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Nastaran Mirfarhadi , Atefeh Ghanbari, Abbas Rahimi,
Volume 11, Issue 1 (5-2017)
Volume 11, Issue 1 (5-2017)
Abstract
Background and Aim: Early diagnosis is a tenet in oncology and enables early treatment with the expectation of improved outcome. The aim of this study was to determine the factors associated with personal characteristics and clinical signs in patients with breast cancer.
Materials and Methods: This research was a descriptive analytic that
cross-sectionally assessed 232 patients with definite breast cancer diagnosis that referred to Razi hospital located in Rasht using a researcher designed questionnaire including demographic and clinical signs. Collected data (mammography, tumor size, pathological stage of tumor) were obtained from medical records of patients. Gathered data analysis was accomplished with SPSS V.19 and for description of data from average and standard deviation for inference statics fisher test with a
P value of 0.05 were used.
Results: Mean age of subject was (49.80+10.27). 44 individuals (14%) had a precedent regular mammography before disease. Hundred and four (44.8%) in first appointment were referred to a general surgeon. Hundred and thirty six (58%) women were in stage III of the disease. Hundred and twenty nine (60%) patients had a tumor size more than 5 cm and 106 (46%) had a lymph node metastasis at the time of diagnosis. Patients referring with advanced stage of breast cancer had a low education (P=0.04) and income level (P=0.01).
Conclusions: Recognizing associated personal and clinical factors with early diagnosis can provide essential information for planning health education, screening and presenting appropriate solutions to overcome barriers to treatment and care in health system planning in this provinc
Seyed Abbas Mahmoodi , Kamal Mirzaie, Seyed Mostafa Mahmoodi ,
Volume 11, Issue 3 (9-2017)
Volume 11, Issue 3 (9-2017)
Abstract
Background and Aim: Gastric cancer is the second leading cause of cancer death in the world. Due to the prevalence of the disease and the high mortality rate of gastric cancer in Iran, the factors affecting the development of this disease should be taken into account. In this research, two data mining techniques such as Apriori and ID3 algorithm were used in order to investigate the effective factors in gastric cancer.
Materials and Methods: Data sets in this study were collected among 490 patients including 220 patients with gastric cancer and 270 healthy samples referred to Imam Reza hospital in Tabriz. The best rules related to this data set were extracted through Apriori algorithm and implementing it in MATLAB. ID3 algorithm was also used to investigate these factors.
Results: The results showed that having a history of gastro esophageal reflux has the greatest impact on the incidence of this disease. Some rules extracted through Apriori algorithm can be a model to predict patient status and the incidence of the disease and investigate factors affecting the disease. The prediction accuracy achieved through ID3 algorithm is 85.56 which was a very good result in the prediction of gastric cancer.
Conclusion: Using data mining, especially in medical data, is very useful due to the large volume of data and unknown relationships between systemic, personal, and Behavioral Features of patients. The results of this study could help physicians to identify the contributing factors in incidence of the disease and predict the incidence of the disease.
Materials and Methods: Data sets in this study were collected among 490 patients including 220 patients with gastric cancer and 270 healthy samples referred to Imam Reza hospital in Tabriz. The best rules related to this data set were extracted through Apriori algorithm and implementing it in MATLAB. ID3 algorithm was also used to investigate these factors.
Results: The results showed that having a history of gastro esophageal reflux has the greatest impact on the incidence of this disease. Some rules extracted through Apriori algorithm can be a model to predict patient status and the incidence of the disease and investigate factors affecting the disease. The prediction accuracy achieved through ID3 algorithm is 85.56 which was a very good result in the prediction of gastric cancer.
Conclusion: Using data mining, especially in medical data, is very useful due to the large volume of data and unknown relationships between systemic, personal, and Behavioral Features of patients. The results of this study could help physicians to identify the contributing factors in incidence of the disease and predict the incidence of the disease.
Ali Akbar Khasseh, Sholeh Zakiani, Faramarz Soheili,
Volume 12, Issue 3 (9-2018)
Volume 12, Issue 3 (9-2018)
Abstract
Background and Aim: Scientometric studies are one of the most effective methods of scientific evaluation in databases. The aim of this study was to investigate Breast cancer in Iran from 2000-2016.
Materials and Methods: This study has an applied approach and was conducted using scientometric indices. The st tistical population was the indexed articles related to Breast cancer between the years 2000 and 2016 by Iranian researchers at the Science Web site.
