This document summarizes research from the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Some key findings include: - Higher fruit and vegetable intake is associated with lower risk of cancers like lung, breast, and colorectal cancer. - Red and processed meat intake increases the risk of colorectal cancer, especially in those with low fiber intake. - Physical activity is associated with lower risk of breast cancer in postmenopausal women. - Alcohol intake increases the risk of breast cancer, especially at intakes above 30g/day.

1. Carlos A. González
Unit of Nutrition, Environment and Cancer
Contribuciones del estudio
prospectivo europeo EPIC al
conocimiento sobre la nutrición
y el cáncer.
CYTALIA XIV, Madrid, Abril 2009.

2. Causas de cáncer
(R Doll, R Peto,
1981)

5. Nutrition and cancer: Convincing evidence (WRCF&AICR)
2007
• Fruit&Veg -
• Cereals -
• Fish -
• Alcohol oropharynx, oesophagus
liver, breast, colorectum
• Red,processed meat colorectum
• Aflatoxins liver
• Physical activity colon
• Obesity oesophagus, colorectum,
pancreas, breast,

6. Main features of the EPIC design
(to overcome limitations of previuos studies)
1. Large sample (most 35-69 years)
2. Wide range of dietary intake
3. Relatively large and detailed number of food items
4. Calibration method to reduce measurement error
5. Blood samples: plasma, serum, buffy-coat, red cells
* to measure biomechical markers of exposure
* to explore interactions between nutritional,
genetic and hormone factors

7. 6
The EPIC Study
I.A.R.C
W.H.O
European Prospective Investigation
into Cancer and Nutrition

8. IARC, 2007
Follow-up of EPIC subjects, 1994-2007
Breast 532 1007 924 1350 595 767 3903 784 396 145 10403
Lung 76 349 511 385 217 172 164 156 145 98 2273
Ovary 81 118 96 201 58 75 222 84 58 34 1027
Corpus uteri 64 150 147 175 53 89 351 107 90 18 1244
Cervix uteri 25 238 29 353 84 23 77 41 50 19 939
Bladder 14 242 228 259 174 75 41 126 122 32 1313
Pancreas 14 154 95 114 75 32 84 50 48 11 713
Kidney 17 92 66 95 107 44 74 70 45 21 631
Colon-rectum 113 568 512 689 310 283 516 313 251 77 3632
Prostate . 1095 385 633 459 63 . 154 218 43 3050
Stomach 14 97 66 107 77 45 32 91 71 44 644
Nor Swe Den UK Ger NL Fra Ita Spa Gre EPIC
Cancer Incidence (41,768 incident cancer cases)

9. BASELINE
•Subjects recruitment
•Questionnaires data
•Anthropometry data
•Blood/DNA collection
•Data Base & Biorepository
1993…………………………..…….1999………… 2000…….2002……………………2005
EPIC Time Table
Spain
N
orway
France
Italy
U
K
N
etherlands
Germ
any
Greece
FOLLOW-UP:
• Cancer diagnosis
• Vital status
• Causes of death
• Changes in Lifestyle
Development of common/standardized Nutrient and lifestyle Data Bases
Setting up of lab facilities for sample handling / DNA extraction etc
ETIOLOGICAL
STUDIES
Sweden
DK

10. The EPIC Study
 30 ml blood, standard process,
storage in liquid nitrogen at
-196ºC in 0.5 ml CBS strawsTM
 28 aliquots: half (14 straws)
stored in IARC (Lyon), half in
each regional centre
 28 aliquots (materials)
plasma: 12(red straws)
serum 8 (yellow straws)(yellow straws)
buffy coat 4(blue straws)
erythrocytes 4 (green straws)
 urine collected in some centres

11. Follow-up through
Cancer Registries
• Denmark
• Italy (4 regions)
• Netherlands
• Spain
• Sweden
• UK
• Norway
Based on registries
members of the
European Network of
Cancer Registries
• Germany
• France
• Greece
• Naples
Active Follow-up

