Dietary patterns and risk of pancreatic cancer: a systematic review

Abstract

Context

Pancreatic cancer has the highest case fatality rate of all major cancers.

Objective

A systematic review using PRISMA guidelines was conducted to summarize the associations between dietary patterns and risk of pancreatic cancer.

Data Sources

PubMed and Web of Science databases were searched for case–control and cohort studies published up to June 15, 2016.

Study Selection

Eligible studies included a dietary pattern as exposure and pancreatic cancer incidence or mortality as outcome and reported odds ratios, hazard ratios, or relative risks, along with corresponding 95%CIs.

Data Extraction

Important characteristics of each study, along with the dietary assessment instrument, the component foods or nutrients included in each dietary pattern or the scoring algorithm of a priori dietary patterns, were presented. For each dietary pattern identified, the estimate of association and the 95%CI comparing the highest versus the lowest category from the model with the most covariate adjustment were reported.

Results

A total of 16 studies were identified. Among the 8 studies that examined data-driven dietary patterns, significant positive associations were found between pancreatic cancer risk and the Animal Products, Starch Rich, and Western dietary patterns, with effect estimates ranging from 1.69 to 2.40. Significant inverse relationships were found between risk of pancreatic cancer and dietary patterns designated as Fruits and Vegetables, Vitamins and Fiber, and Prudent, with effect estimates ranging from 0.51 to 0.55. Eight studies of a priori dietary patterns consistently suggested that improved dietary quality was associated with reduced risk of pancreatic cancer.

Conclusions

Better diet quality is associated with reduced risk of pancreatic cancer. The associations between dietary patterns and pancreatic cancer were stronger in case–control studies than in cohort studies and were stronger among men than among women.

INTRODUCTION

Pancreatic cancer is one of the most rapidly fatal malignancies, with the highest case fatality rate among all of the major cancers.^1,2 It is the fourth leading cause of cancer death in the United States among both men and women, despite its low incidence.¹ The 1- and 5-year survival rates for pancreatic cancer are 29% and 7%, respectively, for all stages combined.² Etiologically, pancreatic cancer is a multifactorial disease, with pathogenesis related to both genetic and environmental factors.³ Some well-recognized risk factors include age, body fatness, adult-attained height, cigarette smoking, higher level of alcohol consumption, diabetes, family history of pancreatic cancer, and medical history of diabetes and chronic pancreatitis.^2,4,5 Diet is an important modifiable lifestyle factor, but epidemiological studies evaluating pancreatic cancer risk in relation to individual nutrients or foods, such as red meat,^6–12 processed meat,^6,10,11 vegetables and fruits and associated vitamins and minerals,^13–17 fiber,¹⁸ and fat and fatty acids,^19–21 have reported inconsistent results. Dietary pattern research has emerged as an alternative to the analysis of individual foods or nutrients to examine associations with disease risk.^22–25 A dietary pattern approach allows for the consideration of complex interactions between different dietary components that affect bioavailability and absorption.²² It also avoids collinearity produced by studying separate effects of highly correlated nutrients in the statistical model.²⁶ In addition, it may be easier to detect the cumulative effects of multiple components in a dietary pattern on disease risk than to identify the effect of a single nutrient or dietary component, which may be too small to detect.^24,27

There are 2 main methods for defining dietary patterns: a priori and data-driven analysis. A priori dietary patterns, also known as score-based or investigator-defined patterns, are defined by criteria that are specified in advance, usually on the basis of external evidence such as dietary guidelines or hypotheses about diet–disease mechanisms.²⁸ In contrast, data-driven or a posteriori patterns are defined based on the analysis of dietary data from the study population being investigated. Data-driven patterns can be further grouped into outcome-independent or outcome-dependent patterns if an outcome is taken into consideration when the pattern is derived.^27,28 Factor analysis and principal component analysis are 2 common methods used to derive data-driven, outcome-independent patterns. Despite a few theoretical differences between these methods, the vast majority of dietary pattern studies are based on the principal factor method, which generally produces similar results.²² Data-driven, outcome-dependent methods establish dietary patterns by finding combinations of food intakes that explain the most variation in health outcomes. Specifically, reduced-rank regression requires outcome-related intermediate response variables, such as biomarkers, to be specified first. The data are then analyzed to determine the combinations of food intake that explain the most variation in those response variables.²⁸

Given the importance of identifying modifiable risk factors, including diet, to reduce the burden of pancreatic cancer, a systematic review of published results from case–control and cohort studies was conducted to examine the association between dietary patterns and pancreatic cancer risk and to summarize the current evidence on this topic.

METHODS

The present study was conducted and reported according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, as applicable for the topic of this review.²⁹ The PICOS (Population, Intervention, Comparison, Outcomes, and Study Design) criteria (Table 1) were used to formulate the following research question: Among adults, is better diet quality associated with reduced pancreatic cancer incidence or mortality risk in case–control and cohort studies?³⁰ A literature search of epidemiological studies on the association between dietary patterns and pancreatic cancer risk was conducted using the PubMed and Web of Science databases. Each term related to dietary pattern or the method of deriving the dietary pattern (diet pattern, dietary pattern, diet index, dietary index, diet quality, dietary quality, dietary indices, diet score, diet, food, eating habit, eating pattern, cluster analysis, reduced-rank regression, principal component analysis, factor analysis) was searched in combination with each term related to pancreatic cancer outcome (pancreatic cancer, pancreatic neoplasm, pancreatic carcinoma, pancreatic adenoma, pancreatic tumor) using an “AND” command in both databases. The search was restricted to human studies published up to June 15, 2016, in English. Eligible studies met the following criteria: (1) used case–control or cohort as the study design; (2) reported dietary patterns as an exposure; (3) reported pancreatic cancer incidence or mortality as the outcome; and (4) provided odds ratios (ORs), hazard ratios (HRs), or relative risks (RRs) with corresponding standard errors or 95%CIs. The references of identified articles and relevant reviews were also searched to identify additional eligible studies. If a publication included multiple studies with different populations in each study, each study was treated as a separate study and results were reported separately by study population. The study selection process is detailed in Figure 1.

Table 1.

PICOS criteria for inclusion and exclusion of studies

Parameter	Inclusion criteria	Exclusion criteria
Population	Adults aged ≥ 18 y and free of pancreatic cancer at baseline for cohort studies	Participants aged < 18 y
		Participants include pancreatic cancer survivors in cohort studies
Intervention/exposure	Highest category of dietary pattern score (quintiles, quartiles, tertiles, upper half of total score)
Comparison	Lowest category of dietary pattern score (quintiles, quartiles, tertiles, lower half of total score)
Outcomes	Incidence of pancreatic cancer	Recurrence of pancreatic cancer
	Mortality of pancreatic cancer	Metastasis of pancreatic cancer
Study design	Case–control studies Nested case–control studies Prospective cohort studies Retrospective cohort studies Case–cohort studies	Editorials Case reports and other descriptive studies Cross-sectional studies Ecological studies Intervention studies Reviews Meta-analyses

Figure 1.

Flow diagram of the literature search process.

Two investigators (J.Z. and M.G.) independently performed the literature search and selected eligible articles on the basis of prespecified inclusion criteria. For eligible studies, both authors extracted data and assessed study quality on the basis of STROBE (Strengthening The Reporting of OBservational Studies in Epidemiology) recommendations to determine if the study was of sufficient quality to be included in this review.³¹ Discrepancies were resolved by consensus between the 2 authors. Several criteria were used to determine study quality: adequately defined method of population selection, clearly defined exposures and outcomes, description of the method used to derive the dietary pattern, control for confounding, and reporting of multivariable-adjusted risk estimates. Only studies that met a minimum standard of quality were included in this review, although quality scores were not assigned to individual studies. The following study characteristics were extracted (Table 2^32–44): name of first author; year of publication; study design and cohort name, if applicable; study location; data collection period; number of cases; number of participants for cohort studies and number of controls for case–control studies; age range of participants at baseline; method used to derive dietary patterns; and covariates adjusted for in the multivariable model.

Table 2.