Results: During the period 2000-2016, researchers have published 2198 articles on Breast cancer that indicate a steady and steady increase in the number of studies conducted in this area. The results of the study showed that Qaderi is the most prolific researcher in the field of Breast cancer in terms of the number of articles in Iran, Ebrahimi and Montazeri are in the second and third positions respectively. The highest H-index belongs to Montazeri, Qaderi and Abraham, respectively. Researchers in the field of Breast cancer have collaborated with researchers from 65 countries and more with the United States and Canada. The most co-operation has been between researchers in Tehran and Tabriz. The analysis of the keywords used in Breast cancer research in the form of supragloss showed that Iran, Apoptosis and Polymorphism were the most frequent keywords in the studied works.
Conclusion: The upward trend in Breast cancer research indicates the growing importance of this area in Iran. Given the global growth of Breast cancer research and the importance of international research participation, Iranianresearchers should more and more engage in scientific collaboration with their counterparts abroad.
Materials and Methods: This study has an applied approach and was conducted using scientometric indices. The st tistical population was the indexed articles related to Breast cancer between the years 2000 and 2016 by Iranian researchers at the Science Web site.
Results: During the period 2000-2016, researchers have published 2198 articles on Breast cancer that indicate a steady and steady increase in the number of studies conducted in this area. The results of the study showed that Qaderi is the most prolific researcher in the field of Breast cancer in terms of the number of articles in Iran, Ebrahimi and Montazeri are in the second and third positions respectively. The highest H-index belongs to Montazeri, Qaderi and Abraham, respectively. Researchers in the field of Breast cancer have collaborated with researchers from 65 countries and more with the United States and Canada. The most co-operation has been between researchers in Tehran and Tabriz. The analysis of the keywords used in Breast cancer research in the form of supragloss showed that Iran, Apoptosis and Polymorphism were the most frequent keywords in the studied works.
Conclusion: The upward trend in Breast cancer research indicates the growing importance of this area in Iran. Given the global growth of Breast cancer research and the importance of international research participation, Iranianresearchers should more and more engage in scientific collaboration with their counterparts abroad.
Maryam Valizadeh, Leila Rouhi, Seyed Hossein Hejazi,
Volume 12, Issue 3 (9-2018)
Volume 12, Issue 3 (9-2018)
Abstract
Background and Aim: Breast cancer is one of the most common types of cancers and is the second leading cause of death form of cancer in women. In recent years, many scientific and medical studies have shown that Green tea has anti-proliferative, anti-mutagenic, anti-oxidant, antibacterial and antiviral effects. Some Green tea polyphenols have anti-cancer activity. In the present study, the effect of Green tea extract was evaluated on the Breast cancer cell line (SK-BR-3) and compared with human fibroblast cell line (HU-02).
Materials and Methods: SK-BR-3 and HU-02 cell lines were treated for 24, 48 and 72 hours with different concentrations of Green tea (50, 100, 200, 400 and 800 μg/ml). Then, Bioavailability was analyzed by MTT kit and Apoptosis was analyzed by flow cytometry using an Annexin V-FITS Kit.
Results: With increasing concentrations of Green tea extract in dose and time dependent manner, bioavailability of cells showed a decrease as compared to control group. Increased incidence of apoptosis was significantly higher in other experimental groups than the control group, while the concentration of 800 μg/ml of Green tea extract was more effective in SKBR3 cell line. Green tea did not show significant effect in HU-02 cells.
Conclusion: Due to the fact that cell proliferation and abnormal apoptosis are one of the main characteristics of cancer cells, Green tea can be used to reduce cell proliferation and increase apoptosis in prevention and treatment of Breast cancer.
Materials and Methods: SK-BR-3 and HU-02 cell lines were treated for 24, 48 and 72 hours with different concentrations of Green tea (50, 100, 200, 400 and 800 μg/ml). Then, Bioavailability was analyzed by MTT kit and Apoptosis was analyzed by flow cytometry using an Annexin V-FITS Kit.
Results: With increasing concentrations of Green tea extract in dose and time dependent manner, bioavailability of cells showed a decrease as compared to control group. Increased incidence of apoptosis was significantly higher in other experimental groups than the control group, while the concentration of 800 μg/ml of Green tea extract was more effective in SKBR3 cell line. Green tea did not show significant effect in HU-02 cells.
