Closed: Modifiable lifestyle factors and breast cancer survival and recurrence
Project background
There is growing evidence that lifestyle factors, such as physical activity and obesity after breast cancer diagnosis reduce the risk of breast cancer mortality (Tsilidis, 2023). Many studies support an increased risk of breast cancer mortality in relation to greater post-diagnosis body fatness with a recent meta-analysis reporting a summary RR of 1.10 per 5 units of BMI (kg/m2) (Chan 2022).
For physical activity there are fewer studies and the estimated magnitude of the reduction in breast cancer mortality for recreational physical activity was 16% per 10 metabolic equivalent of task (MET)-hours per week. Some studies have also evaluated the relationship with breast cancer recurrence and found an increased risk with higher BMI (RR=1.05 per 5 kg/m2) that was stronger for premenopausal breast cancer, but no consistent relationship with physical activity levels but there are concerns about the quality of the outcome assessment (Chan 2022; Carioulou 2023). In the physical activity meta-analysis studies ranged in size from 500-5000 breast cancer survivors, with only one study having >4000 women and treatment data. The authors concluded that there was limited, but suggestive evidence that higher levels of post - diagnostic recreational physical activity improves breast cancer outcomes. The cautious conclusion was due to the study limitations including confounding by treatment and reverse causation.
These biases are related to the study designs that have been employed including small but dedicated breast cancer survivor cohorts and etiological studies (both case-control and cohorts) that have been converted into outcome studies. These studies have different strengths and weaknesses relating to the timing of the exposure data in relation to diagnosis, length of follow-up post-diagnosis, and availability of treatment data and prognostic factors (Berrington de Gonzalez, 2012).
The Generations Study is a prospective cohort of 112,000 women in the UK originally designed to study the causes of breast cancer. The rich array of data including multiple questionnaires, biological specimens and linkage to NHS data with long-term follow-up now affords the opportunity to also study outcomes in the 5000+ women who have developed breast cancer. The sub-cohort of breast cancer survivors provides an opportunity to study the relationship between lifestyle factors and breast cancer mortality and recurrence in a large UK population. The study will address the key limitations of the previous studies including high-quality data on breast cancer treatments and recurrence, pre and post-diagnosis assessments of lifestyle and long-term follow-up.
Project aims
- Establish the Generations Study Survivorship Cohort as a sub -study of the Generations Study using serial questionnaires and NHS treatment data to develop a resource for evaluating outcomes after breast cancer (including mortality, breast cancer recurrence and other diseases)..
- Examine the relationship between pre and post-diagnosis lifestyle factors (including physical activity, alcohol consumption and obesity) and breast cancer mortality and recurrence.
- Evaluate the impact of changes in these lifestyle factors on the risk of breast cancer mortality and recurrence in the subset of breast cancer patients with multiple questionnaires after breast cancer diagnosis.
- Conduct a systematic bias analysis to carefully evaluate and quantify the role of different biases such as reverse causation, confounding by treatment and misclassification error.
Further details & requirements
The project will use state-of-the-art causal inference and quantitative bias assessment methodology and leverage the UK Generation study and linked NHS cancer treatment datasets. The PhD candidate will use advanced epidemiological methods to explore the impact of change in lifestyle factors on breast cancer outcomes and provide evidence-based recommendations for lifestyle modifications that can improve patient prognosis and long -term survival.
Study Populations
The Generations Study is a prospective cohort of 112,000 women in the UK designed originally to study the etiology of breast cancer (Swerdlow et al., 2011). Recruitment started in 2003 and to date 5000+ women have been diagnosed with breast cancer. The sub-study of these breast cancer survivors includes repeated questionnaires providing lifestyle data before and after diagnosis, treatment and outcome information from linkage to the NHS cancer treatment datasets described above and genotyping data. Aetiolog ical studies can be an efficient study setting to also examine cancer survivorship if the necessary array of data are available (Berrington de González and Morton, 2012).