12. Two dietary measurements:
Dietary questionnaire on usual diet from all 520.000 subjects
• Very detailed, 150 to 300 foods per questionnaire
• Diet history (Spain, Ragusa) 600 items
One day “actual” diet from a 7% sample of subjects (32.000)
• Computerized, 3000 foods and 700 recipes per country
• To calibrate dietary measurements between countries
EPIC data on diet

13. RESULTS

14. Scientific production in EPIC: review
 PubMed search: “European”, “prospective”,
“investigation”, “nutrition” (any field, no limits)
SUMMARY
 EPIC: 351 (inc. 5 Spanish, 4 German, 1 French, 1 Danish)
 use of biomarkers: 124 (35%)
(study including any kind of biological measurement)

15. Use of biomarkers in EPIC
distribution by year of the publication

16. Use of biomarkers in EPIC
Biomarkers measured in serum or plasma
(30%)
(23%)
Vitamin C, carotenoids and retinol, vitamins B (folate, B12), vitamin E, vitamin D
mainly sex steroid hormones; also IGF-1 and IGFBP-3
triglycerides, cholesterol, LDL, HDL
very long-chain
PUFA, other
phytoestrogens
resveratrol
H. Pylori, HPV, IgE
cotinine, enzymes, DNA, HbA(1c), CRP

17. Lung Cancer in EPIC
EPICEurope Against Cancer
European Commission
I.A.R.C
W.H.O

18. HAZARD RATIO OF LUNG CANCER BY QUINTILE OF FRUIT AND VEGETABLE INTAKE.HAZARD RATIO OF LUNG CANCER BY QUINTILE OF FRUIT AND VEGETABLE INTAKE.
Adjusted for smoking, weight and height; stratified by sex and centre.Adjusted for smoking, weight and height; stratified by sex and centre.
EPIC (Miller et al. Int J Cancer 2003)EPIC (Miller et al. Int J Cancer 2003)
Vegetables
Fruits
(Median 192 gr)
(Median 287 gr)
(Median 488 gr)

19. Total cohort RR = 1.00 (0.85-1.19)
Current smokers RR = 0.78 (0.62-0.98)
Former smokers RR = 1.30 (0.95-1.76)
Never smokers RR = 1.42 (0.85-2.40)
VEGETABLES AND LUNG CANCERVEGETABLES AND LUNG CANCER
1.126 casos, calibrado, Linseisen et al, IJC 2007

20. Prostate Cancer in EPIC
EPICEurope Against Cancer
European Commission
I.A.R.C
W.H.O

21. Fruit and vegetables: data for 1,104 cases among 130,000
men in EPIC
Key et al 2004
170 244 321 414 634
Fruit and vegetables, g/day
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
Relative risk and 95% CI
5-a-day=400 g
Key et al, Int. J. Cancer, 2004
Fruit and vegetables: data for 1.104
cases among 130.000 men in EPIC

22. PROSTATE CANCER RISK ACCORDING TO PLASMA LEVELS OF
CAROTENOIDS (HIGHEST VS LOWEST), AND DISEASE STAGE (EPIC)
(Key et Am J Clin Nutr 2007)
Local disease Advanced disease
509 cases and 592 controls 205 cases and 218 controls
P for
heterogeneity
Micronutrients by stage
Relative Risk P for Relative Risk P for
linear trend linear trend
B-carotene 0.86(0.57-1.28) 0.44 0.51(0.25-1.02) 0.05 0.09
Lycopene 1.11(0.73-1.68) 0.62 0.42(0.20-0.85) 0.01 <0.01
Sum of carotenoids 0.91(0.60-1.38) 0.65 0.38(0.17-0.84) 0.01 0.02

23. PROSTATE CANCER RISK ACCORDING TO
ANIMAL FOOD, PROTEIN, DAIRY AND CALCIUM
INTAKE.
(Allen N et al. British J Cancer 2008)
142,251 men
2,727 incident cases
8.7 years of follow-up

