Strengthening the reporting of genetic risk prediction studies (GRIPS): explanation and elaboration

[1]  享義 黒柳,et al.  Framingham Risk Scoreと動脈硬化リスクについての検討 , 2013 .

[2]  J. Houwing-Duistermaat,et al.  Genome-wide association study (GWAS)-identified disease risk alleles do not compromise human longevity , 2010, Proceedings of the National Academy of Sciences.

[3]  John P. A. Ioannidis,et al.  American Journal of Epidemiology Commentary the Emergence of Translational Epidemiology: from Scientific Discovery to Population Health Impact , 2022 .

[4]  A. Hofman,et al.  American Journal of Epidemiology Practice of Epidemiology Improvement of Risk Prediction by Genomic Profiling: Reclassification Measures versus the Area under the Receiver Operating Characteristic Curve , 2022 .

[5]  Sunila R. Kalkar,et al.  Financial Conflicts of Interest Checklist 2010 for clinical research studies , 2010, Open medicine : a peer-reviewed, independent, open-access journal.

[6]  Sally Hopewell,et al.  The quality of reports of randomised trials in 2000 and 2006: comparative study of articles indexed in PubMed , 2010, BMJ : British Medical Journal.

[7]  Muin J. Khoury,et al.  Application of support vector machine modeling for prediction of common diseases: the case of diabetes and pre-diabetes , 2010, BMC Medical Informatics Decis. Mak..

[8]  M. Khoury,et al.  Assessment of improved prediction beyond traditional risk factors: when does a difference make a difference? , 2010, Circulation. Cardiovascular genetics.

[9]  D. Moher,et al.  Guidance for Developers of Health Research Reporting Guidelines , 2010, PLoS medicine.

[10]  S. Humphries,et al.  Utility of genetic and non-genetic risk factors in prediction of type 2 diabetes: Whitehall II prospective cohort study , 2010, BMJ : British Medical Journal.

[11]  J. Gulcher,et al.  Genetic risk information for common diseases may indeed be already useful for prevention and early detection , 2010, European journal of clinical investigation.

[12]  N. Obuchowski,et al.  Assessing the Performance of Prediction Models: A Framework for Traditional and Novel Measures , 2010, Epidemiology.

[13]  D. Moher,et al.  A catalogue of reporting guidelines for health research , 2010, European journal of clinical investigation.

[14]  J. Ioannidis,et al.  Assessment of claims of improved prediction beyond the Framingham risk score. , 2009, JAMA.

[15]  John P A Ioannidis,et al.  Researching Genetic Versus Nongenetic Determinants of Disease: A Comparison and Proposed Unification , 2009, Science Translational Medicine.

[16]  P. Visscher,et al.  Common polygenic variation contributes to risk of schizophrenia and bipolar disorder , 2009, Nature.

[17]  J. Ioannidis,et al.  The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration , 2009, Annals of Internal Medicine [serial online].

[18]  P. Royston,et al.  Prognosis and prognostic research: application and impact of prognostic models in clinical practice , 2009, BMJ : British Medical Journal.

[19]  Nancy R Cook,et al.  Advances in Measuring the Effect of Individual Predictors of Cardiovascular Risk: The Role of Reclassification Measures , 2009, Annals of Internal Medicine.

[20]  Jan P Vandenbroucke,et al.  STREGA, STROBE, STARD, SQUIRE, MOOSE, PRISMA, GNOSIS, TREND, ORION, COREQ, QUOROM, REMARK... and CONSORT: for whom does the guideline toll? , 2009, Journal of clinical epidemiology.

[21]  Yvonne Vergouwe,et al.  Prognosis and prognostic research: validating a prognostic model , 2009, BMJ : British Medical Journal.

[22]  F. Harrell,et al.  Criteria for Evaluation of Novel Markers of Cardiovascular Risk: A Scientific Statement From the American Heart Association , 2009, Circulation.

[23]  Johanna M Seddon,et al.  Prediction model for prevalence and incidence of advanced age-related macular degeneration based on genetic, demographic, and environmental variables. , 2009, Investigative ophthalmology & visual science.

[24]  T. Hansen,et al.  Combined analysis of 19 common validated type 2 diabetes susceptibility gene variants shows moderate discriminative value and no evidence of gene–gene interaction , 2009, Diabetologia.

[25]  John P A Ioannidis,et al.  Overinterpretation of clinical applicability in molecular diagnostic research. , 2009, Clinical chemistry.

[26]  Yvonne Vergouwe,et al.  Prognosis and prognostic research: Developing a prognostic model , 2009, BMJ : British Medical Journal.

[27]  A. Cecile J.W. Janssens,et al.  Eye color and the prediction of complex phenotypes from genotypes , 2009, Current Biology.

[28]  J. Stanford,et al.  Clinical utility of five genetic variants for predicting prostate cancer risk and mortality , 2009, The Prostate.

[29]  S. Rhee,et al.  Framingham Risk Scores by Occupational Group: Based on the 3rd Korean National Health and Nutrition Examination Survey , 2009 .

