ]. Oxidative stress, characterized by an imbalance between reactive oxygen species (ROS) production and antioxidant defense mechanisms, has been implicated in various pathophysiological processes, including diabetes, degenerative disease, atherosclerosis, and carcinogenesis [ 9 , 10 ]. Lipid peroxidation, a key consequence of oxidative stress, leads to the formation of reactive aldehydes and oxidation of native low density lipoproteins that can damage cellular structures and promote tumorigenesis, the imbalance between ROS production and antioxidant defense mechanisms may contribute to increased oxidative stress in breast cancer patients. The evaluation of lipid peroxidation and total antioxidant status in breast cancer patients holds immense clinical significance as it provides valuable insights into disease progression, prognosis, and treatment outcomes. Monitoring these biomarkers can help healthcare providers tailor personalized therapeutic strategies aimed at reducing oxidative stress, enhancing antioxidant capacity, and improving patient outcomes. Additionally, targeting lipid peroxidation pathways or boosting antioxidant defenses may represent novel therapeutic approaches for managing breast cancer and mitigating treatment-related side effects. The primary objective of the present study is to conduct a comparative analysis of circulating biomarkers associated with oxidative stress. Specifically, the focus will be on evaluating the levels of Total Antioxidant Capacity and Oxidized Low-Density Lipoproteins in individuals diagnosed with breast cancer and those who are considered healthy controls, and to evaluate the potential value of the quantitative analysis of these biomarkers and circulating markers CEA and CA 15 − 3 in the diagnosis of breast cancer. Understanding how lipid peroxidation and total antioxidant status influence breast cancer progression offers new avenues for precision medicine and personalized treatment strategies. Materials and Methods Subjects This study included 50 female patients with benign breast mass (mean age 33.9± 1.9 yrs) and 50 female patients with malignant breast cancer mainly of postmenopausal age not receiving antitumor therapy (mean age 50.6± 1.5) (Table 1). Patients were selected and examined in the oncology clinic of King Abdallah Medical City, In Makkah. Saudi Arabia. The control healthy women were 50 volunteers (mean age 40.7 ±0.93). All groups were age, weight, and menopausal state matched. Fasting blood sample was collected. Serum was separated by centrifugation (3500-4000 rpm) of clotted samples and stored at -20 °C until analysis. Ethics Statement This study was carried out in accordance with the ethical guidelines of the 1975 Declaration of Helsinki and was approved by the medical ethics committee of the Faculty of Medicine- Umm Al-Qura University, Makkah, KSA. Written informed consent was obtained from every participated patient. Characteristics of the study groups All participants underwent a clinical examination and a questionnaire including medical and family history. The exclusion criteria were for those with positive neoadjuvant chemotherapy or past-history of malignancy, radiotherapy or/and chemotherapy. Blood samples were obtained before any surgical intervention. Medical records of included subjects were reviewed for cytopathology reports including stage, tumor characteristics, Estrogen and Progesterone Receptors status. History and clinical examination were carried out to obtain information on demographic characteristics including reproductive variables (age at menarche, age at menopause, age at first full term pregnancy, number of full term pregnancies, previous use of exogenous hormones such as hormone replacement therapy and oral contraceptives), medical history, and tobacco smoking. Family history of cancer in general including breast cancer was collected for first-degree relatives (parents and siblings) and for second-degree relatives (grandparents, uncles and aunts). BC was pathologically staged according to the TNM classification [11]. Determination of serum levels of (Total Antioxidant Capacity) TAC TAC serum levels were determined by a competitive inhibition enzyme immunoassay kit, (MBS9304157, MyBioSource, sunny Southern California, San Diego (USA)) according to the provided assay procedure. ( https://www.mybiosource.com/ ). Determination of serum levels of Oxidized low Density Lipoprotein (Ox-LDL) Ox-LDL serum levels were determined by a competitive inhibition enzyme immunoassay kit, (SEA527Hu 96 Testes, Cloud-Clone Corp, Houston, USA) according to the provided assay procedure. (http://www.Cloud.Clone.US). Determination of Serum levels of cancer antigen 15-3 (CA15-3) Serum CA15.3 was measured using an ELISA kit (My BioSource, Inc. San Diego, USA). CA15-3 ELISA test is an adapted solid-phase sequential sandwich ELISA. Samples and biotinylated monoclonal antibodies are added to wells coated with streptavidin. CA15-3 in the patient sample binds to a biotinylated capture antibody. The biotinylated antibody simultaneously binds to the streptavidin-coated plate. After a wash step, anti-CA15-3-HRP enzyme conjugate is added and forms a sandwich around captured CA15-3. Unbound antibodies are washed off. TMB substrate is added resulting in the development of a blue color. The concentration of CA15-3 is directly proportional to the color intensity developed. A standard curve is generated relating color intensity to CA15-3 concentration. Determination of serum levels of carcinoembryonic antigen (CEA) Serum CEA was measured using an ELISA kit (Cloud-clone Corp., Assembled by US Co Life Science Inc. USA). This kit is a Sandwich enzyme immunoassay. The microtiter plate provided in this kit has been pre-coated with an antibody specific to Carcinoembryonic Antigen (CEA). Standards or samples are then added to the appropriate microtiter plate wells with a biotin-conjugated antibody specific to Carcinoembryonic Antigen (CEA). Next, Avidin conjugated to Horseradish Peroxidase (HRP) is added to each microplate well and incubated. After TMB substrate solution is added, only those wells that contain Carcinoembryonic Antigen (CEA), biotin-conjugated antibody and enzyme-conjugated Avidin will exhibit a change in color. The enzyme-substrate reaction is terminated by the addition of sulphuric acid solution and the color change is measured spectrophotometrically at a wavelength of 450nm ± 10nm. The concentration of Carcinoembryonic Antigen (CEA) in the samples is then determined by comparing the O.D. of the samples to the standard curve. The detection range was from 19.6 to1250 ng/ml. Statistical Analysis Data was analyzed using SPSS (version 20, Sydney, NSW, Australia). Statistical analysis was performed using an independent sample test for parametric variables and Chi-square for categorical variables. Relationship between variables was detected by Pearson’s correlation coefficient and linear regression analysis was performed to analyze TAC and Ox-LDL as dependent variables. Quantitative data was expressed as mean ± SE and qualitative data as frequencies and percentages. The differences were considered significant at p-value <0.05. Evaluation of the diagnostic performance of serum TAC, Ox-LDL, and CA15.3 using ROC curve analysis We apply to our data set the analysis of the Receiver Operating Characteristic (ROC) curve. Accuracy is measured by the area under the ROC curve. An area of 1 represents a perfect test; an area of 0.5 represents a worthless test. A rough guide for classifying the accuracy of a diagnostic test is the traditional academic point system: 0.9-1 = excellent (A), 0.8-0.9 = good (B), 0.7-0.8 = fair (C), 0.6-0.7 = poor (D), and 0.5-0.6 = fail (F). Results The clinical and demographic characteristics of subjects: Blood samples from diagnosed breast cancer patients were collected before any treatment. The diagnosis was confirmed by histopathology, clinical data as well as medical records. The clinical details and demographic characteristics of both BC and Benign patients are summarized in Table 1. The BC and benign patients were age-matched with control subjects. Out of 50 BC patients, 6 (12%) patients were grade I, 31 (62%) were grade II, 11 (22%) were grade III, and 2 (4%) were grade IV (Table 1). According to immunohistochemistry data estrogen-receptor-positive (ER+), samples were 35 (70%), progesterone-receptor-positive (PR+) were 28 (56%), and human epidermal growth factor receptor 2 positive (Her2+) were 14 (28%) (Table 1). Out of 50 BC patients, 48 (96%) had mass 2 (4%) had no mass, 2 (4%) had discharge (including blood discharge) and 48 (96%) had no discharge. Out of 50 benign patients with benign breast mass, 39 were diagnosed as fibroadenoma, while 11 patients were diagnosed as other types including granulomatous mastitis, papilloma, fibroglandular tissue, ductal ectasia…etc. (Table 1). Histopathological studies of 50 BC patients showed invasive ductal carcinoma in 47 (94%) and lobular carcinoma in 3 (6%). In BC patients 37 (74%) had lymph nodes, 13 (26%) hadn’t any lymph nodes and 21 (42 %) had cancer metastasis and 29 (58%) hadn’t any cancer metastasis as shown in Table 1. Table 1: The clinical and characteristic features of the studied groups: Serum levels of TAC, Ox-LDL, CA15-3, and CEA: The serum level of TAC in BC was highly significantly decreased than in patients with benign lesions with mean values of 8.3 U/ml and 16.04 U/ml (P<0.001) respectively (Table 2 and Fig. 1) in comparison with normal health control (43.4 U/ml). By contrast, there was no significant difference between the levels of TAC (16.04 U/ml) in the benign group compared to the control group. Figure 1: Serum level of TAC, Ox-LDL, CA15.3, and CEA compared between the Benign and Malignant BC groups with the normal group*** p<.001 Also, The serum level of Ox-LDL in BC was highly and significantly increased in malignant cases compared to patients with benign lesions with mean values of 3831 pg/ml and 1234 pg/ml (P<0.001), respectively (Table 2 and Fig. 1) in comparison with normal health control (682 pg/ml). In contrast, there was no significant difference between the levels of Ox-LDL in the benign group compared to the controls. Table 2: The serum levels of studied biomarkers in normal, benign, and malignant groups of breast cancer patients. The data are expressed in Mean ± SE: Remarkably, the mean value of the levels of the other studied two parameters CEA and CA15-3 sharply increased in the BC group compared to a control group. The mean CEA was found to be 472.56, 328.42, and 314.55 ng/dl in malignant, benign and control groups respectively (P<.001), while the means of CA 15.3 was 