25. Diet and Colorectal Cancer in EPIC
EPICEurope Against Cancer
European Commission
I.A.R.C
W.H.O

26. 0,0
0,2
0,4
0,6
0,8
1,0
1,2
10 20 30 40 50
Calibrated Uncalibrated CI calibrated lower CI calibrated upper
Fibre (g/day)
RREstimate
Fibre Intake and CR Cancer in EPIC (1065
cases)
Bingham et al. Lancet 2003

27. Cohort
HR (95% CI)
for one gram of increase
Denmark
France
Postdam, Germany
Italy
Bilthoven, Netherlands
Utrecht, Netherlands
Norway
Spain
Malmo, Sweden
Umea, Sweden
UK
UK Healthy Conscious
0.90 (0.80-1.01)
0.96 (0.81-1.13)
0.88 (0.70-1.12)
0.84 (0.71-1.00)
0.90 (0.65-1.26)
0.87 (0.69-1.10)
0.92 (0.58-1.46)
0.90 (0.74-1.10)
0.79 (0.67-0.94)
0.87 (0.68-1.12)
0.88 (0.73-1.06)
1.00 (0.81-1.24)
HR 0.4 0.8 1 1.2 1.4
Cox’s regression using age, sex, energy from non-fat sources (continuous variable), energy from fat sources
(continuous variable), height and weight (tertiles defined for each sex and centre), folate, physical activity (5
categories), alcohol consumption (g/day), smoking status (never, former, current smoker, missing), educational
level, and intake of meat and processed meat
p-test of heterogeneity: 0.72p-test of heterogeneity: 0.72
Fibre and CR Cancer in EPIC cohortsFibre and CR Cancer in EPIC cohorts

28. Red and Processed Meat
Q2 Q3 Q4 Q5 p
trend
HR * 1.04 1.33 1.39 1.57 0.001
CI 0.79 - 1.38 1.04 - 1.71 1.02 - 1.80
1.13 - 2.17
HR ** 0.98 1.22 1.23 1.35
0.03
CI 0.74 - 1.30 0.95 - 1.56 0.94 - 1.60
0.96 - 1.88
Meat andMeat and CR cancer in EPIC (1329CR cancer in EPIC (1329
cases)cases)
Norat et al, JNCI 2005
* adjusted for age, fat and non-fat energy; <20g - >160g
** adjusted as above, and with height, weight, physical activity,
smoking, dietary fibre, alcohol

29. 0,50
0,75
1,00
1,25
1,50
1,75
0 20 40 60 80 100g/day
RRestimate
Red meat after
calibration
Red meat
Fish
Fish after
calibration
Relative risks of colorectal cancer for red meat and fishRelative risks of colorectal cancer for red meat and fish
before and after calibrationbefore and after calibration. (1329 cases) Norat et al. EPIC.. (1329 cases) Norat et al. EPIC.
JNCI 2005JNCI 2005
Cox regression with meats and fish as continuous variables. Age as primary time variable. Covariates are sex, energy from
fat (logarithmic scale), energy from non-fat sources (logarithmic scale), height (sex and centre defined tertiles), weight (sex
and centre defined tertiles), current ethanol consumption (logarithmic scale), physical activity at work, smoking status
(never, former, current smoker), center, consumer status (yes, no)

30. Low
Me dium
High
Low
Medium
High
1,30
1,38*
1,50*
0,93
1,22
1,20
1 1,00 1,09
1,0
1,1
1,2
1,3
1,4
1,5
Red and processed meat increases risk of colorectalRed and processed meat increases risk of colorectal
cancer particularly in people who eat little < 17 g fibrecancer particularly in people who eat little < 17 g fibre
Fibre
Meat
(>17, 28, <28g fibre. Interaction p 0.06 Norat et al, JNCI 2005)

31. Breast Cancer in EPIC
EPICEurope Against Cancer
European Commission
I.A.R.C
W.H.O

32. Total Intake of Vegetables and Fruits and BreastTotal Intake of Vegetables and Fruits and Breast
Cancer in EPICCancer in EPIC Van Gils et al JAMA 2005

33. *ALCOHOL AND BREAST CANCER: Adjusted for height (linear), weight (linear), age at menarche
(≤12, 13-14, ≥15), parity (yes/no), current oral contraceptive use (yes/no), current use of hormone replacement therapy
(yes/no), menopausal status (pre-, peri-, postmenopausal), smoking status (current, former, never) and education (none,
primary school, technical/professional school, secondary school, university).

