Browsing by Subject "Breast Cancer"

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    Open Access
    Breast cancer patients' experience with receiving pathogenic germline genetic results: single center experience in Oman
    (2025) Balushi, Amira; Wessels, Tina; Van Wyk, Chantel
    Introduction: In Oman, little is known about breast cancer patients' experiences of receiving pathogenic germline genetic results. Receiving a positive germline genetic result can have a wide range of emotional and practical effects on breast cancer patients. This study explored the lived experiences of Omani women navigating a positive pathogenic germline genetic test result for hereditary breast cancer. Driven by the increasing prevalence of genetic testing and limited research on its psychosocial impact within this specific cultural context, the study aimed to understand how Omani women experience and make sense of a positive genetic test result. Methods: This is a qualitative study based on an interpretive phenomenological approach. Semi structured interviews were conducted with nine Omani women who had received a positive germline genetic result for breast cancer predisposition gene. Thematic analysis was employed to identify key themes emerging from these women's experiences. Result and Discussion: Four themes emerged from the thematic analysis in this study. These included “Cancer journey”, “Genetic testing motivation and expectations”, “Receiving the positive result”, and “Adapting to hereditary breast cancer diagnosis”. The findings revealed the complex and multifaceted experience of breast cancer women with receiving positive germline genetic result. The perceived causation of their breast cancer, such as stress and pre-existing cultural beliefs, as well as their lived experiences during the cancer diagnosis and treatment, all influenced these women's response and understanding of their genetic test result. Emotional responses varied, ranging from anxiety and fear to relief and empowerment, highlighting the individual nature of this experience. Coping strategies were active coping such as leaving the matter to God's hand, increased surveillance and risk-reducing surgeries, engagement coping with family and friends for support, and meaning-focused coping, often grounded in religious and spiritual beliefs. Family dynamics and cultural norms played a crucial role in disclosure practices, with concerns about protecting family members from psychological stress having influenced their decisions about information sharing. x Conclusion: This research contributes valuable insights into the lived experiences of Omani women with hereditary breast cancer, highlighting the need for culturally sensitive and individualised support throughout the testing and decision-making process. The findings have implications for healthcare professionals, genetic counsellors, and policymakers, emphasizing the importance of providing comprehensive support that addresses the emotional, social, and cultural dimensions of hereditary cancer risk.
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    Open Access
    Evaluating deep learning for enhanced breast cancer diagnosis: a comparative analysis of CNN architectures
    (2025) Frankle, Solyle; Sinkala, Musalula
    Artificial Intelligence (AI), particularly its machine learning (ML) subfield, has revolutionised various sectors, including healthcare. In breast cancer care, AI's ability to analyse vast datasets and extract complex patterns from medical images has the potential to transform diagnostics and treatment strategies. Breast cancer remains one of the most prevalent cancers affecting women globally, with early and accurate diagnosis being crucial for effective treatment. AI, through its advanced image analysis capabilities, significantly improves the accuracy and efficiency of breast cancer diagnosis, specifically in distinguishing between cancer subtypes. Here, we aim to explore the application of deep learning, particularly convolutional neural networks (CNNs), in breast cancer subtype classification using histology images. A custom CNN model, alongside well-established models like ResNet50 and EfficientNetB0, was developed and evaluated for its accuracy in predicting benign and malignant breast cancer subtypes. The results demonstrated that while the custom CNN achieved an accuracy of 65% for malignant and 67% for benign subtypes with ROC-AUC scores of 0.86 and 0.90, respectively, ResNet50 significantly outperformed both the custom model and EfficientNetB0. ResNet50 attained an accuracy of 77% in classifying malignant subtypes and 77% for benign subtypes, accompanied by ROC-AUC scores of 0.92 and 0.96, respectively. Additionally, ResNet50 exhibited higher precision (0.68 for malignant, 0.67 for benign), recall (0.65 for malignant, 0.67 for benign), and F1 scores (0.65 for malignant, 0.67 for benign) across most subtypes, underscoring its robust performance and reliability in clinical settings. In conclusion, AI, specifically through advanced CNN architectures, can greatly enhance breast cancer diagnosis by providing more accurate subtype classifications. Future work should focus on integrating these models into clinical workflows, enabling faster and more personalised treatment planning. Moreover, continued refinement of these models, including addressing the complexities of tumour heterogeneity and incorporating multimodal data, will be crucial for their widespread adoption in oncology.
