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Showing 28 results for Cancer
Sakineh Abbasi, Shahrzad Sharifpour Vajari,
Volume 15, Issue 5 (1-2022)
Volume 15, Issue 5 (1-2022)
Abstract
Background and Aim: Cervical cancer is the fourth main cause of mortality among women, and annually about half a million new cases are detected in developed countries. Based on oncological studies, human papillomavirus (HPV) is classified into two categories: high-risk type and low-risk type, and most cases are related to the high-risk type of human papillomavirus. HPV 16 and 18 are among the more dangerous ones in this type of cancer. Human papillomavirus is a small group of uncoated viruses with double-stranded DNA that belong to the papillomaviridae family.
Materials and Methods: In this review study, more than 200 articles related to human papillomavirus and immune system function against this virus were reviewed from 2015 to 2020 and among them, 34 articles related to markers and cytokines in cervical cancer were chosen from Google Scholar, Scopus, and PubMed.
Results: One of In-vitro methods in markers detection , is using vectors to infect dendritic cells to present antigen, increase the expression of markers and mature T cell, which leads to the identification of a variety of markers and cytoklines such as PD, PDL, CD, MHC, FASL, IFN, IL, TLR associated with cervical cancer.
Conclusion: Cervical cancer prevention can reduce the economic as well as the social burden of having the disease in the community. Important cytokines expressed when exposed to HPV include IL-6 and IL-8. Several agonist epitopes with enhanced binding power to the human leukocyte antigen (HLA-A2) A2 class I antigen have been described to enhance cytotoxic T lymphocyte responses and to be used in the development of effective HPV vaccines; this is because it has already been shown that different epitopes of 16 HPVs, such as E6 and E7, are able to elicit human cytotoxic T lymphocyte (CTL) responses by binding to HLA-A2.
Mostafa Shanbehzadeh, Hadi Kazemi-Arpanahi, Raoof Nopour,
Volume 16, Issue 2 (5-2022)
Volume 16, Issue 2 (5-2022)
Abstract
Background and Aim: Breast cancer is one of the most common and aggressive malignancies in women. Timely diagnosis of breast cancer plays an important role in preventing the progression of this disease, timely treatment measures, and aftermath reducing the mortality rate of these patients. Machine learning has the potential ability to diagnose diseases quickly and cost-effectively. This study aims to design a CDSS based on the rules extracted from the decision tree algorithm with the best performance to diagnose breast cancer in a timely and effective manner.
Materials and Methods: The data of 597 suspected people with breast cancer (255 patients and 342 healthy people) were retrospectively extracted from the electronic database of Ayatollah Taleghani Hospital in Abadan city with 24 characteristics, mainly pertained to lifestyle and medical histories. After selecting the most important variables by using the Chi-square Pearson and one-way analysis of variance (P<0.05), the performance of selected data mining algorithms including RF, J-48, DS, RT and XG -Boost was evaluated for breast cancer diagnosis in Weka 3.4 software. Finally, the breast cancer diagnostic system was designed based on the best model and through C# programming language and Dot Net Framework V3.5.4.
Results: Fourteen variables including personal history of breast cancer, breast sampling, and chest X-ray, high blood pressure, increased LDL blood cholesterol, presence of mass in upper inner quadrant of the breast, hormone therapy with estrogen, hormone therapy with Estrogen-progesterone, family history of breast cancer, age, history of other cancers, waist-to-hip ratio and fruit and vegetable consumption showed a significant relationship with the output class at the P<0.05. Based on the results of the performance evaluation of selected algorithms, the RF model with sensitivity, specificity, accuracy, and F- measure equal to 0.97, 0.99, 0.98, 0.974, respectively, AUC=0.936 had higher performance than other selected algorithms and was suggested as the best model for breast cancer diagnosis.
Conclusion: It seems that using modifiable variables such as lifestyle and reproductive-hormonal characteristics as input to the RF algorithm to design the CDSS, can detect breast cancer cases with optimal accuracy. In addition, the proposed system can be effectively adapted in real clinical environments for quick and effective disease diagnosis.