57.28, 15.16, and 14.35 U/ml in malignant, benign and controls respectively, with a significant difference between groups (P<.001), as shown in Table 2 and Fig. 1. Correlations of TAC, Ox-LDL, and CA15-3: The studied marker TAC showed a significant negative correlation with CA15-3 ( r = 0.255, P<0.01). A significant positive correlation between Ox-LDL and CA15-3 was observed (r= 0.441, P<0.001). A significant negative correlation between TAC and Ox-LDL (r = 0.419, P<0.001) is shown in Figure 2. Figure 2: Correlation between the serum level of TAC, Ox-LDL and CA15.3, ( A ) TAC and CA 15.3, ( B ) Ox-LDL and CA 15.3 Association between predictive immunohistochemistry (IHC) and TAC, Ox-LDL : Serum levels of TAC, Ox-LDL, CA15-3, and CEA in the BC patients with different histopathology observations ( A ) positive estrogen receptors (ER), ( B ) positive progesterone receptors (PR), and ( C ) positive human epidermal growth factor receptor-2 (Her2/neu) are illustrated in figure 3. Figure 3: Serum levels of TAC, Ox-LDL, CA15-3, and CEA in the BC patients with different histopathology observations ( A ) positive estrogen receptors (ER), ( B ) positive progesterone receptors (PR), and ( C ) positive human epidermal growth factor receptor-2 (Her2/neu). Diagnostic performance of serum TAC and Ox-LDL for breast cancer: The analysis of the ROC curve of TAC serum levels of studied subjects was applied, to, know how well the TAC test discrimination between the samples with and without BC. Figure 4 shows the area under the ROC curve. A significant area under the curve (AUC) was observed from data analysis of the ROC curve (0.975, P<0.001). The sensitivity (100) and specificity (86.4%) were selected at a cutoff value of TAC equal to 18.9U/ml (Table 3). Also, the analysis of the ROC curve of Ox-LDL serum levels of studied subjects was applied, to know how well the Ox-LDL test discrimination between the samples with and without BC. Figure 4 shows the area under the ROC curve. Figure 4: ROC curve analysis and interactive dot diagrams of studied parameters in BC patients . Sens: sensitivity; spec : specificity, Blue lines indicate the cutoff value of each parameter. A significant area under the curve (AUC) was observed from data analysis of the ROC curve (0.986, P<0.001). The sensitivity (97.9) and specificity (100 %) were selected at a cutoff value of Ox-LDL equal to 998 pg/ml as shown in Table 3. Table 3. Diagnostic data of serum levels of TAC, Ox-LDL, and CA 15-3 using ROC curve Discussion Cancer is one of the most frequent causes of death worldwide with breast cancer as the most common malignancy in women, accounting for 30% of all cancers diagnosed in women each year [ 12 ]. Biomarkers that explore the progression and are used as diagnostic tools in the disease attract considerable attention in the field. Few biomarkers are used for a better understanding of how oxidative stress is involved in cancer pathophysiology [ 13 ]. The present study was conducted to compare levels of biomarkers related to oxidative stress in individuals with breast cancer and healthy individuals. Specifically, the study will focus on Total Antioxidant Capacity and Oxidized Low-Density Lipoproteins, as well as the potential diagnostic value of CEA and CA 15 − 3 in breast cancer. Lipid peroxidation and total antioxidant capacity (TAC) in breast cancer patients show an intricate relationship in previous works. Studies have revealed that lipid peroxidation is significantly elevated in breast cancer patients, suggesting increased oxidative stress [ 14 , 15 ]. Furthermore, the oxidative/antioxidant profile in breast cancer patients was influenced by various prognostic factors such as cancer stage, tumor size, and molecular markers, highlighting the dynamic interplay between oxidative stress and antioxidant capacity in breast cancer progression [ 13 ]. In our study, the results of TAC and Ox-LDL levels support the previous findings reporting that the increased formation or inadequate removal of ROS may lead to cancer [ 6 , 13 ]. OxLDL levels were found to be increased and TAC levels were found to be decreased in cases of BC compared to the control group. Moreover, the most increased levels of Ox-LDL were observed in malignant cases as shown in Fig. 1. When we read these results with the decreased antioxidant defense as expressed in low levels of TAC in malignant cases, we can suggest that oxidative stress is correlated strongly with the development of the disease. These findings are inconsistent with previous studies which suggest that disturbance in antioxidant defense and oxidative stress promotes DNA damage in cancers and may be associated with benign and malignant tumors [ 16 , 17 ]. Multiple marker assays may significantly improve the sensitivity of detecting heterogeneous tumor cells compared with single marker assays [ 18 ]. Multiple serum-based tumor markers have been described for breast cancer, the most widely tumor markers used are CA 15 − 3 and CEA [ 19 ]. Breast cancer is only one condition that may cause high levels of CA 15 − 3. The pre-operative concentration of CA 15 − 3 thus might be combined with existing prognostic factors for predicting outcomes in patients with newly diagnosed breast cancer. It has been proposed that the assessment of multiple tumor markers in one blood sample would enhance the sensitivity of tumor cell detection [ 20 ]. TAC values, according to our data (sensitivity 100% and specificity 86.4%) as shown in Fig. 4, could be a potential marker for identifying BC patients from healthy people. it could be used as a screening indicator for BC early identification. Moreover, if oxidative stress is a treatment target, it could be applied as a disease marker for monitoring and evaluating the therapeutic effect. Many previous studies suggest that antioxidant defenses can be increased through physiological signaling, dietary components, or potential pharmaceutical intervention [ 9 , 13 ]. The diagnostic value of Ox-LDL in our study shows considerable good performance, especially in excluding negative cases of BC as reflected by its high specificity (100%), with a sensitivity of 97.9% and AUC of 0.986. The levels of TAC were found to be significantly higher in BC patients with negative ER and PR whereas the level of CA15-3 is significantly higher in BC patients with negative Her2/neu. There was no difference in the levels of these parameters in BC patients with positive ER and PR tests as shown in Fig. 3. Several investigations have found a relationship between estrogen-induced breast cancer and oxidative stress [ 21 ]. Furthermore, it has been documented that oxidative DNA damage is highly correlated with the presence of the estrogen receptor (ER) and is higher in breast cancer tissue as compared to normal breast tissue [ 22 , 23 ]. These findings may suggest that oxidative stress might be related to ER expression, and thus there is a need for further investigation to explore this relationship. A significant negative correlation was observed between TAC and the biomarkers under investigation, CA15-3, and CEA, supporting the proposed relationship with BC, Fig. 2A. Furthermore, we observed that Ox-LDL levels significantly and positively correlated with the two investigated biomarkers, CA15-3 and CEA as well as shown in Fig. 2B. This suggests that the pattern of Ox-LDL concentration increases with both known biomarkers in a nearly comparable way in malignant, benign, and normal samples. Our findings could potentially endorse the diagnostic utility of TAC and Ox-LDL in BC. To the best of our knowledge, prior research evaluating the oxidative stress state of BC patients has concentrated on one or a small number of oxidants/antioxidant indicators, and the use of these biomarkers in clinical settings is still not well-established [ 24 , 25 ]. Even though these results show a correlation between the investigated biomarkers and the onset and development of BC, they are insufficient to indicate the patients' actual oxidative stress state or to identify a viable panel of diagnostic or prognostic biomarkers for BC. The utilization of Ox-LDL, TAC, and oxidative stress in the management of breast cancer shows great potential as an approach that can be further developed to enhance patient outcomes and improve overall management. However, interpretation of these biomarkers should be handled with care and based on proper assessment of analytical and clinical validations because these biomarkers in particular were correlated to many other pathologic scenarios such as hyperglycemia [ 2 ], cancers [ 13 , 16 ], aging [ 26 ], and cardiovascular events [ 27 ]. Based on the solid foundations of these established relationships, further research is required to validate the utilization of these biomarkers in clinical settings. Conclusion In the present study, it was observed that breast cancer patients exhibited lower serum levels of TAC and higher serum levels of Ox-LDL, indicating elevated oxidative stress compared to the control group. This suggests a potential association between increased oxidative stress and breast cancer. Based on our findings, TAC and Ox-LDL levels could serve as additional parameters for monitoring cancer prevention, diagnosis, and treatment. The exact mechanism behind the heightened oxidative stress, whether it stems from increased ROS production or reduced antioxidant defenses, remains unclear. Therefore, conducting further studies on oxidative stress and antioxidant therapy in breast cancer is recommended. Declarations Acknowledgments The authors express their gratitude to the staff of the oncology unit at King Abdallah Medical City in Makkah for their assistance in conducting the research by examining the sample individuals and collecting data. Conflicts of Interest All authors declare no conflicts of interest from any person or organization in the subject matter or materials discussed in this manuscript. Funding Non Data availability Available on reasonable request. 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Nutrients, 11(9) Tables Table 1: The clinical and characteristic features of the studied groups P value Healthy ( N = 50) Benign ( N = 50) Malignant ( N = 50 ) Characteristic Features / pathological parameters mean±SE (%) No. mean±SE (%) No. mean±SE (%) No. .076 40.8± 0.93 42 % 58 % 0.0% 21 29 0 33.9± 1.9 66 % 30 % 4 % 33 15 2 50.6± 1.5 16.3% 67.3% 16.3% 8 33 8 age ˂40 40-60 >60 .066 66 % 34 % 33 17 96 % 4 % 48 2 58 % 42 % 29 21 Menstrual phase Premenopausal Postmenopausal .066 64 % 34% 2% 0 % 32 17 1 0 58 % 40 % 2 % 0 % 29 20 1 0 69.4% 20.4% 4.1 % 6.1% 34 10 2 3 Marital Status Married Single Divorced Widowed .047 30% 70% 15 35 52% 48% 26 24 71.4% 28.6% 35 14 Parity status Nulliparous Multiparous .170 34.9% 76% 24 38 54% 46% 27 23 68% 32% 34 16 Lactation History Lactating Non-Lactating .076 4% 96% 2 48 4 % 96 % 2 48 2% 98% 1 48 Smoking Smoker Non-Smokers .342 10% 90% 5 45 12% 88% 6 44 14% 86% 7 43 Family history of BC Yes No 78 % 22% 39 11 Benign Types fibro adenoma others 54% 34% 12% 27 17 6 44% 56% 22 28 0 Right Breast Side of complain Left Breast Both side 82% 18% 41 9 96% 4% 48 2 Mass No-Mass 8% 92% 4 46 4% 96% 2 48 Discharge No-Discharge 94 % 6 % 47 3 Cancer types Invasive ductal carcinoma Lobular carcinoma 42% 58.