Affiliations of authors: D. S. Michaud, Nutritional Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD; S. Liu, Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, and Department of Nutrition, Harvard School of Public Health, Boston; E. Giovannucci, W. C. Willett, Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, and Departments of Nutrition and Epidemiology, Harvard School of Public Health; G. A. Colditz, Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, and Department of Epidemiology, Harvard School of Public Health; C. S. Fuchs, Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, and Department of Adult Oncology, Dana-Farber Cancer Institute, Boston.
Correspondence to: Dominique Michaud, Sc.D., National Cancer Institute, 6120 Executive Blvd., EPS Rm. 3032, Rockville, MD 20852 (e-mail: michaudd{at}mail.nih.gov).
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ABSTRACT |
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INTRODUCTION |
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Whether diabetes mellitus is a consequence or a cause of pancreatic cancer has been a longstanding debate, but recent reviews favor a causal association (3,4). In a meta-analysis of epidemiologic studies, diabetes diagnosed 5 or more years prior to cancer detection was associated with a twofold increase in risk of pancreatic cancer (5), and in a recent publication (6), a 50% increase was observed for diabetes diagnosed 10 or more years prior to cancer detection. In numerous studies (711), overweight individuals were consistently at higher risk of pancreatic cancer compared with leaner individuals. The associations between body weight and diabetes suggest that insulin resistance may play a role in pancreatic carcinogenesis. This hypothesis was supported by a recent study (12) in which a direct link was reported between postload plasma glucose levels and pancreatic cancer risk.
Much effort has been invested in understanding how dietary factors affect postprandial glucose levels, given the direct implications for diabetics. More recently, epidemiologic studies (1317) have examined how these glycemic measures can be applied to long-term dietary intakes. Studies (1820) indicate that estimates of dietary glycemic load (a quantitative measure of glycemic effect) can reliably predict circulating triglycerides and high-density lipoprotein levels. Glycemic load has been related to the risk of diabetes and heart disease in several (1315), but not all (16,17), recent prospective studies.
Given that recent studies on pancreatic cancer suggest that glucose intolerance and insulin resistance may play a role in carcinogenesis, dietary factors that increase postprandial plasma glucose levels may have a direct impact on pancreatic cancer risk. Given that high glycemic index and glycemic load have been observed to be associated with the risk of diabetes, heart disease, and lipid levels in this cohort (13,18,21), we chose to examine these variables. The glycemic index reflects the glucose response of each unit of carbohydrate-containing foods and thus provides an indication of carbohydrate quality. The glycemic load (the glycemic index multiplied by the carbohydrate content) reflects both the quality and quantity of dietary carbohydrates consumed. In addition, intake of simple sugars such as sucrose and fructose can also predict postprandial glucose levels (22). We examined glycemic index, glycemic load, sucrose, fructose, and carbohydrate intakes in relation to the risk of pancreatic cancer in a large prospective cohort of women with 18 years of follow-up.
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SUBJECTS AND METHODS |
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The Nurses' Health Study (NHS) was initiated in 1976 when 121 700 female registered nurses aged 3055 years responded to a mailed questionnaire with detailed information on individual characteristics and habits. Important changes in habits (e.g., smoking, vitamin use, medication use, exercise), other factors (e.g., menopausal status, blood pressure, family history of common diseases), and disease onset were updated biennially by using mailed questionnaires. In 1980, 98 462 of the participants returned a dietary questionnaire. Most of the deaths in this cohort were reported by family members or by the postal service in response to the follow-up questionnaires. In addition, the National Death Index (NDI) was searched for nonrespondents; this method has been shown to have a sensitivity of 98% (i.e., the NDI did not identify 2% of deaths) (23). This study was approved by the Human Research Committee at Brigham and Women's Hospital.
After excluding participants with 10 or more blank items on the dietary questionnaire, with an implausibly high or low caloric intake (<500 or >3500 kcal/day, respectively), or with a cancer diagnosis (other than nonmelanoma skin cancer) prior to baseline, 88 802 women were eligible for analysis.