Materials and Methods: The data of 597 suspected people with breast cancer (255 patients and 342 healthy people) were retrospectively extracted from the electronic database of Ayatollah Taleghani Hospital in Abadan city with 24 characteristics, mainly pertained to lifestyle and medical histories. After selecting the most important variables by using the Chi-square Pearson and one-way analysis of variance (P<0.05), the performance of selected data mining algorithms including RF, J-48, DS, RT and XG -Boost was evaluated for breast cancer diagnosis in Weka 3.4 software. Finally, the breast cancer diagnostic system was designed based on the best model and through C# programming language and Dot Net Framework V3.5.4.
Results: Fourteen variables including personal history of breast cancer, breast sampling, and chest X-ray, high blood pressure, increased LDL blood cholesterol, presence of mass in upper inner quadrant of the breast, hormone therapy with estrogen, hormone therapy with Estrogen-progesterone, family history of breast cancer, age, history of other cancers, waist-to-hip ratio and fruit and vegetable consumption showed a significant relationship with the output class at the P<0.05. Based on the results of the performance evaluation of selected algorithms, the RF model with sensitivity, specificity, accuracy, and F- measure equal to 0.97, 0.99, 0.98, 0.974, respectively, AUC=0.936 had higher performance than other selected algorithms and was suggested as the best model for breast cancer diagnosis.
Conclusion: It seems that using modifiable variables such as lifestyle and reproductive-hormonal characteristics as input to the RF algorithm to design the CDSS, can detect breast cancer cases with optimal accuracy. In addition, the proposed system can be effectively adapted in real clinical environments for quick and effective disease diagnosis.
Saman Mohammadpour, Reza Rabiei, Elham Shabahrami, Kamyar Fathisalari, Maryam Khakzad, Mostafa Langarizadeh,
Volume 16, Issue 2 (5-2022)
Volume 16, Issue 2 (5-2022)
Abstract
Background and Aim: Cancer is the second leading cause of death in the world, which leads to the death of more than 10 million people in the world every year. Its early diagnosis, management and proper treatment play an important role in reducing complications and mortality. One of the support tools in early diagnosis, treatment and management of this disease are Clinical Decision Support System (CDSS), which are divided into two groups, rule-based and non-rule-based. Rule-based decision support systems are created based on clinical guidelines, while non-rule-based decision support systems use machine learning. In this research, the effects of decision support systems, rule-based and non-rule-based, on cancer diagnosis, treatment and management were measured.
Materials and Methods: The present study was conducted using a systematic review method, which was conducted by searching the Web of Science, Scopus, IEEE and PubMED databases until 12/31/2021. After removing duplicates and evaluating the characteristics of the inclusion and exclusion criteria, studies related to the goal were selected. The selection of articles was based on the title, abstract and full text The data collection tool was the data extraction form, which included year of study, type of study, system of body, organ of body, the service provided by the decision support system, type of decision support system, effect, effect index and the score of effect index. Narrative synthesis were used for data analysis.
Results: Out of 768 articles, 16 articles related to the objectives of the study were identified. Studies were presented in two categories of clinical decision-support systems: Rule-based and non-Rule based. The effects evaluated in the clinical decision support systems were Rule-based, dose adjustment, symptoms, adherence to treatment guidelines, care time, smoking, need for chemotherapy and pain management, all of which except pain management were significant and positive. The effects evaluated were in the category of non-Rule based clinical decision support systems, diagnostic and therapeutic decisions, controlling neutropenia, all of which were significant and positive except controlling neutropenia.
Conclusion: The results obtained for the effectiveness of both Rule-based and non-Rule-based decision support systems indicated different benefits of these two categories. Therefore, using their combination in the field of cancer can bring very useful results.
Materials and Methods: The present study was conducted using a systematic review method, which was conducted by searching the Web of Science, Scopus, IEEE and PubMED databases until 12/31/2021. After removing duplicates and evaluating the characteristics of the inclusion and exclusion criteria, studies related to the goal were selected. The selection of articles was based on the title, abstract and full text The data collection tool was the data extraction form, which included year of study, type of study, system of body, organ of body, the service provided by the decision support system, type of decision support system, effect, effect index and the score of effect index. Narrative synthesis were used for data analysis.
Results: Out of 768 articles, 16 articles related to the objectives of the study were identified. Studies were presented in two categories of clinical decision-support systems: Rule-based and non-Rule based. The effects evaluated in the clinical decision support systems were Rule-based, dose adjustment, symptoms, adherence to treatment guidelines, care time, smoking, need for chemotherapy and pain management, all of which except pain management were significant and positive. The effects evaluated were in the category of non-Rule based clinical decision support systems, diagnostic and therapeutic decisions, controlling neutropenia, all of which were significant and positive except controlling neutropenia.