% 21 29 Cancer metastasis Yes no 74% 26% 37 13 LN involvement Yes No 12 % 62% 22% 4% 6 31 11 2 Grade: grade I grade II grade III grade IV 70% 56% 28% 35 28 14 ER Immunohistochemistry (IHC) PR Her2 Table 2: The serum levels of studied biomarkers in normal, benign, and malignant groups of breast cancer patients. The data are expressed in Mean ± SE Normal Benign Malignant P value TAC (U/ml) Mean ± SE Range N 43.3 ± 3.09 12-81 45 16.04 ± 0.75 6.7-26.3 40 8.3±0.7 2-18 40 P<.001 Ox-LDL (pg/ml) Mean ± SE Range N 682 ± 29.7 331-998 40 1234± 70.3 466-2121 36 3831±367 643-9951 47 P<.001 CEA (ng/ml) Mean ± SE Range N 314.55 ± 15.67 148 – 494 40 328.42 ± 25.27 107 – 780 38 472.56 ± 44.96 137 – 990 39 P<.001 CA15-3 (U/ml) Mean ± SE Range N 14.35 ± 1.07 3.3 – 24.7 29 15.16 ± 0.91 4 – 29 44 57.28 ± 8.89 17.1 – 170 32 P<.001 Table 3. Diagnostic data of serum levels of TAC, ox-LDL, and CA 15-3 using ROC curve Variable AUC SE 95% CI sensitivity specificity Cutoff value TAC 0.975 0.0247 0.870 to 0.997 100 86.4 18.9 Ox-LDL 0.986 0.0225 0.887 to 0.999 97.9 100 998 CA 15.3 0.913 0.0518 0.736 to 0.947 69.7 96.4 22.1 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4477726","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":307000667,"identity":"9f3e752c-cb2a-42b2-822f-e685ec5ff051","order_by":0,"name":"Abdullatif Taha Babakr","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIiWNgGAWjYFACHgZmBoYEBn4Ij5kIHWxQLZINJGsxOECsFv75vQc/F9Sk5RvfSN4mwVBhndjAf/gBXi0Sx/iSpWccy7HcdiOtTILhTHpig0SaAX5rjvEYSPOwVRiY3cgxk2BsOwzUwoBfi/wxHuPfPP8qDIxngLT8A2rhP/4BrxaDYzxm0rxtOQYGEiAtDUAtDDn4bTE8lpdmPbMvzUDizLNii4Rj6cZtEjkFeLXIHT57+HbBt2QD/vbkjTc+1FjL9vMf34BXC4ojgdEDjCii1YO1jIJRMApGwSjABgAxJ0HMpw0d2wAAAABJRU5ErkJggg==","orcid":"","institution":"Umm Al-Qura University","correspondingAuthor":true,"prefix":"","firstName":"Abdullatif","middleName":"Taha","lastName":"Babakr","suffix":""},{"id":307000668,"identity":"6b991f9d-a420-4d43-8dd4-ab744a2067a4","order_by":1,"name":"Mohamed Mahmoud Nour Eldein","email":"","orcid":"","institution":"Umm Al-Qura University","correspondingAuthor":false,"prefix":"","firstName":"Mohamed","middleName":"Mahmoud Nour","lastName":"Eldein","suffix":""}],"badges":[],"createdAt":"2024-05-25 17:51:42","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4477726/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4477726/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58155163,"identity":"2d34c4bd-67ab-4682-87b4-69a1171c0191","added_by":"auto","created_at":"2024-06-11 20:43:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":76279,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eSerum level of TAC, Ox-LDL, CA15.3, and CEA compared between the Benign and Malignant BC groups with the normal group*** p\u0026lt;.001\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4477726/v1/0350217edd8989ad7b7ebb28.png"},{"id":58153856,"identity":"beff921b-c83c-4cee-8311-41af171fc14b","added_by":"auto","created_at":"2024-06-11 20:35:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":63199,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eCorrelation between the serum level of TAC, Ox-LDL and CA15.3, \u003c/em\u003e(\u003cstrong\u003eA\u003c/strong\u003e) TAC and CA 15.3, (\u003cstrong\u003eB\u003c/strong\u003e) Ox-LDL and CA 15.3\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4477726/v1/2ef367711c44ef66fdd679e7.png"},{"id":58153859,"identity":"b1e8d8bf-1464-4ff2-96e3-24acb3d0a609","added_by":"auto","created_at":"2024-06-11 20:35:57","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":136808,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eSerum levels of TAC, Ox-LDL, CA15-3, and CEA in the BC patients with different histopathology observations\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e(\u003cstrong\u003eA\u003c/strong\u003e) positive estrogen receptors (ER), (\u003cstrong\u003eB\u003c/strong\u003e) positive progesterone receptors (PR), and (\u003cstrong\u003eC\u003c/strong\u003e) positive human epidermal growth factor receptor-2 (Her2/neu).\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4477726/v1/70d8788d6c10113d59394477.png"},{"id":58153857,"identity":"da984d21-803d-48e2-beea-35d313b0bcbe","added_by":"auto","created_at":"2024-06-11 20:35:56","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":536655,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eROC curve analysis and interactive dot diagrams of studied parameters in BC patients\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e. Sens: \u003c/strong\u003e\u003c/em\u003e\u003cem\u003esensitivity; \u003c/em\u003e\u003cem\u003e\u003cstrong\u003espec\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e: specificity, Blue lines indicate the cutoff value of each parameter.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4477726/v1/71e86c5b1003b8a311029dac.png"},{"id":58155919,"identity":"036ff1c6-d888-496b-85ff-61c2a3b51fbd","added_by":"auto","created_at":"2024-06-11 21:00:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1630728,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4477726/v1/e96913a5-ad06-4c18-9089-097df668d8ab.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessment of Lipid peroxidation and total antioxidant capacity in patients with breast carcinoma","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBreast cancer is a prevalent and life-threatening disease that affects millions of women worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Studies exploring the mechanisms underlying breast cancer progression and treatment is crucial for developing effective therapies. One area of interest in breast cancer research is the evaluation of lipid peroxidation and total antioxidant status in patients with breast cancer. Lipid peroxidation is a process that involves the oxidative modification of lipids, especially low density lipoproteins, caused by reactive oxygen species (ROS) that can damage cells and tissues leading to serious pathologies [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. On the other hand, dietary antioxidants and/or antioxidant defense system in the body play a vital role in protecting cells from oxidative stress [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Understanding the balance between lipid peroxidation and antioxidant status in breast cancer patients can provide valuable insights into disease progression, potential therapeutic strategies, and management options to increase the patient outcomes.\u003c/p\u003e \u003cp\u003eThe evaluation of lipid peroxidation and total antioxidant status in patients with breast cancer has garnered significant attention in the medical community as researchers strive to better understand the underlying mechanisms of this disease. Parisa Kangar et al found that levels of malondialdehyde (MDA), a marker of lipid peroxidation, were significantly higher in breast cancer patients compared to healthy controls [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This increase in MDA levels was associated with tumor size and stage, suggesting a link between lipid peroxidation and disease severity. Didžiapetrienė and colleagues investigate the oxidative stress biomarkers in breast cancer patients in pre-and post-operative periods and report the significance of these biomarkers to evaluate oxidative stress in breast cancer patients [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Moreover, Ioannis et al suggest a possible involvement of Ox-LDL in the process of malignancy in 32 patients diagnosed with breast or ovarian cancer [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition to lipid peroxidation, a considerable body of research has also explored total antioxidant status in breast cancer patients. A study by Khalaf et al. (2021) demonstrated that breast cancer patients had lower levels of antioxidants such as glutathione and ceruloplasmin compared to healthy individuals [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Oxidative stress, characterized by an imbalance between reactive oxygen species (ROS) production and antioxidant defense mechanisms, has been implicated in various pathophysiological processes, including diabetes, degenerative disease, atherosclerosis, and carcinogenesis [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Lipid peroxidation, a key consequence of oxidative stress, leads to the formation of reactive aldehydes and oxidation of native low density lipoproteins that can damage cellular structures and promote tumorigenesis, the imbalance between ROS production and antioxidant defense mechanisms may contribute to increased oxidative stress in breast cancer patients.\u003c/p\u003e \u003cp\u003eThe evaluation of lipid peroxidation and total antioxidant status in breast cancer patients holds immense clinical significance as it provides valuable insights into disease progression, prognosis, and treatment outcomes. Monitoring these biomarkers can help healthcare providers tailor personalized therapeutic strategies aimed at reducing oxidative stress, enhancing antioxidant capacity, and improving patient outcomes. Additionally, targeting lipid peroxidation pathways or boosting antioxidant defenses may represent novel therapeutic approaches for managing breast cancer and mitigating treatment-related side effects.\u003c/p\u003e \u003cp\u003eThe primary objective of the present study is to conduct a comparative analysis of circulating biomarkers associated with oxidative stress. Specifically, the focus will be on evaluating the levels of Total Antioxidant Capacity and Oxidized Low-Density Lipoproteins in individuals diagnosed with breast cancer and those who are considered healthy controls, and to evaluate the potential value of the quantitative analysis of these biomarkers and circulating markers CEA and CA 15\u0026thinsp;\u0026minus;\u0026thinsp;3 in the diagnosis of breast cancer. Understanding how lipid peroxidation and total antioxidant status influence breast cancer progression offers new avenues for precision medicine and personalized treatment strategies.