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Type 2 Diabetes And Cancer: Umbrella Review Of Meta-analyses Of Observational Studies

Konstantinos K Tsilidis, John C Kasimis, David S Lopez, Evangelia E. Ntzani, John P. A. Ioannidis
Published 2015 · Medicine
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Objectives To summarise the evidence and evaluate the validity of the associations between type 2 diabetes and the risk of developing or dying from cancer. Design An umbrella review of the evidence across meta-analyses of observational studies of type 2 diabetes with risk of developing or dying from any cancer. Data sources PubMed, Embase, Cochrane database of systematic reviews, and manual screening of references. Eligibility criteria Meta-analyses or systematic reviews of observational studies in humans that examined the association between type 2 diabetes and risk of developing or dying from cancer. Results Eligible meta-analyses assessed associations between type 2 diabetes and risk of developing cancer in 20 sites and mortality for seven cancer sites. The summary random effects estimates were significant at P=0.05 in 20 meta-analyses (74%); and all reported increased risks of developing cancer for participants with versus without diabetes. Of the 27 meta-analyses, eventually only seven (26%) compiled evidence on more than 1000 cases, had significant summary associations at P≤0.001 for both random and fixed effects calculations, and had neither evidence of small study effects nor evidence for excess significance. Of those, only six (22%) did not have substantial heterogeneity (I2>75%), pertaining to associations between type 2 diabetes and risk of developing breast, cholangiocarcinoma (both intrahepatic and extrahepatic), colorectal, endometrial, and gallbladder cancer. The 95% prediction intervals excluded the null value for four of these associations (breast, intrahepatic cholangiocarcinoma, colorectal, and endometrial cancer). Conclusions Though type 2 diabetes has been extensively studied in relation to risk of developing cancer and cancer mortality and strong claims of significance exist for most of the studied associations, only a minority of these associations have robust supporting evidence without hints of bias.
This paper references
10.1037/1089-2680.2.2.175
Confirmation Bias: A Ubiquitous Phenomenon in Many Guises
R. S. Nickerson (1998)
10.1111/j.1572-0241.2008.01796.x
Hepatitis B Virus Infection and Intrahepatic Cholangiocarcinoma in Korea: A Case-Control Study
Tae Yoon Lee (2008)
10.1093/jnci/djn191
False-Positive Results in Cancer Epidemiology: A Plea for Epistemological Modesty
Paolo Boffetta (2008)
10.1073/pnas.1313476110
Revised standards for statistical evidence
Valen E. Johnson (2013)
No commercial reuse: See rights and reprints http://www.bmj.com/permissions Subscribe: http://www.bmj.com/subscribe
(2014)
10.1001/jama.295.6.676
Comparison of two methods to detect publication bias in meta-analysis.
Jaime L Peters (2006)
Cite this...
10.1371/journal.pmed.0040079
Selection in Reported Epidemiological Risks: An Empirical Assessment
Fotini K. Kavvoura (2007)
10.1097/EDE.0b013e31821b506e
The False-positive to False-negative Ratio in Epidemiologic Studies
John P A Ioannidis (2011)
10.1136/bmj.d4002
Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials
Jonathan A C Sterne (2011)
10.1097/CEJ.0b013e3283481d89
Diabetes mellitus and increased risk of cholangiocarcinoma: a meta-analysis
Wei Jing (2012)
10.1002/(SICI)1097-0258(19980730)17:14<1623::AID-SIM871>3.0.CO;2-S
A simple method of sample size calculation for linear and logistic regression.
Frank Y. Hsieh (1998)
10.1177/1740774507079441
An exploratory test for an excess of significant findings
John P A Ioannidis (2007)
10.1371/journal.pbio.1001609
Evaluation of Excess Significance Bias in Animal Studies of Neurological Diseases
Konstantinos K Tsilidis (2013)
10.1186/1471-2407-13-310
Risk of bladder cancer in patients with diabetes mellitus: an updated meta-analysis of 36 observational studies
Zhaowei Zhu (2012)
10.1371/journal.pmed.0020124
Why Most Published Research Findings Are False
John P. A. Ioannidis (2005)
From Egger's regression asymmetry test
10.1093/jnci/dji184
Selective reporting biases in cancer prognostic factor studies.
Panayiotis A. Kyzas (2005)
10.1097/MEG.0b013e32834b8d73
Diabetes mellitus and risk of gastric cancer: a systematic review and meta-analysis of observational studies
Zhenming Ge (2011)
10.1016/j.ejca.2013.02.025
Diabetes mellitus as an independent risk factor for lung cancer: a meta-analysis of observational studies.
