CONTRIBUCIONES DEL ESTUDIO PROSPECTIVO EUROPEO EPIC AL CONOCIMIENTO SOBRE LA NUTRICIÓN Y EL...

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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.

Transcript of CONTRIBUCIONES DEL ESTUDIO PROSPECTIVO EUROPEO EPIC AL CONOCIMIENTO SOBRE LA NUTRICIÓN Y EL...

Page 1: CONTRIBUCIONES DEL ESTUDIO PROSPECTIVO EUROPEO  EPIC AL CONOCIMIENTO SOBRE LA NUTRICIÓN Y EL CÁNCER

Carlos A. GonzálezUnit of Nutrition, Environment and Cancer

Contribuciones del estudio prospectivo europeo EPIC al conocimiento sobre la nutrición y el cáncer.

CYTALIA XIV, Madrid, Abril 2009.

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

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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, kidney, endometrium

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Main features of the EPIC design(to overcome limitations of previuos studies)

1. Large sample (most 35-69 years) 2. Wide range of dietary intake3. Relatively large and detailed number of food items4. Calibration method to reduce measurement error5. Blood samples: plasma, serum, buffy-coat, red cells

* to measure biomechical markers of exposure

* to explore interactions between nutritional,

genetic and hormone factors

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The EPIC Study

I.A.R.CW.H.O

European Prospective Investigation

into Cancer and Nutrition

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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)

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BASELINE•Subjects recruitment •Questionnaires data•Anthropometry data•Blood/DNA collection•Data Base & Biorepository

1993…………………………..…….1999………… 2000…….2002……………………2005

EPIC Time Table

Spain Norway

France

Italy

UK Netherlan

d

sGerm

any

Greec

e

FOLLOW-UP:• Cancer diagnosis• Vital status • Causes of death• Changes in Lifestyle

Development of common/standardized Nutrient and lifestyle Data BasesSetting up of lab facilities for sample handling / DNA extraction etc

ETIOLOGICAL STUDIES

Swed

en

DK

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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 (yellow straws) straws) buffy coat 4 (blue straws) erythrocytes 4 (green straws)

urine collected in some centres

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Follow-up throughCancer Registries

• Denmark • Italy (4 regions) • Netherlands• Spain• Sweden• UK • Norway

Based on registries members of the European Network ofCancer Registries

• Germany • France • Greece• Naples

Active Follow-up

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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

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RESULTS

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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)

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Use of biomarkers in EPICdistribution by year of the publication

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Use of biomarkers in EPICBiomarkers 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-chainPUFA, other

phytoestrogensresveratrol

H. Pylori, HPV, IgE

cotinine, enzymes, DNA, HbA(1c), CRP

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Lung Cancer in EPIC

EPICEurope Against CancerEuropean Commission

I.A.R.CW.H.O

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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)

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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 CANCER1.126 casos, calibrado, Linseisen et al, IJC 2007

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Prostate Cancer in EPIC

EPICEurope Against CancerEuropean Commission

I.A.R.CW.H.O

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Fruit and vegetables: data for 1,104 cases among 130,000 men in EPIC

Key et al 2004

170 244 321 414 634Fruit and vegetables, g/day

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4Relative 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

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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 heterogeneityMicronutrients 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

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PROSTATE CANCER RISK ACCORDING TO ANIMAL FOOD, PROTEIN, DAIRY AND CALCIUM

INTAKE. (Allen N et al. British J Cancer 2008)

142,251 men2,727 incident cases

8.7 years of follow-up

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Diet and Colorectal Cancer in EPIC

EPICEurope Against CancerEuropean Commission

I.A.R.CW.H.O

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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)

RR

Est

imat

eFibre Intake and CR Cancer in EPIC (1065 cases)

Bingham et al. Lancet 2003

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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 meatp-test of heterogeneity: 0.72p-test of heterogeneity: 0.72