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eSubjects\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study included 50 female patients with benign breast mass (mean age 33.9\u0026plusmn; 1.9 yrs)\u0026nbsp;and 50 female patients with malignant breast cancer mainly of postmenopausal age not receiving antitumor therapy (mean age 50.6\u0026plusmn; 1.5)\u0026nbsp;(Table 1). Patients were selected and examined in the oncology clinic of King Abdallah Medical City, In Makkah. Saudi Arabia. \u0026nbsp;The control healthy women were 50 volunteers (mean age 40.7\u0026nbsp;\u0026plusmn;0.93).\u0026nbsp;All groups were age, weight, and menopausal state matched.\u0026nbsp;\u0026nbsp;Fasting blood sample was collected. Serum was separated by centrifugation (3500-4000 rpm) of clotted samples and stored at -20 \u0026deg;C until analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was carried out in accordance with the ethical guidelines of the 1975 Declaration of Helsinki and was approved by the medical ethics committee of the Faculty of Medicine- Umm Al-Qura University, Makkah, KSA. Written informed consent was obtained from every participated patient.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCharacteristics of the study groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants underwent a clinical examination and a questionnaire including medical and family history. The exclusion criteria were for those with positive neoadjuvant chemotherapy or past-history of malignancy, radiotherapy or/and chemotherapy. Blood samples were obtained before any surgical intervention.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMedical records of included subjects were reviewed for cytopathology reports including stage, tumor characteristics, Estrogen and Progesterone Receptors status. History and clinical examination were carried out to obtain information on demographic characteristics including reproductive variables (age at menarche, age at menopause, age at first full term pregnancy, number of full term pregnancies, previous use of exogenous hormones such as hormone replacement therapy and oral contraceptives), medical history, and tobacco smoking. Family history of cancer in general including breast cancer was collected for first-degree relatives (parents and siblings) and for second-degree relatives (grandparents, uncles and aunts). BC was pathologically staged according to the TNM classification [11].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetermination of serum levels of (Total Antioxidant Capacity) TAC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTAC serum levels were determined by a competitive inhibition enzyme immunoassay kit, (MBS9304157, MyBioSource, sunny Southern California, San Diego (USA)) according to the provided assay procedure. (\u003ca href=\"https://www.mybiosource.com/\"\u003ehttps://www.mybiosource.com/\u003c/a\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetermination of serum levels of Oxidized low Density Lipoprotein (Ox-LDL)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOx-LDL serum levels were determined by a competitive inhibition enzyme immunoassay kit, (SEA527Hu 96 Testes, Cloud-Clone Corp, Houston, USA) according to the provided assay procedure. (http://www.Cloud.Clone.US).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetermination of Serum levels of cancer antigen 15-3 (CA15-3)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSerum CA15.3 was measured using an ELISA kit (My BioSource, Inc. San Diego, USA). CA15-3 ELISA test is an adapted solid-phase sequential sandwich ELISA. Samples and biotinylated monoclonal antibodies are added to wells coated with streptavidin. CA15-3 in the patient sample binds to a biotinylated capture antibody. The biotinylated antibody simultaneously binds to the streptavidin-coated plate. After a wash step, anti-CA15-3-HRP enzyme conjugate is added and forms a sandwich around captured CA15-3. Unbound antibodies are washed off. TMB substrate is added resulting in the development of a blue color. The concentration of CA15-3 is directly proportional to the color intensity developed. A standard curve is generated relating color intensity to CA15-3 concentration.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetermination of serum levels of carcinoembryonic antigen (CEA)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSerum CEA was measured using an ELISA kit (Cloud-clone Corp., Assembled by US Co Life Science Inc. USA). This kit is a Sandwich enzyme immunoassay. The microtiter plate provided in this kit has been pre-coated with an antibody specific to Carcinoembryonic Antigen (CEA). Standards or samples are then added to the appropriate microtiter plate wells with a biotin-conjugated antibody specific to Carcinoembryonic Antigen (CEA). Next, Avidin conjugated to Horseradish Peroxidase (HRP) is added to each microplate well and incubated. After TMB substrate solution is added, only those wells that contain Carcinoembryonic Antigen (CEA), biotin-conjugated antibody and enzyme-conjugated Avidin will exhibit a change in color. The enzyme-substrate reaction is terminated by the addition of sulphuric acid solution and the color change is measured spectrophotometrically at a wavelength of 450nm \u0026plusmn; 10nm. The concentration of Carcinoembryonic Antigen (CEA) in the samples is then determined by comparing the O.D. of the samples to the standard curve. The detection range was from 19.6 to1250 ng/ml.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData was analyzed using SPSS (version 20, Sydney, NSW, Australia). Statistical analysis was performed using an independent sample test for parametric variables and Chi-square for categorical variables. Relationship between variables was detected by Pearson\u0026rsquo;s correlation coefficient and linear regression analysis was performed to analyze TAC and Ox-LDL as dependent variables. Quantitative data was expressed as mean \u0026plusmn; SE and qualitative data as frequencies and percentages.\u0026nbsp;The differences were considered significant at p-value \u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEvaluation of the diagnostic performance of serum TAC, Ox-LDL, and CA15.3 using ROC curve analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe apply to our data set the analysis of the Receiver Operating Characteristic (ROC) curve. Accuracy is measured by the area under the ROC curve. An area of 1 represents a perfect test; an area of 0.5 represents a worthless test. A rough guide for classifying the accuracy of a diagnostic test is the traditional academic point system: 0.9-1 = excellent (A), 0.8-0.9 = good (B), 0.7-0.8 = fair (C), 0.6-0.7 = poor (D), and 0.5-0.6 = fail (F).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eThe clinical and demographic characteristics of subjects:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBlood samples from diagnosed breast cancer patients were collected before any treatment. The diagnosis was confirmed by histopathology, clinical data as well as medical records. The clinical details and demographic characteristics of both BC and Benign patients are summarized in Table 1. The BC and benign patients were age-matched with control subjects. Out of 50 BC patients, 6 (12%) patients were grade I, 31 (62%) were grade II, 11 (22%) were grade III, and 2 (4%) were grade IV (Table 1). According to immunohistochemistry data estrogen-receptor-positive (ER+), samples were 35 (70%), progesterone-receptor-positive (PR+) were 28 (56%), and human epidermal growth factor receptor 2 positive (Her2+) were 14 (28%) (Table 1). Out of 50 BC patients, 48 (96%) had mass 2 (4%) had no mass, 2 (4%) had discharge (including blood discharge) and 48 (96%) had no discharge. Out of 50 benign patients with benign breast mass, 39 were diagnosed as fibroadenoma, while 11 patients were diagnosed as other types including granulomatous mastitis, papilloma, fibroglandular tissue, ductal ectasia\u0026hellip;etc. (Table 1). Histopathological studies of 50 BC patients showed invasive ductal carcinoma in 47 (94%) and lobular carcinoma in 3 (6%). In BC patients 37 (74%) had lymph nodes, 13 (26%) hadn\u0026rsquo;t any lymph nodes and 21 (42 %) had cancer metastasis and 29 (58%) hadn\u0026rsquo;t any cancer metastasis as shown in Table 1.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1:\u003c/strong\u003e The clinical and characteristic features of the studied groups:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSerum levels of TAC, Ox-LDL, CA15-3, and CEA:\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe serum level of TAC in BC was highly significantly decreased than in patients with benign lesions with mean values of 8.3 U/ml and 16.04 U/ml (P\u0026lt;0.001) respectively (Table 2 and Fig. 1) in comparison with normal health control (43.4 U/ml). By contrast, there was no significant difference between the levels of TAC (16.04 U/ml) in the benign group compared to the control group.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 1:\u003c/strong\u003e Serum level of TAC, Ox-LDL, CA15.3, and CEA compared between the Benign and Malignant BC groups with the normal group*** p\u0026lt;.001\u003c/p\u003e\n\u003cp\u003eAlso, The serum level of Ox-LDL in BC was highly and significantly increased in malignant cases compared to patients with benign lesions with mean values of \u0026nbsp;3831 pg/ml and 1234 pg/ml (P\u0026lt;0.001), respectively (Table 2 and Fig. 1) in comparison with normal health control (682 pg/ml). In contrast, there was no significant difference between the levels of Ox-LDL in the benign group compared to the controls.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u0026nbsp;\u003c/strong\u003eThe serum levels of studied biomarkers in normal, benign, and malignant groups of breast cancer patients. The data are expressed in Mean \u0026plusmn; SE:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRemarkably, the mean value of the levels of the other studied two parameters CEA and CA15-3 sharply increased in the BC group compared to a control group. The mean CEA was found to be 472.56, 328.42, and 314.55 ng/dl in malignant, benign and control groups respectively (P\u0026lt;.001), while the means of CA 15.3 was 57.28, 15.16, and 14.35 U/ml in malignant, benign and controls respectively, with a significant difference between groups (P\u0026lt;.001), as shown in Table 2 and Fig. 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelations of TAC, Ox-LDL, and CA15-3:\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe studied marker TAC showed a significant negative correlation with CA15-3 ( r = 0.255, P\u0026lt;0.01). A significant positive correlation between Ox-LDL and CA15-3 was observed (r= 0.441, P\u0026lt;0.001). A significant negative correlation between TAC and Ox-LDL (r = 0.419, P\u0026lt;0.001) is shown in Figure 2. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 2:\u003c/strong\u003e Correlation between the serum level of TAC, Ox-LDL and CA15.3, (\u003cstrong\u003eA\u003c/strong\u003e) TAC and CA 15.3, (\u003cstrong\u003eB\u003c/strong\u003e) Ox-LDL and CA 15.3 \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssociation between predictive immunohistochemistry (IHC) and TAC, Ox-LDL\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSerum levels of TAC, Ox-LDL, CA15-3, and CEA in the BC patients with different histopathology observations (\u003cstrong\u003eA\u003c/strong\u003e) positive estrogen receptors (ER), (\u003cstrong\u003eB\u003c/strong\u003e) positive progesterone receptors (PR), and (\u003cstrong\u003eC\u003c/strong\u003e) positive human epidermal growth factor receptor-2 (Her2/neu) are illustrated in figure 3.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFigure 3:\u0026nbsp;\u003c/strong\u003eSerum levels of TAC, Ox-LDL, CA15-3, and CEA in the BC patients with different histopathology observations\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e(\u003cstrong\u003eA\u003c/strong\u003e) positive estrogen receptors (ER), (\u003cstrong\u003eB\u003c/strong\u003e) positive progesterone receptors (PR), and (\u003cstrong\u003eC\u003c/strong\u003e) positive human epidermal growth factor receptor-2 (Her2/neu).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiagnostic performance of serum TAC and Ox-LDL for breast cancer:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analysis of the ROC curve of TAC serum levels of studied subjects was applied, to, know how well the TAC test discrimination between the samples with and without BC. Figure 4 shows the area under the ROC curve. A significant area under the curve (AUC) was observed from data analysis of the ROC curve (0.975, P\u0026lt;0.001). The sensitivity (100) and specificity (86.4%) were selected at a cutoff value of TAC equal to 18.9U/ml (Table 3).\u003c/p\u003e\n\u003cp\u003eAlso, the analysis of the ROC curve of Ox-LDL serum levels of studied subjects was applied, to know how well the Ox-LDL test discrimination between the samples with and without BC. Figure 4 shows the area under the ROC curve.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 4:\u0026nbsp;\u003c/strong\u003eROC curve analysis and interactive dot diagrams of studied parameters in BC patients\u003cstrong\u003e. Sens:\u0026nbsp;\u003c/strong\u003esensitivity; \u003cstrong\u003espec\u003c/strong\u003e: \u0026nbsp;specificity, Blue lines indicate the cutoff value of each parameter.\u003c/p\u003e\n\u003cp\u003eA significant area under the curve (AUC) was observed from data analysis of the ROC curve (0.986, P\u0026lt;0.001). The sensitivity (97.9) and specificity (100 %) were selected at a cutoff value of Ox-LDL equal to 998 pg/ml as shown in Table 3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eDiagnostic data of serum levels of TAC, Ox-LDL, and CA 15-3 using ROC curve\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eCancer is one of the most frequent causes of death worldwide with breast cancer as the most common malignancy in women, accounting for 30% of all cancers diagnosed in women each year [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Biomarkers that explore the progression and are used as diagnostic tools in the disease attract considerable attention in the field. Few biomarkers are used for a better understanding of how oxidative stress is involved in cancer pathophysiology [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The present study was conducted to compare levels of biomarkers related to oxidative stress in individuals with breast cancer and healthy individuals. Specifically, the study will focus on Total Antioxidant Capacity and Oxidized Low-Density Lipoproteins, as well as the potential diagnostic value of CEA and CA 15\u0026thinsp;\u0026minus;\u0026thinsp;3 in breast cancer. Lipid peroxidation and total antioxidant capacity (TAC) in breast cancer patients show an intricate relationship in previous works. Studies have revealed that lipid peroxidation is significantly elevated in breast cancer patients, suggesting increased oxidative stress [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Furthermore, the oxidative/antioxidant profile in breast cancer patients was influenced by various prognostic factors such as cancer stage, tumor size, and molecular markers, highlighting the dynamic interplay between oxidative stress and antioxidant capacity in breast cancer progression [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn our study, the results of TAC and Ox-LDL levels support the previous findings reporting that the increased formation or inadequate removal of ROS may lead to cancer [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOxLDL levels were found to be increased and TAC levels were found to be decreased in cases of BC compared to the control group. Moreover, the most increased levels of Ox-LDL were observed in malignant cases as shown in Fig.\u0026nbsp;1. When we read these results with the decreased antioxidant defense as expressed in low levels of TAC in malignant cases, we can suggest that oxidative stress is correlated strongly with the development of the disease. These findings are inconsistent with previous studies which suggest that disturbance in antioxidant defense and oxidative stress promotes DNA damage in cancers and may be associated with benign and malignant tumors [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMultiple marker assays may significantly improve the sensitivity of detecting heterogeneous tumor cells compared with single marker assays [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Multiple serum-based tumor markers have been described for breast cancer, the most widely tumor markers used are CA 15\u0026thinsp;\u0026minus;\u0026thinsp;3 and CEA [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Breast cancer is only one condition that may cause high levels of CA 15\u0026thinsp;\u0026minus;\u0026thinsp;3. The pre-operative concentration of CA 15\u0026thinsp;\u0026minus;\u0026thinsp;3 thus might be combined with existing prognostic factors for predicting outcomes in patients with newly diagnosed breast cancer. It has been proposed that the assessment of multiple tumor markers in one blood sample would enhance the sensitivity of tumor cell detection [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTAC values, according to our data (sensitivity 100% and specificity 86.4%) as shown in Fig.\u0026nbsp;4, could be a potential marker for identifying BC patients from healthy people. it could be used as a screening indicator for BC early identification. Moreover, if oxidative stress is a treatment target, it could be applied as a disease marker for monitoring and evaluating the therapeutic effect. Many previous studies suggest that antioxidant defenses can be increased through physiological signaling, dietary components, or potential pharmaceutical intervention [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The diagnostic value of Ox-LDL in our study shows considerable good performance, especially in excluding negative cases of BC as reflected by its high specificity (100%), with a sensitivity of 97.9% and AUC of 0.986.\u003c/p\u003e \u003cp\u003eThe levels of TAC were found to be significantly higher in BC patients with negative ER and PR whereas the level of CA15-3 is significantly higher in BC patients with negative Her2/neu. There was no difference in the levels of these parameters in BC patients with positive ER and PR tests as shown in Fig.\u0026nbsp;3. Several investigations have found a relationship between estrogen-induced breast cancer and oxidative stress [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Furthermore, it has been documented that oxidative DNA damage is highly correlated with the presence of the estrogen receptor (ER) and is higher in breast cancer tissue as compared to normal breast tissue [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. These findings may suggest that oxidative stress might be related to ER expression, and thus there is a need for further investigation to explore this relationship.\u003c/p\u003e \u003cp\u003eA significant negative correlation was observed between TAC and the biomarkers under investigation, CA15-3, and CEA, supporting the proposed relationship with BC, Fig.\u0026nbsp;2A. Furthermore, we observed that Ox-LDL levels significantly and positively correlated with the two investigated biomarkers, CA15-3 and CEA as well as shown in Fig.\u0026nbsp;2B. This suggests that the pattern of Ox-LDL concentration increases with both known biomarkers in a nearly comparable way in malignant, benign, and normal samples. Our findings could potentially endorse the diagnostic utility of TAC and Ox-LDL in BC. To the best of our knowledge, prior research evaluating the oxidative stress state of BC patients has concentrated on one or a small number of oxidants/antioxidant indicators, and the use of these biomarkers in clinical settings is still not well-established [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Even though these results show a correlation between the investigated biomarkers and the onset and development of BC, they are insufficient to indicate the patients' actual oxidative stress state or to identify a viable panel of diagnostic or prognostic biomarkers for BC. The utilization of Ox-LDL, TAC, and oxidative stress in the management of breast cancer shows great potential as an approach that can be further developed to enhance patient outcomes and improve overall management. However, interpretation of these biomarkers should be handled with care and based on proper assessment of analytical and clinical validations because these biomarkers in particular were correlated to many other pathologic scenarios such as hyperglycemia [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], cancers [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], aging [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], and cardiovascular events [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Based on the solid foundations of these established relationships, further research is required to validate the utilization of these biomarkers in clinical settings.