Survival and Predictors of Mortality among Breast Cancer Patients in Northwest Ethiopia: A Retrospective Cohort Study

Automated Segmentation of Breast Cancer Focal Lesions on Ultrasound Images

Ultrasound (US) remains the main modality for the differential diagnosis of changes revealed by mammography. However, the US images themselves are subject to various types of noise and artifacts from reflections, which can worsen the quality of their analysis. Deep learning methods have a number of disadvantages, including the often insufficient substantiation of the model, and the complexity of collecting a representative training database. Therefore, it is necessary to develop effective algorithms for the segmentation, classification, and analysis of US images. The aim of the work is to develop a method for the automated detection of pathological lesions in breast US images and their segmentation. A method is proposed that includes two stages of video image processing: (1) searching for a region of interest using a random forest classifier, which classifies normal tissues, (2) selecting the contour of the lesion based on the difference in brightness of image pixels. The test set included 52 ultrasound videos which contained histologically proven suspicious lesions. The average frequency of lesion detection per frame was 91.89%, and the average accuracy of contour selection according to the IoU metric was 0.871. The proposed method can be used to segment a suspicious lesion.

Breast cancer survival in Ethiopia: a systematic review and meta-analysis of rates and predictors

BACKGROUND

Evidence on breast cancer survival and factors affecting survival is crucial for evaluating treatment effectiveness and formulating breast cancer control strategies. Although original research has been conducted on the survival rate of breast cancer patients and their determinants in Ethiopia, there is a shortage of comprehensive scientific evidence. The present study systematically reviewed literature on the survival rate of breast cancer patients and the predictors of survival in Ethiopia.

METHODS

A comprehensive search was conducted in the PubMed, HINARI, Global Index Medicus, and Google Scholar databases up to August 26, 2024. Without any design restrictions, studies on breast cancer patients that measured survival at different time points in Ethiopia were included. The results are summarized in a table, the survival rates are pooled, and risk factors are narratively synthesized. To assess the risk of bias, the Newcastle Ottawa Scale was utilized. Heterogeneity between studies was assessed using the I2 statistic. Potential publication bias was assessed using a funnel plot. To examine robustness, a leave-one-out sensitivity analysis was performed.

RESULTS

The pooled survival rates in the first, second, third, fifth, and sixth years were 90%, 70%, 68%, 46%, and 44%, respectively. Advanced age, lower socioeconomic status, late clinical stage, delayed diagnosis, higher histological grade, metastasis, lymph node involvement, presence of comorbidity, tumor size, and estrogen receptor positive were factors that increased the risk of mortality in the included studies.

CONCLUSION

Survival rate of breast cancer patients in later time including fifth and sixth years was comparably lower than other countries. It is crucial to raise awareness about breast cancer screening, early diagnosis, and therapy initiation to increase the survival rate of breast cancer patients in Ethiopia. In addition, it is important to emphasize the risky population groups, which includes those with lower socioeconomic status and advanced clinical parameters.

Predictors of survival rates among breast cancer patients in Ethiopia: a systematic review and meta-analysis 2024

INTRODUCTION

Breast cancer remains the most common cancer and a leading cause of cancer-related deaths among women worldwide. In Ethiopia, the survival rate of breast cancer patients is influenced by various socio-demographic, clinical, and health system factors. This systematic review and meta-analysis aimed to identify and synthesize the predictors of survival rates among breast cancer patients in Ethiopia.

METHODS

We conducted a systematic review of observational cohort studies. The literature search was performed between August 1 and 30, 2024, using PubMed, Hinari, EMBASE, Google, Google Scholar, and Web of Science. The Newcastle Ottawa 2016 Critical Appraisal Checklist assessed methodological quality. Publication bias was evaluated using a funnel plot and Egger's test, and heterogeneity was examined with the I-squared test. Data were extracted with Microsoft Excel and analyzed using Stata 11.

RESULTS

A total of 15 articles with 6,375 study participants from six regions were included. We found that significant predictors of decreased survival rate among breast cancer patients were age (aHR 1.05, 95% CI 1.02-1.08), illiteracy (aHR 7.34, 95% CI 4.38-10.3), married (aHR 1.21, 95% CI 1.03-1.40), rural residence (aHR 1.71, 95% CI 1.06-2.36), two or more lymph node involvement (aHR 3.57, 95% CI 1.02-6.13), histological grade two or more (aHR 1.44, 95% CI 1.12-2.77), overweight (aHR 0.56, 95% CI 0.24-0.87), and having comorbidity (aHR 1.86, 95% CI 1.04-2.68).