Conclusion: The results obtained for the effectiveness of both Rule-based and non-Rule-based decision support systems indicated different benefits of these two categories. Therefore, using their combination in the field of cancer can bring very useful results.
Keyhan Fatehi, Farimah Rahimi, Reza Rezayatmand,
Volume 17, Issue 1 (3-2023)
Volume 17, Issue 1 (3-2023)
Abstract
Background and Aim: Colorectal cancer is one of the most common cancers that its incidence and prevalence and so deaths due to this cancer have increased worldwide recently. This study examines the economic burden of colorectal cancer from different perspectives by conducting a scoping review.
Materials and Methods: In this scoping review, by searching Scopus, PubMed, Embase, Cochrane, and Web of Science, the articles reporting the costs of CRC were reviewed. The search was limited to those published in the past years leading up to 2020. In addition to categorizing different aspects of the reviewed paper, per capita costs were adjusted with the purchasing power parity in order to make some comparisons possible. In this study, the calculated costs of retrieved studies were categorized based on the perspective of each study.
Results: Out of 29 studies, only two have reported indirect costs of CRC, and 4 studies have reported both direct and indirect costs. In other studies, only direct costs of CRC have been reported. Nearly 40% of studies calculated CRC costs from the provider’s perspective. The highest reported annual per-patient cost was $175020(PPP-adjusted) which is related to the average annual costs of patients with CRC at the fourth stage in the United States from a provider perspective. The lowest reported amount was $ 954(PPP-adjusted) which was related to average annual inpatient costs in Brazil from a provider perspective.
Conclusion: Due to variations in study characteristics in terms of perspective, type of costs, type of patient included, etc. any comparison between the economic burden of CRC should be made with caution. However, reviewing various aspects of the economic burden of CRC reported in included studies, will provide researchers and policymakers with a better insight into the CRC burden while designing intervention programs will reduce the budget impact of the those programs.
Materials and Methods: In this scoping review, by searching Scopus, PubMed, Embase, Cochrane, and Web of Science, the articles reporting the costs of CRC were reviewed. The search was limited to those published in the past years leading up to 2020. In addition to categorizing different aspects of the reviewed paper, per capita costs were adjusted with the purchasing power parity in order to make some comparisons possible. In this study, the calculated costs of retrieved studies were categorized based on the perspective of each study.
Results: Out of 29 studies, only two have reported indirect costs of CRC, and 4 studies have reported both direct and indirect costs. In other studies, only direct costs of CRC have been reported. Nearly 40% of studies calculated CRC costs from the provider’s perspective. The highest reported annual per-patient cost was $175020(PPP-adjusted) which is related to the average annual costs of patients with CRC at the fourth stage in the United States from a provider perspective. The lowest reported amount was $ 954(PPP-adjusted) which was related to average annual inpatient costs in Brazil from a provider perspective.
Conclusion: Due to variations in study characteristics in terms of perspective, type of costs, type of patient included, etc. any comparison between the economic burden of CRC should be made with caution. However, reviewing various aspects of the economic burden of CRC reported in included studies, will provide researchers and policymakers with a better insight into the CRC burden while designing intervention programs will reduce the budget impact of the those programs.
Shima Derakhshan, Negar Yavari Tehrani Fard, Nahid Abotalbe, Maryam Naseroleslami,
Volume 17, Issue 2 (5-2023)
Volume 17, Issue 2 (5-2023)
Abstract
Background and Aim: Today, natural compounds such as peptides and probiotics can be mentioned as a supplement to the treatment of diseases such as cancer. These compounds may be effective in preventing the progression or treatment of cancer by affecting some molecular pathways including inflammation. The aim of this study was to investigate the effect of D-peptide-B and B.bifidum probiotic lysate on the expression of TNF-α and IL-1 genes in gastric cancer cells of AGS cell line.
Materials and Methods: In this study, AGS and HEK cells were cultured in DMEM medium with 10% bovine serum. The cells were treated with different concentrations of D-peptide-B and B.bifidum lysate and were incubated for 24 hours. The cell viability was checked by MTT. For molecular investigations, after RNA extraction and cDNA synthesis, the relative expression of TNF-α and IL-1 genes was evaluated using Real time PCR, and the data were analyzed using statistical methods One-way ANOVA.