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn the present study, it was observed that breast cancer patients exhibited lower serum levels of TAC and higher serum levels of Ox-LDL, indicating elevated oxidative stress compared to the control group. This suggests a potential association between increased oxidative stress and breast cancer. Based on our findings, TAC and Ox-LDL levels could serve as additional parameters for monitoring cancer prevention, diagnosis, and treatment. The exact mechanism behind the heightened oxidative stress, whether it stems from increased ROS production or reduced antioxidant defenses, remains unclear. Therefore, conducting further studies on oxidative stress and antioxidant therapy in breast cancer is recommended.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors express their gratitude to the staff of the oncology unit at King Abdallah Medical City in Makkah for their assistance in conducting the research by examining the sample individuals and collecting data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare no conflicts of interest from any person or organization in the subject matter or materials discussed in this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNon\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAvailable on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBoth authors contributed to the study conception and design, material preparation, data collection, analysis, writing and revising the manuscript. Both authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWilkinson L, Gathani T (2022) Understanding breast cancer as a global health concern. Br J Radiol 95(1130):20211033\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNour Eldin EE et al (2014) Oxidized low density lipoprotein and total antioxidant capacity in type-2 diabetic and impaired glucose tolerance Saudi men. Diabetol Metab Syndr 6(1):94\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDemirci-\u0026Ccedil;eki\u0026ccedil; S et al (2022) Biomarkers of Oxidative Stress and Antioxidant Defense. J Pharm Biomed Anal 209:114477\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eT., B.A. and A. M., Impact of Antioxidant-Rich Diet on Decreasing Oxidized Low-Density Lipoproteins, 8-Hydroxy-2\u0026acute;-Deoxyguanosine and Hba1c in Saudi Men. Biomed Pharmacol J, (2023) 16(2): p. 9\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKangari P et al (2018) Enzymatic Antioxidant and Lipid Peroxidation Evaluation in the Newly Diagnosed Breast Cancer Patients in Iran. Asian Pac J Cancer Prev 19(12):3511\u0026ndash;3515\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDidžiapetrienė J et al (2020) Oxidant/Antioxidant Status of Breast Cancer Patients in Pre- and Post-Operative Periods. Med (Kaunas), 56(2)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDelimaris I et al (2007) Oxidized LDL, serum oxidizability and serum lipid levels in patients with breast or ovarian cancer. Clin Biochem 40(15):1129\u0026ndash;1134\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhalaf MY et al (2021) The correlation of antioxidant levels of breast cancer: A case controlled study. 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Nutrients, 11(9)\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1:\u003c/strong\u003e \u003cem\u003eThe clinical and characteristic features of the studied groups\u003c/em\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable dir=\"rtl\" border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"626\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.424920127795527%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eP value\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.68370607028754%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eHealthy ( N = 50)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.08626198083067%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eBenign ( N = 50)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.56549520766773%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eMalignant ( N = 50 )\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.23961661341853%\" colspan=\"2\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eCharacteristic Features /\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003epathological parameters\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.519607843137255%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003emean\u0026plusmn;SE\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.970588235294118%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003e(%)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.313725490196079%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eNo.\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.519607843137255%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003emean\u0026plusmn;SE\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.519607843137255%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003e(%)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.313725490196079%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eNo.\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.519607843137255%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003emean\u0026plusmn;SE\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003e(%)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.823529411764707%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eNo.\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.44%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e.076\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e40.8\u0026plusmn;\u003cbr\u003e\u0026nbsp;0.93\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e42 %\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e58 %\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0.0%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e21\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e29\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e33.9\u0026plusmn;\u003cbr\u003e\u0026nbsp;1.9\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e66 %\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e30 %\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e4 %\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e33\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e15\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e50.6\u0026plusmn;\u003cbr\u003e\u0026nbsp;1.5\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.16%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e16.3%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e67.3%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e16.3%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.76%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e8\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e33\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e8\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.28%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eage\u003cbr\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003cspan dir=\"LTR\"\u003e˂40\u003cbr\u003e\u0026nbsp;40-60\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026gt;60\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.44%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e.066\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e66 %\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e34 %\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e33\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e17\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e96 %\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e4 %\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e48\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.16%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e58 %\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e42 %\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.76%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e29\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e21\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.28%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"LTR\"\u003e\u003cstrong\u003eMenstrual phase\u003c/strong\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003ePremenopausal\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003ePostmenopausal\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.44%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e.066\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e64 %\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e34%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0 %\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e32\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e17\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e58 %\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e40 %\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2 % \u0026nbsp;\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0 % \u0026nbsp;\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e29\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e20\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.16%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e69.4%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e20.4%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e4.1 %\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e6.1%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.76%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e34\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e10\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.28%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eMarital Status\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eMarried\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eSingle\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eDivorced\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eWidowed\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.44%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e.047\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e30%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e70%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e15\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e35\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e52%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e48%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e26\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e24\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.16%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e71.4%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e28.6%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.76%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e35\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e14\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.28%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eParity