CONCLUSION

This systematic review and meta-analysis identified several key predictors of reduced survival rates among breast cancer patients in Ethiopia, including older age, illiteracy, rural residence, involvement of two or more lymph nodes, higher histological grade, marital status, and the presence of comorbidities. Interestingly, being overweight was associated with improved survival. Health stakeholders and policymakers emphasizing public health education, managing comorbidities, and expanding access to early detection and treatment, especially in rural areas, are critical.

A 14-Year Analysis of Breast Cancer Risk Factors and Its Determinants of Mortality in Rural Southwestern Nigeria

Background

Research on breast cancer risk factors and mortality is gaining recognition and attention globally; there is need to add more information on its determinants among patients admitted in hospital. Some studies on risk factors and mortality of breast cancer in Nigeria hospitals conducted in the urban and suburban areas have been documented. Therefore, an addition of a study conducted in the setting of a rural health institution is necessary. This study assessed the risk factors and determinants of mortality among patients admitted for breast cancer in rural Southwestern Nigeria.

Methods

A retrospective observational study was conducted on 260 patients who were admitted for breast cancer between January 2010 and December 2023 using a data form and a standardized information form. The data were analyzed using SPSS version 22.0. The risk factors and the determinants of mortality of patients with breast cancer were identified using multivariate regression model.

Results

The breast cancer risk factors were old age, family history, tobacco smoking, combined oral contraceptives, and hormonal therapy use. The case fatality rate was 38.1%, and its determinants of mortality were patients who were older (adjusted odds ratio [AOR], 1.956; 95% confidence interval [CI]:1.341-4.333), obese (AOR, 2.635; 95% CI: 1.485-6.778), stage IV (AOR, 1.895; 95% CI: 1.146-8.9742), mastectomy (AOR, 2.512; 95% CI: 1.003-6.569), discontinued adjuvant chemotherapy (AOR, 1.785; 95% CI: 1.092-4.6311), and yet to commence adjuvant chemotherapy (AOR, 2.568; 95% CI: 1.367-5.002).

Conclusion

The study revealed that patients with breast cancer were associated with high mortality. Sustained health education to promote early diagnosis, managed co-morbidities, and access to treatment may contribute to reduction in breast cancer mortality in rural Nigeria.

Modelling of the time to death of breast cancer patients at Hiwot Fana Specialized University Hospital

Breast cancer is the most common cause of cancer death and is a frequently diagnosed cancer among women worldwide. It is becoming a challenging health condition in Ethiopia with a high rate of morbidity and mortality. The main aim of this study was to model the time to death in breast cancer patients at Hiwot Fana Specialized University Hospital. A retrospective cohort study was carried out from April 1st, 2020, to April 1st, 2023, and 296 women were included in the study. We used nonparametric methods and Bayesian accelerated failure time models (with Laplace approximation) to identify risk factors and choose a model fitting breast cancer patient data. Model comparison was performed using the marginal likelihood, deviance information criterion and Watanabe Akaike information criterion. From the total of 296 patients in the study, 56 (18.9%) died. The estimated median survival time was 33 months. The log-rank test showed that age group, stage, alcohol consumption, smoking habit, and comorbidity were potential risk factors associated with the time to death in breast cancer patients at the 5% level of significance. The Bayesian Weibull accelerated failure time model was found to be the best fitted model for predicting the survival time of patients with minimum DIC (520.39) and WAIC (521.59) values. The final Bayesian Weibull AFT model with the integrated nested Laplace approximation estimation technique revealed that age group, stage, alcohol consumption, smoking habit, and comorbidity were significantly associated with the time to death in breast cancer patients. Individuals older than 65 years, with stage IV disease, drinking alcohol, smoking cigarettes and having comorbidities had shortened survival times in patients with breast cancer. Hence, Hiwot Fana Specialized University Hospital and related bodies should work on awareness creation to reduce smoking habits and alcohol use as well as give due attention to elderly and stage IV breast cancer patients during intervention.