Dietary Assessment
A 61-item food-frequency questionnaire (FFQ) was mailed to all study participants in 1980. To maximize statistical power, all eligible participants who returned the 1980 baseline questionnaire were included in the analysis. On this questionnaire, participants were asked to report their average frequency of intake over the previous year for a specified serving size of each food. Individual nutrient intakes were calculated by multiplying the frequency of each food consumed by the nutrient content of the specified portion size [obtained from the U.S. Department of Agriculture (24) and supplemented with information from manufacturers] and then summing the contributions from all foods.
The glycemic index is based on the postprandial blood glucose response compared with the glucose response to a reference food. Glycemic index values for foods that appear in the food-frequency questionnaire were obtained either from published estimates (25) or from direct testing of food items at the Nutrition Center of the University of Toronto (provided by D. Jenkins). The glycemic index value is calculated by the following formula: ( incremental blood glucose area under the curve of test food/
incremental blood glucose area under the curve of reference food) x 100%. The glycemic index value for a meal containing mixed foods can be predicted as the weighted mean of the glycemic index values for each of the component foods (26,27).
Using these glycemic index values, we then calculated the average dietary glycemic load (GL) during the past year for each participant by multiplying the carbohydrate content (grams per serving) for each food by its glycemic index value, multiplying that product by the frequency of consumption (servings of that food per day), and summing values for all food items reported:
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Each unit of GL represents the equivalent of 1 g of carbohydrate from white bread. In addition, the overall dietary glycemic index was calculated by dividing GL by the total amount of carbohydrate; the resulting value represents the overall quality of carbohydrate intake for each participant.
In a validity study of 173 women, an FFQ was compared with four 1-week diet records. For individual food items that have high glycemic index values, correlation coefficients between the average intake assessed by two 1-week diet records completed 6 months apart and the FFQ were as follows: 0.71 for white bread, 0.77 for dark bread, 0.66 for potatoes, 0.84 for orange or grapefruit juice, and 0.56 for noncarbonated fruit drinks (includes fruit-flavored punch) (28). Correlation coefficients for total carbohydrate and sucrose were 0.45 and 0.54, respectively, when comparing two 1-week diet records and the FFQ in the same validation study of women (29).
Assessment of Nondietary Factors
Height, current weight, and smoking history (including time since quitting for past smokers) were initially reported at baseline. During follow-up, data on current weight and smoking status were obtained from the biennial mailed questionnaires. We estimated body mass index (BMI) from weight and height (kg/height in meters2), as a measure of total adiposity. Participants were asked about history of diabetes at baseline and in all subsequent questionnaires. In 1982, and biennially thereafter, participants were asked about their history of cholecystectomy. For physical activity, we derived a score on the basis of questions asked in the 1980 questionnaire ("At least once a week, do you engage in any regular activity similar to brisk walking, jogging, bicycling, etc., long enough to break a sweat?" "If yes, how many times per week?" "What activity is this?"). The physical activity variable from the 1980 questionnaire has been shown to predict the risk of non-insulin-dependent diabetes mellitus in this cohort of women (30).
Identification of Pancreatic Cancer Case Subjects
Participants were asked to report specified medical conditions, including cancers, that were diagnosed in the 2-year period between each follow-up questionnaire. Whenever a participant (or next-of-kin for decedents) reported a diagnosis of pancreatic cancer, we asked for permission to obtain related medical records or pathology reports. If permission to obtain records was denied, we attempted to confirm the self-reported cancer with an additional letter or phone call to the participant. If the primary cause (or secondary cause) of death as reported by a death certificate was a previously unreported pancreatic cancer case, we contacted a family member to obtain permission to retrieve medical records or at least to confirm the diagnosis of pancreatic cancer. In the NHS, 180 confirmed incident pancreatic cancer case subjects, diagnosed between the date of return of the questionnaire in 1980 and May 31, 1998, were available for the dietary analyses.
