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Ni Z, Kundu P, McKean DF, Wheeler W, Albanes D, Andreotti G, Antwi SO, Arslan AA, Bamlet WR, Beane-Freeman LE, Berndt SI, Bracci PM, Brennan P, Buring JE, Chanock SJ, Gallinger S, Gaziano JM, Giles GG, Giovannucci EL, Goggins MG, Goodman PJ, Haiman CA, Hassan MM, Holly EA, Hung RJ, Katzke V, Kooperberg C, Kraft P, LeMarchand L, Li D, McCullough ML, Milne RL, Moore SC, Neale RE, Oberg AL, Patel AV, Peters U, Rabe KG, Risch HA, Shu XO, Smith-Byrne K, Visvanathan K, Wactawski-Wende J, White E, Wolpin BM, Yu H, Zeleniuch-Jacquotte A, Zheng W, Zhong J, Amundadottir LT, Stolzenberg-Solomon RZ, Klein AP. Genome-Wide Analysis to Assess if Heavy Alcohol Consumption Modifies the Association between SNPs and Pancreatic Cancer Risk. Cancer Epidemiol Biomarkers Prev 2024; 33:1229-1239. [PMID: 38869494 DOI: 10.1158/1055-9965.epi-24-0096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 04/03/2024] [Accepted: 06/10/2024] [Indexed: 06/14/2024] Open
Abstract
BACKGROUND Pancreatic cancer is a leading cause of cancer-related death globally. Risk factors for pancreatic cancer include common genetic variants and potentially heavy alcohol consumption. We assessed if genetic variants modify the association between heavy alcohol consumption and pancreatic cancer risk. METHODS We conducted a genome-wide interaction analysis of single-nucleotide polymorphisms (SNP) by heavy alcohol consumption (more than three drinks per day) for pancreatic cancer in European ancestry populations from genome-wide association studies. Our analysis included 3,707 cases and 4,167 controls from case-control studies and 1,098 cases and 1,162 controls from cohort studies. Fixed-effect meta-analyses were conducted. RESULTS A potential novel region of association on 10p11.22, lead SNP rs7898449 (interaction P value (Pinteraction) = 5.1 × 10-8 in the meta-analysis; Pinteraction = 2.1 × 10-9 in the case-control studies; Pinteraction = 0.91 in the cohort studies), was identified. An SNP correlated with this lead SNP is an expression quantitative trait locus for the neuropilin 1 gene. Of the 17 genomic regions with genome-wide significant evidence of association with pancreatic cancer in prior studies, we observed suggestive evidence that heavy alcohol consumption modified the association for one SNP near LINC00673, rs11655237 on 17q25.1 (Pinteraction = 0.004). CONCLUSIONS We identified a novel genomic region that may be associated with pancreatic cancer risk in conjunction with heavy alcohol consumption located near an expression quantitative trait locus for neuropilin 1, a protein that plays an important role in the development and progression of pancreatic cancer. IMPACT This work can provide insights into the etiology of pancreatic cancer, particularly in heavy drinkers.