Proportion of early-stage breast cancer at diagnosis in Ethiopia: a systematic review and meta-analysis

BACKGROUND

Breast cancer is the most common cancer-affecting women globally, with disproportionally high mortality rates in lower-income countries, including Ethiopia. The stage at diagnosis is a well-defined predictive system that determines the likelihood of breast cancer mortality. Early-stage breast cancer at diagnosis is associated with better treatment outcomes as compared with late stage. Although there are numerous primary studies on women with breast cancer with different proportions of early-stage breast cancer, there is currently no summary data on what proportion of breast cancer was diagnosed at early-stage in Ethiopia. This study focused on a pooled proportion of early-stage breast cancer at diagnosis in Ethiopia.

METHODS

By using key terms, Medline through Pub-Med, Google Scholar, Science Direct, HINARI and Medley were searched about breast cancer in Ethiopia, and a total of 288 articles were retrieved. After screening the articles and quality of each article was assessed using Newcastle-Ottawa Scale. Finally, 41 articles were used for the final pooled proportion. A random effects model was used to estimate the pooled prevalence and heterogeneity of included studies that were then assessed by using prediction interval.

RESULTS

Pooled proportion of early-stage breast cancer at diagnosis in Ethiopian hospitals was found to be 36% with a 95% confidence interval ranging from 31 to 41% and a 95% prediction interval ranging from 28 to 45%.

CONCLUSION

Most breast cancer patients (64%) in Ethiopia are diagnosed at a late-stage. This contributes to the high mortality rates of breast cancer among women in Ethiopia. Therefore, in line with recommendations by the World Health Organization, we recommend that there should be an emphasis in Ethiopia to focus on early detection of breast cancer.

Late-stage diagnosis: The driving force behind high breast cancer mortality in Ethiopia: A systematic review and meta-analysis

INTRODUCTION

Breast cancer continues to be the most common malignancy and the leading cause of cancer-related deaths in Ethiopia. The poor prognosis and high mortality rate of breast cancer patients in the country are largely caused by late-stage diagnosis. Hence, understanding the epidemiology of late-stage diagnosis is essential to address this important problem. However, previous reports in Ethiopia indicated inconsistent findings. Therefore, this literature review was conducted to generate dependable evidence by summarizing the prevalence and determinants of late-stage diagnosis among breast cancer patients in Ethiopia.

METHODS

Pertinent articles were retrieved by systematically searching on major electronic databases and gray literature. Data were extracted into an Excel spreadsheet and analyzed using the STATA 17 statistical software. The pooled estimates were summarized using the random effect meta-analysis model. Heterogeneity and small study effect were evaluated using the I2 statistics and Egger's regression test in conjunction with the funnel plot, respectively. Meta-regression, sub-group analysis, and sensitivity analysis were also employed. Protocol registration number: CRD42024496237.

RESULTS

The pooled prevalence of late-stage diagnosis after combining reports of 24 studies with 8,677 participants was 65.85 (95% CI: 58.38, 73.32). Residence (adjusted OR: 1.92; 95% CI: 1.45, 2.53), patient delay at their first presentation (adjusted OR: 2.65; 95% CI: 1.56, 4.49), traditional medicine use (adjusted OR: 2.54; 95% CI: 1.89, 3.41), and breast self-examination practice (adjusted OR: 0.28; 95% CI: 0.09, 0.88) were significant determinants of late-stage diagnosis.

CONCLUSION

Two-thirds of breast cancer patients in Ethiopia were diagnosed at an advanced stage. Residence, delay in the first presentation, traditional medicine use, and breast self-examination practice were significantly associated with late-stage diagnosis. Public education about breast cancer and its early detection techniques is crucial to reduce mortality and improve the survival of patients. Besides, improving access to cancer screening services is useful to tackle the disease at its curable stages.

Survival Patterns Among Patients With Breast Cancer in Sub-Saharan Africa: A Systematic Review and Meta-Analysis

Importance

Breast cancer is the most prevalent cancer globally with tremendous disparities both within specific regions and across different contexts. The survival pattern of patients with breast cancer remains poorly understood in sub-Saharan African (SSA) countries.

Objective

To investigate the survival patterns of patients with breast cancer in SSA countries and compare the variation across countries and over time.

Data Sources

Embase, PubMed, Web of Science, Scopus, and ProQuest were searched from inception to December 31, 2022, with a manual search of the references.