Statistical Analysis
We computed person-time of follow-up for each participant from the return date of the baseline questionnaire to the date of pancreatic cancer diagnosis, death from any cause, or the end of follow-up (May 31, 1998), whichever came first. Incidence rates of pancreatic cancer were calculated by dividing the number of incident cases by the number of person-years in each category of dietary exposure. We computed the relative risk (RR) for each of the upper categories by dividing the rates in these categories by the rate in the lowest category.
RRs adjusted for potential confounders were estimated by using Cox proportional hazards models stratified on age in years. The assumptions of proportionality were satisfied. In these models, cigarette smoking was categorized as follows [on the basis of a previous analysis of these cohorts (31)]: never smoker, quit 15 years ago, quit <15 years ago and smoked
25 pack-years in past 15 years, quit <15 years ago and smoked >25 pack-years in past 15 years, current smoker with
25 pack-years in past 15 years, or current smoker with >25 pack-years in past 15 years. In addition, we controlled for body mass index (<23, 2324.9, 2526.9, 2729.9,
30), height (quintiles), total energy intake (quintiles), physical activity (five categories), and history of diabetes and cholecystectomy (5,32,33). History of diabetes and cholecystectomy were updated every other year with data from the follow-up questionnaires. BMI was not updated in the main analyses because pancreatic cancer is frequently associated with profound weight loss, and our previous findings showed the strongest associations between BMI in 1976 (NHS cohort baseline) and pancreatic cancer risk. Although we examined dietary associations by creating quintiles of the dietary intakes in our main analysis, we used quartiles for the stratified analyses to avoid small numbers. All P values are based on two-sided tests. We performed tests for trend by assigning the median value to each category and modeling this variable as a continuous variable.
We performed additional analyses by using the 1984 dietary questionnaire (which contained 126 food items) as baseline, and we performed separate analyses by using cumulative updating of the dietary exposures with follow-up data for 1984, 1986, and 1990 (34).
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RESULTS |
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DISCUSSION |
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A number of previous epidemiologic studies have examined intake of carbohydrates in relation to pancreatic cancer; however, findings have been mixed. In a large pooled casecontrol study (35) of 802 case subjects and 1669 control subjects from five different countries (SEARCH [Surveillance of Environmental Aspects Related to Cancer in Humans] program), pancreatic cancer risk was statistically significantly higher among those individuals consuming a high carbohydrate diet (for highest to lowest quintile comparison: RR = 2.57, 95% CI = 1.64 to 4.03, after controlling for lifetime cigarette consumption). In a separate case-control study (36), strong associations with pancreatic cancer risk were reported for carbohydrate intake and for added sugar (i.e., sugar added to coffee, cereal, fruit, and other foods) among women only (highest to lowest tertile comparison: RR = 3.5, 95% CI = 1.4 to 8.5 and RR = 3.7, 95% CI = 1.5 to 9.1, respectively). Carbohydrate intake was not associated with the risk of pancreatic cancer in two other casecontrol studies (37,38) that were not included in the SEARCH study.
Because of high fatality rates, casecontrol studies examining risk factors of pancreatic cancer have often relied on proxy information for case subjects and are, consequently, particularly prone to error and biases. To our knowledge, no prospective study has examined associations between specific macronutrients and pancreatic cancer risk. To overcome some of the issues of unreliable information obtained from next-of-kin, a recent casecontrol study (8) relied solely on direct interviews to collect exposure data. In that study, an increase in total carbohydrate intake (as a percentage of total caloric intake) was associated with an increased risk of pancreatic cancer in women, but the association did not reach statistical significance.
