Effect of DietEffect of Dairy Consumption on the Increased Risk of Aggressive Prostate Cancer on Skin

Effect of Diet on Skin

Research Proposal: Prostate Cancer Epidemiology

Determining the Effect of Dairy Consumption on the Increased Risk of Aggressive Prostate Cancer



Research Context and Contribution to the Research Field: Due to the wide international variation in prostate cancer incidence (1), environmental and lifestyle factors have been proposed as possible risk factors for the disease (2). For instance, the role of diet in the development of prostate cancer is uncertain and associations may vary depending on the grade or stage of the disease (3). To date, no dietary factors have been undoubtedly associated with the incidence of aggressive prostate cancer. Therefore, this research seeks to determine if there is an association between the level of dairy consumption and incidence of aggressive prostate cancer. A Cox proportional hazard regression analysis will be performed using the European Prospective Investigation into Cancer and Nutrition (EPIC). It will examine the risk of different levels of dairy consumption with the overall incidence of aggressive prostate cancer.

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Prostate cancer is projected to be the most commonly diagnosed cancer of any cancer in the UK by 2035 (4). Due to its heterogeneous nature, the clinical management and detailed understanding of the disease are challenging. This is because although prostate cancer can spread locally and metastasise, many men, especially at older ages, are found to have previously undetected and presumably asymptomatic prostate cancers at autopsy (5). Furthermore, the natural history of prostate cancer is not confirmed. Hence, it is impossible to distinguish which prostate cancers will have an indolent course, local progression, or progress to distant metastases over the long-term.

Working at Prostate Cancer UK (PCUK) as the Knowledge Officer (Research and Evidence) has enabled me to recognise the extent of research gaps regarding prostate cancer. For example, PCUK would like to focus their efforts on promoting the prevention of prostate cancer, but due to lack of substantive evidence, it is not possible. The only risk factors for prostate cancer that are supported by strong evidence are age (6), ethnicity (7), and family history (8). None of these are modifiable. Therefore, PCUK focusses on promoting earlier/accurate diagnosis and campaigns around these high-risk individuals. In the short-term this will suffice. However, to address the future pressures instigated by the growing aging population of men who will be diagnosed with prostate cancer, there needs to be appropriate evidence about modifiable risk factors, such as diet. Hence, the objective of this study is to understand whether some dietary factors such as dairy consumption modulate the risk of advanced prostate cancer. This may allow for the diagnosis of fatal aggressive prostate cancers to be reduced by dietary modification or chemoprevention. This DPhil at Oxford in Prostate Cancer Epidemiology is essential to for me to help provide the evidence needed to fill this gap the research that contributes to policy. Furthermore, I hope to have the opportunity to extend this research into other cohorts including the data from the UK Biobank to investigate potential mechanisms, taking advantage of the breadth of the resources in the EPIC prostate cancer nested case-control study, with data on nutritional, hormonal and metabolomic biomarkers.


Research Aims:

  • Determine if there is a significant risk associated with dairy consumption and diagnosis of aggressive prostate cancer.
  • Determine if there are any factors which modify the relationship.


Literature Review: While some nutrients have been linked to the development of prostate cancer, it remains unclear whether these nutrients modulate the risk of it clinically significant forms of advanced prostate cancer. Many studies have explored hypotheses regarding the increased risk of prostate cancer from diets rich in meat and fat, and may be lowered by diets high in fiber, fruit/vegetables, and various micronutrients (9). However, many studies do not take into account progression or aggressiveness of the disease.

Song et al (2013) (10) found that among men diagnosed with non-metastatic prostate cancer, men who consumed >1 serving/day of whole milk had a significantly increased risk of disease progression to fatal prostate cancer compared with men who drank <0.5 servings/day (HR 2.17, P ≤0.001) (11). Furthermore, two meta-analyses on dairy products and prostate cancer (12,13) reported a statistically significant positive association RR 1.11 and RR 1.18, respectively when comparing highest versus lowest categories of intake. Nevertheless, they do not account for the difference between low risk and aggressive disease. Findings of an increased risk with higher calcium intake are consistent with several (14-16) but not all (17-18) existing studies. One mechanism for the association is that there are increased circulating concentrations of insulin-like growth factor I (IGF-1) in dairy products (19-20). IGF-1 promotes proliferation and inhibits apoptosis in vitro in both normal and prostate cancer cells (21) which may increase prostate cancer risk. This was established in a meta-analysis of cross- sectional studies and randomized trials (22). Although there are many studies finding a relationship between dairy consumption and prostate cancer, the World Cancer Research Fund recently downgraded the evidence for dairy consumption from strong to limited evidence because of a lack of separation in research regarding aggressive and low risk cancers.