[30]  A. Kroon,et al.  The contribution of six polymorphisms to cardiovascular risk in a Dutch high-risk primary care population: the HIPPOCRATES project , 2009, Journal of Human Hypertension.

[31]  A. Janssens,et al.  Genome-based prediction of common diseases: methodological considerations for future research , 2009, Genome Medicine.

[32]  E. Steyerberg,et al.  Usefulness of genetic polymorphisms and conventional risk factors to predict coronary heart disease in patients with familial hypercholesterolemia. , 2009, The American journal of cardiology.

[33]  C. Ball,et al.  Repeatability of published microarray gene expression analyses , 2009, Nature Genetics.

[34]  Nancy R Cook,et al.  Cardiovascular Disease Risk Prediction With and Without Knowledge of Genetic Variation at Chromosome 9p21.3 , 2009, Annals of Internal Medicine.

[35]  K. Narayan,et al.  Clinical risk factors, DNA variants, and the development of type 2 diabetes. , 2009, The New England journal of medicine.

[36]  T. Hansen,et al.  Common type 2 diabetes risk gene variants associate with gestational diabetes. , 2009, The Journal of clinical endocrinology and metabolism.

[37]  Christian Gieger,et al.  Loci influencing lipid levels and coronary heart disease risk in 16 European population cohorts , 2009, Nature Genetics.

[38]  J. Ioannidis,et al.  Strengthening the reporting of genetic association studies (STREGA): an extension of the STROBE statement , 2009, European Journal of Epidemiology.

[39]  L. T. Middleton,et al.  Risk prediction of prevalent diabetes in a Swiss population using a weighted genetic score—the CoLaus Study , 2009, Diabetologia.

[40]  R. D'Agostino,et al.  Genotype score in addition to common risk factors for prediction of type 2 diabetes. , 2008, The New England journal of medicine.

[41]  Holly Janes,et al.  Assessing the Value of Risk Predictions by Using Risk Stratification Tables , 2008, Annals of Internal Medicine.

[42]  A. Cecile J.W. Janssens,et al.  Predicting Type 2 Diabetes Based on Polymorphisms From Genome-Wide Association Studies , 2008, Diabetes.

[43]  Mark I. McCarthy,et al.  Assessing the Combined Impact of 18 Common Genetic Variants of Modest Effect Sizes on Type 2 Diabetes Risk , 2008, Diabetes.

[44]  Cornelia M van Duijn,et al.  Genome-based prediction of common diseases: advances and prospects. , 2008, Human molecular genetics.

[45]  C. Wijmenga,et al.  Molecular prediction of disease risk and severity in a large Dutch Crohn’s disease cohort , 2008, Gut.

[46]  S. Yusuf,et al.  Polygenic determinants of severe hypertriglyceridemia. , 2008, Human molecular genetics.

[47]  J. Ioannidis.  Why Most Discovered True Associations Are Inflated , 2008, Epidemiology.

[48]  Margaret S Pepe,et al.  Gauging the performance of SNPs, biomarkers, and clinical factors for predicting risk of breast cancer. , 2008, Journal of the National Cancer Institute.

[49]  Iveta Simera,et al.  EQUATOR: reporting guidelines for health research , 2008, Open medicine : a peer-reviewed, independent, open-access journal.

[50]  Olle Melander,et al.  Polymorphisms associated with cholesterol and risk of cardiovascular events. , 2008, The New England journal of medicine.

[51]  Pär Stattin,et al.  Cumulative association of five genetic variants with prostate cancer. , 2008, The New England journal of medicine.

[52]  M. Pencina,et al.  Evaluating the added predictive ability of a new marker: From area under the ROC curve to reclassification and beyond , 2008, Statistics in medicine.

[53]  C. Dina,et al.  Impact of Common Type 2 Diabetes Risk Polymorphisms in the DESIR Prospective Study , 2008, Diabetes.

[54]  Yingye Zheng,et al.  Integrating the predictiveness of a marker with its performance as a classifier. , 2007, American journal of epidemiology.

[55]  B. Balkau,et al.  Predicting Diabetes: Clinical, Biological, and Genetic Approaches Data from the Epidemiological Study on the Insulin Resistance Syndrome (DESIR) , 2008 .

[56]  D. Lawlor,et al.  Clustered Environments and Randomized Genes: A Fundamental Distinction between Conventional and Genetic Epidemiology , 2007, PLoS medicine.

[57]  M. Spitz,et al.  Projecting individualized probabilities of developing bladder cancer in white individuals. , 2007, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[58]  S. Pocock,et al.  The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. , 2007, Preventive medicine.

[59]  John P A Ioannidis,et al.  Almost all articles on cancer prognostic markers report statistically significant results. , 2007, European journal of cancer.

[60]  Douglas G Altman,et al.  The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies. , 2014, International journal of surgery.

[61]  S. Pocock,et al.  Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration , 2007, PLoS medicine.

[62]  K. Sirotkin,et al.  The NCBI dbGaP database of genotypes and phenotypes , 2007, Nature Genetics.

[63]  M. Khoury,et al.  The continuum of translation research in genomic medicine: how can we accelerate the appropriate integration of human genome discoveries into health care and disease prevention? , 2007, Genetics in Medicine.