status\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eNulliparous\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eMultiparous\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.44%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e.170\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e34.9%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e76%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e24\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e38\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e54%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e46%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e27\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e23\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.16%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e68%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e32%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.76%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e34\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e16\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.28%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eLactation History\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eLactating\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eNon-Lactating\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.44%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e.076\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e4%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e96%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e48\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e4 %\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e96 %\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e48\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.16%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e98%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.76%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e1\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e48\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.28%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eSmoking\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eSmoker\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eNon-Smokers\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.44%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e.342\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e10%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e90%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e5\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e45\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e12%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e88%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e6\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e44\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.16%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e14%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e86%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.76%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e7 \u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e43\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.28%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eFamily history of BC\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eYes\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eNo\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.44%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e78 %\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e22%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e39\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e11\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.16%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.76%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.28%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eBenign Types\u003c/span\u003e\u003c/strong\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003efibro adenoma\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eothers\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.44%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e54%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e34%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e12%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e27\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e17\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e6\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.16%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e44%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e56%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.76%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e22\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e28\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.68%\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cem\u003e\u003cspan dir=\"LTR\"\u003eRight Breast\u003c/span\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.6%\" rowspan=\"3\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eSide of complain\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cem\u003e\u003cspan dir=\"LTR\"\u003eLeft Breast\u003c/span\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cem\u003e\u003cspan dir=\"LTR\"\u003eBoth side\u003c/span\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.44%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e82%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e18%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e41\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e9\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e96%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e4%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.16%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e48\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.76%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.28%\" colspan=\"2\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cem\u003e\u003cspan dir=\"LTR\"\u003eMass\u003c/span\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"2\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cem\u003e\u003cspan dir=\"LTR\"\u003eNo-Mass\u003c/span\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.44%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e8%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e92%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e4\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e46\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e4%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e96%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.16%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e48\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.76%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.28%\" colspan=\"2\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cem\u003e\u003cspan dir=\"LTR\"\u003eDischarge\u003c/span\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"2\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cem\u003e\u003cspan dir=\"LTR\"\u003eNo-Discharge\u003c/span\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.44%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u003cbr\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.16%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e94 %\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e6 %\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.76%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e47\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.28%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eCancer types\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003cspan dir=\"LTR\"\u003eInvasive ductal carcinoma\u003cbr\u003e\u0026nbsp;Lobular carcinoma\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.44%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.16%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e42%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e58.%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.76%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e21\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e29\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.28%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eCancer metastasis\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eYes\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eno\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.44%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.16%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e74%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e26%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.76%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e37\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e13\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.28%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eLN involvement\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eYes\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003eNo\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.44%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u003cbr\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.16%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e12 %\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e62%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e22%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e4%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.76%\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e6\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e31\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e11\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.28%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eGrade:\u003cbr\u003e\u0026nbsp;\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003cspan dir=\"LTR\"\u003egrade \u0026nbsp;I\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;grade II\u0026nbsp;\u003c/span\u003e \u003cspan dir=\"LTR\"\u003e\u003cbr\u003e\u0026nbsp; grade III\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003egrade