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Abstract Background Diphereline is a Gonadotropin-Releasing Hormone agonist commonly used in patients with breast cancer. This study aimed to compare the efficacy and safety of one-month and three-month Microrelin injections produced by Homa Pharmed Company with three-month Diphereline injections manufactured by IPSEN, France. Methods The study was a non-inferiority randomized clinical trial conducted between 2019 and 2023 on premenopausal women candidates for endocrine therapy. The participants were randomly assigned in blocks of six to one of three groups named A (Diphereline 11.25 mg), B (Microrelin 11.25 mg), and C (Microrelin 3.75 mg). The participants’ menopausal symptoms, estradiol, and FSH serum levels were recorded in three-month intervals for one year. The efficacy of each medication and its side effects were compared among the three groups by statistical analysis during the one-year follow-up. Results The study included 133 patients with breast cancer. A decreasing trend in the serum levels of FSH and estradiol and an increasing trend of menopausal symptoms were recorded during the study. No specific side effects leading to drug disruption, hospitalization, or exclusion from the study were observed. Adjusting the effect of study group and time showed no significant changes in estradiol levels between groups B (p = 0.506) and C (p = 0.607) and group A. Also, serum FSH changes between groups B (p = 0.132) and C (p = 0.104) compared to group A were not significant. Moreover, the menopausal symptoms during the one-year follow-up did not significantly increase in group B (p = 0.108) and C (p = 0.113) compared to group A. Conclusions It can be concluded that injections of both Microrelin 11.25 mg and 3.75 mg, produced by Homa Pharmed, Iran, are non-inferior in terms of effectiveness and incidence of menopausal symptoms compared to Diphereline, manufactured by IPSEN, France. Trial registration IRCT.ir, IRCT20201227049847N1; Registered on 09/01/2021.

Abstract Background Identifying breast cancer risk factors is a critical component of preventative strategies for this disease. This study aims to identify modifiable and non-modifiable risk factors of breast cancer in Iranian women. Methods We used international databases (PubMed/Medline, Scopus, Web of Knowledge, and Embase) and national databases (SID, Magiran, and ISC) to retrieve relevant studies until November 13, 2022. The odds ratio (OR) with a 95% confidence interval using the random-effect model was used to estimate the pooled effect. The publication bias was assessed by the Egger and Begg test. A sensitivity analysis was conducted to evaluate the effect of each included study on the final measurement. Results Of the 30,351 retrieved articles, 24 matched case–control records were included with 12,460 participants (5675 newly diagnosed cases of breast cancer and 6785 control). This meta-analysis showed that of the known modifiable risk factors for breast cancer, obesity (vs normal weight) had the highest risk (OR = 2.17, 95% CI 1.47 to 3.21; I 2 = 85.7) followed by age at marriage (25–29 vs

Abstract Background Breast cancer-related lymphedema is one of the most important complications that adversely affect patients' quality of life. Lymphedema can be managed if its risk factors are known and can be modified. This study aimed to select an appropriate model to predict the risk of lymphedema and determine the factors affecting lymphedema. Method This study was conducted on data of 970 breast cancer patients with lymphedema referred to a lymphedema clinic. This study was designed in two phases: developing an appropriate model to predict the risk of lymphedema and identifying the risk factors. The first phase included data preprocessing, optimizing feature selection for each base learner by the Genetic algorithm, optimizing the combined ensemble learning method, and estimating fitness function for evaluating an appropriate model. In the second phase, the influential variables were assessed and introduced based on the average number of variables in the output of the proposed algorithm. Result Once the sensitivity and accuracy of the algorithms were evaluated and compared, the Support Vector Machine algorithm showed the highest sensitivity and was found to be the superior model for predicting lymphedema. Meanwhile, the combined method had an accuracy coefficient of 91%. The extracted significant features in the proposed model were the number of lymph nodes to the number of removed lymph nodes ratio (68%), feeling of heaviness (67%), limited range of motion in the affected limb (65%), the number of the removed lymph nodes ( 64%), receiving radiotherapy (63%), misalignment of the dominant and the involved limb (62%), presence of fibrotic tissue (62%), type of surgery (62%), tingling sensation (62%), the number of the involved lymph nodes (61%), body mass index (61%), the number of chemotherapy sessions (60%), age (58%), limb injury (53%), chemotherapy regimen (53%), and occupation (50%). Conclusion Applying a combination of ensemble learning approach with the selected classification algorithms, feature selection, and optimization by Genetic algorithm, Lymphedema can be predicted with appropriate accuracy. Developing applications by effective variables to determine the risk of lymphedema can help lymphedema clinics choose the proper preventive and therapeutic method.