Results: The MTT results indicated that the AGS cancer cells’ survival rate decreased after treatment with dipeptide-B and lysate of B.bifidum as compared to HEK control cells. Furthermore, the study found that the expression levels of TNF-α and IL-1 genes in gastric cancer cells were significantly higher after treatment with D-Peptide-B, bacterial lysate, or both, when compared to normal HEK cells (P≤0.05). Specifically, the IL-1 gene expression increased by 300% (4 times) for peptide treatment, 100% (2 times) for bacterial treatment, and 650% (7.5 times) for combined treatment. Similarly, the TNF-α gene expression increased by 350% for peptide treatment, 100% for bacterial treatment, and 520% for combined treatment. These results suggest that these compounds may have induced cell death in cancer cells by affecting other molecular pathways.
Conclusion: Considering that D-peptide-B and B.bifidum lysate had no significant toxicity on normal cells and caused a significant decrease in the survival of cancer cells and this toxicity was dose dependent, therefore, consideration might be given to these natural compounds in treatment of gastric cancer.
Materials and Methods: In this study, AGS and HEK cells were cultured in DMEM medium with 10% bovine serum. The cells were treated with different concentrations of D-peptide-B and B.bifidum lysate and were incubated for 24 hours. The cell viability was checked by MTT. For molecular investigations, after RNA extraction and cDNA synthesis, the relative expression of TNF-α and IL-1 genes was evaluated using Real time PCR, and the data were analyzed using statistical methods One-way ANOVA.
Results: The MTT results indicated that the AGS cancer cells’ survival rate decreased after treatment with dipeptide-B and lysate of B.bifidum as compared to HEK control cells. Furthermore, the study found that the expression levels of TNF-α and IL-1 genes in gastric cancer cells were significantly higher after treatment with D-Peptide-B, bacterial lysate, or both, when compared to normal HEK cells (P≤0.05). Specifically, the IL-1 gene expression increased by 300% (4 times) for peptide treatment, 100% (2 times) for bacterial treatment, and 650% (7.5 times) for combined treatment. Similarly, the TNF-α gene expression increased by 350% for peptide treatment, 100% for bacterial treatment, and 520% for combined treatment. These results suggest that these compounds may have induced cell death in cancer cells by affecting other molecular pathways.
Conclusion: Considering that D-peptide-B and B.bifidum lysate had no significant toxicity on normal cells and caused a significant decrease in the survival of cancer cells and this toxicity was dose dependent, therefore, consideration might be given to these natural compounds in treatment of gastric cancer.
Seyedeh Nasim Mirbahari, Sina Salari, Shabnam Shahrokh, Mohammadreza Zali, Mehdi Totonchi,
Volume 18, Issue 1 (3-2024)
Volume 18, Issue 1 (3-2024)
Abstract
Background and Aim: Oncolytic viruses, as novel and advanced tools in the field of treating various types of cancer, have played a very important role in medical developments. The term “oncolytic” refers to the ability of these viruses to destroy and damage cancer cells while preserving the surrounding healthy cells.
Materials and Methods: To conduct this study, a total of 270 initial results were collected through searching in the PubMed, Scopus, and Google Scholar databases from 2012 to 2024. The primary researcher reviewed 68 relevant articles, extracted and summarized the contents, and finally compiled the findings.
Results: The findings from this review study demonstrate that cancer cells possess distinct characteristics that differentiate them from normal cells, including continuous growth signaling, resistance to anti-growth signaling, evasion of apoptosis, increased angiogenesis, and invasion into other body parts. Oncolytic viruses utilize these distinctive features to selectively target and infect cancer cells. Most oncolytic viruses directly eliminate host tumor cells, resulting in viral replication and induction of host antiviral responses. Moreover, these viruses can destroy cancer cells through the production of specific proteins. The cytotoxic potential of oncolytic viruses depends on viral type, genetic manipulation, optimal virus dosage for injection, natural and induced viral tropism, and cancer cell sensitivity to various forms of cell death. The mechanism driving the selective replication of oncolytic viruses in cancer cells likely relates to defects in signaling pathways specific to tumor cells. Phase III clinical trials have demonstrated significant improvements in the treatment outcomes of various cancers, including head and neck cancer, melanoma, glioblastoma, and bladder cancer, through the use of H101 (Oncorine), T-Vec, ECHO-7, and Teserpaturev (Delytact) viruses.