Proposed Research Methodology: Analyses will be performed with STATA 14. This research will utilise data from the European Prospective Investigation into Cancer and Nutrition (EPIC) study. EPIC represents the largest single resource available today world-wide for prospective investigations on the aetiology of cancers (and other diseases) that can integrate questionnaire data on lifestyle and diet, biomarkers of diet and of endogenous metabolism and genetic polymorphisms (23). The potential full cohort that would be studied is 153,457 men who were recruited from eight centers. Men will be excluded if they were diagnosed with cancer (except non-melanoma skin cancer) before recruitment, those with missing dates of prostate cancer diagnosis or follow-up.

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Questionnaires and computer‐guided, face‐to‐face interviews were used to collect information about basic demographic variables, past illnesses, use of medications and lifestyle. (24). The food frequency questionnaire (FFQ) is validated against 24-hour recall questionnaires (25). To calibrate dietary measurements, a standardized, computer-assisted 24-hour dietary recall was implemented at each centre on stratified random samples of the participants. Estimated daily nutrient intakes will be estimated similarly to the previously used methodology in Allen et al (2008). The nutrient intakes will be calculated by multiplying the nutrient content of each food of a specific portion size by the frequency of consumption as stated on the food frequency questionnaire (FFQ) using national food tables from each country, similar to the methodology in Allen et al (2008) (26).

Information on tumor-node-metastasis (TNM) staging code and grade of prostate cancer (based on Gleason sum) will be used depending on what was collected from each centre. Prostate cancer will be defined as low-intermediate (Gleason score of < 8), or high-risk (Gleason score of ≥8). Localized stage included those confined within the prostate and with no metastases at diagnosis (TNM staging score of T1-T2 and/or N0 and M0, or stage coded in the recruitment center as localized) Advanced cases included tumors that had spread beyond the prostate at diagnosis (T3-T4 and/or N1-N3 and/or M1, and/or stage coded in the recruitment center as metastatic. Fatal cases were those who died of prostate cancer. Aggressive prostate cancer will be categorized as either high risk, advanced, or metastatic.

Cox proportional hazard regression analysis will be used to estimate hazard ratios and 95% confidence intervals using age as the time variable (<50, 50-59, 60-69, 70-79, ≥80). Tests for heterogeneity of trends for case-defined characteristics grade (low-intermediate or high risk), tumor stage (localized or advanced) will also be performed. All models will be adjusted control potential confounding variables such as: race (White, Black/Caribbean, Asian, other), family history of prostate cancer, educational level (no degree, degree), marital status (married/cohabiting, not married/cohabiting), BMI (<25, ≥25) and frequency of PSA screening. Further adjustments will be made for physical activity (physically inactive, moderately active, active) smoking (never, past, current), use of cholesterol-lowering drugs, and intakes or fish, tomato sauce, fresh tomato products, cruciferous vegetables, and coffee/tea, red meat, processed meat and eggs and dairy. Missing values will be reported as unknown and to assess the impact of missing values a sensitivity analysis will be conducted.

Important limitations of the methodology include the following: there is significant competing mortality from other chronic diseases due to prolonged survival after a diagnosis of prostate cancer, hence death from prostate cancer as an outcome is problematic. Furthermore, diet will be assessed only at baseline, therefore, men’s consumption may have changed during follow-up and resulted in exposure misclassification. Moreover, as with every observational study, one cannot exclude the possibility of residual confounding by other potential risk factors. Finally, most centers used self-administered dietary questionnaires results in inherent self-reported bias.



