Grant: Project Grant - PA: Women's Health Research - Early Career Researcher Grant
University of British Columbia
$100,000.00
Improving endometrial cancer risk prediction by including genetic, environmental, and temporal exposures
EF 2022-23
Résumé
Cancer of the uterus, also known as endometrial cancer, is the most common gynecological cancer in Canada and the developing world, and is increasingly affecting women and all individuals with a uterus. Identifying those at high risk for endometrial cancer in the general population allows us to direct them to risk-reducing and screening programs for early detection. We want to better understand what factors lead to endometrial cancer. We previously proposed to validate models that predict cancer risk using participants characteristics using data from the large Canadian partnership for tomorrow health study, CanPATH, which recruited and followed thousands of healthy Canadians for many years. At the time of recruitment, CanPATH participants filled out questionnaires that collected health information about their lifestyle habits. We have linked this information with provincial cancer registries and administrative databases in three provinces, to monitor which participants eventually received an endometrial cancer diagnosis or had any underlying conditions that may ultimately lead to one. In this study, we propose to improve risk modelling by including additional data, such as environmental exposure data, from the CANUE database, as well as genetic data, previously measured on a subset of CanPATH participants. In addition, the data we have obtained from linking to medical databases enables us to see what happened to participants over time. This gives us the opportunity to update their risk calculations to take into account any changes that influence risk. This research will give us an encompassing view of what factors most influence risk so that they can be used in risk prediction models that guide which participants can benefit from risk-reducing and early detection programs.
Programme
Project Grant - PA: Women's Health Research - Early Career Researcher Grant
Bénéficiaire
Emplacement
British Columbia, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
CIHR Funding Decisions Database
Tel que publié
Id
473461
Name
Talhouk Aline
Region
British Columbia
Country
Canada
Orgtype
Institution Paid; Research Institution
Instname2
Cancer Research
Theme2
Social / Cultural / Environmental / Population Health
Prcname2
Public, Community & Population Health 2
Projecttitle
Improving endometrial cancer risk prediction by including genetic, environmental, and temporal exposures
Programtype2
Operating Grants
Orgnameinp2
University of British Columbia
Cihramount2
$100,000
Cihrequipment2
$0
Programname2
Project Grant - PA: Women's Health Research - Early Career Researcher Grant
Keyworddelim
Canpath; Canue; Dynamic Risk Models; Endometrial Cancer; Etiology; Gender Role; Precision Prevention; Risk Prediction Modelling; Single Nucleotide Polymorphism; Socio-Economic Factors
Abstract
Cancer of the uterus, also known as endometrial cancer, is the most common gynecological cancer in Canada and the developing world, and is increasingly affecting women and all individuals with a uterus. Identifying those at high risk for endometrial cancer in the general population allows us to direct them to risk-reducing and screening programs for early detection. We want to better understand what factors lead to endometrial cancer. We previously proposed to validate models that predict cancer risk using participants characteristics using data from the large Canadian partnership for tomorrow health study, CanPATH, which recruited and followed thousands of healthy Canadians for many years. At the time of recruitment, CanPATH participants filled out questionnaires that collected health information about their lifestyle habits. We have linked this information with provincial cancer registries and administrative databases in three provinces, to monitor which participants eventually received an endometrial cancer diagnosis or had any underlying conditions that may ultimately lead to one. In this study, we propose to improve risk modelling by including additional data, such as environmental exposure data, from the CANUE database, as well as genetic data, previously measured on a subset of CanPATH participants. In addition, the data we have obtained from linking to medical databases enables us to see what happened to participants over time. This gives us the opportunity to update their risk calculations to take into account any changes that influence risk. This research will give us an encompassing view of what factors most influence risk so that they can be used in risk prediction models that guide which participants can benefit from risk-reducing and early detection programs.
Competitiondate
202209
Approvedterm2
1 yr 0 mth
Pinamesdelim
Talhouk, Aline
Approvedterm
1 an 0 mois
Cihrcontribution2
~ $100,000~ $0~