Study Selection

Cohort studies of human participants that reported 1-, 2-, 3-, 4-, 5-, and 10-year survival from diagnosis among men, women, or both with breast cancer in SSA were included.

Data Extraction and Synthesis

Independent extraction of study characteristics by multiple observers was performed using open-source software, then exported to a standard spreadsheet. A random-effects model using the generalized linear mixed-effects model was used to pool data. The Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guideline for reporting was followed.

Main Outcome and Measures

Survival time from diagnosis.

Results

Forty-nine studies were included in the review with a sample size ranging from 21 to 2311 (total, 14 459; 196 [1.35%] men, 13 556 [93.75%] women, and 707 [4.90%] unspecified; mean age range, 38 to 71 years), of which 40 were summarized using meta-analysis. The pooled 1-year survival rate of patients with breast cancer in SSA was 0.79 (95% CI, 0.67-0.88); 2-year survival rate, 0.70 (95% CI, 0.57-0.80); 3-year survival rate, 0.56 (95% CI, 0.45-0.67); 4-year survival rate, 0.54 (95% CI, 0.43-0.65); and 5-year survival rate, 0.40 (95% CI, 0.32-0.49). The subgroup analysis showed that the 5-year survival rate ranged from 0.26 (95% CI, 0.06-0.65) for studies conducted earlier than 2010 to 0.47 (95% CI, 0.32-0.64) for studies conducted later than 2020. Additionally, the 5-year survival rate was lower in countries with a low human development index (HDI) (0.36 [95% CI, 0.25-0.49) compared with a middle HDI (0.46 [95% CI, 0.33-0.60]) and a high HDI (0.54 [95% CI, 0.04-0.97]).

Conclusions and Relevance

In this systematic review and meta-analysis, the survival rates for patients with breast cancer in SSA were higher in countries with a high HDI compared with a low HDI. Enhancing patient survival necessitates a comprehensive approach that involves collaboration from all relevant stakeholders.

Assessing the survival time of women with breast cancer in Northwestern Ethiopia: using the Bayesian approach

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.

Mortality rate and predictors among patients with breast cancer at a referral hospital in northwest Ethiopia: A retrospective follow-up study

BACKGROUND

Breast cancer is one of the common global health concerns that affects2.1 million women each year and causes the highest number of cancer-related morbidity and mortality among women. The objective of this study was to determine the mortality rate and its predictors among breast cancer patients at the referral hospitals, in northwest Ethiopia.

METHODS

A retrospective follow-up study was conducted on breast cancer patients registered between February 01, 2015 and February 28, 2018. They were selected by simple random sampling using computer-generated method and followed until February 29, 2020, in Amhara region referral hospital. A pre-tested data extraction checklist was used to collect data from the registration book and patient medical records. The collected data were entered into Epi-Data version 3.1 and exported to STATA version 14 for analysis. The mortality rate by person-year observation was computed. The Kaplan-Meier survival curve with the log-rank test was used to estimate the survival probabilities of the patients. Bivariate and multivariate Cox regression model was used to identify predictors of mortality.

RESULTS

The overall mortality rate of breast cancer was 16.9 per 100 person-years observation. The median survival time was 38.3 (IQR: 26.23, 49.4) months. Independent predictors of breast cancer mortality was; Clinical stage IV and stage III (aHR:10.44,95% CI: 8.02,11.93 and aHR: 9.43, 95% CI: 6.29,11.03respectively), number of positive lymph node in the category of 10 and more and number of positive lymph node within the category of 4-9 (aHR:12.58, 95%CI: 5.2, 30.46 and aHR: 4.78, 95% CI: 2.19, 10.43respectively), co-morbidities (aHR:1.5, 95%CI: 1.01,2.21), Postmenopausal (aHR:2.03,95% CI: 1.37, 3), histologic grade III (aHR:2.12, 95% CI: 1.26,3.55) and not received hormonal therapy (aHR: 2.19, 95%CI: 1.52,3.15) were independent predictors of mortality.

CONCLUSION

The overall mortality rate was 16.9 per 100 person-years. The finding was higher compared to high-income countries. Advanced clinical stage, co-morbidities, menopausal status, and hormonal therapy are the significant predictors of mortality. Early detection and treatment of breast cancer is needed to reduce the mortality rate.