Summary of 16 epidemiology studies on dietary patterns and pancreatic cancer

Reference	Study design (cohort name)	Location (data collection period)	No. of cases (no. by sex)a	No. of controls or no. of individuals at risk (no. by sex)	Age	Type of dietary pattern/dietary pattern identification methodb	Variables for adjustmentc
Nkondjock et al. (2005)39	Population-based case–control	Canada (1994–1997)	585 (335 M, 250 F)	4779 (2422 M, 2357 F)	30–74 y	Data-driven outcome-independent/FA	Age, smoking status, BMI, physical activity, province, educational attainment, total energy intake
Bosetti et al. (2013)32	Hospital-based case–control	Italy (1983–1992)	362 (229 M, 133 F)	1552 (1114 M, 411 F)	18–86 y	A priori	Age, center, sex, year of interview, education, BMI, smoking status, alcohol consumption, history of diabetes
Bosetti et al. (2013)32	Hospital-based case–control	Italy (1992–2008)	326 (174 M, 152 F)	652 (348 M, 304 F)	34–80 y	A priori	Age, center, sex, year of interview, education, BMI, smoking status, alcohol consumption, history of diabetes, total energy intake
Bosetti et al. (2013)40	Hospital-based case–control	Italy (1991–2008)	326 (174 M, 152 F)	652 (348 M, 304 F)	34–80 y	Data-driven outcome-independent/PCFA	Age, sex, study center, year of interview, education, BMI, smoking status, alcohol consumption, history of diabetes
Chan et al. (2013)41	Population-based case–control	USA (1995–1999)	532 (291 M, 241 F)	1701 (883 M, 818 F)	21–85 y	Data-driven outcome-independent/PCFA, separately for M and F	Age, sex, race, education, history of diabetes, BMI, smoking status, alcohol consumption, leisure time physical activity, total energy
Shivappa et al. (2015)33	Hospital-based case–control	Italy (1991–2008)	326 (174 M and 152 F)	652 (348 M, 304 F)	34–80 y	A priori	Age, sex, study center, year of interview, education, BMI, smoking status, alcohol consumption, history of diabetes, total energy
Antwi et al. (2016)34	Hospital-based case–control	USA (2000–2015)	817 (461 M, 356 F)	1756 (955 M, 801 F)	24–94 y	A priori	Age, sex, race, history of diabetes, BMI, pack-years of smoking within smoking status categories, education
Lucas et al. (2016)35	Hospital-based case–control	Italy (1991–2008)	326 (174 M, 152 F)	652 (348 M, 304 F)	30–84 y	A priori	Age, sex, study center, year of interview, education, BMI, smoking status, alcohol consumption, history of diabetes, energy intake
Michaud et al. (2005)42	Cohort (HPFS)	USA (1986–2000)	185	47 493 (men only)	40–75 y	Data-driven outcome-independent/PCFA	Age, BMI, pack-years, physical activity, history of diabetes, energy intake, height, multivitamin use
Michaud et al. (2005)42	Cohort (NHS)	USA (1984–2000)	181	77 179 (women only)	30–55 y	Data-driven outcome-independent/PCFA	Age, BMI, pack-years, physical activity, history of diabetes, energy intake, height, multivitamin use
Nöthlings et al. (2008)44	Cohort (MEC)	USA (1993–2003)	610	183 513 d	45–75 y	Data-driven outcome-dependent/RRR	Age, sex, ethnicity, BMI, duration of follow-up, history of diabetes, history of pancreatic cancer, smoking status, pack-years, energy intake
Nöthlings et al. (2008)44	Cohort (EPIC)	Europe (1994–2007)	517	424 978 d	35–70 y	Data-driven outcome-dependent/RRR	Age at enrollment, center, sex, smoking status, pack-years, history of diabetes, BMI, energy intake
Jiao et al. (2009)36	Cohort (NIH-AARP Diet and Health Study)	USA (1995–2003)	1057	450 416 (263 398 M, 187 018 F)	50–71 y	A priori	Age, sex, race, education, marital status, energy intake, smoking status, alcohol consumption, BMI, physical activity
Inoue-Choi et al. (2011)43	Cohort (IWHS)	USA (1986–2007)	256	34 642 (women only)	55–69 y	Data-driven outcome-independent/PCA	Age, race, education, alcohol consumption, smoking status, physical activity
Tognon et al. (2012)37	Cohort (VIP population study)	Sweden (1990–2008)	92	77 151(37 546 M, 39 605 F)	30–60 y	A priori	Age, obesity, smoking status, education, physical activity
Arem et al. (2013)38	Cohort (NIH-AARP Diet and Health Study)	USA (1994–2006)	2383	537 218 (316 670 M, 220 548 F)	50–71 y	A priori	Sex, smoking status at baseline, history of diabetes, BMI, calorie intake

Abbreviations: BMI, body mass index; EPIC, European Prospective Investigation into Cancer and Nutrition; F, female; FA, factory analysis; HPFS, Health Professionals Follow-Up Study; IWHS, Iowa Women’s Health Study; M, male; MEC, Multiethnic Cohort Study; NHS, Nurses’ Health Study; NIH-AARP, National Institutes of Health-American Association of Retired Persons; PCFA, principal component factor analysis; RRR, reduced rank regression; VIP, Västerbotten Intervention Programme.

^aThe number of cases for each sex was presented in case–control studies only because cohort studies included in this review did not provide such information.

^bThe method of dietary pattern identification was noted for data-driven methods only.

^cVariables adjusted were those in the final multivariable-adjusted model.

^dInformation on number of men and women was not available.

Table 3 ^39–44 and Table 4^32–38 describe important characteristics of the dietary assessment instrument for data-driven dietary patterns and a priori dietary patterns, respectively. The name of the dietary pattern, the component foods or nutrients included in each data-driven dietary pattern, and the scoring algorithm of a priori dietary patterns are also presented. For each dietary pattern identified, the estimate of association (ie, OR, HR, RR), the 95%CI for the highest vs the lowest category of dietary pattern scores from the model with the most covariate adjustment, and the P value for trend, if applicable, were reported. Sex-specific associations and associations with continuous exposures were also presented if they were reported in the original studies. Forest plots were used to show the relative risk of pancreatic cancer for the highest vs the lowest category of scores for each dietary pattern identified and the sex-specific associations, if reported. A meta-analysis to quantitatively assess the summary estimates was not conducted in the present review because of wide variations in the derivation and application of the dietary patterns assessed.

Table 3.

Summary of characteristics of data-driven dietary patterns and main results for the associations between data-driven dietary patterns and pancreatic cancer risk