Conclusion: Oncolytic viruses are constructed from various types of viruses and are currently being evaluated in laboratory, preclinical, and clinical stages. The use of these viruses for the treatment of cancer as a new and targeted approach has been proposed, which requires further investigation and achievement of more precise mechanisms for their better performance.
Materials and Methods: To conduct this study, a total of 270 initial results were collected through searching in the PubMed, Scopus, and Google Scholar databases from 2012 to 2024. The primary researcher reviewed 68 relevant articles, extracted and summarized the contents, and finally compiled the findings.
Results: The findings from this review study demonstrate that cancer cells possess distinct characteristics that differentiate them from normal cells, including continuous growth signaling, resistance to anti-growth signaling, evasion of apoptosis, increased angiogenesis, and invasion into other body parts. Oncolytic viruses utilize these distinctive features to selectively target and infect cancer cells. Most oncolytic viruses directly eliminate host tumor cells, resulting in viral replication and induction of host antiviral responses. Moreover, these viruses can destroy cancer cells through the production of specific proteins. The cytotoxic potential of oncolytic viruses depends on viral type, genetic manipulation, optimal virus dosage for injection, natural and induced viral tropism, and cancer cell sensitivity to various forms of cell death. The mechanism driving the selective replication of oncolytic viruses in cancer cells likely relates to defects in signaling pathways specific to tumor cells. Phase III clinical trials have demonstrated significant improvements in the treatment outcomes of various cancers, including head and neck cancer, melanoma, glioblastoma, and bladder cancer, through the use of H101 (Oncorine), T-Vec, ECHO-7, and Teserpaturev (Delytact) viruses.
Conclusion: Oncolytic viruses are constructed from various types of viruses and are currently being evaluated in laboratory, preclinical, and clinical stages. The use of these viruses for the treatment of cancer as a new and targeted approach has been proposed, which requires further investigation and achievement of more precise mechanisms for their better performance.
Fatemeh Mirshekari, Elham Maserat,
Volume 18, Issue 2 (5-2024)
Volume 18, Issue 2 (5-2024)
Abstract
Background and Aim: Considering the growing trend of cancer in Iran, the development and implementation of digital health literacy systems accelerates the capabilities of digital health and the self-management process of patients. Digital health literacy means the ability to effectively and consciously use digital technologies to access health-related information and services. This skill plays an important role in accessing medical information, disease management, improving the quality of life of people, especially cancer patients. Digital health literacy is considered as one of the most key factors of equal access to digital health information. The purpose of the present study was to formulate the requirements of the digital health literacy system with a focus on cancer.
Materials and Methods: The present study was conducted in two phases of literature review and validity and reliability of requirements in 2023. In the first stage, a literature review was conducted with the keywords of digital health literacy, cancer, requirements, system and application in databases such as PubMed, Scopus, Google Scholar, academic Jihad scientific database and specialized websites. To check the content validity of the survey, 62 experts were surveyed and CVI and CVR were calculated.
Results: Hundered and twenty seven functional and non-functional components were approved. Requirements in the functional section was divided in six main dimensions information literacy module (8 functional components), information and communication technology literacy module (18 functional components), media literacy (5 functional components), public, specialized and population-oriented health literacy module (47 functional components) ), digital health literacy module (28 functional components), and digital health literacy module in cancer (6 functional components) were divided. In the section of digital health literacy in cancer, the main components of needs assessment, digital health literacy training, evaluation and monitoring of the effectiveness of digital interventions and information search skills were approved. Fifteen non-functional components were also approved. Cronbach’s alpha coefficient obtained (92%) indicated high reliability and reproducibility.
Conclusion: Digital health literacy systems can facilitate health care services. Considering the acceptable validity and reliability of the study, the defined requirements can be used to implement digital health literacy systems centered on cancer.
Materials and Methods: The present study was conducted in two phases of literature review and validity and reliability of requirements in 2023. In the first stage, a literature review was conducted with the keywords of digital health literacy, cancer, requirements, system and application in databases such as PubMed, Scopus, Google Scholar, academic Jihad scientific database and specialized websites. To check the content validity of the survey, 62 experts were surveyed and CVI and CVR were calculated.