34. Dietary fat and breast cancer
• Sieri et al. (in press).
• 328,238 women
• 7,119 incident cases
• 8,8 ys follow-up
• HR 1.13 (1.00-1.27) highest vs lowest
quintile of saturated fat intake
• Among menopausal women who do not
use HT at baseline HR 1.21 (0.99-1.48)

35. Combined recreational and
household physical activity
Premenopausal Postmenopausal
N=90,060 N= 128,109
MET-h/wk HR (95% CI) HR (95% CI)
86-126 0.91 (0.74-1.1) 0.86 (0.76-0.96)
126 0.82 (0.66-1.03) 0.83 (0.73-0.95)
P trend 0.107 0.002
Physical activity and BREAST CANCER (EPIC)Physical activity and BREAST CANCER (EPIC)
Lahman P.H. et al. CEB&P 2007 (3,423 cases)

36. Gastric Cancer in EPIC
EPICEurope Against Cancer
European Commission
I.A.R.C
W.H.O

37. Intake of specific vegetables and the risk of
stomach and oesophagus adenocarcinoma
(Gonzalez et al IJC 2006)
* For oesophagus, tertiles have been used instead of quartiles, due to the small sample
Quartiles and tertiles are full cohort sex-specific
Full cohort analysis:
Stratified by center and age.
Adjusted by sex, height, weight, education level, tobacco smoking, cigarrette smoking intensity, work and
leisure physical activity, alcohol intake, energy intake, red meat intake and processed meat intake.
HR (CI95%)
LEAFY VEG. Stomach 330 0.96 1.11 1.19 0.36 1.01 (0.88-1.16)
(except cabbages) Oesophagus 65 0.82 0.35 * 0.07 0.75 (0.42-1.34)
ONION, GARLIC Stomach 300 0.94 0.87 0.77 0.25 0.89 (0.62-1.28)
Intestinal 99 0.64 0.65 0.47 0.06 0.70 (0.38-1.29)
Diffuse 106 1.35 1.20 1.64 0.23 1.30 (0.75-2.23)
Q2 HRSite / TypeFood
(Umea & France
excluded)
Cases
number
Calibrated (per 10g)
p trendQ4 HRQ3 HR

38. 25
Plasma NUTRIENTS and gastric cancer
Jenab et al BJC 2006
Plasma β-cryptoxanthin
Plasma zeaxanthin
Plasma α-tocopherol
No differences by site, histological type
or Hp infection, except a-tocopherol,
protective only for diffuse type
Retinol seems to be associated with a
reduced GC risk as well

39. 26
Plasma NUTRIENTS and gastric cancer
Jenab et al Carcinogenesis 2006
Q4 p trend OR per 1SD increase
Plasma Vitamin C 0.55 (0.31-0.97) 0.04 0.93 (0.77 - 1.12)
Diet Vitamin C 1.02 (0.60-1.74) 0.77 1.09 (0.90 - 1.33)
Plasma Vitamin C
CARDIAL 0.36 (0.10-1.33) 0.12 0.65 (0.40 - 1.06)
NON-CARDIAL 0.63 (0.28-1.42) 0.52 1.06 (0.82 - 1.37)
DIFFUSE 0.36 (0.13-0.99) 0.09 0.96 (0.72 - 1.27)
INTESTINAL 0.59 (0.20-1.73) 0.14 0.85 (0.59 - 1.21)
Plasma Vitamin C