Fibre and CR Cancer in EPIC cohortsFibre and CR Cancer in EPIC cohorts

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Red and Processed MeatQ2 Q3 Q4 Q5 p

trend

HR * 1.04 1.33 1.39 1.570.001

CI 0.79 - 1.38 1.04 - 1.71 1.02 - 1.80 1.13 - 2.17

HR ** 0.98 1.22 1.23 1.350.03

CI 0.74 - 1.30 0.95 - 1.56 0.94 - 1.60 0.96 - 1.88

Meat and Meat and CR cancer in EPIC (1329 cases)CR cancer in EPIC (1329 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

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0,50

0,75

1,00

1,25

1,50

1,75

0 20 40 60 80 100g/day

RR e

stim

ate

Red meat aftercalibration

Red meat

Fish

Fish aftercalibration

Relative risks of colorectal cancer for red meat and fish Relative 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)

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Low Medium

High

Low

Medium

High

1,30

1,38*

1,50*

0,93

1,221,20

1 1,00 1,091,0

1,1

1,2

1,3

1,4

1,5

Red and processed meat increases risk of colorectal cancer Red and processed meat increases risk of colorectal cancer particularly in people who eat little < 17 g fibreparticularly in people who eat little < 17 g fibre

Fibre

Meat(>17, 28, <28g fibre. Interaction p 0.06 Norat et al, JNCI 2005)

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Breast Cancer in EPIC

EPICEurope Against CancerEuropean Commission

I.A.R.CW.H.O

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

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*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).

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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)

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Combined recreational and household physical activity

Premenopausal Postmenopausal N=90,060 N= 128,109MET-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)

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Gastric Cancer in EPIC

EPICEurope Against CancerEuropean Commission

I.A.R.CW.H.O

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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 sampleQuartiles and tertiles are full cohort sex-specificFull 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

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Plasma NUTRIENTS and gastric cancer Jenab et al BJC 2006

Plasma -cryptoxanthin

Plasma zeaxanthin

Plasma -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

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Plasma NUTRIENTS and gastric cancer Jenab et al Carcinogenesis 2006

Q4 p trend OR per 1SD increasePlasma 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

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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 159Total 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 65Total 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 Calibrated OriginalSite / type Cases number Q2 HR Q3 HR

* Tertiles instead of quartiles

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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% pTotal 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) *

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Figure 1. Apparent total nitrosocompounds (ATNC) formation * regarding meat intake and iron

0

50

100

150

200

250

50 60 60 60 120 240 240 240 420 420 420

meat intake ( g/day)

ATNC

( m

icro

g/da

y)

020406080

100120140160180200

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)

ATN

C (m

icro

g/da

y)

Meat intake and ATNC

Iron from meat and ATNC levels

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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 (CI 95%) RR (CI 95%) RR (CI 95%)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 numberSite Log-2Original (‡)

CONTINUOUSTERTILES †2 3 p trend

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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) 0.09Infected 1.82 (1.32-2.51)Not infected 0.22 (0.003-15.3) 0.13Infected 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 mg/d)

Log-2

Continuous (x40 mg/d)

Log-2

Plasma Vitamin C

Plasma Vitamin C

Hp Infection

Hp Infection

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METODOLOGÍA II – ÍNDICE DE DMMedir 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 2Vegetables Tertile 1 Tertile 2 Tertile 3Fruit (incl. nuts & seeds) Tertile 1 Tertile 2 Tertile 3Legumes Tertile 1 Tertile 2 Tertile 3Fish (fresh) Tertile 1 Tertile 2 Tertile 3Cereals Tertile 1 Tertile 2 Tertile 3Olive oil Tertile 1 Tertile 2 Tertile 3Meat Tertile 3 Tertile 2 Tertile 1

Dairy products Tertile 3 Tertile 2 Tertile 1

Alcohol2 Outside Range - Inside Range

MD Comp (g/1000kcal* day)

Mediterranean Diet Score

2Alcohol (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

*

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Low Medium HighEach 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:1anatomical location (cardia & non cardia) p=0.219 and between 2histological 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

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Thank for your attention

Catalan Institute of Oncology- Barcelona