Results: Hundered and twenty seven functional and non-functional components were approved. Requirements in the functional section was divided in six main dimensions information literacy module (8 functional components), information and communication technology literacy module (18 functional components), media literacy (5 functional components), public, specialized and population-oriented health literacy module (47 functional components) ), digital health literacy module (28 functional components), and digital health literacy module in cancer (6 functional components) were divided. In the section of digital health literacy in cancer, the main components of needs assessment, digital health literacy training, evaluation and monitoring of the effectiveness of digital interventions and information search skills were approved. Fifteen non-functional components were also approved. Cronbach’s alpha coefficient obtained (92%) indicated high reliability and reproducibility.
Conclusion: Digital health literacy systems can facilitate health care services. Considering the acceptable validity and reliability of the study, the defined requirements can be used to implement digital health literacy systems centered on cancer.
Fateme Hami Kargar, Narges Nikkhah Ghamsari, Mohammad Ganji,
Volume 18, Issue 4 (10-2024)
Volume 18, Issue 4 (10-2024)
Abstract
Background and Aim: Breast cancer treatment is associated with changes in women’s bodies. Changes that are related to their femininity in addition to the appearance aspect and can face challenges in the part of women’s identity that is related to their body. This research deals with the process of changes in women’s physical identity in the context of culture and society
Materials and Methods: A qualitative method was used for the research, and in this regard, in-depth and semi-structured interviews were conducted with 15 women from Tehran who had undergone treatment for breast cancer, along with 5 companions who were alongside the patients during their illness, and 3 surgical doctors. The interviews focused on the experiences, emotions, and actions of the women in response to bodily changes. Sampling was conducted through purposive and snowball sampling methods. The thematic analysis technique developed by Braun and Clarke was employed for analyzing the interviews.
Results: The participating women were aged 27 to 65 years, with 8 holding bachelor’s degrees or higher. Seven women were housewives, 8 were employed, and 13 had undergone mastectomies. The main themes identified include changes in the female body, societal challenges, disruption of body image, support and companionship, economic constraints, and the redefinition of body image. These themes explain the process of women’s coping with bodily changes. Following bodily changes, women face challenges from society. Society judges women’s bodies after these changes and views them negatively. Furthermore, women experience dissatisfaction with their bodies, perceiving them as inadequate for fulfilling feminine roles and responsibilities as wives and mothers. However, over time, through acceptance of the changes and body management, women strive to reconstruct their body image. In addition, the women’s economic situation and the support and companionship of those around them—manifesting as acceptance of the bodily changes and emotional support—can facilitate the acceptance of these changes.
Conclusion: Given the importance of the body in defining femininity, women, after experiencing breast cancer, face not only the suffering of the disease but also identity challenges. Therefore, breast cancer treatment, alongside clinical interventions, requires societal awareness of how to interact with affected women.
Materials and Methods: A qualitative method was used for the research, and in this regard, in-depth and semi-structured interviews were conducted with 15 women from Tehran who had undergone treatment for breast cancer, along with 5 companions who were alongside the patients during their illness, and 3 surgical doctors. The interviews focused on the experiences, emotions, and actions of the women in response to bodily changes. Sampling was conducted through purposive and snowball sampling methods. The thematic analysis technique developed by Braun and Clarke was employed for analyzing the interviews.
Results: The participating women were aged 27 to 65 years, with 8 holding bachelor’s degrees or higher. Seven women were housewives, 8 were employed, and 13 had undergone mastectomies. The main themes identified include changes in the female body, societal challenges, disruption of body image, support and companionship, economic constraints, and the redefinition of body image. These themes explain the process of women’s coping with bodily changes. Following bodily changes, women face challenges from society. Society judges women’s bodies after these changes and views them negatively. Furthermore, women experience dissatisfaction with their bodies, perceiving them as inadequate for fulfilling feminine roles and responsibilities as wives and mothers. However, over time, through acceptance of the changes and body management, women strive to reconstruct their body image. In addition, the women’s economic situation and the support and companionship of those around them—manifesting as acceptance of the bodily changes and emotional support—can facilitate the acceptance of these changes.
Conclusion: Given the importance of the body in defining femininity, women, after experiencing breast cancer, face not only the suffering of the disease but also identity challenges. Therefore, breast cancer treatment, alongside clinical interventions, requires societal awareness of how to interact with affected women.
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