[64]  P. Donnelly,et al.  New models of collaboration in genome-wide association studies: the Genetic Association Information Network , 2007, Nature Genetics.

[65]  J. Pankow,et al.  Prediction of coronary heart disease risk using a genetic risk score: the Atherosclerosis Risk in Communities Study. , 2007, American journal of epidemiology.

[66]  John P A Ioannidis,et al.  Limitations are not properly acknowledged in the scientific literature. , 2007, Journal of clinical epidemiology.

[67]  N. Cook.  Use and Misuse of the Receiver Operating Characteristic Curve in Risk Prediction , 2007, Circulation.

[68]  J. Ioannidis,et al.  Quality of reporting of cancer prognostic marker studies: association with reported prognostic effect. , 2007, Journal of the National Cancer Institute.

[69]  S. Humphries,et al.  Candidate gene genotypes, along with conventional risk factor assessment, improve estimation of coronary heart disease risk in healthy UK men. , 2007, Clinical chemistry.

[70]  Mark Walker,et al.  Combining Information from Common Type 2 Diabetes Risk Polymorphisms Improves Disease Prediction , 2006, PLoS medicine.

[71]  P. Bossuyt,et al.  The quality of diagnostic accuracy studies since the STARD statement , 2006, Neurology.

[72]  D. Moher,et al.  Does the CONSORT checklist improve the quality of reports of randomised controlled trials? A systematic review , 2006, The Medical journal of Australia.

[73]  Johanna M Seddon,et al.  Common variation in three genes, including a noncoding variant in CFH, strongly influences risk of age-related macular degeneration , 2006, Nature Genetics.

[74]  W. White,et al.  Inflammatory Gene Polymorphisms and Risk of Postoperative Myocardial Infarction After Cardiac Surgery , 2006, Circulation.

[75]  Ewout W Steyerberg,et al.  Predictive testing for complex diseases using multiple genes: Fact or fiction? , 2006, Genetics in Medicine.

[76]  Douglas G Altman,et al.  Reporting recommendations for tumor marker prognostic studies. , 2005, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[77]  L. Groop,et al.  Genetic Prediction of Future Type 2 Diabetes , 2005, PLoS medicine.

[78]  L. Klotz.  Can clinically localized prostate cancer be managed conservatively? , 2005, Nature Clinical Practice Urology.

[79]  W. Sauerbrei,et al.  Reporting recommendations for tumor marker prognostic studies (REMARK). , 2005, Journal of the National Cancer Institute.

[80]  J. Ioannidis.  Why Most Published Research Findings Are False , 2005, PLoS medicine.

[81]  John P A Ioannidis,et al.  Selective reporting biases in cancer prognostic factor studies. , 2005, Journal of the National Cancer Institute.

[82]  Andrew N Freedman,et al.  Cancer risk prediction models: a workshop on development, evaluation, and application. , 2005, Journal of the National Cancer Institute.

[83]  Matthias Egger,et al.  The scandal of poor epidemiological research , 2004, BMJ : British Medical Journal.

[84]  R Brian Haynes,et al.  BMC Medicine BioMed Central , 2003 .

[85]  Nicole A. Lazar,et al.  Statistical Analysis With Missing Data , 2003, Technometrics.

[86]  D E Grobbee,et al.  External validation is necessary in prediction research: a clinical example. , 2003, Journal of clinical epidemiology.

[87]  David Moher,et al.  The STARD Statement for Reporting Studies of Diagnostic Accuracy: Explanation and Elaboration , 2003, Annals of Internal Medicine [serial online].

[88]  D. Rennie,et al.  Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative , 2003, BMJ : British Medical Journal.

[89]  R. Brian Haynes,et al.  Developing Optimal Search Strategies for Detecting Sound Clinical Prediction Studies in MEDLINE , 2003, AMIA.

[90]  Richard Horton,et al.  The hidden research paper. , 2002, JAMA.

[91]  Mathew W. Wright,et al.  Guidelines for human gene nomenclature. , 2002, Genomics.

[92]  D. Moher,et al.  The Revised CONSORT Statement for Reporting Randomized Trials: Explanation and Elaboration , 2001, Annals of Internal Medicine.

[93]  Elizabeth M. Smigielski,et al.  dbSNP: the NCBI database of genetic variation , 2001, Nucleic Acids Res..

[94]  M Docherty,et al.  The case for structuring the discussion of scientific papers , 1999, BMJ.

[95]  I Chalmers,et al.  Discussion sections in reports of controlled trials published in general medical journals: islands in search of continents? , 1998, JAMA.

[96]  M. Khoury,et al.  The Human Genome Epidemiology Network. , 1998, American journal of epidemiology.

[97]  G H Guyatt,et al.  A Consumer's Guide to Subgroup Analyses , 1992, Annals of Internal Medicine.

[98]  Chris Chatfield,et al.  19. Statistical Analysis with Missing Data , 1988 .

[99]  D. Rubin,et al.  Statistical Analysis with Missing Data. , 1989 .