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    Extended cost effectiveness analysis of interventions for early detection, screening and breast cancer control: case studies of South Africa and Uganda
    (2026) Abewe, Christabell; Sinanovic, Edina; Moodley, Jennifer
    The global statistics for the year 2022 indicate that female breast cancer is the second leading cause of global cancer incidence with an estimated 2.3 million cases and among women, it is the most frequently diagnosed cancer and the leading cause of cancer death among women in 157 countries [1]. In the African region, breast cancer incidence and mortality are on an upward trajectory and predicted to double in Sub-Saharan African by 2050. Given the growing burden of breast cancer in low- and middle-income countries (LMICs), these countries now face the challenge of effectively detecting and treating a disease that was previously considered too uncommon to merit the allocation of finite health care resources. As such, in LMICs there is a need to scale up early detection and screening strategies that can improve on the too common pattern of disease presentation at a stage when prognosis is very poor. We constructed a dynamic state transition model to estimate the cost effectiveness of three breast cancer down-staging interventions in Uganda and South Africa. Our model is premised on a comprehensive mathematical framework that estimates the stage shifts in early versus late stages of breast cancer diagnosis based on proportional performance rates of three early detection and screening interventions (awareness raising, clinical breast examination (CBE) and mammography) spanning 40 years. This study then used the extended cost effectiveness analysis framework to assess the possible distributional impact of utilizing universal public financing as a tool to increase access and coverage of breast cancer early detection interventions in these two countries. This dissertation found that biennial CBE and awareness raising interventions are not only crucial for down-staging breast cancer diagnosis, but they are also economically attractive and viable for options for both Uganda and South Africa. Biennial CBE coupled with treatment interventions for all stages was cost-effective for South Africa with an ICER of $2,708 per healthy life year gained. Awareness raising interventions were also found to be cost effective with an ICER of 3,201 per health life year gained. Mammography screening combined with treatment for all stages was not found to be a cost-effective intervention for South Africa with an ICER of $9,491 per healthy life year gained. For Uganda, we found awareness raising interventions to be the most cost-effective interventions for breast cancer control with a dominant ICER of $-118 per healthy life year gained. Biennial CBE for women aged 40-74 combined with treatment for all stages was also cost effective with an ICER of $416 per healthy life year gained. Biennial MMG screening combined with treatment for all stages was not cost effective with an ICER of $3,110 per healthy life year gained. Further, this thesis demonstrated that publicly financing early detection and screening interventions in LMICs for breast cancer can alleviate a considerable proportion of breast cancer burden and catastrophic health expenditures benefiting the poorest wealth quintiles. In South Africa 44% of the deaths averted are in the wealthiest two quintiles while the poorest two quintiles would account for 34% of the total deaths averted. Regarding financial protection, our analysis shows that publicly financing breast cancer control interventions could avert approximately US $7.89 million over the 40years, this translates to US $197,254 annually. The distribution of catastrophic health expenditures averted is pro-poor, with the poorest wealth quintile accounting for 76% of the averted catastrophic 2 health expenditure cases, on the other hand, the wealthiest two quintiles account for approximately 1.4% of the catastrophic health expenditure cases averted. In Uganda, our analysis shows that 55% of the deaths averted are concentrated in the wealthiest two quintiles while the poorest two quintiles would account for 26% of the total deaths averted. Regarding financial protection, our analysis shows that publicly financing breast cancer control interventions could avert approximately US $29.2 million over the 40-years, this translates to US$729,098 annually. The distribution of catastrophic health expenditures averted is pro-poor, with the lowest three wealth quintiles accounting for 63% of the catastrophic cases averted while the richest two quintiles account for 37% of the cases of catastrophic expenditures averted. The findings from this thesis are notable for breast cancer policy in LMICs as the analysis demonstrated significant down-staging associated with early detection and screening interventions for breast cancer. Implementation of these interventions will require substantial additional financial investments, but our analysis shows that the health benefits will broadly outweigh these requirements for CBE and awareness raising interventions.