40. HR of cardia, non-cardia and oesophagus adenocarcinoma
and the intake of total MEAT, red meat and processed meat
in the EPIC cohort. (Gonzalez et al JNCI 2006)
HR (CI 95%) HR (CI 95%)
CARDIA 94
Total Meat 0.82 1.15 1.00 0.75 0.84 (0.31-2.28)
Red Meat 1.56 1.48 1.17 0.85 1.09 (0.46-2.59)
Processed meat 1.19 1.04 1.14 0.91 0.76 (0.29-1.96)
NON-CARDIA 159
Total Meat 1.49 1.95 2.19 0.01 3.52 (1.96-6.34)
Red Meat 0.90 1.29 1.65 0.03 1.73 (1.03-2.88)
Processed meat 1.02 1.02 1.92 0.01 2.45 (1.43-4.21)
OESOPHAGUS 65
Total Meat 0.96 1.79 * 0.10 1.56 (1.11-2.19) 1.84 (0.78-4.39)
Red Meat 1.73 1.67 * 0.23 1.13 (0.84-1.51) 0.75 (0.26-2.13)
Processed meat 2.08 3.54 * 0.002 1.16 (0.82-1.65) 1.44 (0.64-3.22)
Q4 HR p trend
CalibratedOriginal
Site / type
Cases
number
Q2 HR Q3 HR
* Tertiles instead of quartiles

41. Odds ratio (OR) of non-cardia stomach adenocarcinoma
for total meat, red meat and processed meat calibrated
intake, in Hp not infected and infected subjects.
EPIC-EURGAST cohort ((Gonzalez et al JNCI 2006).
*Number of Hp- and Hp+ controls is 372 and 769 respectively
p for interaction with Hp (likelihood ratio test)
Nested analysis: adjusted by sex, age, center, date of blood extraction (except for oesophagus), height, weight,
education level, tobacco smoking, cigarette smoking intensity, work and leisure physical activity, alcohol
intake, energy intake, citrus and non-citrus fruits intake and Hp infection.
Food Hp status OR CI 95% p
Total meat (x 100 gr) Not infected 0.21 (0.001-38.0) 0.14
Infected 5.32 (2.10-13.4)
Red meat (x 50 gr) Not infected 1.22 (0.01-237) 0.28
Infected 1.93 (0.90-4.12)
Processed meat Not infected 0.002 (<0.001-62.6) 0.25
(x 50gr) Infected 2.67 (1.20-5.93)
Non-cardia
(12/113)
(Number of Hp-/Hp+
cases) *

42. Figure 1. Apparent total nitrosocompounds (ATNC) formation * regarding meat
intake and iron
meat intake and ATNC
0
50
100
150
200
250
50 60 60 60 120 240 240 240 420 420 420
meat intake ( g/day)
ATNC(microg/day)
iron from meat and ATCN levels
0
20
40
60
80
100
120
140
160
180
200
0,45 0,9 1,2 1,73 1,78 2,93 3,46 4,82 8,5 11,26
iron from meat ( mg/day)
ATNC(microg/day)
Meat intake and ATNC
Iron from meat and ATNC levels

43. Endogenous Nitrosocompounds Exposure Index (ENEI)
and Nitrosodimethylamine (NDMA) exposure and the risk
of non-cardia adenocarcinoma*
(Jakszyn P., González CA. Carcinogenesis 2006)
† Tertiles are full cohort sex-specific. Cut points are ENEI: Men (78 and 106), women (65 and 87); NDMA: men (0.12
and 0.28), women (0.06 and 0.11)
‡ Per 40 mg/day for ENEI and per 1 mg/day for NDMA
* Full cohort analysis:
Stratified by center and age
Adjusted by sex, height, weight, education level, tobacco smoking, cigarette smoking intensity, work and leisure
physiscal activity, citrus and non citrus fruits intake, vegetables intake, alcohol intake, energy intake and nitrites.
RR (CI95%) RR (CI95%) RR (CI95%) RR (CI95%)
NDMA 155 1.04 (0.66-1.63) 1.09 (0.65-1.81) 0.75 1.09 (0.69-1.73) 0.96 (0.83-1.12)
ENEI 155 1.22 (0.79-1.88) 1.61 (1.01-2.58) 0.04 1.42 (1.14-1.78) 1.93 (1.28-2.91)
Cases
number
Site Log-2Original(‡)
CONTINUOUSTERTILES†
2 3
ptrend