Jung-Yun Lee (2013)
10.1136/bmj.d549
Interpretation of random effects meta-analyses
Richard D Riley (2011)
International Diabetes Federation. Diabetes atlas. International Diabetes Federation
(2013)
10.1093/biostatistics/kxq046
Treatment-effect estimates adjusted for small-study effects via a limit meta-analysis.
Gerta Rücker (2011)
10.1038/pcan.2009.39
Does pre-existing diabetes affect prostate cancer prognosis? A systematic review
Claire F Snyder (2010)
10.1016/j.ejca.2007.08.030
Almost all articles on cancer prognostic markers report statistically significant results.
Panayiotis A. Kyzas (2007)
This is an Open Access article distribut...
(2007)
10.1093/annonc/mdt372
Potential increased risk of cancer from commonly used medications: an umbrella review of meta-analyses.
John P A Ioannidis (2014)
10.1007/s10552-011-9874-9
Risk of esophageal cancer in diabetes mellitus: a meta-analysis of observational studies
Wen Wei Huang (2011)
10.3322/caac.20078
Diabetes and cancer: a consensus report.
Edward L. Giovannucci (2010)
10.1016/j.jdiacomp.2013.01.004
Diabetes mellitus and incidence and mortality of kidney cancer: a meta-analysis.
Cuiping Bao (2013)
No commercial reuse: See rights and reprints http://www.bmj.com/permissions Subscribe
10.1136/bmj.39343.408449.80
Uncertainty in heterogeneity estimates in meta-analyses
John P A Ioannidis (2007)
10.2307/2531021
Sample-size formula for the proportional-hazards regression model.
David Alan Schoenfeld (1983)
10.1158/1055-9965.EPI-13-0146
Transforming Epidemiology for 21st Century Medicine and Public Health
Muin J. Khoury (2013)
10.1182/blood-2011-06-362830
Increased incidence of non-Hodgkin lymphoma, leukemia, and myeloma in patients with diabetes mellitus type 2: a meta-analysis of observational studies.
Jorge J Castillo (2012)
Transforming epidemiology for 21 st century medicine and public health
MJ Khoury (2013)
10.1007/s10654-011-9617-y
Diabetes mellitus and incidence and mortality of colorectal cancer: a systematic review and meta-analysis of cohort studies
Ying Jiang (2011)
10.1158/1055-9965.EPI-12-0995
False Positives in Cancer Epidemiology
Joseph K. Mclaughlin (2012)
10.1007/s10620-009-0944-8
Colorectal Cancer Outcomes, Recurrence, and Complications in Persons With and Without Diabetes Mellitus: A Systematic Review and Meta-Analysis
Kelly B. Stein (2009)
10.1038/pcan.2012.40
Type 2 diabetes and risk of prostate cancer: a meta-analysis of observational studies
Dipika Bansal (2013)
10.1053/j.gastro.2004.12.048
Risk factors of intrahepatic cholangiocarcinoma in the United States: a case-control study.
Yasser H. Shaib (2005)
10.1111/cas.12043
Diabetes mellitus and cancer risk: review of the epidemiological evidence.
Kentaro Shikata (2013)
10.1007/s10654-013-9865-0
Physical activity, diabetes, and risk of thyroid cancer: a systematic review and meta-analysis
Daniela Schmid (2013)
10.1016/0197-2456(86)90046-2
Meta-analysis in clinical trials.
Rebecca Dersimonian (1986)
10.1016/j.ejca.2011.03.003
Diabetes mellitus and risk of pancreatic cancer: A meta-analysis of cohort studies.
Qiwen Ben (2011)
10.1200/JCO.2009.27.3011
Diabetes mellitus and breast cancer outcomes: a systematic review and meta-analysis.
Kimberly S. Peairs (2011)
10.1007/s00125-012-2526-0
Diabetes and cancer (2): evaluating the impact of diabetes on mortality in patients with cancer
Andrew G Renehan (2012)
10.1001/jama.2012.8144
The importance of potential studies that have not existed and registration of observational data sets.
John P A Ioannidis (2012)
10.4158/EP10357.RA
Significantly increased risk of cancer in patients with diabetes mellitus: a systematic review and meta-analysis.
Hiroshi Noto (2011)
10.1371/journal.pone.0003081
Systematic Review of the Empirical Evidence of Study Publication Bias and Outcome Reporting Bias
Kerry M Dwan (2008)
10.1016/j.jclinepi.2004.04.005
Agreement between self-report questionnaires and medical record data was substantial for diabetes, hypertension, myocardial infarction and stroke but not for heart failure.
