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Background: Despite declining mortality in most countries and in Lithuania, ovarian cancer burden has remained high. Studies have indicated that antihypertensive medications use may help to improve ovarian cancer survival, however findings remain controversial. The aim of the study was to analyse the association between post-diagnosis antihypertensive medications intake and cancer-specific survival in ovarian cancer patients. Methods: This retrospective cohort study included 588 ovarian cancer cases diagnosed between 2013 and 2015. Hazard ratios (HR) and corresponding 95% confidence intervals (95%CI) were estimated using multivariable Cox proportional hazards models to assess associations between antihypertensive medications and ovarian cancer-specific mortality. Results: In total, 279 (47%) patients died during the follow-up; 242 (87%) of them died due to ovarian cancer. The risk of ovarian cancer death was reduced in angiotensin-converting enzyme inhibitors (ACE inhibitors) users vs. non-users (HR 0.55, 95% CI: 0.36–0.83). Subgroup analysis showed better ovarian cancer survival in higher dose ACE inhibitors users (HR 0.46, 95% CI: 0.28–0.77, p for trend 0.002); the effect was also stronger in age 51–65 years, stage I–III, surgery or chemotherapy treatment, pre-diagnosis ACE inhibitor users' and pre-diagnosis hypertension subgroups. The risk of cancer-specific death was slightly lower among calcium-channel blocker and angiotensin-receptor blocker users and higher among beta-blocker users as compared to non-users, however chance and confounding could not be ruled out. We found no association between the use of centrally and peripherally acting antiadrenergic agents and diuretics and risk of ovarian cancer-specific mortality. Conclusions: Our findings imply that post-diagnosis use of ACE inhibitors may be associated with reduced ovarian cancer-specific mortality; however, further research is needed for the comprehensive assessment. [ABSTRACT FROM AUTHOR]

Background: Despite the significant weight of difficulty, Ethiopia's survival rate and mortality predictors have not yet been identified. Finding out what influences outpatient breast cancer patients' survival time was the major goal of this study. Methods: A retrospective study was conducted on outpatients with breast cancer. In order to accomplish the goal, 382 outpatients with breast cancer were included in the study using information obtained from the medical records of patients registered at the University of Gondar referral hospital in Gondar, Ethiopia, between May 15, 2016, and May 15, 2020. In order to compare survival functions, Kaplan-Meier plots and the log-rank test were used. The Cox-PH model and Bayesian parametric survival models were then used to examine the survival time of breast cancer outpatients. The use of integrated layered Laplace approximation techniques has been made. Results: The study included 382 outpatients with breast cancer in total, and 148 (38.7%) patients died. 42 months was the estimated median patient survival time. The Bayesian Weibull accelerated failure time model was determined to be suitable using model selection criteria. Stage, grade 2, 3, and 4, co-morbid, histological type, FIGO stage, chemotherapy, metastatic number 1, 2, and >=3, and tumour size all have a sizable impact on the survival time of outpatients with breast cancer, according to the results of this model. The breast cancer outpatient survival time was correctly predicted by the Bayesian Weibull accelerated failure time model. Conclusions: Compared to high- and middle-income countries, the overall survival rate was lower. Notable variables influencing the length of survival following a breast cancer diagnosis were weight loss, invasive medullar histology, comorbid disease, a large tumour size, an increase in metastases, an increase in the International Federation of Gynaecologists and Obstetricians stage, an increase in grade, lymphatic vascular space invasion, positive regional nodes, and late stages of cancer. The authors advise that it is preferable to increase the number of early screening programmes and treatment centres for breast cancer and to work with the public media to raise knowledge of the disease's prevention, screening, and treatment choices. [ABSTRACT FROM AUTHOR]

Background: Radiotherapy improves survival for many cancer patients. However, some patients still refuse radiotherapy despite the recommendations of their physicians. We aimed to investigate the impact of refusing recommended radiotherapy on overall survival in patients with gynecological cancers (GC) and attempted to describe what characteristics are associated with the refusal of radiotherapy. Methods: Data were extracted from the Surveillance, Epidemiology and End Result (SEER) database for patients who were diagnosed with GC and recommended for radiotherapy between 1988 and 2016. Kaplan–Meier and multivariate Cox regression analyses were utilized to analyze the impact of refusal of radiotherapy on overall survival. Univariate and multivariate logistic regression analyses were used to identify characteristics associated with refusal of radiotherapy. Results: In total, 1,226 of 208,093 patients (0.6%) refused radiotherapy. Multivariate Cox regression analysis showed that refusal of radiotherapy was associated with poorer overall survival in GC patients with stage I/II [hazard ratio (HR) = 1.64; 95% confidence interval (CI), 1.50–1.79], but may not affect overall survival in patients with stage III/IV (HR = 1.03; 95%CI, 0.84–1.25). Multivariate logistic regression analysis demonstrated that factors such as older age (40–65 years, > 65 years), unmarried status (divorced, single, widowed), higher foreign-born rate (1.87-2.82%, 1.51–2.19), refusal of surgery (recommended but not performed), and higher grade (poorly differentiated, undifferentiated/anaplastic) may increase the likelihood of refusing radiotherapy (all P < 0.05). Factors that may reduce the likelihood of refusing radiotherapy include higher income (> 42,810$), lower grade (well-differentiated), primary site of ovarian cancer, and no/unknown chemotherapy (all P < 0.05). Conclusion: Refusal of radiotherapy is related to worse overall survival in GC patients with stage I/II, and many characteristics may affect a patient's choice of refusal of radiotherapy. [ABSTRACT FROM AUTHOR]