Reference	Country of study	Study design	Dietary assessment instrument (no. of items included)	Period of dietary assessment	Assessment of validation and reproducibility	Dietary pattern and component foods	Main resultsa
Nkondjock et al. (2005)39	Canada	Population based case–control	Interviewer-administered semiquantitative FFQ (69 items)	2 y before diagnosis of pancreatic cancer for cases, or 2 y before interview for controls	Validity and reproducibility were assessed in other populations but not in the study population	Western: processed meat, sweets and desserts, refined grains, potatoes, processed fish, organ meats, soft drinks, legume products, snacks, margarine, nuts, mayonnaise, eggs, oil, high-fat dairy products, red meats, fruits, tea, dark yellow vegetables, low-fat dairy products, tomatoes Fruits and Vegetables: fruits, cruciferous vegetables, green and other vegetables, dark yellow vegetables, low-fat dairy products, rice and pasta, whole grains, soups, poultry products, water, cold breakfast cereals, legumes, tomatoes, fruit juice, fish Drinker: liquor, wine, beer, spices and herbs, coffee	Western: Males: OR = 1.30 (95% CI: 0.75–2.25), P trend = 0.56 Females: OR = 1.40 (95% CI: 0.76–2.59), P trend = 0.10 Fruits and Vegetables: Males: OR = 0.55 (95% CI: 0.32–0.93), P trend < 0.01 Females: OR = 1.06 (95% CI: 0.58–1.96), P trend = 0.98 Drinker: Males: OR = 1.51 (95% CI: 0.92–2.47), P trend = 0.09 Females: OR = 0.95 (95% CI: 0.53–1.71), P trend = 0.80
Bosetti et al. (2013)40	Italy	Hospital-based case–control	Interviewer-administered FFQ(78 items)	2 y before diagnosis of pancreatic cancer for cases, or 2 y before hospital admission for controls	Validity and reproducibility were assessed	Animal Products: animal protein, cholesterol, saturated fatty acids, calcium, phosphorus, zinc, and vitamin B12 Unsaturated Fats: linoleic acid, linolenic acid, other PUFAs, vitamin E Vitamins and Fiber: soluble carbohydrates, potassium, total folate, vitamin C, beta carotene, total fiber Starch Rich: vegetable protein, starch, sodium	Animal Products: OR = 2.03 (95%CI: 1.29–3.19), P trend = 0.0008 Unsaturated Fats: OR = 1.13 (95%CI: 0.71–1.78), P trend = 0.68 Vitamins and Fiber: OR = 0.55 (95%CI: 0.35–0.86), P trend = 0.0035 Starch Rich: OR = 1.69 (95%CI: 1.02–2.79), P trend = 0.06
Chan et al. (2013)41	USA	Population based case–control	Interviewer-administered semiquantitative FFQ (131 items)	1 y before diagnosis of pancreatic cancer for cases, or 1 y before interview for controls	Validity and reproducibility were assessed	Western: for both men and women: red meat, fried potatoes and chips, high-fat dairy products, eggs, butter, sweetened grains and desserts, sweets, sugar-added beverages, refined grains, pizza, organ meats, potatoes, and beer. Additionally, for men: nuts, coffee; additionally, for women: seafood, garlic and onions, poultry, low-fat dairy products Prudent: for both men and women: yellow vegetables, cruciferous vegetables, legumes and legume products, green leafy vegetables, tomatoes, fruit, garlic and onions, seafood, poultry, whole grains, tea, fruit juice, potatoes, refined grains. Additionally, for men: wine; additionally for women: nuts, eggs, low-fat dairy products	Western: Males: OR = 2.40 (95%CI: 1.30–4.20), P trend = 0.008 Females: OR = 0.90 (95%CI: 0.50–1.60), P trend = 0.70 Prudent: Males: OR = 0.51 (95%CI: 0.31–0.84), P trend = 0.001 Females: OR = 0.51 (95%CI: 0.29–0.90), P trend = 0.04
Michaud et al. (2005)42	USA	Cohort (HPFS)	Self-administered FFQ (approx. 130 items)	1 y previous to FFQ	Validity and reproducibility were assessed	Western: red meat, processed meat, French fries, refined grains, high-fat dairy products, condiments, eggs, sweets and desserts, mayonnaise, snacks, sugary drinks, butter, margarine, potatoes, coffee, pizza, creamed soup or chowder, nuts, beer Prudent: vegetables, legumes, fruit, tomatoes, fish, whole grains, poultry, salad dressing, fruit juice, condiments, potatoes, nuts	Western: RR = 0.89 (95%CI: 0.47–1.69), P trend = 0.97 Prudent: RR = 1.88 (95%CI: 1.06–3.32), P trend = 0.09
Michaud et al. (2005)42	USA	Cohort (NHS)	Self-administered FFQ (approx. 130 items)	1 y previous to FFQ	Validity and reproducibility were assessed	Western: legumes, tomatoes, red meat, processed meat, French fries, refined grains, high-fat dairy products, condiments, eggs, sweets and desserts, mayonnaise, snacks, sugary drinks, butter, margarine, potatoes, pizza, nuts, creamed soup or chowder Prudent: vegetables, legumes, fruit, tomatoes, fish, whole grains, poultry, salad dressing, fruit juice, low-fat dairy products, organ meats, eggs, mayonnaise, nuts	Western: RR = 0.94 (95%CI: 0.46–1.94), P trend = 0.56 Prudent: RR = 0.93 (95%CI: 0.52–1.64), P trend = 0.57
Nöthlings et al. (2008)44	USA	Cohort (MEC)	Self-administered FFQ (>180 food items)	1 y previous to FFQ	Validity was assessed	Simplified Food Group (predictive for quercetin, kaempferol, and myricetin): tea, cabbage, fresh fruit, wine Simplified Food Item (predictive for quercetin, kaempferol, and myricetin): black tea, dark leafy greens, apples and applesauce, red wine, chili	Simplified Food Group: RR = 0.85 (95%CI: 0.64–1.13), P trend = 0.67 Simplified Food Item: RR = 0.97 (95%CI: 0.74–1.27), P trend = 0.57
Nöthlings et al. (2008)44	Europe	Cohort (EPIC)	Country-specific dietary assessment method, which included self-administered quantitative dietary questionnaires, semiquantitative FFQs, and combined use of semiquantitative FFQs and 7-day food records (up to 260 food items)	1 y previous to FFQ	Validity was assessed	Simplified Food Group (predictive for quercetin, kaempferol, and myricetin): tea, cabbage, fresh fruit, wine	Simplified Food Group: Current smokersb: RR = 0.88 (95%CI: 0.45–1.73), P trend = 0.78
Inoue-Choi et al. (2011)43	USA	Cohort (IWHS)	Self-administered FFQ (127 food items)	1 y previous to FFQ	Validity and reproducibility were assessed	Study did not provide information on food components	High Vegetable: HR = 1.25 (95%CI: 0.84–1.87), P trend = 0.03 Low Fat: HR = 0.97 (95%CI: 0.64–1.47), P trend = 0.99 Mediterranean: HR = 1.27 (95%CI: 0.84–1.90), P trend = 0.14 High Fiber: HR = 0.85 (95%CI: 0.56–1.29), P trend = 0.74 High Sweet: HR = 0.74 (95%CI: 0.48–1.13), P trend = 0.10 High Fruit: HR = 0.96 (95%CI: 0.64–1.43), P trend = 0.41

Abbreviations: EPIC, European Prospective Investigation into Cancer and Nutrition; FFQ, food frequency questionnaire; HPFS, Health Professionals Follow-Up Study; HR, hazard ratio; IWHS, Iowa Women’s Health Study; MEC, Multiethnic Cohort Study; NHS, Nurses’ Health Study; OR, odds ratio; PUFAs, polyunsaturated fatty acids; RR, risk ratio.

^aThis column includes the relative risk of pancreatic cancer, comparing the highest vs the lowest dietary pattern score category in the fully adjusted model with the largest number of total individuals and included P value for trend. Sex-specific associations and associations for continuous exposure were presented if they were reported in the original study.

^bResults for simplified food group pattern and pancreatic cancer risk were only reported among current smokers in the study.

Table 4.

Summary of characteristics of a priori dietary patterns and main results for associations between a priori dietary patterns and pancreatic cancer risk