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Affiliation(s)
- Zhanmo Ni
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Prosenjit Kundu
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - David F McKean
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, Maryland
| | | | - Demetrius Albanes
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Gabriella Andreotti
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Samuel O Antwi
- Department of Quantitative Health Sciences Research, Mayo Clinic College of Medicine, Jacksonville, Florida
| | - Alan A Arslan
- Department of Obstetrics and Gynecology, New York University School of Medicine, New York, New York
- Department of Population Health, New York University School of Medicine, New York, New York
- Department of Environmental Medicine, New York University School of Medicine, New York, New York
| | - William R Bamlet
- Department of Quantitative Health Sciences Research, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Laura E Beane-Freeman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Sonja I Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Paige M Bracci
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California
| | - Paul Brennan
- International Agency for Research on Cancer, Lyon, France
| | - Julie E Buring
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Steven Gallinger
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System and University of Toronto, Toronto, Canada
| | - J M Gaziano
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts
- Division of Aging, Brigham and Women's Hospital, Boston, Massachusetts
- Boston VA Healthcare System, Boston, Massachusetts
| | - Graham G Giles
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia
| | - Edward L Giovannucci
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Michael G Goggins
- Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Phyllis J Goodman
- SWOG Statistical Center, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Christopher A Haiman
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Manal M Hassan
- Department of Gastrointestinal Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Elizabeth A Holly
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California
| | - Rayjean J Hung
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System and University of Toronto, Toronto, Canada
| | - Verena Katzke
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Peter Kraft
- Trans-Divisional Research Program (TDRP), Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Loic LeMarchand
- Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii
| | - Donghui Li
- Department of Gastrointestinal Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas
| | | | - Roger L Milne
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia
| | - Steven C Moore
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Rachel E Neale
- Department of Population Health, QIMR Berghofer Medical Research Institute, Queensland, Australia
| | - Ann L Oberg
- Department of Quantitative Health Sciences Research, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Alpa V Patel
- Department of Population Science, American Cancer Society, Atlanta, Georgia
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Kari G Rabe
- Department of Quantitative Health Sciences Research, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Harvey A Risch
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, Connecticut
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Karl Smith-Byrne
- Cancer Epidemiology Unit, The Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Kala Visvanathan
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Jean Wactawski-Wende
- Department of Epidemiology and Environmental Health, University at Buffalo, Buffalo, New York
| | - Emily White
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington
- Department of Epidemiology, University of Washington, Seattle, Washington
| | - Brian M Wolpin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Herbert Yu
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii
| | - Anne Zeleniuch-Jacquotte
- Department of Population Health, New York University School of Medicine, New York, New York
- Perlmutter Cancer Center, New York University School of Medicine, New York, New York
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Jun Zhong
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Laufey T Amundadottir
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Rachael Z Stolzenberg-Solomon
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Alison P Klein
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, Maryland
- Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins School of Medicine, Baltimore, Maryland
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
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Liu J, Zhang YJ, Zhou J, Zhang ZJ, Wen Y. Pancreatic mucinous adenocarcinoma has different clinical characteristics and better prognosis compared to non-specific PDAC: A retrospective observational study. Heliyon 2024; 10:e30268. [PMID: 38720717 PMCID: PMC11076975 DOI: 10.1016/j.heliyon.2024.e30268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 04/11/2024] [Accepted: 04/23/2024] [Indexed: 05/12/2024] Open
Abstract
Background Pancreatic mucinous adenocarcinoma (PMAC) is a rare malignant tumour, and there is limited understanding of its epidemiology and prognosis. Initially, PMAC was considered a metastatic manifestation of other cancers; however, instances of non-metastatic PMAC have been documented through monitoring, epidemiological studies, and data from the Surveillance, Epidemiology, and End Results (SEER) database. Therefore, it is crucial to investigate the epidemiological characteristics of PMAC and discern the prognostic differences between PMAC and the more prevalent pancreatic ductal adenocarcinoma (PDAC). Methods The study used data from the SEER database from 2000 to 2018 to identify patients diagnosed with PMAC or PDAC. To ensure comparable demographic characteristics between PDAC and PMAC, propensity score matching was employed. Kaplan-Meier analysis was used to analyse overall survival (OS) and cancer-specific survival (CSS). Univariate and multivariate Cox regression analyses were used to determine independent risk factors influencing OS and CSS. Additionally, the construction and validation of risk-scoring models for OS and CSS were achieved through the least absolute shrinkage and selection operator-Cox regression technique. Results The SEER database included 84,857 patients with PDAC and 3345 patients with PMAC. Notably, significant distinctions were observed in the distribution of tumour sites, diagnosis time, use of radiotherapy and chemotherapy, tumour size, grading, and staging between the two groups. The prognosis exhibited notable improvement among married individuals, those receiving acceptable chemotherapy, and those with focal PMAC (p < 0.05). Conversely, patients with elevated log odds of positive lymph node scores or higher pathological grades in the pancreatic tail exhibited a more unfavourable prognosis (p < 0.05). The risk-scoring models for OS or CSS based on prognostic factors indicated a significantly lower prognosis for high-risk patients compared to their low-risk counterparts (area under the curve OS: 0.81-0.82, CSS: 0.80-0.82). Conclusion PMAC exhibits distinct clinical characteristics compared to non-specific PDAC. Leveraging these features and pathological classifications allows for accurate prognostication of PMAC or PDAC.
