Exposure-wide epidemiology: revisiting Bradford Hill

Bradford Hill, 1965, The environment and disease: association or causation?, Proceedings of the Royal Society of Medicine, 58, 295, 10.1177/003591576505800503

Ioannidis, 2014, Estimates of the continuously publishing core in the scientific workforce, PLoS One, 9, e101698, 10.1371/journal.pone.0101698

Khabsa, 2014, The number of scholarly documents on the public Web, PLoS One, 9, e93949, 10.1371/journal.pone.0093949

Ioannidis, 2009, Integration of evidence from multiple meta-analyses: a primer on umbrella reviews, treatment networks and multiple treatments meta-analyses, CMAJ, 181, 488, 10.1503/cmaj.081086

Khoury, 2009, Genome-wide association studies, field synopses, and the development of the knowledge base on genetic variation and human diseases, American Journal of Epidemiology, 170, 269, 10.1093/aje/kwp119

Burgio, 2013, Collaborative cancer epidemiology in the 21st century: the model of cancer consortia, Cancer Epidemiology, Biomarkers and Prevention, 22, 2148, 10.1158/1055-9965.EPI-13-0591

Panagiotou, 2013, The power of meta-analysis in genome-wide association studies, Annual Review of Genomics and Human Genetics, 14, 441, 10.1146/annurev-genom-091212-153520

Ioannidis, 2013, Implausible results in human nutrition research, BMJ, 347, f6698, 10.1136/bmj.f6698

Schoenfeld, 2013, Is everything we eat associated with cancer? A systematic cookbook review, The American Journal of Clinical Nutrition, 97, 127, 10.3945/ajcn.112.047142

Serghiou, 2016, Field-wide meta-analyses of observational associations can map selective availability of risk factors and the impact of model specifications, Journal of Clinical Epidemiology, 71, 58, 10.1016/j.jclinepi.2015.09.004

Khoury, 2014, Medicine. Big data meets public health, Science, 346, 1054, 10.1126/science.aaa2709

Tobacco and Genetics Consortium, 2010, Genome-wide meta-analyses identify multiple loci associated with smoking behavior, Nature Genetics, 42, 441, 10.1038/ng.571

Tzoulaki, 2012, A nutrient-wide association study on blood pressure, Circulation, 126, 2456, 10.1161/CIRCULATIONAHA.112.114058

Patel, 2015, Systematic assessment of the correlations of household income with infectious, biochemical, physiological, and environmental factors in the United States, 1999-2006, American Journal of Epidemiology, 181, 171, 10.1093/aje/kwu277

Patel, 2012, Systematic evaluation of environmental factors: persistent pollutants and nutrients correlated with serum lipid levels, International Journal of Epidemiology, 41, 828, 10.1093/ije/dys003

Rappaport, 2010, Epidemiology. Environment and disease risks, Science, 330, 460, 10.1126/science.1192603

Siontis, 2011, Risk factors and interventions with statistically significant tiny effects, International Journal of Epidemiology, 40, 1292, 10.1093/ije/dyr099

Ioannidis, 2011, Re: Fruit and vegetable intake and overall cancer risk in the European Prospective Investigation into Cancer and Nutrition, Journal of the National Cancer Institute, 103, 280, 10.1093/jnci/djq503

Pereira, 2012, Empirical evaluation of very large treatment effects of medical interventions, JAMA, 308, 1676, 10.1001/jama.2012.13444

Ioannidis, 2011, Comparison of effect sizes associated with biomarkers reported in highly cited individual articles and in subsequent meta-analyses, JAMA, 305, 2200, 10.1001/jama.2011.713

Ioannidis, 2012, Minimal and null predictive effects for the most popular blood biomarkers of cardiovascular disease, Circulation Research, 110, 658, 10.1161/RES.0b013e31824da8ad

Ioannidis, 2005, Why most published research findings are false, PLoS Medicine, 2, e124, 10.1371/journal.pmed.0020124

Pan, 2005, Local literature bias in genetic epidemiology: an empirical evaluation of the Chinese literature, PLoS Medicine, 2, e334, 10.1371/journal.pmed.0020334

Ioannidis, 2005, Molecular bias, European Journal of Epidemiology, 20, 739, 10.1007/s10654-005-2028-1

Ioannidis, 2011, The false-positive to false-negative ratio in epidemiologic studies, Epidemiology, 22, 450, 10.1097/EDE.0b013e31821b506e

Ioannidis, 2007, Molecular evidence-based medicine: evolution and integration of information in the genomic era, European Journal of Clinical Investigation, 37, 340, 10.1111/j.1365-2362.2007.01794.x

Ioannidis, 2008, Assessment of cumulative evidence on genetic associations: interim guidelines, International Journal of Epidemiology, 37, 120, 10.1093/ije/dym159

Ioannidis, 2006 Jun, Commentary: grading the credibility of molecular evidence for complex diseases, International Journal of Epidemiology, 35, 593, 10.1093/ije/dyl003

Tatsioni, 2007, Persistence of contradicted claims in the literature, JAMA, 298, 2517, 10.1001/jama.298.21.2517

Ioannidis, 2009, Researching genetic versus nongenetic determinants of disease: a comparison and proposed unification, Science Translational Medicine, 18

Patel, 2014, Studying the elusive environment in large scale, JAMA, 311, 2173, 10.1001/jama.2014.4129

Patel, 2014, Placing epidemiological results in the context of multiplicity and typical correlations of exposures, Journal of Epidemiology and Community Health, 68, 1096, 10.1136/jech-2014-204195

Patel, 2015, Assessment of vibration of effects due to model specification can demonstrate the instability of observational associations, Journal of Clinical Epidemiology, 68, 1046, 10.1016/j.jclinepi.2015.05.029

Ioannidis, 2007, Selective discussion and transparency in microarray research findings for cancer outcomes, European Journal of Cancer, 43, 1999, 10.1016/j.ejca.2007.05.019

Ioannidis, 2005, Contradicted and initially stronger effects in highly cited clinical research, JAMA, 294, 218, 10.1001/jama.294.2.218

Young, 2011, Deming, data and observational studies: a process out of control and needing fixing, Significance, 8, 116, 10.1111/j.1740-9713.2011.00506.x

Fanelli, 2010, “Positive” results increase down the Hierarchy of the Sciences, PLoS One, 5, e10068, 10.1371/journal.pone.0010068

Ioannidis, 2013, This I believe in genetics: discovery can be a nuisance, replication is science, implementation matters, Frontiers in Genetics, 4, 33, 10.3389/fgene.2013.00033

Ioannidis, 2015, Meta-research: evaluation and improvement of research methods and practices, PLoS Biology, 13, e1002264, 10.1371/journal.pbio.1002264

Ioannidis, 2014, How to make more published research true, PLoS Medicine, 11, e1001747, 10.1371/journal.pmed.1001747