Yuji Okura (2004)
10.1136/bmj.315.7109.629
Bias in meta-analysis detected by a simple, graphical test
Matthias Egger (1997)
10.1056/NEJMoa1008862
Diabetes mellitus, fasting glucose, and risk of cause-specific death.
Sreenivasa Rao Kondapally Seshasai (2011)
10.1093/jnci/djs437
Evaluation of excess statistical significance in meta-analyses of 98 biomarker associations with cancer risk.
Konstantinos K Tsilidis (2012)
10.1037/0033-295X.94.2.211
Confirmation, Disconfirmation, and Informa-tion in Hypothesis Testing
Joshua Klayman (1987)
10.1055/s-0031-1297969
Diabetes mellitus and incidence and mortality of gastric cancer: a meta-analysis.
Ting Tian (2012)
10.1002/sim.1186
Quantifying heterogeneity in a meta-analysis.
Julian P. T. Higgins (2002)
10.1007/s00125-007-0681-5
Diabetes mellitus and risk of endometrial cancer: a meta-analysis
Ebba Friberg (2007)
10.1007/s10552-011-9754-3
Diabetes mellitus and increased risk of biliary tract cancer: systematic review and meta-analysis
Hong-bo Ren (2011)
10.3945/ajcn.112.047142
Is everything we eat associated with cancer? A systematic cookbook review.
Jonathan D Schoenfeld (2013)
World Health Organization. The global burden of disease: 2004 update. WHO
(2008)
10.1186/1471-2288-9-2
Assessment of regression-based methods to adjust for publication bias through a comprehensive simulation study
Santiago González Moreno (2009)
10.1097/IGC.0b013e31828189b2
Diabetes Mellitus and Ovarian Cancer Risk: A Systematic Review and Meta-Analysis of Observational Studies
Jung-Yun Lee (2013)
†Relative risk when SE=0, extrapolated from fitted Egger's regression line. ‡I 2 metric of inconsistency (95% CI) and P value of Q test
10.1001/jama.2008.824
Long-term all-cause mortality in cancer patients with preexisting diabetes mellitus: a systematic review and meta-analysis.
Bethany B. Barone (2008)
10.1136/bmj.322.7280.226
Sifting the evidence—what's wrong with significance tests?
Jonathan A C Sterne (2001)
10.1097/EDE.0b013e31818131e7
Why Most Discovered True Associations Are Inflated
John P. A. Ioannidis (2008)
10.1007/s00125-012-2525-1
Diabetes and cancer (1): evaluating the temporal relationship between type 2 diabetes and cancer incidence
Jonathan Andrew Johnson (2012)
10.1002/ijc.22717
Diabetes mellitus and risk of breast cancer: a meta-analysis.
Susanna C. Larsson (2007)
10.1002/dmrr.1291
Diabetes mellitus and risk of hepatocellular carcinoma: a systematic review and meta-analysis.
Ping Wang (2012)
10.1002/sim.2380
A modified test for small-study effects in meta-analyses of controlled trials with binary endpoints.
Roger M. Harbord (2006)
10.1016/J.JMP.2013.03.002
Clarifications on the application and interpretation of the test for excess significance and its extensions
John P. A. Ioannidis (2013)



This paper is referenced by
Metformin, statins and the risk and prognosis of endometrial cancer in women with type 2 diabetes
Reetta Arima (2019)
10.14309/ajg.0000000000000225
Risk of Mortality and Hospitalization After Post-Pancreatitis Diabetes Mellitus vs Type 2 Diabetes Mellitus: A Population-Based Matched Cohort Study
Jaelim Cho (2019)
10.1016/S2214-109X(18)30488-1
Disparities by province, age, and sex in site-specific cancer burden attributable to 23 potentially modifiable risk factors in China: a comparative risk assessment.
Wanqing Chen (2019)
10.1371/journal.pone.0182359
Associations between self-reported diabetes and 78 circulating markers of inflammation, immunity, and metabolism among adults in the United States
Alison L Van Dyke (2017)
10.1002/ijc.32753
Predicted Basal Metabolic Rate and Cancer Risk in the European Prospective Investigation into Cancer and Nutrition (Epic).
Nathalie Kliemann (2019)
10.1007/978-3-030-42667-5
Reviews on New Drug Targets in Age-Related Disorders
Paul c. Guest (2020)
10.1093/jnci/djx043
Editorial: Mendelian Randomization Analysis Identifies Body Mass Index and Fasting Insulin as Potential Causal Risk Factors for Pancreatic Cancer Risk.