Considerable evidence supports a role for insulin and insulin resistance in pancreatic cancer etiology in both animals and humans. In a recent study (39), pancreatic cancer was inhibited by the drug metformin, which reduces insulin resistance, in a hamster pancreatic adenocarcinoma model. Previous work (40) in the same hamster model demonstrated that pancreatic ductal cancers often arise from islet cells themselves or from some common progenitor cell that can give rise to both islets and duct cells. Because peripheral insulin resistance is associated with hyperactivity, and most probably the proliferation of islet cells, it may be involved in promoting pancreatic cancer.
We have previously demonstrated (18), in a subset of healthy women from the NHS, that our variable for glycemic load (estimated from the food-frequency questionnaires) can predict fasting plasma triacylglycerol and high-density lipoprotein (HDL) levels better than total carbohydrate intake. The association between triacylglycerol levels and glycemic load was even stronger among women with a BMI greater than 25 kg/m2 (18) than among women with a lower BMI, indicating that overweight women are particularly susceptible to the quality of the carbohydrates they consume, probably because of some degree of insulin resistance. In our analyses, pancreatic cancer risk increased more dramatically across quartiles of glycemic load intake among women with a BMI greater than or equal to 25 kg/m2 than among those with a BMI of less than 25 kg/m2.
Physical activity is another important factor that is known to modify insulin resistance (41). Therefore, like individuals with higher BMI, individuals who are inactive are likely to be more susceptible to the carbohydrate quality of foods they consume because of the strong insulin response to high glycemic foods. In our data, women who were sedentary and had high glycemic index and glycemic load intakes had elevated risks of pancreatic cancer, whereas active women did not have elevated risks.
In this cohort, carbohydrate intake was not associated with pancreatic cancer risk, and strata analyses were not always consistent with findings for glycemic load or index scores. For sucrose, which has an effect on postprandial glycemic response similar to that of white bread or potatoes (42), we observed associations that were consistent with the glycemic variables. The strongest risks for pancreatic cancer in this study were observed with fructose intake. Foods that contribute to dietary fructose (as a monosaccharide) include soda, punch, and fruit juices, which collectively account for a high percentage of dietary glycemic load. The association observed with fructose therefore supports a role for an effect of postprandial glycemic response. However, fructose intake may be related to pancreatic cancer via other mechanisms; in a recent study (43), fructose contributed directly to oxidative stress in hamster islet tumor cells. Although fructose intake may itself play an important role in the risk of pancreatic cancer, it may also be a marker of a high-sugar diet. More studies are needed to elucidate the precise role of fructose in pancreatic carcinogenesis.
We observed a weakened association when using a cumulative updating approach for the same dietary exposures. Cumulative updating, by integrating multiple dietary assessments, is generally thought to reduce measurement error and has been shown to strengthen dietary associations with heart disease endpoints in the Nurses' Health Study cohort (44). However, because cumulative updating incorporates recent measurement of dietary intakes, cumulative updating is more likely to attenuate associations that require long latency (induction) periods. Because cancer initiation and progression is slow and occurs over many decades, an earlier dietary assessment may better represent the 'relevant' diet, especially if changes have occurred over time. It is thus possible that the relevant time period for pancreatic cancer is many years prior to the detection of this disease (which occurs at very late stages). In this situation, updating dietary intake may lead to an attenuation of the effect of diet on pancreatic cancer risk.
The strengths of this study include a prospective design and detailed information on diet as well as potential risk factors of pancreatic cancer. The prospective design precluded recall bias and the need to use next-of-kin respondents. Moreover, because exposure data were collected before the diagnosis of any cases of pancreatic cancer, any error in recall would have attenuated rather than exaggerated a true association. Differential follow-up is unlikely to have made a material contribution to these findings, because follow-up was high (45).