Plan of Investigation and Methodology
Serial questionnaires in the Generations Study will be used to ascertain lifestyle before and after the date of breast cancer diagnosis to examine the relationship between pre and post-diagnosis lifestyle factors (including physical activity, alcohol consumption and obesity) and breast cancer mortality and recurrence. In addition, for the subset of breast cancer patients with multiple questionnaires after breast cancer diagnosis the impact of changes in these lifestyle factors on the risk of breast cancer mortality and recurrence will be assessed. The ICR CTSU have developed an algorithm for identifying breast cancer recurrence using these national datasets and validated it using actively ascertained recurrence data from four randomized trials (Kilburn et al., 2017). This algorithm will be used to identify breast cancer recurrence in the Generations Study breast cancer survivors.
Several biases could be operating that result in over-estimation or under-estimation of these associations. A systematic bias analysis will be conducted to carefully evaluate and quantify the role of different biases. Reverse causation is of greatest concern, whereby the disease progression or severity results in lifestyle changes such as decreased physical activity. Confounding by treatment could also bias the relationship if those with, for example, lower levels of physical activity are less likely to receive or comply with effective treatments for example due to co - morbidities.
A variety of direct and indirect approaches will be used to examine these biases (Berrington de Gonzalez et al, in press). For example, examining whether the relationships are weaker for breast cancer recurrence than mortality could provide indirect indication of reverse causation. Sensitivity analyses will be used to quantify the impact of measurement error in the lifestyle risk factors and outcome data (Fox et al, 20xx). Accelerometer data have also been collected for a subset of the breast cancer patients.
Impact
The purpose is to advance our understanding of the impact of change in physical activity on breast cancer outcomes and provide evidence-based recommendations for lifestyle modifications that can improve patient prognosis and long-term survival.
Note: the ICR’s standard minimum entry requirement is a relevant undergraduate Honours degree (First or 2:1).
Pre-requisite qualifications of applicants: Master in Epidemiology, Public Health, Data Science or related field; or equivalent experience in these areas.
Intended learning outcomes:
- Develop expertise in cancer survivorship research and advanced epidemiological methods
- Critically read and analyse scientific literature, fostering a deep understanding and the ability to integrate current research with historical perspectives.
- Develop hypotheses that build upon existing knowledge.
- Apply rigorous epidemiological methods for study design, data generation, analyses and interpretation, accounting for potential biases.
- Learn to work in a collaborative research environment, leveraging the support of internal teams and external collaborators to enhance research outcomes.
- Communicate research goals, methods, results and implications in both writing and orally.
- Understand and adhere to the ethical considerations and guidelines pivotal in research involving human samples and data.
[1] Berrington de González A, Morton LM. Converting epidemiologic studies of cancer etiology to survivorship studies: approaches and challenges. Cancer Epidemiol Biomarkers Prev. 2012 Jun;21(6):875-80.
[2] Berrington de Gonzalez A, Richardson D, Schubaueur-Berigan (Eds). Statistical Methods in Cancer Research Vol 5. Bias assessment in case-control and cohort studies for cancer hazard identification. IARC Scientific Publications, Lyon France (in press).
[3] Cariolou M, Abar L, Aune D, Balducci K, Becerra-Tomás N, Greenwood DC, Markozannes G, Nanu N, Vieira R, Giovannucci EL, Gunter MJ, Jackson AA, Kampman E, Lund V, Allen K, Brockton NT, Croker H, Katsikioti D, McGinley-Gieser D, Mitrou P, Wiseman M, Cross AJ, Riboli E, Clinton SK, McTiernan A, Norat T, Tsilidis KK, Chan DSM. Postdiagnosis recreational physical activity and breast cancer prognosis: Global Cancer Update Programme (CUP Global) systematic literature review and meta-analysis. Int J Cancer. 2023 Feb 15;152(4):600-615.