Konstantinos K Tsilidis (2017)
10.1016/j.ejca.2016.09.026
Diet, body size, physical activity and risk of prostate cancer: An umbrella review of the evidence.
Georgios Markozannes (2016)
10.1371/journal.pbio.2005761
Reporting bias in the literature on the associations of health-related behaviors and statins with cardiovascular disease and all-cause mortality
Leandro Fórnias Machado de Rezende (2018)
10.1093/aje/kwx150
Concordance With Prevention Guidelines and Subsequent Cancer, Cardiovascular Disease, and Mortality: A Longitudinal Study of Older Adults
Heather Greenlee (2017)
10.1007/s00761-017-0311-x
Diabetes und Krebs – den Zusammenhängen auf der Spur
Friederike Klein (2017)
10.1177/0969141319874834
Type 2 diabetes and colorectal cancer screening: Findings from the English Longitudinal Study of Ageing
Christian von Wagner (2019)
10.1007/978-3-030-11866-2_11
To Be Healthy, Wealthy, and Wise: Using Decision Modeling to Personalize Policy in Health, Hunger Relief, and Education
Julie S. Ivy (2020)
10.1111/dme.13536
Risk of prostate cancer across different racial/ethnic groups in men with diabetes: a retrospective cohort study
Christopher B Chen (2018)
10.1007/s00404-015-3896-6
Number of parity and the risk of gallbladder cancer: a systematic review and dose–response meta-analysis of observational studies
Peng Guo (2015)
Modifiable CVD Risk Factors and Their Cancer Risk Obesity
Ryan J Koene (2016)
10.21037/TCR.2020.03.14
Association between diabetes, obesity, aging, and cancer: review of recent literature
Judy K. Qiang (2020)
10.1080/09513590.2020.1725972
Does metformin effect mammographic breast density in postmenopausal women with type 2 diabetes.
Mehmet Hayrullah Ozturk (2020)
10.1038/srep46527
Higher risk of colorectal cancer in patients with newly diagnosed diabetes mellitus before the age of colorectal cancer screening initiation
Sander de Kort (2017)
10.1158/1055-9965.EPI-19-1623
Diabetes, Glycated Hemoglobin, and Risk of Cancer in the UK Biobank Study
Rita Peila (2020)
10.3332/ecancer.2018.802
A systematic review of the literature exploring the interplay between prostate cancer and type two diabetes mellitus
Danielle Crawley (2018)
10.1016/j.canep.2020.101710
Impact of preexisting type 2 diabetes mellitus and antidiabetic drugs on all-cause and cause-specific mortality among Medicaid-insured women diagnosed with breast cancer.
Wayne R Lawrence (2020)
10.2337/db20-0084
Is Type 2 Diabetes Causally Associated With Cancer Risk? Evidence From a Two-Sample Mendelian Randomization Study
Shuai Yuan (2020)
10.1016/B978-0-12-804011-9.00049-2
Cancer and Bariatric Surgery
Daniela Schaan Casagrande (2017)
10.1158/1055-9965.EPI-17-0936
Association of Metformin with Breast Cancer Incidence and Mortality in Patients with Type II Diabetes: A GRADE-Assessed Systematic Review and Meta-analysis
Grace H Tang (2018)
10.1002/cam4.3051
Non‐genetic biomarkers and colorectal cancer risk: Umbrella review and evidence triangulation
Xiaomeng Zhang (2020)
10.1007/978-3-319-64940-5_1
Epidemiology, Energy Balance and Prostate Cancer Incidence and Mortality
Nikos Papadimitriou (2018)
10.1093/annonc/mdz044
Meeting report from the joint IARC–NCI international cancer seminar series: a focus on colorectal cancer
Marc J. Gunter (2019)
10.1186/s13046-018-0711-9
Stearoyl-CoA desaturase-1 promotes colorectal cancer metastasis in response to glucose by suppressing PTEN
Hui Ran (2018)
10.22465/KJUO.2018.16.3.103
Relationship of Prostate-Specific Antigen Level With Obesity Indices in Korean Middle-Aged Population
Seung Ki Min (2018)
10.1002/ijc.31961
Risk factors for endometrial cancer: An umbrella review of the literature.
Olivia Raglan (2018)
10.1530/ERC-15-0400
Obesity and cancer: mechanistic insights from transdisciplinary studies.
Emma H. Allott (2015)
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