Although the glycemic index is designed to reflect the postprandial glucose response of specific foods, an earlier study (46) suggested that the response may differ with the consumption of mixed meals. However, more recent work (47) has shown that the weighted average glycemic index of component foods provides an excellent estimate of the glycemic index of a meal. The dietary glycemic index has proven to be a strong predictor of several biomarkers (18) and to be independently associated with diabetes and coronary heart disease in the NHS cohort, where the FFQ was used to estimate glycemic index (13,14). Random misclassification due to eating mixed meals would underestimate a true association. Ultimately, an insulin index of foods may be a better measure of the adverse aspect of carbohydrate consumption, but data for this type of index are only now being developed (48).
In summary, the overall association between dietary glycemic load and pancreatic cancer risk failed to achieve statistical significance. However, the statistically significant influence of glycemic load on pancreatic cancer risk among overweight and sedentary individuals supports the hypothesis that abnormal glucose metabolism and states of relative hyperinsulinemia enhance pancreatic carcinogenesis.
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NOTES |
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REFERENCES |
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1 Cancer facts and figures 2002. Atlanta (GA): American Cancer Society, Inc.; 2002.
2 Ries LA, Eisner MP, Kosary CL, Hankey BF, Miller BA, Clegg L, et al., editors. SEER cancer statistics review, 19731999. Bethesda (MD): National Cancer Institute; 2002. [Last accessed: 7/26/02.] Also available at: http://seer.cancer.gov/csr/1973_1999/.
3 DeMeo MT. Pancreatic cancer and sugar diabetes. Nutr Rev 2001;59:1125.[Medline]
4 Fisher WE. Diabetes: risk factor for the development of pancreatic cancer or manifestation of the disease? World J Surg 2001;25:5038.[Medline]
5 Everhart J, Wright D. Diabetes mellitus as a risk factor for pancreatic cancer. A meta-analysis. JAMA 1995;273:16059.[Abstract]
6 Silverman DT. Risk factors for pancreatic cancer: a case-control study based on direct interviews. Teratog Carcinog Mutagen 2001;21:725.[Medline]
7 Ji BT, Hatch MC, Chow WH, McLaughlin JK, Dai Q, Howe GR, et al. Anthropometric and reproductive factors and the risk of pancreatic cancer: a case-control study in Shanghai, China. Int J Cancer 1996;66:4327.[Medline]
8 Silverman DT, Swanson CA, Gridley G, Wacholder S, Greenberg RS, Brown LM, et al. Dietary and nutritional factors and pancreatic cancer: a case-control study based on direct interviews. J Natl Cancer Inst
1998;90:17109.
9 Coughlin SS, Calle EE, Patel AV, Thun MJ. Predictors of pancreatic cancer mortality among a large cohort of United States adults. Cancer Causes Control 2000;11:91523.[Medline]
10 Friedman G, Van Den Eeden S. Risk factors for pancreatic cancer: an exploratory study. Int J Epidemiol 1993;22:307.[Abstract]
11 Moller H, Mellemgaard A, Lindvig K, Olsen JH, Miller H. Obesity and cancer risk: a Danish record-linkage study. Eur J Cancer 1994;30A:34450.
12 Gapstur SM, Gann PH, Lowe W, Liu K, Colangelo L, Dyer A. Abnormal glucose metabolism and pancreatic cancer mortality. JAMA
2000;283:25528.
13 Liu S, Willett WC, Stampfer MJ, Hu FB, Franz M, Sampson L, et al. A prospective study of dietary glycemic load, carbohydrate intake, and risk of coronary heart disease in US women. Am J Clin Nutr
2000;71:145561.
14 Salmeron J, Manson JE, Stampfer MJ, Colditz GA, Wing AL, Willett WC. Dietary fiber, glycemic load, and risk of non-insulin-dependent diabetes mellitus in women. JAMA 1997;277:4727.[Abstract]
15 Salmeron J, Ascherio A, Rimm EB, Colditz GA, Spiegelman D, Jenkins DJ, et al. Dietary fiber, glycemic load, and risk of NIDDM in men. Diabetes Care 1997;20:54550.[Abstract]
16 Meyer KA, Kushi LH, Jacobs DR Jr, Slavin J, Sellers TA, Folsom AR. Carbohydrates, dietary fiber, and incident type 2 diabetes in older women. Am J Clin Nutr
2000;71:92130.