Conclusion: Due to the fact that cell proliferation and abnormal apoptosis are one of the main characteristics of cancer cells, Green tea can be used to reduce cell proliferation and increase apoptosis in prevention and treatment of Breast cancer.
Amir Hossein Eskandari, Sadaf Alipour,
Volume 13, Issue 3 (9-2019)
Volume 13, Issue 3 (9-2019)
Abstract
Background and goals: Breast surgery is one of the most common surgical operations performed worldwide as well as in Iran. Acute postoperative pain is managed by different therapeutic modalities in these procedures, and opioid are the most frequently used option; however their adverse consequences imposes restriction of use. The goal of this article is to review the effects of gabapentin on postoperative pain and opioid use in breast surgeries.
Materials and Method: PubMed, Ovid Medline, and Scopus databases from 2000 to 2019; as well as Google scholar, first 350 results, were searched for all clinical trials and review articles about the subject, using various related keywords. Sixty-two articles were reviewed by 2 researchers and finally data from 22 papers were gathered and assessed.
Results: This review demonstrates that gabapentin is effective in reducing acute postoperative pain after operations of the breast. Also, rate of opioid consumption, an important objective in the period after surgery, is reduced by use of opioids.
Conclusion: This study prompts the effectiveness of gabapentin in controlling postoperative pain in breast operations; since this drug is very seldom used for this purpose in our country, we propose that medical staff consider it as a powerful option after breast procedures.
Materials and Method: PubMed, Ovid Medline, and Scopus databases from 2000 to 2019; as well as Google scholar, first 350 results, were searched for all clinical trials and review articles about the subject, using various related keywords. Sixty-two articles were reviewed by 2 researchers and finally data from 22 papers were gathered and assessed.
Results: This review demonstrates that gabapentin is effective in reducing acute postoperative pain after operations of the breast. Also, rate of opioid consumption, an important objective in the period after surgery, is reduced by use of opioids.
Conclusion: This study prompts the effectiveness of gabapentin in controlling postoperative pain in breast operations; since this drug is very seldom used for this purpose in our country, we propose that medical staff consider it as a powerful option after breast procedures.
Azita Yazdani, Ali Asghar Safaei, Reza Safdari, Maryam Zahmatkeshan,
Volume 13, Issue 3 (9-2019)
Volume 13, Issue 3 (9-2019)
Abstract
Background and Aim: Breast cancer is the most common type of cancer and the main cause of death from cancer in women worldwide. Technologies such as data mining, have enabled experts in this area to improve decision making in the early diagnosis of the disease. Therefore, the purpose of this research is to develop an automatic diagnostic model for breast cancer by employing data mining methods and selecting the model with the highest accuracy of diagnosis.
Materials and Methods: In this study, 654 available patient records of Motahari breast cancer Clinic in Shiraz" were used as the sample. The number of records was reduced to 621 after the pre-processing operation. These samples had 22 features that ultimately used ten were used as effective features in the design of the model. Three types of Decision tree, Naive Bayes and Artificial neural network were used for diagnosis of breast cancer and 10-fold cross-validation method for constructing and evaluating the model on the collected data set.
Results: The results of the three techniques mentioned all three models showed promising results in detecting breast cancer. Finally, the artificial neural network accounted for the highest accuracy of 94/49%(sensitivity 96/19%, specificity 86/36%) in the diagnosis of breast cancer.
Conclusion: Based on the results of the decision tree, the risk factors such as age, weight, Age of menstruation, menopause, OCP of records duration, and the age of the first pregnancy were among the factors affecting the incidence of breast cancer in women.
Materials and Methods: In this study, 654 available patient records of Motahari breast cancer Clinic in Shiraz" were used as the sample. The number of records was reduced to 621 after the pre-processing operation. These samples had 22 features that ultimately used ten were used as effective features in the design of the model. Three types of Decision tree, Naive Bayes and Artificial neural network were used for diagnosis of breast cancer and 10-fold cross-validation method for constructing and evaluating the model on the collected data set.
Results: The results of the three techniques mentioned all three models showed promising results in detecting breast cancer. Finally, the artificial neural network accounted for the highest accuracy of 94/49%(sensitivity 96/19%, specificity 86/36%) in the diagnosis of breast cancer.