[4] Chan DSM, Vieira R, Abar L, Aune D, Balducci K, Cariolou M, Greenwood DC, Markozannes G, Nanu N, Becerra-Tomás N, Giovannucci EL, Gunter MJ, Jackson AA, Kampman E, Lund V, Allen K, Brockton NT, Croker H, Katsikioti D, McGinley-Gieser D, Mitrou P, Wiseman M, Cross AJ, Riboli E, Clinton SK, McTiernan A, Norat T, Tsilidis KK Postdiagnosis body fatness, weight change and breast cancer prognosis: Global Cancer Update Program (CUP global) systematic literature review and meta-analysis. Int J Cancer. 2023 Feb 15;152(4):572-599.
[5] Fox, Matthew P., Richard F. MacLehose, and Timothy L. Lash. Applying quantitative bias analysis to epidemiologic data. Cham: Springer, 2023.
[6] Kilburn LS, Aresu M, Banerji J, Barrett-Lee P, Ellis P, Bliss JM. Can routine data be used to support cancer clinical trials? A historical baseline on which to build: retrospective linkage of data from the TACT (CRUK 01/001) breast cancer trial and the National Cancer Data Repository. Trials. 2017 Nov 23;18(1):561.
[7] Lash TL, Fink AK, Fox MP. Multidimensional bias analysis. In Applying Quantitative Bias Analysis to Epidemiologic Data (pp. 109-116). New York: Springer; 2009.).
[8] Ramin C, Mullooly M, Schonfeld SJ, Advani PG, Bodelon C, Gierach GL, Berrington de González A. Risk factors for contralateral breast cancer in postmenopausal breast cancer survivors in the NIH-AARP Diet and Health Study. Cancer Causes Control. 2021 Aug;32(8):803-813.
[9] Swerdlow, A J, M E Jones, M J Schoemaker, J Hemming, D Thomas, J Williamson, and A Ashworth. “The Breakthrough Generations Study: Design of a Long-Term UK Cohort Study to Investigate Breast Cancer Aetiology.” British Journal of Cancer 105, no. 7 (September 2011): 911–17. https://doi.org/10.1038/bjc.2011.337.
[10] Timmins IR, Jones ME, O’Brien KM, Adami H-O, Aune D, Baglietto L, Bertrand KA, Brantley KD, Chen Y, DeHart JC, Clendenen TV, Dossus L, Eliassen AH, Fletcher O, Fournier A, Håkansson N, Hankinson SE, Houlston RS, Joshu CE, Kirsh VA, Kitahara CM, Koh W-P, Linet MS, Park HL, Lynch BM, May AM, Mellemkjær L, Milne RL, Palmer JR, Ricceri F, Rohan TE, Ruddy KJ, Sánchez M-J, Shu X-O, Smith-Byrne K, Steindorf K, Sund M, Vachon CM, Vatten LJ, Visvanathan K, Weiderpass E, Willett WC, Wolk A, Yuan J - M, Wei Zheng W, Nichols HB, Sandler D, Swerdlow AJ, Schoemaker MJ. An international pooled analysis of leisure-time physical activity and premenopausal breast cancer in 547,000 women from 19 cohorts. Submitted: Journal of Clinical Oncology (22/05/2023)
[11] Tsilidis KK, Cariolou M, Becerra-Tomás N, Balducci K, Vieira R, Abar L, Aune D, Markozannes G, Nanu N, Greenwood DC, Giovannucci EL, Gunter MJ, Jackson AA, Kampman E, Lund V, Allen K, Brockton NT, Croker H, Katsikioti D, McGinley-Gieser D, Mitrou P, Wiseman M, Cross AJ, Riboli E, Clinton SK, McTiernan A, Norat T, Chan DSM. Postdiagnosis body fatness, recreational physical activity, dietary factors and breast cancer prognosis: Global Cancer Update Programme (CUP Global) summary of evidence grading. Int J Cancer. 2023 Feb 15;152(4):635-644.