17 van Dam RM, Visscher AW, Feskens EJ, Verhoef P, Kromhout D. Dietary glycemic index in relation to metabolic risk factors and incidence of coronary heart disease: the Zutphen Elderly Study. Eur J Clin Nutr 2000;54:72631.[Medline]
18 Liu S, Manson JE, Stampfer MJ, Holmes MD, Hu FB, Hankinson SE, et al. Dietary glycemic load assessed by food-frequency questionnaire in relation to plasma high-density-lipoprotein cholesterol and fasting plasma triacylglycerols in postmenopausal women. Am J Clin Nutr
2001;73:5606.
19 Miller JC. Importance of glycemic index in diabetes. Am J Clin Nutr 1994; 59(3 Suppl):747S52S.[Abstract]
20 Ford ES, Liu S. Glycemic index and serum high-density lipoprotein cholesterol concentration among US adults. Arch Intern Med
2001;161:5726.
21 Salmeron J, Manson JE, Stampfer MJ, Colditz GA, Wing AL, Willett WC. Dietary fiber, glycemic load, and risk of non-insulin-dependent diabetes mellitus in women. JAMA 1997;277:4727.[Abstract]
22 Daly ME, Vale C, Walker M, Alberti KG, Mathers JC. Dietary carbohydrates and insulin sensitivity: a review of the evidence and clinical implications. Am J Clin Nutr 1997;66:107285.[Abstract]
23 Rich-Edwards JW, Corsano KA, Stampfer MJ. Test of the National Death Index and Equifax Nationwide Death Search. Am J Epidemiol 1994;140:10169.[Abstract]
24 U.S. Department of Agriculture. Composition of foodsraw, processed, and prepared, 19631992. Agricultural Handbook No. 8 Series. Washington (DC): Government Printing Office; 1993.
25 Foster-Powell K, Miller JB. International tables of glycemic index. Am J Clin Nutr 1995;62:871S90S.[Abstract]
26 Wolever TM, Jenkins DJ. The use of the glycemic index in predicting the blood glucose response to mixed meals. Am J Clin Nutr 1986;43:16772.[Abstract]
27 Wolever TM, Jenkins DJ, Jenkins AL, Josse RG. The glycemic index: methodology and clinical implications. Am J Clin Nutr 1991;54:84654.[Abstract]
28 Salvini S, Hunter DJ, Sampson L, Stampfer MJ, Colditz GA, Rosner B, et al. Food-based validation of a dietary questionnaire: the effects of week-to-week variation in food consumption. Int J Epidemiol 1989;18:85867.[Abstract]
29 Willett WC, Sampson L, Stampfer MJ, Rosner B, Bain C, Witschi J, et al. Reproducibility and validity of a semiquantitative food frequency questionnaire. Am J Epidemiol 1985;122:5165.[Abstract]
30 Manson JE, Rimm EB, Stampfer MJ, Colditz GA, Willett WC, Krolewski AS, et al. A prospective study of physical activity and the incidence of non-insulin-dependent diabetes mellitus in women. Lancet 1991;338:7748.[Medline]
31 Fuchs C, Colditz G, Stampfer M, Giovannucci E, Hunter D, Rimm E, et al. A prospective study of cigarette smoking and the risk of pancreatic cancer. Arch Intern Med 1996;156:225560.[Abstract]
32 Silverman D, Schiffman M, Everhart J, Goldstein A, Lillemoe K, Swanson G, et al. Diabetes mellitus, other medical conditions and familial history of cancer as risk factors for pancreatic cancer. Br J Cancer 1999;80:18307.[Medline]
33 Chow WH, Johansen C, Gridley G, Mellemkjaer L, Olsen JH, Fraumeni JF Jr. Gallstones, cholecystectomy and risk of cancers of the liver, biliary tract and pancreas. Br J Cancer 1999;79:6404.[Medline]
34 Willett WC. Chapter 13: Issues in analysis and presentation of dietary data. In: Nutritional epidemiology. 2nd ed. New York (NY): Oxford University Press; 1998.