Reference	Country of study	Study design	Dietary assessment instrument (no. of items included)	Period of dietary assessment	Assessment of validity and reproducibility	Dietary pattern and scoring algorithm	Main resultsa
Bosetti et al. (2013)32	Italy	Hospital-based case–control	Interviewer-administered simplified dietary section (14 items);	Past usual diet before diagnosis of pancreatic cancer for cases or before hospital admission for controls	No information on validity and reproducibility	MDS: Cereals, fruit, vegetables, fish, olive oil/butter, and margarine: 1 point each for intake at or greater than the sex-specific median. Milk and dairy products, meat and meat products: 1 point each for intake less than the sex-specific median. Alcohol: 1 point for moderate drinkers (consumption over 0 and below the median) and 0 points for non-drinkers or heavy drinkers (consumption above the median)	MDS: OR = 0.57 (95%CI: 0.34–0.95), P trend = 0.0009; ORa unit increment of the MDS = 0.88 (95%CI: 0.81–0.95)
Bosetti et al. (2013)32	Italy	Hospital-based case–control	Interviewer-administered FFQ (78 items)	2 y before diagnosis of pancreatic cancer for cases, or 2 y before hospital admission for controls	Validity and reproducibility were assessed	MDS: Cereals, fruit, vegetables, legumes, fish, MUFA to SFA ratio: 1 point each for intake at or greater than the sex-specific median. Milk and dairy products, meat and meat products: 1 point each for intake less than the sex-specific median. Alcohol: 1 point each for moderate drinkers (consumption over 0 and below the median) and 0 points for non-drinkers or heavy drinkers (consumption above the median). MDP: Sum of the standardized residuals of the regression of cereals, fruit, vegetables, legumes, alcohol, MUFA to SFA ratio on total calories, minus those of milk and meat. MDP was then expressed as a percentage of adherence, using the range of the values in the sample MAI: Divide the sum of the intake of typical Mediterranean foods (ie, bread, cereals, fruit, vegetables, legumes, potatoes, fish, red wine, and vegetable oils) as a percentage of total energy by the sum of the intake of nontypical Mediterranean foods (ie, milk, cheese, meat, eggs, animal fats and margarines, sweet beverages, cakes, pies and cookies, and sugar) as the percentage of total energy	MDS: OR = 0.51 (95%CI: 0.29–0.92), P trend = 0.05; ORa unit increment of the MDS = 0.89 (95%CI: 0.81–0.99) MDP: OR = 0.44 (95%CI: 0.27–0.73), P trend = 0.003; OR10 units increment of the MDP = 0.79 (95%CI: 0.69–0.90) MAI: OR = 0.68 (95%CI: 0.42–1.11), P trend = 0.07; ORa unit increment of the MAI = 0.82 (95%CI: 0.69–0.98)
Shivappa et al. (2015)33	Italy	Hospital based case–control	Interviewer-administered FFQ (78 items)	2 y before diagnosis of pancreatic cancer for cases, or 2 y before hospital admission for controls	Validity and reproducibility were assessed	E-DII: Dietary intake of carbohydrate, protein, fat, alcohol, fiber, cholesterol, SFAs, MUFAs, PUFAs, n-3 fatty acids, n-6 fatty acids, niacin, thiamin, riboflavin, vitamin B6, Fe, Zn, vitamin A, vitamin C, vitamin D, vitamin E, folic acid, β-carotene, anthocyanidins, flavan-3-ol, flavonol, flavonones, flavones, isoflavones, caffeine, and tea was first energy adjusted and standardized relative to a worldwide representative diet database that included diet data from 11 populations across the world. This standardized value was then converted to a centered percentile score, which was then multiplied by the respective literature-derived food parameter effect score to obtain the food-parameter-specific DII score. All food-parameter-specific DII scores were then summed to obtain the overall E-DII score	E-DII: Males: OR = 1.85 (95%CI: 0.91–3.76), P trend = 0.10; ORa unit increment of the DII = 1.17 (95%CI: 1.00–1.36) Females: OR = 3.71 (95%CI: 1.73–7.94), P trend = 0.001; ORa unit increment of the DII = 1.33 (95%CI: 1.12–1.57) Males and females: OR = 2.48 (95%CI: 1.50–4.10), P trend = 0.0015; ORa unit increment of the DII = 1.24 (95%CI: 1.11–1.38)
Antwi et al. (2016)34	USA	Hospital-based case–control	Self-administered FFQ (144 items)	During the last 5 y before interview for cases and controls	Validity and reproducibility were assessed	E-DII: Dietary intake of alcohol, β-carotene, caffeine, carbohydrates, cholesterol, fiber, iron, isoflavones, magnesium, MUFAs, n-3 and n-6 fatty acids, niacin, protein, energy, PUFAs, riboflavin, saturated fat, selenium, thiamin, total fat, vitamins A, B6, B12, C, D, and E zinc was first energy adjusted and standardized relative to a worldwide representative diet database that included diet data from 11 populations across the world. This standardized value was then converted to a centered percentile score, which was then multiplied by the respective literature-derived food-parameter inflammatory effect score to obtain the individual’s food parameter-specific DII score. All food-parameter-specific DII scores were then summed to create the overall E-DII score	E-DII: Males: OR = 2.72 (95%CI: 1.77–4.17), P trend < 0.0001 Females: OR = 2.23 (95%CI: 1.43–3.48), P trend = 0.0005 Males and females: OR = 2.54 (95%CI: 1.87–3.46), P trend < 0.0001
Lucas et al. (2016)35	Italy	Hospital-based case–control	Interviewer-administered FFQ (83 items)	2 y before diagnosis of pancreatic cancer for cases, or 2 y before hospital admission for controls	Validity and reproducibility were tested	TEAC, TRAP, and FRAP: Using the Italian food composition database, an ad hoc database was developed to calculate total antioxidant capacity for each of the three indices (ie, TEAC, TRAP, and FRAP) based on experimental assessment of the food extracts.56,57 In total, 64 food items contribute to assessment of TEAC, 57 to TRAP, and 59 to FRAP in this study	TEAC: OR = 0.61 (95%CI: 0.39–0.94), P trend = 0.03 TRAP: OR = 0.78 (95%CI: 0.49–1.24), P trend = 0.27 FRAP: OR = 0.63 (95%CI: 0.41–0.99), P trend = 0.05
Jiao et al. (2009)36	USA	Cohort (NIH-AARP Diet and Health Study)	Self-administered FFQ (124 items);	1 y previous to FFQ	Validity and reproducibility were tested	No-alcohol aMDS: 1 point each assigned to intakes that were at or greater than the sex-specific median for each of 7 components: vegetables other than white potatoes, legumes, fruits, fish, nuts, whole grains, and ratio of MUFAs to SFAs. 1 point was assigned to intakes less than the sex-specific median for red and processed meats	No-alcohol aMDS: Males: RR = 0.89 (95%CI: 0.76–1.05) Females: RR = 0.98 (95%CI: 0.79–1.21) Males and females: RR = 0.92 (95%CI: 0.81–1.05)
Tognon et al. (2012)37	Sweden	Cohort (VIP population study)	Two self-administered FFQs (84 items from 1990–1996, 65 items since 1997)	1 y previous to FFQ	Validity and reproducibility were tested	A refined version of the MDS: 1 point was assigned to intakes at or greater than the sex- and FFQ-specific median for each of the 6 components: vegetables and potatoes, fruit and juices, whole-grain cereals, fish and fish products, ratio of MUFAs + PUFAs to SFAs, alcohol intake. 1 point was assigned to intakes less than the sex- and FFQ-specific median for each of 2 components: dairy products and meat or meat products	A refined version of the MDS: Males: HR = 0.82 (95%CI: 0.68–0.99), P trend < 0.05 Females: HR = 0.83 (95%CI: 0.69–1.00), P trend = 0.06 Males and females: HR = 0.82 (95% CI: 0.72–0.94), P trend < 0.01
Arem et al. (2013)38	USA	Cohort (NIH-AARP Diet and Health Study)	Self-administered FFQ (124 items)	1 y previous to FFQ	Validity and reproducibility were tested	HEI-2005: 0–5 points were assigned to each of the following 6 components, with higher consumption awarded higher points in a linear, prorated fashion: total fruit, nonjuice fruit, total vegetables, dark green and orange vegetables and legumes, total grains, and whole grains. 0–10 points were assigned to each of the following 3 components, with higher consumption awarded higher points in a linear, prorated fashion: milk products (including soy), healthy oils, and meat and beans (including meat, poultry, fish, and legumes). 0–10 points awarded, with reverse scoring for each of 2 components: sodium and calories from saturated fat 0–20 points awarded, with reverse scoring for calories from solid fat, alcohol, and added sugar	HEI-2005: Males: HR = 0.83 (95%CI: 0.70–0.98), P trend = 0.008; HRinterquartile range of the total HEI-2005 score = 0.91 (95%CI: 0.84–0.98) Females: HR = 0.87 (95%CI: 0.70–1.09), P trend = 0.16; HRinterquartile range of the total HEI-2005 score = 0.92 (95%CI: 0.83–1.02) Males and females: HR = 0.85 (95%CI: 0.74–0.97), P trend = 0.003; HRinterquartile range of the total HEI-2005 score = 0.90 (95%CI: 0.85–0.95)

Abbreviations: aMDS, alternate Mediterranean diet score; E-DII, energy-adjusted Dietary Inflammatory Index; FFQ, food frequency questionnaire; FRAP, ferric-reducing antioxidant power; HEI-2005, Healthy Eating Index-2005; HR, hazard ratio; MAI, Mediterranean Adequacy Index; MDP, Mediterranean Dietary Pattern Adherence Index; MDS, Mediterranean diet score; MUFAs, monounsaturated fatty acids; NIH-AARP, National Institutes of Health-American Association of Retired Persons; OR, odds ratio; PUFAs, polyunsaturated fatty acids; RR, risk ratio; SFAs, saturated fatty acids; TEAC, Trolox equivalent antioxidant capacity; TRAP, total radical-trapping antioxidant parameter; VIP, Västerbotten Intervention Programme.

^aThis column includes the relative risk of pancreatic cancer, comparing the highest vs the lowest category of dietary pattern scores in the fully adjusted model with the largest number of individuals and included the P value for trend. Sex-specific associations and associations for continuous exposure were presented if they were available in the original study.

RESULTS

Study selection

The initial search from PubMed and Web of Science identified 827 articles after duplicate publications were removed. After titles and abstracts were examined, 27 articles were considered eligible, 14 of which were excluded after full-text review (reasons shown in Figure 1). Therefore, 13 articles were included: 7 focused on a priori dietary patterns,^32–38 5 reported data-driven outcome-independent dietary patterns,^39–43 and 1 reported data-driven outcome-dependent dietary patterns.⁴⁴ Three articles each reported 2 different study populations; each study population was counted as a separate study.^32,42,44 Therefore, a total of 16 studies were included in the present review (Figure 1).

