E-Thesis 192 views
Development of a Large Welsh Breast Cancer Prognostic Research Database and Analysis of Influential Demographic, Pathological and Socioeconomic Factors on Survival / LEEN INTABLI
Swansea University Author: LEEN INTABLI
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DOI (Published version): 10.23889/SUthesis.59497
Abstract
Breast cancer is the most common neoplasm in women in the UK with around 55,000 new diagnosed cases every year. Due to major advancements made in research and therapy in srecent years, breast cancer is now one of the best understood human cancers. It is understood that breast cancer is a group of bi...
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Swansea
2021
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Institution: | Swansea University |
Degree level: | Doctoral |
Degree name: | Ph.D |
Supervisor: | Lewis, Paul |
URI: | https://cronfa.swan.ac.uk/Record/cronfa59497 |
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2022-03-07T12:24:13.1686065 v2 59497 2022-03-04 Development of a Large Welsh Breast Cancer Prognostic Research Database and Analysis of Influential Demographic, Pathological and Socioeconomic Factors on Survival 13d7d1fc2af45ddc9e285f0c988bdb24 LEEN INTABLI LEEN INTABLI true false 2022-03-04 Breast cancer is the most common neoplasm in women in the UK with around 55,000 new diagnosed cases every year. Due to major advancements made in research and therapy in srecent years, breast cancer is now one of the best understood human cancers. It is understood that breast cancer is a group of biologically different diseases, each influenced by a number of pathological and demographic factors. Age at diagnosis has been heavily studied and linked to different survival patterns, as tumours diagnosed in younger and older groups are often the outcome of different causes and have different responses to treatment regimens. In the age of data-backed decision making process, recent years have seen a growth in interest in analysis-based research and decision support tools, in medicine and other disciplines. Currently in Wales, there is a lack of a large, comprehensive database of accurately recorded demographic, clinical and socioeconomic information on breast cancer patients that can be utilised in answering a variety of clinical and socioeconomic research questions within the population. The aim of our work was to create a local interactive online analysis and predictive tool that allows users to define prognostic criteria and return survival patterns through multivariate analysis of a database of patients diagnosed in South West Wales. The Welsh Breast Cancer Survival Database of patients diagnosed in Wales between 1996 and 2011 was constructed containing multiple variables including: age at diagnosis, tumour pathology and survival outcomes. For multivariate analysis, principal component analysis (PCA) and partition around Medoids (PAM) clustering methods were implemented using R statistical programming. Survival analysis visualisation and statistical methods included Kaplan-Meier curves and Cox proportional hazards model. CaFro, a web-based analytical tool that allows for variable selection, survival and cluster analyses of various diagnostic and prognostic factors was developed using the shiny package on R studio. The tool was also utilised to compare different age groups within South-West Wales, and differences in survival rates of up to 7% were detected. Another aim of this project was to compare survival patterns based on socioeconomic differences of patients in the area, based on the Welsh Index of Multiple Deprivations (WIMD) score of their address postcodes at the time of diagnosis. Health, income, education and employment deprivations were all shown to influence survival time. E-Thesis Swansea 5 2 2021 2021-02-05 10.23889/SUthesis.59497 Due to Embargo and/or Third Party Copyright restrictions, this thesis is not available via this service. COLLEGE NANME COLLEGE CODE Swansea University Lewis, Paul Doctoral Ph.D 2022-03-07T12:24:13.1686065 2022-03-04T16:46:44.5739276 Faculty of Humanities and Social Sciences School of Management - Business Management LEEN INTABLI 1 |
title |
Development of a Large Welsh Breast Cancer Prognostic Research Database and Analysis of Influential Demographic, Pathological and Socioeconomic Factors on Survival |
spellingShingle |
Development of a Large Welsh Breast Cancer Prognostic Research Database and Analysis of Influential Demographic, Pathological and Socioeconomic Factors on Survival LEEN INTABLI |
title_short |
Development of a Large Welsh Breast Cancer Prognostic Research Database and Analysis of Influential Demographic, Pathological and Socioeconomic Factors on Survival |
title_full |
Development of a Large Welsh Breast Cancer Prognostic Research Database and Analysis of Influential Demographic, Pathological and Socioeconomic Factors on Survival |
title_fullStr |
Development of a Large Welsh Breast Cancer Prognostic Research Database and Analysis of Influential Demographic, Pathological and Socioeconomic Factors on Survival |
title_full_unstemmed |
Development of a Large Welsh Breast Cancer Prognostic Research Database and Analysis of Influential Demographic, Pathological and Socioeconomic Factors on Survival |
title_sort |
Development of a Large Welsh Breast Cancer Prognostic Research Database and Analysis of Influential Demographic, Pathological and Socioeconomic Factors on Survival |
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13d7d1fc2af45ddc9e285f0c988bdb24 |
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13d7d1fc2af45ddc9e285f0c988bdb24_***_LEEN INTABLI |
author |
LEEN INTABLI |
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LEEN INTABLI |
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E-Thesis |
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2021 |
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Swansea University |
doi_str_mv |
10.23889/SUthesis.59497 |
college_str |
Faculty of Humanities and Social Sciences |
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facultyofhumanitiesandsocialsciences |
hierarchy_top_title |
Faculty of Humanities and Social Sciences |
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facultyofhumanitiesandsocialsciences |
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Faculty of Humanities and Social Sciences |
department_str |
School of Management - Business Management{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Business Management |
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0 |
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description |
Breast cancer is the most common neoplasm in women in the UK with around 55,000 new diagnosed cases every year. Due to major advancements made in research and therapy in srecent years, breast cancer is now one of the best understood human cancers. It is understood that breast cancer is a group of biologically different diseases, each influenced by a number of pathological and demographic factors. Age at diagnosis has been heavily studied and linked to different survival patterns, as tumours diagnosed in younger and older groups are often the outcome of different causes and have different responses to treatment regimens. In the age of data-backed decision making process, recent years have seen a growth in interest in analysis-based research and decision support tools, in medicine and other disciplines. Currently in Wales, there is a lack of a large, comprehensive database of accurately recorded demographic, clinical and socioeconomic information on breast cancer patients that can be utilised in answering a variety of clinical and socioeconomic research questions within the population. The aim of our work was to create a local interactive online analysis and predictive tool that allows users to define prognostic criteria and return survival patterns through multivariate analysis of a database of patients diagnosed in South West Wales. The Welsh Breast Cancer Survival Database of patients diagnosed in Wales between 1996 and 2011 was constructed containing multiple variables including: age at diagnosis, tumour pathology and survival outcomes. For multivariate analysis, principal component analysis (PCA) and partition around Medoids (PAM) clustering methods were implemented using R statistical programming. Survival analysis visualisation and statistical methods included Kaplan-Meier curves and Cox proportional hazards model. CaFro, a web-based analytical tool that allows for variable selection, survival and cluster analyses of various diagnostic and prognostic factors was developed using the shiny package on R studio. The tool was also utilised to compare different age groups within South-West Wales, and differences in survival rates of up to 7% were detected. Another aim of this project was to compare survival patterns based on socioeconomic differences of patients in the area, based on the Welsh Index of Multiple Deprivations (WIMD) score of their address postcodes at the time of diagnosis. Health, income, education and employment deprivations were all shown to influence survival time. |
published_date |
2021-02-05T04:16:51Z |
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1763754127340339200 |
score |
11.016235 |