Conclusion: Based on the results of the decision tree, the risk factors such as age, weight, Age of menstruation, menopause, OCP of records duration, and the age of the first pregnancy were among the factors affecting the incidence of breast cancer in women.
Vahid Changizi, Mohammad Reza Zare, Sahel Kasiri,
Volume 13, Issue 5 (1-2020)
Volume 13, Issue 5 (1-2020)
Abstract
Background and Aim: Due to the presence of ionizing radiation sources in the environment and their potential to enter the food chain, the natural radiation in the rice product of Mahmoud Abadu residents of this area should be evaluated.
Materials and Methods: Using standard sampling methods, the number of sampling points and locations (about 10 points) was determined. After recording the geographical location of the sites, 2 kg of soil and 2 kg of rice were removed and 20 samples were coded. 950 g of soil and rice were milled and transferred to standard Marinelli dishes with 50 mesh. The samples were completely sealed and after about one month, they were visualized with ultra-pure germanium detectors (HPGe). Subsequently, specific radionuclide radiosensitivity in soil and rice soil samples, radionuclide transfer factors from soil to rice, annual effective dose and risk of cancer due to rice consumption were measured.
Results: Effective total dose of nuclei studied in #value, lifetime cancer risk of U238 from #value to 0.00019, Ra226 from #value to 0.00008, U235 # value, Th232 from #value to 0.00027, K40 From 0.00014 to 0.00082 and finally for zero cesium.
Conclusion: There is no harmful effect on the people of the region regarding the radionuclides of rice.
Materials and Methods: Using standard sampling methods, the number of sampling points and locations (about 10 points) was determined. After recording the geographical location of the sites, 2 kg of soil and 2 kg of rice were removed and 20 samples were coded. 950 g of soil and rice were milled and transferred to standard Marinelli dishes with 50 mesh. The samples were completely sealed and after about one month, they were visualized with ultra-pure germanium detectors (HPGe). Subsequently, specific radionuclide radiosensitivity in soil and rice soil samples, radionuclide transfer factors from soil to rice, annual effective dose and risk of cancer due to rice consumption were measured.
Results: Effective total dose of nuclei studied in #value, lifetime cancer risk of U238 from #value to 0.00019, Ra226 from #value to 0.00008, U235 # value, Th232 from #value to 0.00027, K40 From 0.00014 to 0.00082 and finally for zero cesium.
Conclusion: There is no harmful effect on the people of the region regarding the radionuclides of rice.
Sanaz Noroozi, Rahim Ahmadi, Minoo Iranshahi,
Volume 14, Issue 2 (5-2020)
Volume 14, Issue 2 (5-2020)
Abstract
Background and Aim: Studies have shown that non-steroid anti-inflammatory drugs have an effect on cancer cells of digestive system, however, the cellular and molecular mechanism of the non-steroidal anti-inflammatory drugs and their effects on the proliferation of gastrointestinal cancer cells is unclear in many cases. The aim of this study was to investigate the effects of cytotoxic dose of tolmetin on BAX and BCL2 genes expression level in gastric cancer cells (AGS).
Materials and Methods: In this laboratory-experimental study, AGS cells were purchased from Pasture institute and divided into control group and groups exposed to different concentrations of tolmetin. MTT assay was used to measure cytotoxic effects of tolmetin. Real-time PCR was used to evaluate BAX and BCL2 genes expression levels. The data were statistically analyzed between groups using ANOVA.
Results: Higher decrease in relative expression level of anti-apoptotic BCL2 was observed than expression level of apoptotic BAX gene in AGS cells exposed to IC50 concentration of tolmetin.
Conclusion: The results of this study indicated that tolmetin can induce apoptosis in gastric cancer cells by decreasing of anti-apoptotic BCL2 gene expression level. Therefore, consideration might be given to tolmetin in treatment of gastric cancer.
Materials and Methods: In this laboratory-experimental study, AGS cells were purchased from Pasture institute and divided into control group and groups exposed to different concentrations of tolmetin. MTT assay was used to measure cytotoxic effects of tolmetin. Real-time PCR was used to evaluate BAX and BCL2 genes expression levels. The data were statistically analyzed between groups using ANOVA.
Results: Higher decrease in relative expression level of anti-apoptotic BCL2 was observed than expression level of apoptotic BAX gene in AGS cells exposed to IC50 concentration of tolmetin.