Study characteristics

Eight cohort studies^{36–38,42–44} and 8 case–control studies^{32–35,39–41} published between 2005 and 2013 were included. Two case–control studies were population based^39,41 and the other 6 were hospital based.^32–35,40 The 16 included studies were conducted in Europe (n = 7)^{32,33,35,37,40,44} or North America (n = 9).^{34,36,38,39,41–44} Of the 7 European studies, 5 were conducted in Italy^32,33,35,40 and 4 used the same study population.^32,33,35,40 One study reported pancreatic cancer mortality as an outcome,³⁷ 1 study included deaths due to pancreatic cancer in the outcome of incident pancreatic cancer cases,³⁸ and all the other studies reported incident cases of pancreatic cancer as the outcome. In total, 1 848 584 individuals aged 18 to 94 years were included in this review, and 8881 cases of pancreatic cancer (number of cases ranged from 92 to 2383 across studies) were identified during 3 to 31 years of data collection. In multivariable models, 11 studies adjusted for important confounders of the association between diet and pancreatic cancer, including age, sex, history of diabetes, body mass index, and smoking^{32–35,40–42,44}; of these, 8 additionally adjusted for total energy intake.^{32,33,35,41,42,44} To determine the type of dietary pattern, 8 studies used a priori dietary patterns and the other 8 used data-driven methods. Of the studies that used data-driven methods, 2 used reduced-rank regression as an outcome-dependent data-driven method⁴⁴ and 6 used outcome-independent data-driven methods, including factor analysis, principal component analysis, and principal component factor analysis (Table 2).

The food frequency questionnaire (FFQ) was the most commonly used method of dietary assessment (n = 14 studies). However, 1 multisite European study used country-specific methods of dietary assessment, such as quantitative dietary questionnaire, semiquantitative FFQ, and combined use of semiquantitative FFQ and 7-day food records.⁴⁴ In another study, a simplified dietary section that contained 14 food items was used.³² Dietary assessment was conducted by an interviewer in 7 studies^{32,33,35,39–41} and was self-administered in the other studies. All studies measured diet at 1 time point only, using the same dietary assessment instrument for each individual except for the multisite European study in which the diet consumed by individuals from different countries was measured using country-specific questionnaires⁴⁴ and another study in which 2 different FFQs were used for participants enrolled at different periods.³⁷ The number of food items included in the different dietary assessment instruments varied from 14¹⁸ to 260.⁴⁴ The dietary assessment instruments evaluated diet over the previous 1 to 2 years in the majority of studies (n = 14) and over the previous 5 years in 1 study,³⁴ while lifetime diet was assessed in 2 studies.³² Both the validity and the reproducibility of the dietary assessment instrument were tested in most studies (n = 12), although 2 studies assessed validity only,⁴⁴ 1 study assessed validity and reproducibility in other populations but not in the study population,³⁹ and 1 study did not provide any information about the assessment of validity or reproducibility³² (Tables 3 and 4).

Association between dietary patterns and pancreatic cancer risk

For organizational purposes, the 8 studies that used data-driven methods to assess dietary patterns were divided into 2 categories: those that found unfavorable dietary patterns and those that found favorable dietary patterns. Results are presented separately in the next 2 sections. Dietary patterns designated as unfavorable include a large proportion of food items and components generally considered harmful to health, such as red and processed meats, French fries, animal protein, and cholesterol. Favorable dietary patterns are those that include substantial amounts of healthy foods, such as fruit and vegetables, fiber, and whole grains.

Unfavorable data-driven dietary patterns

Six studies (3 case–control studies^39–41 and 3 cohort studies^42,43) reported associations between pancreatic cancer risk and unfavorable data-driven dietary patterns. These patterns were designated as Animal Products,⁴⁰ Starch Rich,⁴⁰ Western,^39,41,42 High Sweet,⁴³ and Drinker³⁹ and were derived by factor analysis,³⁹ principal component analysis,⁴³ or principal component factor analysis.^40–42 The reported sex-specific and overall associations were inconsistent across studies, with the adjusted RRs ranging from 0.74²⁷ to 2.40²,⁵ for the highest category of dietary pattern score compared with the lowest category.^41,43 In 2 of the 3 case–control studies, 3 unfavorable dietary patterns (Animal Products among all men and women,⁴⁰ Starch Rich among all men and women,⁴⁰ and Western among men only⁴¹) had significant positive associations with pancreatic cancer, with the corresponding RRs ranging from 1.69⁴⁰ to 2.40.⁴¹ On the other hand, the other unfavorable dietary patterns (Western among men and women separately,³⁹ Drinker among men and women separately,³⁹ and Western among women only⁴¹) reported in 2 case–control studies were not significantly associated with pancreatic cancer risk. None of the unfavorable dietary patterns in the cohort studies were associated with pancreatic cancer risk (Figure 2).

Figure 2.

Forest plot of the sex-specific and overall relative risk of pancreatic cancer for the highest vs the lowest category of scores of unfavorable data-driven dietary patterns.

In 3 case–control studies,^39–41 4 unfavorable data-driven dietary patterns were examined in relation to pancreatic cancer risk, with the estimated RRs for the highest- to the lowest-scoring groups ranging from 0.90 for the Western pattern among women⁴¹ to 2.40 for the Western pattern among men.⁴¹ In a large population-based Canadian case–control study, the Western pattern and the Drinker pattern were derived by factor analysis in men and women separately. Neither pattern was associated with pancreatic cancer risk among men or women after controlling for confounders.³⁹ In another Italian hospital-based case–control study, a significantly increased risk of pancreatic cancer was associated with higher scores for the Starch Rich and Animal Products patterns in the total population (Starch Rich: OR_{Q4 vs Q1} = 1.69; 95%CI, 1.02–2.79; P trend = 0.06; Animal Products: OR_{Q4 vs Q1} = 2.03; 95%CI, 1.29–3.19; P trend = 0.0008).⁴⁰ Chan et al.⁴¹ conducted a large US population-based case–control study in which the Western and Prudent patterns were derived separately for men and women using principal component factor analysis. They identified a significant positive association for Western diet among men only (OR_{Q5 vs Q1} = 2.40; 95%CI, 1.30–4.20; P trend = 0.008). In the same study, researchers also examined the overall dietary pattern score, defined as the sum of an individual’s quintile assignment of the ordinal variables of the Western dietary pattern (participants were assigned value of 1, 2, 3,4, or 5 if in quintile 1, 2, 3, 4, or 5 of the Western dietary pattern, respectively) and Prudent dietary pattern scores (participants were assigned value of −1, −2, −3, −4, or −5 if in quintile 1, 2, 3, 4, or 5 of the Prudent dietary pattern, respectively). An overall dietary pattern score of ≥3 vs ≤−3 (ie, a higher score indicates a more Western diet, while a lower score indicates a more prudent diet) was found to be associated with a 3-fold elevated risk of pancreatic cancer among men only (OR = 3.00; 95%CI, 1.60–5.50; P trend = 0.002).⁴¹ Effect modification by smoking status suggested that ever-smoking women had an increased risk of pancreatic cancer associated with a Western diet (OR_{Q5 vs Q1} = 2.30; 95%CI, 1.00–5.20; P trend = 0.11), but among women who never smoked, the Western diet was inversely associated with pancreatic cancer risk (OR_{Q5 vs Q1} = 0.38; 95%CI, 0.16–0.90; P trend = 0.05; P interaction = 0.07).⁴¹

No unfavorable data-driven dietary patterns were associated with risk of pancreatic cancer in cohort studies. Michaud et al.⁴² identified a Western pattern in large separate cohorts of American women (ie, the Nurses’ Health Study [NHS]) and men (ie, the Health Professionals Follow-Up Study [HPFS]). After adjusting for confounders, no association between Western pattern score and pancreatic cancer risk was observed in the male or the female cohort. After the NHS and HPFS cohorts were pooled, the Western pattern was still not related to pancreatic cancer risk (RR_{Q5 vs Q1} = 0.91; 95%CI, 0.57–1.47; P trend = 0.53).⁴² Inoue-Choi et al.⁴³ used data from postmenopausal women in the Iowa Women’s Health Study to derive a High Sweet pattern (component food items were not reported in the study) and found no association with pancreatic cancer risk in this population.