  1. Center  MM, Jemal A, Lortet-Tieulent, J, et al. International variation in prostate cancer incidence and mortality rates. Eur Urol 2012;6: 92-1079
  2. Gathirua-Mwangi WG, & Zhang J. Dietary factors and risk for advanced prostate cancer. European journal of cancer prevention: the official journal of the European Cancer Prevention Organisation (ECP) 2014;23: 96-109
  3. World Cancer Research Fund/American Institute for Cancer Research. Diet, Nutrition, Physical Activity and Cancer: a Global Perspective. Continuous Update Project Expert Report 2018. Available at dietandcancerreport.org
  1. Smittenaar CR, Petersen KA, Stewart K, et al. Cancer incidence and mortality projections in the UK until 2035. British Journal of Cancer. 2016;115:1147-1155
  2. Jahn JL, Giovannucci EL, Stampfer MJ. The high prevalence of undiagnosed prostate cancer at autopsy: implications for epidemiology and treatment of prostate cancer in the Prostate-specific Antigen-era. International journal of cancer 2015;137: 2795-802.
  3. Leitzmann MF, Rohrmann S. Risk factors for the onset of prostatic cancer: age, location, and behavioral correlates. Clin Epidemiol. 2012;4:1-11.
  4. Lloyd T, Hounsome L, Mehay A, et al. Lifetime risk of being diagnosed with, or dying from, prostate cancer by major ethnic group in England 2008–2010. BMC Medicine 2015;13
  5. Bratt O, Drevin L, Akre O,et al. Family History and Probability of Prostate Cancer, Differentiated by Risk Category: A Nationwide Population-Based Study. Journal of the National Cancer Institute, 2016;108.
  6. World Cancer Research Fund/American Institute for Cancer Research. Diet, Nutrition, Physical Activity and Cancer: a Global Perspective. Continuous Update Project Expert Report 2018. Available at dietandcancerreport.org
  1. Song Y, Chavarro JE, Cao Y, et al. Whole milk intake is associated with prostate cancer-specific mortality among U.S. male physicians. The Journal of nutrition, 2013;143:189-96.
  2. Pettersson A, Kasperzyk JL, Kenfield SA, et al. Milk and dairy consumption among men with prostate cancer and risk of metastases and prostate cancer death. Cancer epidemiology, biomarkers & prevention: a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 2012;21:428-36.
  3. Huncharek et al 2008
  4. Qin LQ, He K, Xu JY. Milk consumption and circulating insulin-like growth factor-I level: a systematic literature review. Int J Food Sci Nutr 2009;60(Suppl 7):330–40
  5. Mitrou PN, Albanes D, Weinstein SJ, et al. A prospective study of dietary calcium, dairy products and prostate cancer risk (Finland). Int J Cancer, 2007;120:2466 – 73.
  6. Giovannucci E, Liu Y, Stampfer MJ, Willett WC. A prospective study of calcium intake and incident and fatal prostate cancer. Cancer Epidemiol Biomarkers Prev 2006;15: 203 – 10.
  7. Tseng M, Breslow RA, Graubard BI, et al. Dairy, calcium, and vitamin D intakes and prostate cancer risk in the National Health and Nutrition Examination Epidemiologic Follow-up Study cohort. Am J Clin Nutr 2005;81:1147 – 54
  8. Koh KA, Sesso HD, Paffenbarger RS, et al. Dairy products, calcium and prostate cancer risk. British journal of cancer 2006;95:1582-1585.
  9. Rohrmann S, Platz EA, Kavanaugh CJ, et al. Meat and dairy consumption and subsequent risk of prostate cancer in a US cohort study. Cancer Causes Control 2007;18: 41 – 50.
  10. Ma J, Giovannucci E, Pollak M, et al. Milk intake, circulating levels of insulin-like growth factor-I, and risk of colorectal cancer in men. J Natl Cancer Inst 2001;93:1330–1336
  11. Giovannucci E, Pollak M, Liu Y, et al. Nutritional predictors of insulin-like growth factor I and their relationships to cancer in men. Cancer Epidemiol Biomarkers Prev 2003;12: 84-89.
  12. Cohen P, Peehl DM, Rosenfeld RG. The IGF axis in the prostate. Horm Metab Res 1994;26:81–84.
  13. Qin LQ, He K, Xu JY. Milk consumption and circulating insulin-like growth factor-I level: a systematic literature review. Int J Food Sci Nutr  2009;60(Suppl 7):330–40
  14. Riboli E, Norat T. Epidemiologic evidence of the protective effect of fruit and vegetables on cancer risk. Am J Clin Nutr 2003;78: 569-599.
  15. Kaaks, R., Sookthai, D., Hemminki, K., Krämer, A., Boeing, H., Wirfält, E., & Weiderpass, E. (2014). Risk factors for cancers of unknown primary site: Results from the prospective EPIC cohort. International Journal of Cancer, 135, 2475-2481.
  16. Racine A, Carbonel F, Chan SS, et al. Dietary Patterns and Risk of Inflammatory Bowel Disease in Europe: Results from the EPIC Study. Inflammatory Bowel Disease 2016;22:345-354.
  17. Allen NE, Key TJ, Appleby PN, et al. Animal foods, protein, calcium and prostate cancer risk: the European Prospective Investigation into Cancer and Nutrition. British journal of cancer 2008;98:1574-81


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