Conclusion: The results of this study indicated that tolmetin can induce apoptosis in gastric cancer cells by decreasing of anti-apoptotic BCL2 gene expression level. Therefore, consideration might be given to tolmetin in treatment of gastric cancer.
Raoof Nopour, Mohammad Shirkhoda, Sharareh Rostam Niakan Kalhori,
Volume 14, Issue 2 (5-2020)
Volume 14, Issue 2 (5-2020)
Abstract
Background and Aim: Colorectal cancer is one of the most common gastrointestinal cancers among human beings and the most important cause of death in the world. Based on the risk of colorectal cancer for individuals, using an appropriate screening program can help to prevent the disease. Therefore, the purpose of this study was to design a model for screening colorectal cancer based on risk factors to increase the survival rate of the disease on the one hand and to reduce the mortality rate on the other.
Materials and Methods: By reviewing articles and patients' records, 38 risk factors were detected. To determine the most important risk factors clinically, CVR(content validity ratio) was used; and considering the collected data, Spearman correlation coefficient and logistic regression analysis were applied for statistical analyses. Then, four algorithms -- J-48, J-RIP, PART and REP-Tree -- were used for data mining and rule generation. Finally, the most common model was obtained based on comparing the performance of the algorithms.
Results: After comparing the performance of algorithms, the J-48 algorithm with an F-Measure of 0.889 was found to be better than the others.
Conclusion: The results of evaluating J-48 data mining algorithm performance showed that this algorithm could be considered as the most appropriate model for colorectal cancer risk prediction.
Materials and Methods: By reviewing articles and patients' records, 38 risk factors were detected. To determine the most important risk factors clinically, CVR(content validity ratio) was used; and considering the collected data, Spearman correlation coefficient and logistic regression analysis were applied for statistical analyses. Then, four algorithms -- J-48, J-RIP, PART and REP-Tree -- were used for data mining and rule generation. Finally, the most common model was obtained based on comparing the performance of the algorithms.
Results: After comparing the performance of algorithms, the J-48 algorithm with an F-Measure of 0.889 was found to be better than the others.
Conclusion: The results of evaluating J-48 data mining algorithm performance showed that this algorithm could be considered as the most appropriate model for colorectal cancer risk prediction.
Saeid Mirzaeian, Khalil Khashei Varnamkhasti,
Volume 15, Issue 2 (5-2021)
Volume 15, Issue 2 (5-2021)
Abstract
Background and Aim: Breast cancer is one of the most common types of cancer and the second leading cause of cancer death in women. The effect of ligustilide - isolated from the Kelussia on MCF-7 breast cancer cell line compared with human fibroblast cell line (HDF1BOM) was evaluated in the present study.
Materials and Methods: MCF-7 and HDF1BOM cell lines were treated for 48 and 72 hours with different concentrations (0, 50, 100, 150 and 200 mg/ml) of Z-ligustilide ((ligustilide (Z)-3-butylidene-4,5-dihydrophthalide)). Then, bioavailability was analyzed by ELISA reader using MTT kit and Apoptosis was assessed by flow cytometry using an Annexin V-FITC/PI kit in two times. Statistical analysis was accomplished by ANOVA and Huynh-Feldt tests using SPSS and FlowJo software.
Results: The results of MTT test showed reduce bioavailability of MCF-7 cell line in all concentrations (from 70.60% in 50 mg/ml to 6.80% in 200 mg/ml (for 48 h of treatment), from 61.95% in 50 mg/ml to 5.84% in 200 mg/ml (for 72 h of treatment)). Also, the results of the Annexin test showed that the induction of apoptosis is not time and concentration dependent manner, and it had increased in most groups. highest percentage of apoptosis were; 98.3% in 50 mg/ml (for 48 h of treatment), and 97.4 % in 100 mg/ml (for 72 h of treatment). The results of MTT test showed reduce bioavailability of HDF1BOM cell line in both times compared to the control group (from 97.24% in 50 mg/ml to 5.97% in 200 mg/ml (for 48 h of treatment), from 90.93% in 50 mg/ml to 5.26% in 200 mg/ml (for 72 h of treatment)). Also, according to the results of Annexin, early apoptotic cells show a higher percentage (4.21% in 150 mg/ml (for 48 h of treatment), 1.67% in 200 mg/ml (for 72 h of treatment)). Ligustilide did not show considerable cytotoxicity in HDF1BOM cells.