Favorable data-driven dietary patterns

Eight studies (3 case–control studies^39–41 and 5 cohort studies^42–44) examined the associations between favorable data-driven dietary patterns and pancreatic cancer risk, reporting inconsistent findings. The sex-specific and overall RRs of pancreatic cancer risk reported for individuals in the highest category of dietary pattern scores compared with the lowest category ranged from 0.51⁴¹ to 1.88.⁴² In 3 case–control studies, 3 favorable data-driven dietary patterns (Fruits and Vegetables among men only,³⁹ Vitamins and Fiber among all men and women,⁴⁰ and Prudent among men and women separately⁴¹) were significantly associated with reduced risk of pancreatic cancer. Other favorable dietary patterns (Fruits and Vegetables among women only³⁹ and Unsaturated Fats among all men and women⁴⁰) were not related to risk of pancreatic cancer. Overall, none of the favorable dietary patterns in cohort studies were associated with risk of pancreatic cancer except for a Prudent pattern identified in the HPFS⁴² (Figure 3).

Figure 3.

Forest plot of the sex-specific and overall relative risk of pancreatic cancer for the highest vs the lowest category of scores of favorable data-driven dietary patterns. Abbreviations: EPIC, European Prospective Investigation into Cancer and Nutrition; MEC, Multiethnic Cohort Study.

Three case–control studies reported the associations between pancreatic cancer risk and 4 favorable dietary patterns derived using factor analysis³⁹ or principal component factor analysis.^40,41 A significant inverse association between pancreatic cancer and a Fruits and Vegetables pattern was observed among men (OR_{Q4 vs Q1} = 0.55; 95%CI, 0.32–0.93; P trend < 0.01) but not among women in the Canadian case–control study.³⁹ The Vitamins and Fiber pattern identified on the basis of nutrient data from the Italian case–control study was significantly inversely associated with pancreatic cancer risk among men and women combined (OR_{Q4 vs Q1} = 0.55; 95%CI, 0.35–0.86; P trend = 0.0035). However, in the same study, the Unsaturated Fats pattern was not associated with pancreatic cancer risk.⁴⁰ In the US case–control study, a prudent diet was associated with an approximately 50% reduced risk of pancreatic cancer when the highest quintile was compared with the lowest quintile in the multivariable analyses of men and women combined.⁴¹

Five cohort studies reported associations between favorable dietary patterns and risk of pancreatic cancer, with estimated RRs ranging from 0.85^43,44 to 1.88⁴² for the highest vs the lowest category of dietary pattern scores. The only favorable dietary pattern associated with pancreatic cancer risk was the Prudent pattern identified by principal component factor analysis in the HPFS.⁴² A statistically significant 88% increased risk of pancreatic cancer was found for men in the highest quintile of prudent diet consumption, although the linear trend was not significant (RR_{Q5 vs Q1} = 1.88; 95%CI, 1.06–3.32; P trend = 0.09). However, after examining the relationship between specific food components that contributed substantially to the Prudent dietary pattern and the risk of pancreatic cancer in the HPFS, no individual food was found to substantially increase the risk of pancreatic cancer.⁴² A secondary analysis using cumulatively updated dietary exposure from multiple follow-up questionnaires rather than just baseline measures yielded an attenuation of the association with a prudent diet among men in the HPFS (RR _{Q5 vs Q1} = 1.67; 95%CI, 0.98–2.86). Residual or unmeasured confounding, measurement error, and the relatively small number of pancreatic cancer cases (n = 185) in the HPFS may be factors that contributed to this unexpected positive association among men.⁴² The Prudent dietary pattern was not associated with pancreatic cancer risk after data from the NHS and HPFS were pooled (RR_{Q5 vs Q1} = 1.32; 95%CI, 0.66–2.63; P trend = 0.83).⁴² In the large US-based Multiethnic Cohort (MEC) Study, Nöthlings et al.⁴⁴ used reduced-rank regression to identify 2 simplified food patterns (ie, Simplified Food Item pattern and Simplified Food Group pattern) predictive of intake of 3 flavonols (ie, quercetin, kaempferol, and myricetin). Neither of the simplified food patterns was significantly associated with pancreatic cancer risk in the overall MEC cohort.⁴⁴ However, stratification of the association by smoking status revealed a significant inverse relationship for the Simplified Food Item pattern among current smokers in the MEC cohort (RR_{Q5 vs Q1} = 0.48; 95%CI, 0.25–0.92; P trend = 0.02) but not for the Simplified Food Group pattern (RR_{Q5 vs Q1} = 0.60; 95%CI, 0.32–1.11; P trend = 0.07).⁴⁴ The derived Simplified Food Group pattern from the MEC cohort was examined in 424 978 European participants in the European Prospective Investigation into Cancer and Nutrition (EPIC) Study, but the inverse association among current smokers was not reproduced.⁴⁴ Stronger associations among smokers have been explained by the ability of flavonol to modulate enzyme activities in the bioactivation of chemical carcinogens that were involved in cigarette smoking.⁴⁵ In the Iowa Women’s Health Study, none of the 5 favorable dietary patterns—High Fiber, High Vegetable, High Fruit, Low Fat, and Mediterranean—was associated with risk of pancreatic cancer.⁴³

A priori dietary patterns

Eight studies (5 case–control studies^32–35 and 3 cohort studies^36–38) addressed the association between a priori dietary patterns and risk of pancreatic cancer. Four studies (2 case–control¹⁸ and 2 cohort^36,37) investigated the association between Mediterranean diet scores and risk of pancreatic cancer, 2 studies (both case–control) examined associations between Dietary Inflammatory Index scores and risk of pancreatic cancer,^33,34 1 study (case–control) examined associations between risk of pancreatic cancer and 3 dietary indices that reflected total dietary antioxidant capacity,³⁵ and another cohort study investigated associations between the Healthy Eating Index-2005 (HEI-2005) scores and risk of pancreatic cancer.³⁸ All sex-specific and overall associations reached or almost reached statistical significance, with the adjusted RRs ranging from 0.27³³ to 0.98³,⁶ for individuals who had the best diet quality compared with those who had the worst diet quality (Figure 4).

Figure 4.

Forest plot of the sex-specific and overall relative risk of pancreatic cancer for the highest vs the lowest category of scores of a priori dietary patterns. Abbreviations: aMDS, alternate Mediterranean diet score; DII, Dietary Inflammatory Index; FRAP, ferric-reducing antioxidant power; HEI-2005, Healthy Eating Index-2005; MAI, Mediterranean Adequacy Index; MDP, Mediterranean Dietary Pattern Adherence Index; MDS, Mediterranean diet score; TEAC, Trolox equivalent antioxidant capacity; TRAP, total radical-trapping antioxidant parameter.

The Mediterranean diet score measures the degree of adherence to a traditional Mediterranean diet.⁴⁶ It includes 9 common characteristics of a Mediterranean diet, as suggested by Trichopoulou et al.,⁴⁷ with scores ranging between 0 for no adherence and 9 for maximum adherence. Two case–control studies³² and 2 cohort studies^36,37 reported associations between Mediterranean diet−related scores and risk of pancreatic cancer, with sex-specific and overall adjusted RRs ranging from 0.44 ³² to 0.98³,⁶ for individuals in the highest compared with the lowest score group.

Stronger associations were observed in case–control studies than in cohort studies. Bosetti et al.³² examined the association between Mediterranean diet score and pancreatic cancer in 2 Italian case–control studies, separately and combined. A significant reduction in pancreatic cancer risk associated with increased Mediterranean diet score was observed in both studies and in combined analyses. Some evidence of significant interaction by education level and history of diabetes suggested that the inverse relationship was stronger in individuals with a lower education level and in those with no history of diabetes as compared with their counterparts.³² The Mediterranean Dietary Pattern Adherence Index and the Mediterranean Adequacy Index were further applied in the second case–control study in the same report.³² The Mediterranean Dietary Pattern Adherence Index is a standardized Mediterranean diet score that ranges from 0% for low adherence to 100% for maximum adherence.⁴⁸ The Mediterranean Adequacy Index assesses the proportion of Mediterranean diet in an individual’s total diet, and the score ranged from 0.33 to 14.18 in the study.^32,49 Results showed both the Mediterranean Dietary Pattern Adherence Index and Mediterranean Adequacy Index were inversely associated with pancreatic cancer risk, with a respective 56% and 32% risk reduction among persons in the highest quintile compared with those in the lowest quintile.³² Jiao et al.³⁶ calculated a no-alcohol alternate Mediterranean diet score in the National Institutes of Health-American Association of Retired Persons (NIH-AARP) Diet and Health Study and treated alcohol as a separate factor in the analysis. The no-alcohol alternate Mediterranean diet score was derived after removing the alcohol component from the alternate Mediterranean diet score, which measured adherence to the Mediterranean diet in an American population.⁵⁰ The no-alcohol alternate Mediterranean diet score included 8 components, and individuals received a score from 0 to 8 (minimum to maximum adherence).³⁶ Compared with an unhealthy dietary quality (scores from 0 to 4), a healthy dietary quality (scores above 4) was associated with a nonsignificant reduced risk for men and women, both separately and combined, although the association was slightly stronger for men than for women (OR = 0.89; 95%CI, 0.76–1.05 for men; and OR = 0.98; 95%CI, 0.79–1.21 for women).³⁶ A refined version of the Mediterranean diet score, which changed the traditional Mediterranean diet score by adding intake of polyunsaturated fat to monounsaturated fat as the numerator and dividing by saturated fat consumption and replacing whole grain with whole-grain cereal, was investigated in relation to the risk of pancreatic cancer mortality in a Swedish cohort.³⁷ A higher level of the refined Mediterranean diet score (score > 4) compared with the lower level was associated with reduced pancreatic cancer mortality in men (HR = 0.82; 95%CI, 0.68–0.99; P < 0.05) and in women, but with borderline significance (HR = 0.83; 95%CI, 0.69–1.00; P = 0.06). The results were confirmed when the refined version of the Mediterranean diet score replaced total alcohol intake with wine.³⁷

