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Contributions of prognostic factors to socioeconomic disparities in cancer survival: protocol for analysis of a cohort with linked data

INTRODUCTION: Socioeconomic disparities in cancer survival have been reported in many developed countries, including Australia. Although some international studies have investigated the determinants of these socioeconomic disparities, most previous Australian studies have been descriptive, as only l...

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Autores principales: Yu, Xue Qin, Goldsbury, David, Yap, Sarsha, Yap, Mei Ling, O'Connell, Dianne L
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6825410/
https://www.ncbi.nlm.nih.gov/pubmed/31427338
http://dx.doi.org/10.1136/bmjopen-2019-030248
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author Yu, Xue Qin
Goldsbury, David
Yap, Sarsha
Yap, Mei Ling
O'Connell, Dianne L
author_facet Yu, Xue Qin
Goldsbury, David
Yap, Sarsha
Yap, Mei Ling
O'Connell, Dianne L
author_sort Yu, Xue Qin
collection PubMed
description INTRODUCTION: Socioeconomic disparities in cancer survival have been reported in many developed countries, including Australia. Although some international studies have investigated the determinants of these socioeconomic disparities, most previous Australian studies have been descriptive, as only limited relevant data are generally available. Here, we describe a protocol for a study to use data from a large-scale Australian cohort linked with several other health-related databases to investigate several groups of factors associated with socioeconomic disparities in cancer survival in New South Wales (NSW), Australia, and quantify their contributions to the survival disparities. METHODS AND ANALYSIS: The Sax Institute’s 45 and Up Study participants completed a baseline questionnaire during 2006–2009. Those who were subsequently diagnosed with cancer of the colon, rectum, lung or female breast will be included. This study sample will be identified by linkage with NSW Cancer Registry data for 2006–2013, and their vital status will be determined by linking with cause of death records up to 31 December 2015. The study cohort will be divided into four groups based on each of the individual education level and an area-based socioeconomic measure. The treatment received will be obtained through linking with hospital records and Medicare and pharmaceutical claims data. Cox proportional hazards models will be fitted sequentially to estimate the percentage contributions to overall socioeconomic survival disparities of patient factors, tumour and diagnosis factors, and treatment variables. ETHICS AND DISSEMINATION: This research is covered by ethical approval from the NSW Population and Health Services Research Ethics Committee. Results of the study will be disseminated to different interest groups and organisations through scientific conferences, social media and peer-reviewed articles.
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spelling pubmed-68254102019-11-18 Contributions of prognostic factors to socioeconomic disparities in cancer survival: protocol for analysis of a cohort with linked data Yu, Xue Qin Goldsbury, David Yap, Sarsha Yap, Mei Ling O'Connell, Dianne L BMJ Open Epidemiology INTRODUCTION: Socioeconomic disparities in cancer survival have been reported in many developed countries, including Australia. Although some international studies have investigated the determinants of these socioeconomic disparities, most previous Australian studies have been descriptive, as only limited relevant data are generally available. Here, we describe a protocol for a study to use data from a large-scale Australian cohort linked with several other health-related databases to investigate several groups of factors associated with socioeconomic disparities in cancer survival in New South Wales (NSW), Australia, and quantify their contributions to the survival disparities. METHODS AND ANALYSIS: The Sax Institute’s 45 and Up Study participants completed a baseline questionnaire during 2006–2009. Those who were subsequently diagnosed with cancer of the colon, rectum, lung or female breast will be included. This study sample will be identified by linkage with NSW Cancer Registry data for 2006–2013, and their vital status will be determined by linking with cause of death records up to 31 December 2015. The study cohort will be divided into four groups based on each of the individual education level and an area-based socioeconomic measure. The treatment received will be obtained through linking with hospital records and Medicare and pharmaceutical claims data. Cox proportional hazards models will be fitted sequentially to estimate the percentage contributions to overall socioeconomic survival disparities of patient factors, tumour and diagnosis factors, and treatment variables. ETHICS AND DISSEMINATION: This research is covered by ethical approval from the NSW Population and Health Services Research Ethics Committee. Results of the study will be disseminated to different interest groups and organisations through scientific conferences, social media and peer-reviewed articles. BMJ Publishing Group 2019-08-18 /pmc/articles/PMC6825410/ /pubmed/31427338 http://dx.doi.org/10.1136/bmjopen-2019-030248 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Epidemiology
Yu, Xue Qin
Goldsbury, David
Yap, Sarsha
Yap, Mei Ling
O'Connell, Dianne L
Contributions of prognostic factors to socioeconomic disparities in cancer survival: protocol for analysis of a cohort with linked data
title Contributions of prognostic factors to socioeconomic disparities in cancer survival: protocol for analysis of a cohort with linked data
title_full Contributions of prognostic factors to socioeconomic disparities in cancer survival: protocol for analysis of a cohort with linked data
title_fullStr Contributions of prognostic factors to socioeconomic disparities in cancer survival: protocol for analysis of a cohort with linked data
title_full_unstemmed Contributions of prognostic factors to socioeconomic disparities in cancer survival: protocol for analysis of a cohort with linked data
title_short Contributions of prognostic factors to socioeconomic disparities in cancer survival: protocol for analysis of a cohort with linked data
title_sort contributions of prognostic factors to socioeconomic disparities in cancer survival: protocol for analysis of a cohort with linked data
topic Epidemiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6825410/
https://www.ncbi.nlm.nih.gov/pubmed/31427338
http://dx.doi.org/10.1136/bmjopen-2019-030248
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