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Affiliation(s)
- Juan Liu
- Clinical Nursing Teaching and Research Section, Second Xiangya Hospital, Central South University, Hunan, China
| | - Yong-jing Zhang
- Department of Obstetrics and Gynecology, Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Jie Zhou
- Department of Breast and Thyroid Surgery, Yiyang Central Hospital, Yiyang, China
| | - Zi-jian Zhang
- Clinical Nursing Teaching and Research Section, Second Xiangya Hospital, Central South University, Hunan, China
| | - Yu Wen
- Clinical Nursing Teaching and Research Section, Second Xiangya Hospital, Central South University, Hunan, China
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Zhu H, Choi J, Kui N, Yang T, Wei P, Li D, Sun R. Identification of Pancreatic Cancer Germline Risk Variants With Effects That Are Modified by Smoking. JCO Precis Oncol 2024; 8:e2300355. [PMID: 38564682 DOI: 10.1200/po.23.00355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Revised: 12/08/2023] [Accepted: 02/08/2024] [Indexed: 04/04/2024] Open
Abstract
PURPOSE Pancreatic cancer (PC) is a deadly disease most often diagnosed in late stages. Identification of high-risk subjects could both contribute to preventative measures and help diagnose the disease at earlier timepoints. However, known risk factors, assessed independently, are currently insufficient for accurately stratifying patients. We use large-scale data from the UK Biobank (UKB) to identify genetic variant-smoking interaction effects and show their importance in risk assessment. METHODS We draw data from 15,086,830 genetic variants and 315,512 individuals in the UKB. There are 765 cases of PC. Crucially, robust resampling corrections are used to overcome well-known challenges in hypothesis testing for interactions. Replication analysis is conducted in two independent cohorts totaling 793 cases and 570 controls. Integration of functional annotation data and construction of polygenic risk scores (PRS) demonstrate the additional insight provided by interaction effects. RESULTS We identify the genome-wide significant variant rs77196339 on chromosome 2 (per minor allele odds ratio in never-smokers, 2.31 [95% CI, 1.69 to 3.15]; per minor allele odds ratio in ever-smokers, 0.53 [95% CI, 0.30 to 0.91]; P = 3.54 × 10-8) as well as eight other loci with suggestive evidence of interaction effects (P < 5 × 10-6). The rs77196339 region association is validated (P < .05) in the replication sample. PRS incorporating interaction effects show improved discriminatory ability over PRS of main effects alone. CONCLUSION This study of genome-wide germline variants identified smoking to modify the effect of rs77196339 on PC risk. Interactions between known risk factors can provide critical information for identifying high-risk subjects, given the relative inadequacy of models considering only main effects, as demonstrated in PRS. Further studies are necessary to advance toward comprehensive risk prediction approaches for PC.