The Dietary Inflammatory Index was developed to assess the inflammatory potential of an individual’s diet. A higher (ie, more positive) Dietary Inflammatory Index score indicates a more proinflammatory diet. A lower (ie, more negative) score indicates a more anti-inflammatory diet.⁵¹ Details of the development and construct validation of the Dietary Inflammatory Index have been described previously.^51–55 The relationship between the Dietary Inflammatory Index and risk of pancreatic cancer was first investigated in 2 case–control studies included in this review, with 1 conducted in the United States³⁴ and the other in Italy.³³ Both studies found a more than 2-fold significantly increased risk of pancreatic cancer in the highest compared with the lowest quintile of the Dietary Inflammatory Index scores. However, when stratified by sex, the Italian case–control study found a significant positive association among women but not among men,³³ whereas Antwi et al.³⁴ found statistically positive associations among both men and women in the US study and found a stronger association among men than among women. Evidence of effect modifications by smoking status and body mass index was documented in the Italian case–control study: a significant positive association was observed among never and past smokers but not among current smokers and among normal and overweight but not among obese individuals, respectively.³³ A subgroup analysis by pancreatic cancer severity conducted in the US study showed significant associations between having a higher Dietary Inflammatory Index score and presenting with resectable (OR_{Q5 vs Q1} = 2.36; 95%CI, 1.48–3.75), locally advanced (OR_{Q5 vs Q1} = 2.21; 95%CI, 1.41–3.46), or metastatic tumor (OR_{Q5 vs Q1} = 3.13; 95%CI,1.85–5.29).³⁴

In the case–control study by Lucas et al.,³⁵ 3 indices that measured dietary antioxidant potential were investigated for their respective association with pancreatic cancer development: Trolox equivalent antioxidant capacity (TEAC), total radical-trapping antioxidant parameter (TRAP), and ferric-reducing antioxidant power (FRAP). The TEAC and FRAP indices measure the ability of antioxidants to scavenge the stable radical cation ABTS + (2,2′-azinobis [3-ethylbenzothiazoline-6-sulfonic acid]) and to reduce ferric ion to ferrous ion, respectively. The TRAP index measures the chain-breaking potential to reduce peroxyl radicals. Using the Italian food composition database, an ad hoc database was developed to calculate total antioxidant capacity for each of the 3 indices on the basis of experimental assessment of the food extracts.^56,57 Significant inverse associations were noted between TEAC and FRAP values and pancreatic cancer risk, and a higher TRAP value was associated with a nonsignificant reduced risk of pancreatic cancer (OR_{Q3 vs Q1} = 0.78; 95%CI, 0.49–1.24; P trend = 0.27).³⁵ The nonsignificant findings for TRAP could be explained by a greater influence of alcoholic beverage consumption on TRAP than on FRAP or TEAC,⁵⁸ and alcohol use is positively related to pancreatic cancer risk.⁵⁹

In another NIH-AARP Diet and Health Study, Arem et al.³⁸ calculated the HEI-2005 score for 537,218 men and women and assessed its association with pancreatic cancer risk. The HEI-2005 was developed to measure overall diet compliance with the Dietary Guidelines for Americans, 2005 (https://health.gov/dietaryguidelines/dga2005/document/), with scores ranging from 0 (to indicate no guidelines were met) to 100 (to indicate all guidelines, including components, were met).⁶⁰ Comparison of the highest with the lowest quintile of HEI-2005 scores showed a significantly reduced pancreatic cancer risk overall and among men only, but not among women.³⁸ Analysis stratified by body mass index showed a statistically significant interaction in men only (P interaction = 0.03), and overweight/obese men had a significantly reduced risk (HR_{Q5 vs Q1} = 0.72; 95%CI, 0.59–0.88, P trend < 0.001), but no association was observed for normal-weight men (HR_{Q5 vs Q1} = 1.21; 95%CI, 0.88–1.67; P trend = 0.23).³⁸

DISCUSSION

This comprehensive systematic review was performed in accordance with PRISMA guidelines to summarize the published epidemiological evidence on dietary patterns and risk of pancreatic cancer. The results for associations between data-driven dietary patterns and pancreatic cancer risk were inconsistent, with significant associations observed largely in case–control studies and, generally, no associations documented in cohort studies. In case–control studies, dietary patterns characterized by high consumption of fruit, vegetables, whole grains, white meat, fiber, low-fat dairy products, folate, and antioxidant nutrients such as vitamin C and beta carotene were associated with a lower risk of pancreatic cancer. In contrast, patterns characterized by greater intake of animal-source foods and associated nutrients, starch, or other typical Western-type foods such as refined grains, potatoes, high-fat dairy products, sweets and desserts, beer, and coffee were associated with an increased risk of pancreatic cancer. Results were more consistent for a priori dietary patterns, which suggested that better diet quality characterized by greater adherence to the Mediterranean diet, the HEI-2005, or a diet with lower inflammatory potential or higher antioxidant capacity was associated with lower risk of pancreatic cancer. Overall, the association between dietary patterns and risk of pancreatic cancer in the present systematic review was stronger in case–control studies than in cohort studies and was stronger among men than among women.

A recently published meta-analysis on dietary patterns and risk of pancreatic cancer incorporated 32 epidemiological studies published up to May 2016 that targeted healthy patterns (ie, total vegetable and fruit intake, Prudent pattern, HEI-2005, and Mediterranean diet), Western-type patterns (ie, total meat, red meat, and patterns characterized by Western-type foods), and Heavy Drinking and Light-Moderate Drinking patterns.⁶¹ This meta-analysis identified a pooled reduced risk of pancreatic cancer associated with healthy patterns (OR_{highest vs lowest category} = 0.86; 95%CI, 0.77–0.95; P = 0.004) and Light-Moderate Drinking patterns (OR_{highest vs lowest category} = 0.90; 95%CI, 0.83–0.98; P = 0.02) and a pooled increased risk for Western-type patterns (OR_{highest vs lowest category} = 1.24; 95%CI, 1.06–1.45; P = 0.008) and Heavy Drinking patterns (OR_{highest vs lowest category} = 1.29; 95%CI, 1.10–1.48; P = 0.002). Associations were stronger in case–control studies than in cohort studies.⁶¹ Unlike that meta-analysis, the present systematic review does not include studies that reported total vegetable and fruit intake, meat intake, or drinking patterns as exposures, but it does include several a priori and data-driven patterns that were not included in the meta-analysis.^{33–35,40,43,44} Despite including different individual studies, the present review also found stronger associations observed in case–control studies than in cohort studies, a decreased risk with healthier dietary patterns, and an increased risk with Western dietary patterns.