Survival and predictors of breast cancer mortality in South Ethiopia: A retrospective cohort study

BACKGROUND

Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer death in over 100 countries. In March 2021, the World Health Organization called on the global community to decrease mortality by 2.5% per year. Despite the high burden of the disease, the survival status and the predictors for mortality are not yet fully determined in many countries in Sub-Saharan Africa, including Ethiopia. Here, we report the survival status and predictors of mortality among breast cancer patients in South Ethiopia as crucial baseline data to be used for the design and monitoring of interventions to improve early detection, diagnosis, and treatment capacity.

METHODS

A hospital-based retrospective cohort study was conducted among 302 female breast cancer patients diagnosed from 2013 to 2018 by reviewing their medical records and telephone interviews. The median survival time was estimated using the Kaplan-Meier survival analysis method. A log-rank test was used to compare the observed differences in survival time among different groups. The Cox proportional hazards regression model was used to identify predictors of mortality. Results are presented using the crude and adjusted as hazard ratios along with their corresponding 95% confidence intervals. Sensitivity analysis was performed with the assumption that loss to follow-up patients might die 3 months after the last hospital visit.

RESULTS

The study participants were followed for a total of 4,685.62 person-months. The median survival time was 50.81 months, which declined to 30.57 months in the worst-case analysis. About 83.4% of patients had advanced-stage disease at presentation. The overall survival probability of patients at two and three years was 73.2% and 63.0% respectively. Independent predictors of mortality were: patients residing in rural areas (adjusted hazard ratio = 2.71, 95% CI: 1.44, 5.09), travel time to a health facility ≥7 hours (adjusted hazard ratio = 3.42, 95% CI: 1.05, 11.10), those who presented within 7-23 months after the onset of symptoms (adjusted hazard ratio = 2.63, 95% CI: 1.22, 5.64), those who presented more than 23 months after the onset of symptoms (adjusted hazard ratio = 2.37, 95% CI: 1.00, 5.59), advanced stage at presentation (adjusted hazard ratio = 3.01, 95% CI: 1.05, 8.59), and patients who never received chemotherapy (adjusted hazard ratio = 6.69, 95% CI: 2.20, 20.30).

CONCLUSION

Beyond three years after diagnosis, patients from southern Ethiopia had a survival rate of less than 60% despite treatment at a tertiary health facility. It is imperative to improve the early detection, diagnosis, and treatment capacities for breast cancer patients to prevent premature death in these women.

Treatment Outcomes and Its Associated Factors Among Adult Patients with Selected Solid Malignancies at Kenyatta National Hospital: A Hospital-Based Prospective Cohort Study

Introduction

The treatment outcome of cancer is poor in the African setting due to inadequate treatment and diagnostic facilities. However, there is a paucity of data on solid cancers in Kenya. Hence, this study aimed to investigate the treatment outcomes and its determinant factors among adult patients diagnosed with selected solid malignancies at Kenyatta National Hospital (KNH).

Materials and Methods

A prospective cohort study was employed at the Oncology Department of KNH from 1^st July 2020 to 31^st December 2021. All new patients with a confirmed diagnosis of lymphoma, prostate cancer and breast cancer were studied. A consecutive sample of 99 breast cancer, 50 lymphomas, and 82 prostate cancer patients was included in the study. Semi-structured questionnaires consisting of socio-demographics, clinical characteristics, and quality of life were employed to collect the data. All enrolled patients were followed prospectively for 12 months. Treatment outcomes were reported as mortality, cancer-specific survival and health-related quality of life. The data were entered and analyzed using the SPSS 20.0 statistical software. Survival outcomes and its predictors were evaluated using the Kaplan–Meier analysis and Cox regression analyses, respectively.

Results

The study showed that the mortality rate among breast and prostate cancer patients was 3% and 4.9%, respectively. In contrast, the mortality rate was 10% among lymphoma patients. Most of the patients had partial remission and a good overall global health-related quality of life. Older age above 60 years, co-morbidity, distant metastasis and advanced stages of disease were significant predictors of mortality.

Conclusion

Although the mortality was not high at 12 months, only a few patients had complete remission. For many patients, the disease was progressing, despite 12-month mortality was not high. Therefore, longer follow-up will be required to report cancer mortality accurately. In addition, most of the patients had a good overall global health-related quality of life.