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Affiliation(s)
- Huili Zhu
- Section of Hematology and Oncology, Department of Medicine, Baylor College of Medicine, Houston, TX
| | - Jaihee Choi
- Department of Statistics, Rice University, Houston, TX
| | - Naishu Kui
- Department of Biostatistics, University of Texas School of Public Health, Houston, TX
| | - Tianzhong Yang
- Division of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, MN
| | - Peng Wei
- Department of Biostatistics, Division of Basic Science, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Donghui Li
- Department of Gastrointestinal Medical Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Ryan Sun
- Department of Biostatistics, Division of Basic Science, The University of Texas MD Anderson Cancer Center, Houston, TX
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Zhao Q, Wang Y, Huo T, Li F, Zhou L, Feng Y, Wei Z. Exploration of Risk Factors for Pancreatic Cancer and Development of a Clinical High-Risk Group Rating Scale. J Clin Med 2023; 12:358. [PMID: 36615158 PMCID: PMC9821400 DOI: 10.3390/jcm12010358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Revised: 12/26/2022] [Accepted: 12/28/2022] [Indexed: 01/04/2023] Open
Abstract
(1) Background: There are few studies on people at high risk for clinical pancreatic cancer (PC). We aimed to explore the risk factors of PC and establish a scale for identifying high-risk populations of clinical PC. (2) Methods: We conducted a matched case-control study, retrospectively collecting demographic data and common clinical indicators from all subjects. Logistic regression was used to explore the risk factors of PC. Based on these factors, we created a high-risk population rating scale, which showed a higher diagnostic value. (3) Results: 385 cases and 428 controls were finally enrolled in our study. Multivariate analysis showed that body mass index (BMI) below 18.5 kg/m2 (OR 5.944, 95%CI: 1.759~20.084), smoking (OR 2.745, 95%CI: 1.555~4.844), new-onset diabetes (OR 5.239, 95%CI: 2.091~13.125), low high-density lipoprotein cholesterol (HDL-C) levels (OR 1.790, 95%CI: 1.044~3.069), and carbohydrate antigen 19-9 (CA19-9) levels no less than 35 U/mL (OR 160.328, 95%CI: 83.392~308.243) were associated with an increased risk of PC, whereas high total cholesterol (TC) levels were related to a lower risk of PC (OR 0.392, 95%CI: 0.211~0.730). The high-risk population scale, whose area under the receiver operating curve reached 0.948 (p < 0.001), showed a greater clinical diagnostic value. (4) Conclusions: Smoking history, new-onset diabetes, BMI, TC, HDL-C, and CA19-9 levels were associated with the risk of PC. The high-risk population rating scale might be used for early clinical PC screening.
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Affiliation(s)
- Qian Zhao
- Department of Epidemiology, School of Public Health, Shanxi Medical University, Taiyuan 030001, China
| | - Yan Wang
- Hepatobiliary and Pancreatic Surgery and Liver Transplantation Center, First Hospital of Shanxi Medical University, Taiyuan 030001, China
| | - Tianyu Huo
- Hepatobiliary and Pancreatic Surgery and Liver Transplantation Center, First Hospital of Shanxi Medical University, Taiyuan 030001, China
| | - Furong Li
- Department of Pathology & Pathophysiology, School of Basic Medicine Shanxi Medical University, Taiyuan 030001, China
| | - Lu Zhou
- Department of Epidemiology, School of Public Health, Shanxi Medical University, Taiyuan 030001, China
| | - Yongliang Feng
- Department of Epidemiology, School of Public Health, Shanxi Medical University, Taiyuan 030001, China
| | - Zhigang Wei
- Hepatobiliary and Pancreatic Surgery and Liver Transplantation Center, First Hospital of Shanxi Medical University, Taiyuan 030001, China
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Li Z, Jin L, Xia L, Li X, Guan Y, He H. Body mass index, C-reactive protein, and pancreatic cancer: A Mendelian randomization analysis to investigate causal pathways. Front Oncol 2023; 13:1042567. [PMID: 36816931 PMCID: PMC9932924 DOI: 10.3389/fonc.2023.1042567] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 01/12/2023] [Indexed: 02/05/2023] Open
Abstract
Aim To explore whether C-reactive protein (CRP) mediates the risk of body mass index (BMI) in pancreatic cancer (PC) and calculate the mediate proportion of CRP in this possible mechanism. Methods Based on two-sample Mendelian randomization (TSMR), a two-step Mendelian randomization (TM) model was conducted to determine whether CRP was a mediator of the causal relationship between BMI and PC. The multivariable Mendelian randomization (MVMR) study was designed for mediating analysis and to calculate the mediating proportion mediated by CRP. Results BMI has a positive causal relationship with PC (n = 393 SNPs, OR = 1.484, 95% CI: 1.021-2.157, p< 0.05). BMI has a positive causal relationship with CRP (n = 179 SNPs, OR = 1.393, 95% CI: 1.320-1.469, p< 0.05). CRP has a positive causal relationship with PC (n = 54 SNPs, OR = 1.348, 95% CI: 1.004-1.809, p< 0.05). After adjusting CRP, BMI has no causal relationship with PC (n = 334 SNPs, OR = 1.341, 95% CI: 0.884-2.037, p< 0.05). After adjusting BMI, there was still a positive causal relationship between CRP and PC (n = 334 SNPs, OR = 1.441, 95% CI: 1.064-1.950, p< 0.05). The mediating effect of CRP was 29%. Conclusions In clinical practice, while actively advocating for weight loss among obese patients, we should focus on chronic inflammation levels in obese patients as well. In addition, anti-inflammatory dietary patterns and appropriate physical activity are important in preventing PC.