Eight studies in this review examined the association between data-driven dietary patterns and pancreatic cancer risk.^39–44 The dietary patterns derived by using data-driven methods are affected by the population under study because these patterns are developed on the basis of the analysis of the study population’s dietary data. Thus, data-driven dietary patterns are likely to differ between different populations, which partially explains the inconsistent findings observed for the association between unfavorable/favorable data-driven dietary patterns and pancreatic cancer risk. The subjectivity introduced at multiple levels of identifying data-driven dietary patterns, including the determination of food groups, the number of factors, and the treatment of input items (eg, whether to use grams, servings, percent energy, or standardized intake), is another factor that contributes to inconsistent results. In addition, data-driven outcome-independent dietary patterns are derived independent of their potential relationship to a health outcome. Consequently, the dietary patterns identified are not necessarily relevant to cancer risk, which may partially explain the lack of an association in some studies.^39,42,43 Even if the resulting patterns are significantly associated with pancreatic cancer risk, the interpretation does not mean that it represents the dietary pattern most associated with the disease. Therefore, the significant associations with pancreatic cancer risk observed in these studies need to be interpreted with caution.^39–41 Similar to the associations found with a priori patterns, associations with data-driven patterns were stronger and more often significant for the case–control studies than for cohort studies. The stronger associations for the case–control studies might be due to biases related to the study design, including research recall, selection of the controls, and reverse causation. These biases may lead to differential misclassification of diet in cases and controls and subsequent overestimation of effects. Moreover, case–control studies of pancreatic cancer are especially prone to biases because of the high and rapid fatality rates of this malignancy, which in turn will produce more information bias in cases than in controls because of the frequent proxy responses used in cases. However, in this review, the use of proxy responses was reported in only 1 case–control study.³⁹

Significant findings for data-driven dietary patterns showed that dietary patterns comprised of animal foods and associated nutrients or other typical Western-type foods elevated the risk of pancreatic cancer. In contrast, dietary patterns characterized by high consumption of plant-based foods, whole grains, white meat, fiber, and low-fat dairy products were associated with reduced risk of pancreatic cancer. These significant findings, which were documented mostly in case–control studies, were consistent with previous findings from case–control studies indicating that certain individual food groups or components were associated with risk of pancreatic cancer. These include red and processed meat,^8,9,62,63 dietary fat,^63–66 cholesterol,^67–71 carbohydrates,^67,72,73 animal protein,^63,74 fruits and vegetables,^17,62,75 fiber,¹⁸ whole grains,⁷⁶ white meat,^8,63 antioxidants,^13,77–81 and folate.^79,82,83 Males had a stronger positive association for the Western pattern⁴¹ and a stronger inverse association for the Fruits and Vegetables pattern than females,³⁹ which was consistent with previously reported divergent associations between males and females and individual food groups such as red meat,^6,12 processed meat,^4,84 carbohydrate,⁸⁵ sweets and soft drinks,⁸⁶ and fruits and vegetables.⁸⁵ A mechanism was hypothesized for sex differences in associations between red meat and pancreatic cancer. Specifically, a chemical contributed primarily by red meat consumption (dietary Nɛ-[carboxymethyl] lysine glycation end products) was associated with a modestly increased risk of pancreatic cancer in men only.¹² Evidence showed there may be a threshold at which an increased risk of pancreatic cancer exists only at very high levels of red meat intake that, in most cases, only men would achieve.⁶ However, the mechanisms of the sex difference in the effect of overall dietary pattern on pancreatic cancer risk are still unknown. Further studies are warranted to verify and elucidate the underlying reasons for this difference.

In a priori dietary pattern analysis, the components of the pattern and how those components are scored are specified in advance, which allows researchers to define the scoring algorithm and calculate the overall score in the same way across studies, allowing for better comparison between different studies than in data-driven approaches.²⁸ Given the standardized assessment of a set of recommendations that a priori dietary patterns provide, consistent findings on a priori dietary patterns and health outcomes across different populations may be interpreted as an indicator of an existing association, although these a priori patterns, like data-driven dietary patterns, are usually not specifically designed for the purpose of preventing diseases.²⁸ Four different a priori dietary patterns (the Mediterranean diet and its related versions, the HEI-2005, the Dietary Inflammatory Index, and 3 indices that measured dietary antioxidant potential) included in this review were examined for their association with pancreatic cancer risk.^32–38 The Mediterranean diet score and the HEI-2005 are calculated on the basis of many similar components, including the adequate consumption of plant-based foods, fresh fruit, grains, fish, and healthy oils and the relatively low intake of meat, saturated fat, and high-fat dairy products.^46,60 The small difference lies in the HEI-2005 recommendations for lean meat and low-fat dairy products and the avoidance of alcohol intake, while the Mediterranean diet score regards all meat and dairy products as unhealthy components but recommends moderate alcohol intake, mainly in the form of wine.^46,60 The potential beneficial effect of Mediterranean diet scores and HEI-2005 scores on pancreatic cancer risk, as also seen for other cancers,^87–97 has been explained by the strong antioxidant and anti-inflammatory properties of the diets on which these scores are based, owing to healthy fatty acid profiles, high fiber content, high antioxidant content, phytochemicals from vegetables and fruits, and low intakes of saturated fat, alcohol, and added sugar.^60,98–102 It is well known that antioxidant and anti-inflammatory characteristics of diet have important anticancer effects through mechanisms involving reduction in oxidative stress and damage, reduction in insulin level and insulin-like growth factor, improvement of insulin sensitivity, increased antimutagens and inhibition of tumor initiation and promotion, stimulation of immune function, and induction of tumor suppressor gene expression.^99,103,104 Therefore, the inverse associations observed between both Mediterranean dietary pattern and HEI-2005 and pancreatic cancer risk may reflect the protective effect of diets with low inflammatory potential and high antioxidant capacity against pancreatic cancer development, which is consistent with the inverse associations observed with the Dietary Inflammatory Index and 3 dietary antioxidant indices. Similar to findings with data-driven dietary patterns, a stronger association was observed among case–control studies than among cohort studies and in males than in females.

This systematic review provides a comprehensive qualitative summary of the published epidemiological evidence on the association between dietary patterns and risk of pancreatic cancer. The adequate number of case–control studies and cohort studies included in this review, with a substantial number of total participants and pancreatic cancer cases, allowed the results to be summarized separately by study design. Several studies in the review reported sex-specific and/or overall associations, which made it possible to compare strength of association by sex. Subsequently, due to the inherent differences in the a priori dietary patterns and data-driven dietary patterns, results were reported separately.

Several limitations should be noted. The data-driven patterns included in this review were derived from analysis of dietary data of different populations using various statistical methods, which made it difficult to make comparisons across studies. Both data-driven and a priori dietary patterns are susceptible to the limitation of subjectivity during the pattern construction, which could also contribute to the inconsistent results, especially in the analysis of data-driven dietary patterns. It should be noted that the dietary assessment tools used, the number of food items included in FFQs, the methods of dietary assessment, the period of dietary assessment, the approaches to ascertaining pancreatic cancer outcome, and the covariate adjustment varied between the included studies, all of which constitute other potential reasons for incomparable and inconsistent results. Information on FFQ relative validity and reproducibility was available for 12 studies in this review, but results varied. In addition, neither the data-driven nor the a priori dietary patterns were designed to target a specific disease, so the significant findings may not necessarily explain the risk of pancreatic cancer. Each included individual study also had limitations, such as the potential for recall bias and selection bias typically seen in case–control studies, information bias during data collection, measurement error inherent in FFQs, and residual or unmeasured confounding. Diet was subject to change in longitudinal studies, but no study measured diet at multiple time points, which may have led to nondifferential misclassification of exposure. Moreover, the diverse dietary patterns reported with various food or nutrient components limited the ability to conduct meta-analyses to quantify the effect of associations with pancreatic cancer.

CONCLUSION

The present review found inconsistent results for associations between data-driven dietary patterns and pancreatic cancer risk, with significant associations observed largely in case–control studies and generally no associations documented in cohort studies. The discrepancy in findings between the 2 study designs could be due to the recall bias and selection bias inherent in case–control studies. Significant findings for data-driven dietary patterns showed that dietary patterns characterized by high consumption of animal foods and associated nutrients, starch, or other typical Western-type foods elevated the risk of pancreatic cancer, and dietary patterns rich in plant-based foods, whole grains, white meat, fiber, and associated antioxidants were associated with reduced risk of pancreatic cancer. Results for a priori dietary patterns were more consistent, suggesting that better diet quality, as represented by greater adherence to the Mediterranean diet, the HEI-2005, or a diet with lower inflammatory potential or better antioxidant capacity, was associated with reduced risk of pancreatic cancer. Overall, the associations between dietary patterns and risk of pancreatic cancer were stronger in case–control studies than in cohort studies and were stronger among men than among women. Future research on this topic should consider assessing diet using repeated dietary measurements to reduce measurement error. Additionally, more studies that examine effect modifications by important lifestyle factors are warranted to provide evidence for summarizing results by these factors in future reviews. Further studies also are warranted to verify and elucidate the underlying reasons for the sex differences in the association between dietary pattern and pancreatic cancer risk.