Professor Claire Vajdic
BOptom (HonsI) - University of NSW 1989
PhD (cancer epidemiology) - University of Sydney 2002
My research program uses large-scale linked health data to drive best practice health care and reduce the burden of cancer.
My vision is to use integrated health 'big data' to develop transformational interventions that prevent cancer and the avoidable consequences of cancer, and reduce unwarranted variation in health care for people with cancer. I have a strong focus on outcomes that impact public health policy and clinical practice, in particular for high-risk and under-served population groups. I apply population health science methods to inform precision medicine across the cancer control continuum of cancer prevention, early detection, diagnosis, treatment and follow-up care, to reduce the burden of care on individuals and on the health system. I also promote policy that supports good practice in the access to and use of real-world data for research.
For the latest comprehensive list of my publications, please click here:
https://www.unsw.edu.au/staff/claire-vajdic
Professional Activities, a selection:
- Steering Committee Member, Brain Cancer Biobanking Australia
- Member, Commonwealth Therapeutic Goods Administration Expert Advisory Panel for Breast Implant Associated Anaplastic Large Cell Lymphoma
- Associate Editor, Cancer Epidemiology
- Editorial Board, Leukaemia and Lymphoma
- Member, International Lymphoma Epidemiology Consortium (InterLymph)
- Member, AIHW Cancer Monitoring Advisory Group
- Member, ARC Medical Research Advisory Group
- Lead, Data Portfolio and Member, CRE Medicines Intelligence Steering Committee
- Deputy Chair, NSW Population and Health Services Research Ethics Committee
Funding Sources:
- National Health & Medical Research Council
- Medical Research Future Fund
- World Cancer Research Fund
- Publications
- Media
- Grants
- Awards
- Research Activities
- Engagement
- Teaching and Supervision
Selection of current grants:
Australian Research Data Commons. Australian Data Partnerships Program. The LINked Data Asset for Australian Health Research (LINDAHR). CI: Vajdic
NHMRC Centre of Research Excellence (APP1196900). Centre of Research Excellence in Medicines Intelligence. CIs: Pearson, Pratt, Buckley, Preen, Degenhardt, van Gool, Vajdic, Jorm, Wilson, Henry
NHMRC Public Health and Chronic Disease Grant Program. Improving palliative care services for people with an intellectual disability. CIs: Trollor, Agar, Cvejic, Currow, Strutt, Vajdic, Chye, Srasuebkul, Weise, Reppermund, Szanto, Harlum, Tuffrey-Wijne
Australian Research Council Discovery Project Grant (DP200100062). Realising big data’s potential to address social and health inequalities. CIs: Stephenson, Ritter, Vajdic, Engelmann
NHMRC Project Grant (APP1164852). Cancer risk in women and children after medically assisted reproduction. CIs: Vajdic, Venetis, Chambers, Sutcliffe, Opdahl, Hacker
NHMRC Project Grant (APP1142980). Integrating immunity and genetics in follicular lymphoma to establish a prognostic score fit for the modern era. CIs: Gandhi, MacManus, Seymour, Vajdic, Fink, Green, Yoon Cheah, Trau, Korbie
NHMRC Project Grant (APP 1123033). Understanding health service system needs for people with intellectual disability. CIs: Trollor, Vajdic, Lennox, Moorin, Reppermund
2010 Premier's Award for Outstanding Cancer Research Fellow
I have built a research program involving the integration of health ‘big data’. Through a number of concurrent projects across three research streams my research aims to reduce the burden of cancer on individuals and on the Australian health care system.
The first stream examines the safety and quality of health services and health technologies that prevent, diagnose and treat cancer. Novel population science methods will be developed and applied to large-scale linked health data resources to (i) identify high-risk patient groups and health technologies, (ii) identify unwarranted variation in cancer care and (iii) design new models of health care.
The second stream examines population data justice in Australia and will develop data governance models for the streamlined and safe access and use of enduring national linked data assets.
The third stream is large-scale, population-based genetic epidemiology. Using next generation genetic sequencing and novel epidemiological and biostatistical approaches we are generating robust evidence on the environmental, behavioural and genetic risk factors for lymphomas and brain cancer. This evidence will inform the pathogenesis of these high-burden malignancies and identify targets for intervention.
All projects are co-produced in partnership with clinicians, consumers, and implementation scientists to advance the control of cancer, reduce the consequences of cancer, and address inequalities and inefficiencies in cancer care and access to linked population-based data.
Consulting projects for not-for-profit health organisations and government
Co-convenor, Australian Real-World Data Network (RADiANT)
Deputy Chair, NSW Population & Health Services Research Ethics Committee
My Research Supervision
- Joint supervisor, Dr Michael Odutola. PhD thesis title “Lifestyle, medical and genetic risk factors for follicular lymphoma”. UNSW Faculty of Medicine, full-time, S1 2019+
- Joint supervisor, Damian Kotevski. PhD thesis title “Using machine learning to understand and improve care and outcomes for head and neck cancer patients”. UNSW Faculty of Medicine, full-time, S1 2019+
- Joint supervisor, Dr Penny Mackenzie. PhD thesis title “Radiotherapy utilization in the elderly”. UNSW Faculty of Medicine, part-time, S2 2019+
- Co-supervisor, Tarun Malviya. PhD thesis title “Comorbidity and cancer using machine learning models”. UNSW Faculty of Engineering, part-time, S1 2019+
- Co-supervisor, Karen Alpen. PhD thesis title “Genetic risk factors for glioma”. University of Melbourne, full time, S1 2020+
- Primary supervisor, Michael Piza. PhD thesis title “The impact of the COVID-19 pandemic on cancer care trajectories and outcomes”. UNSW Faculty of Medicine, part time, S1 2021+
- Joint supervisor, Dr Nada Hamad. PhD thesis title “The equity of access to stem cell transplantation in Australia”. UNSW Faculty of Medicine, part time, S2 2021+
My Teaching
Master of Science in Health Data Science: HDAT9100 Context of Health Data Science