35 Howe GR, Ghadirian P, Bueno de Mesquita HB, Zatonski WA, Baghurst PA, Miller AB, et al. A collaborative case-control study of nutrient intake and pancreatic cancer within the search programme. Int J Cancer 1992;51:36572.[Medline]
36 Lyon JL, Slattery ML, Mahoney AW, Robison LM. Dietary intake as a risk factor for cancer of the exocrine pancreas. Cancer Epidemiol Biomarkers Prev 1993;2:5138.[Abstract]
37 Kalapothaki V, Tzonou A, Hsieh CC, Karakatsani A, Trichopoulou A, Toupadaki N, et al. Nutrient intake and cancer of the pancreas: a case-control study in Athens, Greece. Cancer Causes Control 1993;4:3839.[Medline]
38 Olsen GW, Mandel JS, Gibson RW, Wattenberg LW, Schuman LM. Nutrients and pancreatic cancer: a population-based case-control study. Cancer Causes Control 1991;2:2917.[Medline]
39 Schneider MB, Matsuzaki H, Haorah J, Ulrich A, Standop J, Ding XZ, et al. Prevention of pancreatic cancer induction in hamsters by metformin. Gastroenterology 2001;120:126370.[Medline]
40 Pour P. Islet cells as a component of pancreatic ductal neoplasms. I. Experimental study: ductular cells, including islet cell precursors, as primary progenitor cells of tumors. Am J Pathol 1978;90:295316.[Abstract]
41 Polonsky KS, Sturis J, Bell GI. Seminars in Medicine of the Beth Israel Hospital, Boston. Non-insulin-dependent diabetes mellitusa genetically programmed failure of the beta cell to compensate for insulin resistance. N Engl J Med
1996;334:77783.
42 Bantle JP. Clinical aspects of sucrose and fructose metabolism. Diabetes Care 1989;12:5661; discussion 812.[Abstract]
43 Suzuki K, Islam KN, Kaneto H, Ookawara T, Taniguchi N. The contribution of fructose and nitric oxide to oxidative stress in hamster islet tumor (HIT) cells through the inactivation of glutathione peroxidase. Electrophoresis 2000;21:2858.[Medline]
44 Hu FB, Stampfer MJ, Rimm E, Ascherio A, Rosner BA, Spiegelman D, et al. Dietary fat and coronary heart disease: a comparison of approaches for adjusting total energy intake and modeling repeated dietary measurements. Am J Epidemiol 1999;149:53140.[Abstract]
45 Stampfer MJ, Willett WC, Speizer FE, Dysert DC, Lipnick R, Rosner B, et al. Test of the National Death Index. Am J Epidemiol 1984;119:8379.[Medline]
46 Coulston AM, Hollenbeck CB, Swislocki AL, Reaven GM. Effect of source of dietary carbohydrate on plasma glucose and insulin responses to mixed meals in subjects with NIDDM. Diabetes Care 1987;10:395400.[Abstract]
47 Wolever TM, Bolognesi C. Prediction of glucose and insulin responses of normal subjects after consuming mixed meals varying in energy, protein, fat, carbohydrate and glycemic index. J Nutr 1996;126:280712.[Medline]
48 Holt SH, Miller JC, Petocz P. An insulin index of foods: the insulin demand generated by 1000-kJ portions of common foods. Am J Clin Nutr 1997;66:126476.[Abstract]
Manuscript received September 4, 2001; revised June 4, 2002; accepted July 17, 2002.
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