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Journal of Cancer & Metastasis Research

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Risk factors effect on survival of breast cancer females after recurrence

Joint Event on 2nd World Congress on BREAST CANCER & CANCER SCIENCE AND THERAPY

September 16-17, 2019 | Edinburgh, Scotland

Madiha Liaqat

University of the Punjab, Pakistan

Posters & Accepted Abstracts: J Can Res Metastasis

Abstract :

Statement of the Problem: Women having HER2 positive have a high low survival rate. With all the risk factors including family history, obesity, late or no pregnancy and age, biomarkers such as ER, PR and Her2.neu consider to make prediction of women’s survival. Usually recurrence occurs, previous researches have shown that after recurrence chances of survival decline. But till now no research has shown overall solid results of all the risk factors on survival by including biomarkers. The purpose of this study is to make solid conclusion after applying statistical methods on data collected from the last five years’ cases of breast cancer, parameters are all the risk factors, biomarkers and targeted therapy. The main motivation behind this work is application of modeling to breast cancer data, in order to investigate the abilities of potential biomarkers of breast cancer with other parameters to predict patients’ survival.

Methodology & Theoretical Orientation: It is a retrospective study, in this study patients’ followed for 7 years. Sample size of study is 580. Graphs use to show relationship between different variables. Survival analysis tools and techniques use to depict patients’ survival based on different variables.

Conclusion & Significance: Many variables have significant effect on survival. But many others like ER has not significant effect. Middle ages women have higher probability of death, even after treatment. Recurrence also have significant effect.

Biography :

Madiha Liaqat is a biostatistician doing PhD in Statistics from university of the Punjab, Lahore, Pakistan. She is working on breast cancer, and are developing new statistical tools and techniques which can be used to precisely predict patient's recurrence and survival.

E-mail: mdiyaliaqat@gmail.com

Google Scholar citation report
Citations : 857

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