scholarly journals PCN277 Analysis of Treatment Sequences in HER2-Positive EARLY Breast Cancer Patients: A Retrospective Study from the French National Hospital Database Using a Machine Learning Algorithm, the TAK

2020 ◽  
Vol 23 ◽  
pp. S471-S472
Author(s):  
M. Laurent ◽  
M. Prodel ◽  
A. Vainchtock ◽  
M. Gilberg ◽  
R. Ghorbal ◽  
...  
2021 ◽  
Vol 12 (4) ◽  
pp. 117-137
Author(s):  
Mazen Mobtasem El-Lamey ◽  
Mohab Mohammed Eid ◽  
Muhammad Gamal ◽  
Nour-Elhoda Mohamed Bishady ◽  
Ali Wagdy Mohamed

There are many cancer patients, especially breast cancer patients as it is the most common type of cancer. Due to the huge number of breast cancer patients, many breast cancer-focused hospitals aren't able to process the huge number of patients and might expose some women to late stages of cancer. Thus, the automation of the process can help these hospitals in speeding up the process of cancer detection. In this paper, the authors test several machine learning models such as k-nearest neighbours (KNN), support vector machine (SVM), and artificial neural network (ANN). They then compare their accuracies and losses with themselves and other models that have been developed by other researchers to see whether their approach is efficient or not and to decide what machine learning algorithm is best to use.


2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Gloria Tuwei ◽  
Amsalu Degu

Introduction. HER2-positive breast cancer is associated with poor outcomes and higher mortality rates than other breast cancer subtypes. The advent of trastuzumab has significantly changed the natural history of HER2-positive breast cancer. However, it is not an affordable treatment option in sub-Saharan African countries. Because of the expense, most patients in our setting do not receive trastuzumab for the optimal control of their disease. Additionally, there is a lack of comprehensive data about the survival outcomes of HER2-positive breast cancer patients in our setting. The present study was aimed at determining the survival outcomes among HER2-positive breast cancer patients at the Oncology Department of Kenyatta National Hospital. Methods. A hospital-based retrospective cohort design was used to evaluate the survival outcomes among patients with HER2-positive breast cancer treated from 1st January 2015 to 31st December 2019 at Kenyatta National Hospital. A total of 50 eligible HER2-positive breast cancer patients were included in the study. In the predesigned data abstraction tool, data were collected by reviewing the medical records of the patients. The data were entered and analyzed using the Statistical Package for the Social Sciences version 27 software. The mean survival time was estimated using Kaplan-Meier survival analysis. Results. The mean age was 45.44 ± 12.218  years, with a majority (80%) of the patients being below 60 years. Most patients (64%) had advanced-stage disease. The median follow-up time for patients with curative stages of breast cancer was 41 months, while the median follow-up time for those with the advanced incurable disease was 8.5 months. The 4-year survival rate was 62.5% for those curable-stage HER2-positive breast cancer compared to 5.6% for those with metastatic disease at presentation. Conclusion. The 4-year survival rate for both early-stage and advanced-stage HER2-positive breast cancer in our setting is suboptimal when compared to existing outcome data from health care systems where trastuzumab is more widely available.


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