IV\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.44%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.08%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.52%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.16%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e70%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e56%\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e28%\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.76%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e35\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e28\u003c/span\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cspan dir=\"LTR\"\u003e14\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.68%\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cem\u003e\u003cspan dir=\"LTR\"\u003eER\u003c/span\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.6%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eImmunohistochemistry (IHC)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cem\u003e\u003cspan dir=\"LTR\"\u003ePR\u003c/span\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cem\u003e\u003cspan dir=\"LTR\"\u003eHer2\u003c/span\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u0026nbsp;\u003c/strong\u003eThe serum levels of studied biomarkers in normal, benign, and malignant groups of breast cancer patients. The data are expressed in Mean \u0026plusmn; SE \u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"109%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.3265306122449%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBenign\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMalignant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.3265306122449%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTAC (U/ml)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean \u0026plusmn; SE\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eRange\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\" valign=\"top\"\u003e\n \u003cp\u003e43.3\u0026nbsp;\u0026plusmn; 3.09\u003c/p\u003e\n \u003cp\u003e12-81\u003c/p\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" valign=\"top\"\u003e\n \u003cp\u003e16.04\u0026nbsp;\u0026plusmn; 0.75\u003c/p\u003e\n \u003cp\u003e6.7-26.3\u003c/p\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" valign=\"top\"\u003e\n \u003cp\u003e8.3\u0026plusmn;0.7\u003c/p\u003e\n \u003cp\u003e2-18\u003c/p\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eP\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.3265306122449%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOx-LDL (pg/ml)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean \u0026plusmn; SE\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eRange\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\" valign=\"top\"\u003e\n \u003cp\u003e682\u0026nbsp;\u0026plusmn; 29.7\u003c/p\u003e\n \u003cp\u003e331-998\u003c/p\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" valign=\"top\"\u003e\n \u003cp\u003e1234\u0026plusmn; 70.3\u003c/p\u003e\n \u003cp\u003e466-2121\u003c/p\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" valign=\"top\"\u003e\n \u003cp\u003e3831\u0026plusmn;367\u003c/p\u003e\n \u003cp\u003e643-9951\u003c/p\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eP\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.3265306122449%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCEA (ng/ml)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean \u0026plusmn; SE\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eRange\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\" valign=\"top\"\u003e\n \u003cp\u003e314.55\u0026nbsp;\u0026plusmn; 15.67\u003c/p\u003e\n \u003cp\u003e148 \u0026ndash; 494\u003c/p\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" valign=\"top\"\u003e\n \u003cp\u003e328.42\u0026nbsp;\u0026plusmn; 25.27\u003c/p\u003e\n \u003cp\u003e107 \u0026ndash; 780\u003c/p\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" valign=\"top\"\u003e\n \u003cp\u003e472.56\u0026nbsp;\u0026plusmn; 44.96\u003c/p\u003e\n \u003cp\u003e137 \u0026ndash; 990\u003c/p\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eP\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.3265306122449%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCA15-3 (U/ml)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean \u0026plusmn; SE\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eRange\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\" valign=\"top\"\u003e\n \u003cp\u003e14.35 \u0026plusmn; 1.07\u003c/p\u003e\n \u003cp\u003e3.3 \u0026ndash; 24.7\u003c/p\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" valign=\"top\"\u003e\n \u003cp\u003e15.16 \u0026plusmn; 0.91\u003c/p\u003e\n \u003cp\u003e4 \u0026ndash; 29\u003c/p\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" valign=\"top\"\u003e\n \u003cp\u003e57.28 \u0026plusmn; 8.89\u003c/p\u003e\n \u003cp\u003e17.1 \u0026ndash; 170\u003c/p\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eP\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eDiagnostic data of serum levels of TAC, ox-LDL, and CA 15-3 using ROC curve\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"left\" width=\"641\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.948517940717629%\" valign=\"bottom\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.424336973478939%\" valign=\"bottom\"\u003e\n \u003cp\u003eAUC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.29641185647426%\" valign=\"bottom\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.784711388455538%\" valign=\"bottom\"\u003e\n \u003cp\u003e95%\u0026nbsp;CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.0405616224649%\" valign=\"top\"\u003e\n \u003cp\u003esensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.848673946957877%\" valign=\"top\"\u003e\n \u003cp\u003especificity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.65678627145086%\" valign=\"top\"\u003e\n \u003cp\u003eCutoff value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.948517940717629%\" valign=\"top\"\u003e\n \u003cp\u003eTAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.424336973478939%\" valign=\"top\"\u003e\n \u003cp\u003e0.975\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.29641185647426%\" valign=\"top\"\u003e\n \u003cp\u003e0.0247\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.784711388455538%\" valign=\"top\"\u003e\n \u003cp\u003e0.870 to 0.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.0405616224649%\" valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.848673946957877%\" valign=\"top\"\u003e\n \u003cp\u003e86.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.65678627145086%\" valign=\"top\"\u003e\n \u003cp\u003e18.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.948517940717629%\" valign=\"top\"\u003e\n \u003cp\u003eOx-LDL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.424336973478939%\" valign=\"top\"\u003e\n \u003cp\u003e0.986\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.29641185647426%\" valign=\"top\"\u003e\n \u003cp\u003e0.0225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.784711388455538%\" valign=\"top\"\u003e\n \u003cp\u003e0.887 to 0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.0405616224649%\" valign=\"top\"\u003e\n \u003cp\u003e97.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.848673946957877%\" valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.65678627145086%\" valign=\"top\"\u003e\n \u003cp\u003e998\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.948517940717629%\" valign=\"top\"\u003e\n \u003cp\u003eCA 15.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.424336973478939%\" valign=\"top\"\u003e\n \u003cp\u003e0.913\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.29641185647426%\" valign=\"top\"\u003e\n \u003cp\u003e0.0518\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.784711388455538%\" valign=\"top\"\u003e\n \u003cp\u003e0.736 to 0.947\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.0405616224649%\" valign=\"top\"\u003e\n \u003cp\u003e69.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.848673946957877%\" valign=\"top\"\u003e\n \u003cp\u003e96.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.65678627145086%\" valign=\"top\"\u003e\n \u003cp\u003e22.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4477726/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4477726/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Breast cancer is a prevalent life-threatening disease worldwide. Oxidative stress has been implicated in the development and progression of various cancers, including BC. Assessing lipid peroxidation and overall antioxidant status in breast cancer offers valuable information regarding the advancement, prognosis, and effectiveness of treatment options.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A total of one hundred and fifty women, categorized into three groups Normal, Benign BC, and Malignant BC cases. Patients were selected and examined in the oncology clinic, fasting blood samples were collected and measurements of Total Antioxidant Capacity (TAC), Ox-LDL, CA 15.3, and CEA were performed. Then statistical analysis was done to compare the levels of these parameters in different groups and measure the analytical performance of TAC and Ox-LDL in BC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe serum level of TAC in malignant cases was significantly decreased compared to benign group, 8.3 U/ml and 16.04 U/ml (P\u0026lt;0.001) respectively. Healthy controls show higher levels of TAC (43.4 U/ml). The levels of Ox-LDL in BC was significantly increased in malignant cases and benign group, 3831, and 1234 pg/ml, respectively compared to normal controls (682 pg/ml) (P\u0026lt;0.001). CEA and CA15-3 sharply increased in BC groups compared to control group. A significant area under the curve (AUC) for TAC (0.975, P\u0026lt;0.001), and Ox-LDL (0.986, P\u0026lt;0.001) was observed in ROC curve analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present study revealed that breast cancer patients had lower TAC and higher Ox-LDL serum levels, indicating elevated oxidative stress. Additionally, TAC and Ox-LDL levels may serve as promising monitoring parameters in BC.\u003c/p\u003e","manuscriptTitle":"Assessment of Lipid peroxidation and total antioxidant capacity in patients with breast carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-11 20:35:52","doi":"10.21203/rs.3.rs-4477726/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"13c57315-e92f-4b27-ad69-1b1f6918916a","owner":[],"postedDate":"June 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-11T20:35:54+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-11 20:35:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4477726","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4477726","identity":"rs-4477726","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}