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Affiliation(s)
- Zhenqi Li
- School of Clinical Medicine, Dali University, Dali, China
| | - Liquan Jin
- Department of General Surgery, The First Affiliated Hospital of Dali University, Dali, China
- *Correspondence: Liquan Jin,
| | - Lu Xia
- School of Clinical Medicine, Dali University, Dali, China
| | - Xiangzhi Li
- College of Life Science, Shaanxi Normal University, Xi’an, China
| | - Yunfei Guan
- Department of General Surgery, The First Affiliated Hospital of Dali University, Dali, China
| | - Hongyang He
- Department of General Surgery, The First Affiliated Hospital of Dali University, Dali, China
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Huang Y, Liu F, Chen AM, Yang PF, Peng Y, Gong JP, Li Z, Zhong GC. Type 2 diabetes prevention diet and the risk of pancreatic cancer: A large prospective multicenter study. Clin Nutr 2021; 40:5595-5604. [PMID: 34656956 DOI: 10.1016/j.clnu.2021.09.037] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 09/07/2021] [Accepted: 09/18/2021] [Indexed: 01/28/2023]
Abstract
BACKGROUND & AIMS Type 2 diabetes prevention diet confers a lower risk of type 2 diabetes, which exhibits overlapping mechanisms with pancreatic cancer. We performed a prospective study to examine whether adherence to this dietary pattern is associated with a reduced risk of pancreatic cancer. METHODS A population-based cohort of 101,729 American adults was identified. A dietary diabetes risk reduction score was computed to reflect adherence to this dietary pattern, with higher scores representing greater adherence. Cox regression was used to compute hazard ratios (HRs) for pancreatic cancer incidence. Prespecified subgroup analyses were used to identify the potential effect modifiers. RESULTS After an average follow-up of 8.86 years (900,871.67 person-years), a total of 402 pancreatic cancer cases were observed. In the fully adjusted model, participants in the highest quartile of dietary diabetes risk reduction score were found to have a reduced risk of pancreatic cancer compared with those in the lowest quartile [HRquartiles 4versus1: 0.62; 95% confidence interval (CI): 0.44, 0.86; Ptrend = 0.004], which remained in a series of sensitivity analyses. Subgroup analyses further found that this favorable association was more pronounced in current or former smokers (HRquartiles 4versus1: 0.48; 95% CI: 0.30, 0.77) than in never smokers (HRquartiles 4versus1: 0.71; 95% CI: 0.44, 1.15), although the interaction test did not reach statistical significance (Pinteraction = 0.095). CONCLUSIONS Greater adherence to type 2 diabetes prevention diet is associated with a lower risk of pancreatic cancer in this US population. More studies are needed to confirm our findings.
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Affiliation(s)
- Yan Huang
- Department of Anesthesiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Feng Liu
- Department of Emergency, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - A-Mei Chen
- Key Laboratory of Molecular Biology for Infectious Diseases, Ministry of Education, Institute for Viral Hepatitis, Department of Infectious Diseases, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - Peng-Fei Yang
- Department of Nephrology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yang Peng
- Department of Geriatrics, The Fifth People's Hospital of Chengdu, Chengdu, China
| | - Jian-Ping Gong
- Department of Hepatobiliary Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Zhi Li
- Department of Breast and Thyroid Surgery, The Second Affiliated Hospital of Chongqing Medical University, China.
| | - Guo-Chao Zhong
- Department of Hepatobiliary Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
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