44. Risk of non cardia adenocarcinoma and Endogenous
Nitrosocompounds Exposure Index (ATNC) levels,
stratifies by Hp infection and plasma Vitamin C levels*
(Jakszyn P., González CA. Carcinogenesis 2006)
† 12 cases and 369 controls not infected and 111 cases and 717 controls infected
54 cases and 235 controls below vitamin C median, and 55 cases and 256 controls above vitamin C median
Median of plasmatic vitamin C is 40 micromol/l and is computed among controls
‡ p for interaction with ATNC (likelihood ratio test)
Variable Model Stratified by † Strata OR IC 95% p ‡
Not infected 0.15 (0.01-4.06) 0.09
Infected 1.82 (1.32-2.51)
Not infected 0.22 (0.003-15.3) 0.13
Infected 2.93 (1.63-5.29)
<P50 3.24 (1.77-5.93) 0.02
>=P50 1.10 (0.63-1.93)
<P50 10.10 (3.25-31.1) 0.01
>=P50 1.26 (0.52-3.08)
ATNC
ATNC
Continuous (x40 µg/d)
Log-2
Continuous (x40 µg/d)
Log-2
Plasma Vitamin C
Plasma Vitamin C
Hp Infection
Hp Infection

45. METODOLOGÍA II – ÍNDICE DE DM
Medir el grado de adherencia a una DM: un índice basado en el consumo de 9 alimentos
claves en la DM (adaptación del índice de Trichopoulou et la, BMJ, 1995)
Límites – terciles de consumo ajustados por energía (g/1000kcal/día)
0 1 2
Vegetables Tertile 1 Tertile 2 Tertile 3
Fruit (incl. nuts
& seeds) Tertile 1 Tertile 2 Tertile 3
Legumes Tertile 1 Tertile 2 Tertile 3
Fish (fresh) Tertile 1 Tertile 2 Tertile 3
Cereals Tertile 1 Tertile 2 Tertile 3
Olive oil Tertile 1 Tertile 2 Tertile 3
Meat Tertile 3 Tertile 2 Tertile 1
Dairy products Tertile 3 Tertile 2 Tertile 1
Alcohol
2
Outside Range - Inside Range
MD Comp
(g/1000kcal*
day)
Mediterranean Diet Score
2
Alcohol (g/ethanol/day) Inside range for Males: ≥10g to
<50g, for Females: ≥5g to <25g.
* Aceite de oliva
modificada por el análisis
de CG :
0=no consumidores
1<mediana de consumo
entre consumadores
2>mediana de consumo
entre consumadores
*

46. Low Medium High
Each 1-unit
increase
HR (95%CI) HR (95%CI) HR (95%CI) HR (95%CI)
Total 449/484,579 1(referent) 0.82 (0.64, 1.04) 0.67 (0.47, 0.94) 0.020 0.95 (0.91, 0.99) 0.009
Cardia 132/ 484,896 1 (referent) 0.82 (0.55, 1.24) 0.45 (0.21, 0.91) 0.042 0.90 (0.84, 0.98) 0.011
Noncardia 206/ 484,822 1 (referent) 0.67 (0.46, 0.98) 0.71 (0.44, 1.17) 0.148 0.96 (0.90, 1.02) 0.199
Intestinal 157/ 484,871 1 (referent) 0.78 (0.51, 1.19) 0.61 (0.34, 1.11) 0.103 0.95 (0.88, 1.02) 0.141
Diffuse 158/ 484,870 1 (referent) 0.79 (0.52, 1.19) 0.69 (0.39, 1.22) 0.187 0.93 (0.87, 0.99) 0.045
rMED Score2
- Contin.
P-
value
trend
P-value
Gastric
Adeno-
carcinoma1
Cases/ Non-
Cases
rMED Score2
- Categorical
1
2
Wald Test for heterogeneity between:1
anatomical location (cardia & non cardia) p=0.219 and between 2
histological
type (diffuse and intestinal) p=0.649
Hazard ratio (HR) multivariante para el riesgo de CG por localización
anatómica y tipo histológico, según el índice de la DM
RESULTADOS III - CG

47. Thank for your attention
Catalan Institute of Oncology- Barcelona