Conclusion: Due to the fact that ligustilide has an inhibitory effect on the growth, proliferation and invasion of cancer cells by inducting apoptosis, it seems that ligustilide can be used to reduce cell proliferation of breast cancer.
Materials and Methods: MCF-7 and HDF1BOM cell lines were treated for 48 and 72 hours with different concentrations (0, 50, 100, 150 and 200 mg/ml) of Z-ligustilide ((ligustilide (Z)-3-butylidene-4,5-dihydrophthalide)). Then, bioavailability was analyzed by ELISA reader using MTT kit and Apoptosis was assessed by flow cytometry using an Annexin V-FITC/PI kit in two times. Statistical analysis was accomplished by ANOVA and Huynh-Feldt tests using SPSS and FlowJo software.
Results: The results of MTT test showed reduce bioavailability of MCF-7 cell line in all concentrations (from 70.60% in 50 mg/ml to 6.80% in 200 mg/ml (for 48 h of treatment), from 61.95% in 50 mg/ml to 5.84% in 200 mg/ml (for 72 h of treatment)). Also, the results of the Annexin test showed that the induction of apoptosis is not time and concentration dependent manner, and it had increased in most groups. highest percentage of apoptosis were; 98.3% in 50 mg/ml (for 48 h of treatment), and 97.4 % in 100 mg/ml (for 72 h of treatment). The results of MTT test showed reduce bioavailability of HDF1BOM cell line in both times compared to the control group (from 97.24% in 50 mg/ml to 5.97% in 200 mg/ml (for 48 h of treatment), from 90.93% in 50 mg/ml to 5.26% in 200 mg/ml (for 72 h of treatment)). Also, according to the results of Annexin, early apoptotic cells show a higher percentage (4.21% in 150 mg/ml (for 48 h of treatment), 1.67% in 200 mg/ml (for 72 h of treatment)). Ligustilide did not show considerable cytotoxicity in HDF1BOM cells.
Conclusion: Due to the fact that ligustilide has an inhibitory effect on the growth, proliferation and invasion of cancer cells by inducting apoptosis, it seems that ligustilide can be used to reduce cell proliferation of breast cancer.
Vahid Changizi, Maryam Mohammadi, Samaneh Baradaran, Mehran Taheri,
Volume 15, Issue 4 (10-2021)
Volume 15, Issue 4 (10-2021)
Abstract
Background and Aim: On panoramic radiographs, sensitive organs, including the thyroid, are exposed to radiation. Thyroid cancer is one of the most common cancers in Iran. That is why, in this study the effective dose and risk of thyroid cancer were estimated on panoramic radiography.
Materials and Methods: Seventy GR200 thermoluminescence (TLD) dosimeters were used to estimate the absorbed dose of thyroid. The dosimeters were calibrated and placed on the patients’ necks during panoramic radiography. After dosimeters were read, the mean absorbed dose and effective thyroid dose were calculated in three groups with different radiation conditions. Lifetime Attributable Risk (LAR) of thyroid cancer was estimated using the model presented in the BEIR VII report. GraphPad Prism statistical software was used to analyze the data.
Results: The mean absorbed dose of thyroid lobes in groups M, L, XL (According to mandibular size) was estimated to be 0.116±0.01, 0.123±0.04 and 0.03±0.134 mg, respectively. The right thyroid lobe in group XL with absorption dose of 0.143±0.05 mg and the left lobe in group M with absorption dose of 0.106±0.03 mg had the highest and the lowest absorption doses, respectively. The difference between the absorbed doses of the right and left thyroid lobes in any of the three groups was not statistically significant. Thyroid absorption doses in these three groups were not statistically significant. The highest risk of thyroid cancer in the age range of 15-60 years was related to the age of 15, which was estimated to be 0.238 in women and 0.042 in men per 100,000 people.
Conclusion: In lower ages and among women, the risk of thyroid cancer is higher than that of men. Also, due to the impossibility of limiting thyroid radiation in panoramic radiography using lead thyroid collar that causes metal artifacts, we should reduce the number of panoramic radiographs as much as possible, especially at lower ages.
