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Exploring the complex relationships between pre-existing conditions and cancer diagnosis in an ageing population. Medical School, PhD Studentship (Funded)

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  • Full or part time
    Prof A Spencer
    Prof S Birch
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (Students Worldwide)
    Competition Funded PhD Project (Students Worldwide)

Project Description

The University of Exeter and the University of Queensland are seeking exceptional students to join a world-leading, cross-continental research team tackling major challenges facing the world’s population in global sustainability and wellbeing as part of the QUEX Institute. The joint PhD programme provides a fantastic opportunity for the most talented doctoral students to work closely with world-class research groups and benefit from the combined expertise and facilities offered at the two institutions, with a lead supervisor within each university. This prestigious programme provides full tuition fees, stipend, travel funds and research training support grants to the successful applicants. The studentship funding is provided for up to 42 months (3.5 years)

Ten generous, fully-funded studentships are available for the best applicants, 5 offered by the University of Exeter and 5 by the University of Queensland. This select group will spend at least one year at each University and will graduate with a joint degree from the University of Exeter and the University of Queensland.

Find out more about the PhD studentships www.exeter.ac.uk/quex/phds

Successful applicants will have a strong academic background and track record to undertake research projects based in one of the three themes of: Physical Activity and Nutrition; Healthy Ageing; and Environmental Sustainability.

The closing date for applications is midnight on 26 May 2018 (GMT), with interviews taking place between 25 June and 6 July 2018. The start date will be January 2019.

Please note that of the 10 Exeter led projects advertised, we expect that up to 5 studentships will be awarded.



Supervisors
Exeter Academic Lead: Professor Anne Spencer
Queensland Academic Lead: Professor Stephen Birch


Project Information
Delayed diagnosis for many cancers is associated with poor survival, and while cancer survival in Australia ranks highly in the world the UK still lags behind.1 Early cancer diagnosis is associated with better outcomes and can reduce the high costs of complex end-stage treatments. But the presence of one or more pre-existing health conditions, known to increase with age,2 are likely to delay cancer diagnosis, either through competing for clinical attention 3-5 or the attribution of cancer symptoms to pre-existing conditions 6-9 The world’s population is ageing, with attendant increases in the prevalence both of multiple health conditions and cancer.2 Therefore, a better understanding of how pre-existing conditions impact on the selection of patients for cancer testing and the cost-effectiveness of testing is urgently needed.
This is an exciting multi-disciplinary PhD project, exploring the relationship between pre-existing conditions and cancer diagnostics in symptomatic patients in primary care. The project will incorporate the impact on patients of receiving a positive test in terms of anxiety and costs that are often overlooked in economic-evaluations.10-12 It will deliver new knowledge and increase research capacity by:

1. Exploring the extent to which the clinical benefits/outcomes of diagnostic testing for symptomatic patients differ systematically according to pre-existing conditions.

2. Using choice modelling approaches to explore if patient and practitioner preferences among diagnostic strategies (frequency, invasiveness of test procedures) and outcomes of the tests differ systematically according to the presence/type of pre-existing conditions.

The research would entail three phases:

• A systematic review of the published and unpublished literature on the impact of pre-existing conditions on the effectiveness and characteristics of cancer diagnostics.
• Quantification, using observational data, of the impact of pre-existing conditions on cancer diagnostics on the positive and negative predictive values of symptoms for cancer.13
• Choice-based experiments to explore patient and practitioner preferences towards different diagnostic test strategies and the risk-benefit trade-offs in terms of potential delays in cancer diagnosis.14
Data is available from the Clinical Practice Research Datalink, a dataset of primary care records of patient diagnosed with one of 22 cancers in UK, with linkage to National Cancer Registration Service and Office for National Statistics data. Similar maturing systems exist in primary care in Australia such as the Melbourne East Monash General Practice Database and are available through the CanTest collaborative (www.cantest.org).
The legacy of this project will be twofold: first, an improved understanding of the complex relationships between pre-existing conditions and cancer diagnosis; and, second, international collaboration and capacity building in the health economics of cancer diagnosis for an ageing population.

How to Apply:
Clicking ’Apply Online’ will take you to the University of Exeter application system.

Funding Notes

Full tuition fees, stipend of £15,000 p.a, travel funds of up to £15,000, and RTSG of £15,000 are available over the 3.5 year studentship

References

1. Allemani C, Matsuda T, Di Carlo V, et al. Global surveillance of trends in cancer survival 2000-14 (CONCORD-3). Lancet. 2018.
2. Salisbury C, Johnson L, Purdy S, Valderas JM, Montgomery AA. Epidemiology and impact of multimorbidity in primary care: a retrospective cohort study. Brit J Gen Pract. 2011;61(582).
3. Jaen CR, Stange KC, Nutting PA. Competing Demands of Primary-Care - a Model for the Delivery of Clinical Preventive Services. J Fam Practice. 1994;38(2):166-171.
4. Nutting PA, Baier M, Werner JJ, Cutter G, Conry C, Stewart L. Competing demands in the office visit: what influences mammography recommendations? J Am Board Fam Pract. 2001;14(5):352-361.
5. Ricci-Cabello I, Violan C, Foguet-Boreu Q, Mounce LTA, Valderas JM. Impact of multi-morbidity on quality of healthcare and its implications for health policy, research and clinical practice. A scoping review. Eur J Gen Pract. 2015;21(3):192-202.
6. Lyratzopoulos G, Vedsted P, Singh H. Understanding missed opportunities for more timely diagnosis of cancer in symptomatic patients after presentation. Brit J Cancer. 2015;112:S84-S91.
7. Bain NS, Campbell NC, Ritchie LD, Cassidy J. Striking the right balance in colorectal cancer care - a qualitative study of rural and urban patients. Fam Pract. 2002;19(4):369-374.
8. Robertson R, Campbell NC, Smith S, et al. Factors influencing time from presentation to treatment of colorectal and breast cancer in urban and rural areas. Brit J Cancer. 2004;90(8):1479-1485.
9. Walter FM, Emery JD, Mendonca S, et al. Symptoms and patient factors associated with longer time to diagnosis for colorectal cancer: results from a prospective cohort study. Brit J Cancer. 2016;115(5):533-541.
10. Sharma V, Sundar SS, Breheny K, Monahan M, Sutton AJ. Methods Used in Economic Evaluations of Testing and Diagnosis for Ovarian Cancer A Systematic Review. International Journal of Gynecological Cancer. 2016;26(5):865-872.
11. Guglielmo A, Staropoli N, Giancotti M, Mauro M. Personalized medicine in colorectal cancer diagnosis and treatment: a systematic review of health economic evaluations. Cost Effectiveness and Resource Allocation. 2018;16.
12. Barraclough K. Over-inclusive referral guidance contributes to overdiagnosis. Br Med J. 2012;344.
13. Mounce LTA, Price S, Valderas JM, Hamilton W. Comorbid conditions delay diagnosis of colorectal cancer: a cohort study using electronic primary care records. Brit J Cancer. 2017;116(12):1536-1543.
14. Howard K, Salkeld G, Pignone M, et al. Preferences for CT Colonography and Colonoscopy as Diagnostic Tests for Colorectal Cancer: A Discrete Choice Experiment. Value Health. 2011;14(8):1146-1152.


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