Materials and Methods: Seventy GR200 thermoluminescence (TLD) dosimeters were used to estimate the absorbed dose of thyroid. The dosimeters were calibrated and placed on the patients’ necks during panoramic radiography. After dosimeters were read, the mean absorbed dose and effective thyroid dose were calculated in three groups with different radiation conditions. Lifetime Attributable Risk (LAR) of thyroid cancer was estimated using the model presented in the BEIR VII report. GraphPad Prism statistical software was used to analyze the data.
Results: The mean absorbed dose of thyroid lobes in groups M, L, XL (According to mandibular size) was estimated to be 0.116±0.01, 0.123±0.04 and 0.03±0.134 mg, respectively. The right thyroid lobe in group XL with absorption dose of 0.143±0.05 mg and the left lobe in group M with absorption dose of 0.106±0.03 mg had the highest and the lowest absorption doses, respectively. The difference between the absorbed doses of the right and left thyroid lobes in any of the three groups was not statistically significant. Thyroid absorption doses in these three groups were not statistically significant. The highest risk of thyroid cancer in the age range of 15-60 years was related to the age of 15, which was estimated to be 0.238 in women and 0.042 in men per 100,000 people.
Conclusion: In lower ages and among women, the risk of thyroid cancer is higher than that of men. Also, due to the impossibility of limiting thyroid radiation in panoramic radiography using lead thyroid collar that causes metal artifacts, we should reduce the number of panoramic radiographs as much as possible, especially at lower ages.
Mr Kasra Dolatkhahi, Adel Azar, Tooraj Karimi, Mohammad Hadizadeh,
Volume 15, Issue 4 (10-2021)
Volume 15, Issue 4 (10-2021)
Abstract
Background and Aim: Cancer and in particular Breast cancer are among the diseases that have the highest mortality rate in Iran after heart disease. The accurate prognosis for Breast cancer is important, and the presence of various symptoms and features of this disease makes it difficult for doctors to diagnose. This study aimed to identify the factors affecting Breast cancer, modeling and ultimately diagnosing the risk of Breast cancer.
Materials and Methods: In the present study, first, by content analysis and library studies, the effective factors in Breast cancer were identified, then with the help of a team of experts consisting of physicians and subspecialists in Breast oncology and Breast surgery; With the help of the Delphi method, the factors were adjusted and 26 final factors that were numerically correct and string based on local and climatic conditions were approved. Then, according to the final factors and based on the medical records of 5208 patients in the Cancer Research Center of Shahid Beheshti University of medical sciences, to diagnose cancer, Decision Tree, Random Forest, and Support Vector Machine methods were used as machine learning methods.
Results: In the first step, by content analysis method, 29 effective factors in Breast cancer were identified. Then, taking into account the indigenous and climatic conditions and using the Delphi method and also using the opinions of 18 Experts during three years, 26 factors were finalized. In the final step, using the medical records of the patients and the results obtained from the three methods mentioned, random forest, had the highest accuracy of 94.75% and precision of 97.26% in diagnosing Breast cancer. It has been noted that, compared to other similar studies, indigenous databases have been exploited, the accuracy obtained has been very close to previous studies, and in many cases much better.
Conclusion: Using the random forest method and taking advantage of the factors affecting Breast cancer, the ability to diagnose cancer has been provided with greatest accuracy.
Materials and Methods: In the present study, first, by content analysis and library studies, the effective factors in Breast cancer were identified, then with the help of a team of experts consisting of physicians and subspecialists in Breast oncology and Breast surgery; With the help of the Delphi method, the factors were adjusted and 26 final factors that were numerically correct and string based on local and climatic conditions were approved. Then, according to the final factors and based on the medical records of 5208 patients in the Cancer Research Center of Shahid Beheshti University of medical sciences, to diagnose cancer, Decision Tree, Random Forest, and Support Vector Machine methods were used as machine learning methods.
Results: In the first step, by content analysis method, 29 effective factors in Breast cancer were identified. Then, taking into account the indigenous and climatic conditions and using the Delphi method and also using the opinions of 18 Experts during three years, 26 factors were finalized. In the final step, using the medical records of the patients and the results obtained from the three methods mentioned, random forest, had the highest accuracy of 94.75% and precision of 97.26% in diagnosing Breast cancer. It has been noted that, compared to other similar studies, indigenous databases have been exploited, the accuracy obtained has been very close to previous studies, and in many cases much better.
Conclusion: Using the random forest method and taking advantage of the factors affecting Breast cancer, the ability to diagnose cancer has been provided with greatest accuracy.
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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