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4 results on '"Melillo S"'

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

Author

Janssens AC, Ioannidis JP, Bedrosian S, Boffetta P, Dolan SM, Dowling N, Fortier I, Freedman AN, Grimshaw JM, Gulcher J, Gwinn M, Hlatky MA, Janes H, Kraft P, Melillo S, O'Donnell CJ, Pencina MJ, Ransohoff D, Schully SD, Seminara D, Winn DM, Wright CF, van Duijn CM, Little J, and Khoury MJ

Subjects
Disclosure standards, Disease genetics, Genetic Research, Genome-Wide Association Study standards, Genomics methods, Guidelines as Topic, Humans, Models, Genetic, Risk Assessment, Genetic Predisposition to Disease genetics, Genetic Testing standards, Genome, Human genetics, Genome-Wide Association Study methods, Publishing standards
Abstract

• The rapid and continuing progress in gene discovery for complex diseases is fuelling interest in the potential application of genetic risk models for clinical and public health practice. • The number of studies assessing the predictive ability is steadily increasing, but they vary widely in completeness of reporting and apparent quality. • Transparent reporting of the strengths and weaknesses of these studies is important to facilitate the accumulation of evidence on genetic risk prediction. • A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS), building on the principles established by prior reporting guidelines. • These recommendations aim to enhance the transparency, quality and completeness of study reporting and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct or analysis., (© 2011 The Authors. European Journal of Clinical Investigation © 2011 Stichting European Society for Clinical Investigation Journal Foundation.)

Published
2011
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2. Horizon scanning for new genomic tests.

Author

Gwinn M, Grossniklaus DA, Yu W, Melillo S, Wulf A, Flome J, Dotson WD, and Khoury MJ

Subjects
Humans, United States, United States Food and Drug Administration, Genetic Testing methods, Genetic Testing trends, Genomics methods, Genomics trends, Internet, Search Engine methods
Abstract

Purpose: The development of health-related genomic tests is decentralized and dynamic, involving government, academic, and commercial entities. Consequently, it is not easy to determine which tests are in development, currently available, or discontinued. We developed and assessed the usefulness of a systematic approach to identifying new genomic tests on the Internet., Methods: We devised targeted queries of Web pages, newspaper articles, and blogs (Google Alerts) to identify new genomic tests. We finalized search and review procedures during a pilot phase that ended in March 2010. Queries continue to run daily and are compiled weekly; selected data are indexed in an online database, the Genomic Applications in Practice and Prevention Finder., Results: After the pilot phase, our scan detected approximately two to three new genomic tests per week. Nearly two thirds of all tests (122/188, 65%) were related to cancer; only 6% were related to hereditary disorders. Although 88 (47%) of the tests, including 2 marketed directly to consumers, were commercially available, only 12 (6%) claimed United States Food and Drug Administration licensure., Conclusion: Systematic surveillance of the Internet provides information about genomic tests that can be used in combination with other resources to evaluate genomic tests. The Genomic Applications in Practice and Prevention Finder makes this information accessible to a wide group of stakeholders.

Published
2011
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4. Strengthening the reporting of genetic risk prediction studies (GRIPS): Explanation and elaboration

Author

Christopher J. O'Donnell, David F. Ransohoff, Muin J. Khoury, Jeremy M. Grimshaw, Stephanie Melillo, Caroline F. Wright, Deborah M. Winn, Sara Bedrosian, Daniela Seminara, John P. A. Ioannidis, Holly Janes, Michael J. Pencina, Siobhan M. Dolan, Mark A. Hlatky, Paolo Boffetta, Jeffrey R. Gulcher, Andrew N. Freedman, Isabel Fortier, Nicole F. Dowling, Julian Little, Peter Kraft, A. Cecile J.W. Janssens, Marta Gwinn, Sheri D. Schully, Cornelia M. van Duijn, Janssens, A.C.J.W., Ioannidis, J.P.A., Bedrosian, S., Boffetta, P., Dolan, S.M., Dowling, N., Fortier, I., Freedman, A.N., Grimshaw, J.M., Gulcher, J., Gwinn, M., Hlatky, M.A., Janes, H., Kraft, P., Melillo, S., O'Donnell, C.J., Pencina, M.J., Ransohoff, D., Schully, S.D., Seminara, D., Winn, D.M., Wright, C.F., Van Duijn, C.M., Little, J., Khoury, M.J., Department of Epidemiology [Rotterdam], Erasmus University Medical Center [Rotterdam] (Erasmus MC), Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Biomedical Research Institute, Foundation for Research and Technology, Department of Medicine, Tufts University School of Medicine, Center for Genetic Epidemiology and Modeling and Tufts CTSI, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Stanford Prevention Research Center, Stanford Medicine, Stanford University-Stanford University, Office of Public Health Genomics, Centers for Disease Control and Prevention, The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai [New York] (MSSM), International Prevention Research Institute (IPRI), Department of Obstetrics & Gynecology and Women's Health, Albert Einstein College of Medicine, Montefiore Medical Center, Public Population Project in Genomics (P3G), National Cancer Institute [Bethesda] (NCI-NIH), National Institutes of Health [Bethesda] (NIH), Clinical Epidemiology Program, Ottawa Hospital Research Institute [Ottawa] (OHRI), University of Ottawa [Ottawa], deCODE Genetics, deCODE genetics [Reykjavik], Department of Health Research and Policy, Stanford University, Fred Hutchinson Cancer Research Center [Seattle] (FHCRC), Department of Epidemiology, Harvard School of Public Health, Framingham Heart Study, Boston University [Boston] (BU)-National Heart, Lung, and Blood Institute [Bethesda] (NHLBI), Cardiology Division, Massachusetts General Hospital, Harvard Medical School [Boston] (HMS), Department of Biostatistics, Boston University [Boston] (BU), Harvard Clinical Research Institute, University of North Carolina at Chapel Hill School of Medicine, University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC)-University of North Carolina System (UNC), PHG Foundation, Epidemiology and Community Medicine, O'donnell, C.J., and Epidemiology

Subjects
Gerontology, Male, Epidemiology, Genome-wide association study, Strengthening the reporting of observational studies in epidemiology, Bioinformatics, computer.software_genre, genetic risk, 0302 clinical medicine, Multidisciplinary approach, STROBE, Disease, 030212 general & internal medicine, Genetic risk, Genetics (clinical), Randomized Controlled Trials as Topic, CURVE, 0303 health sciences, medicine.diagnostic_test, GRIPS, ASSOCIATION, Genomics, Middle Aged, Checklist, Risk prediction, 3. Good health, Policy, Risk analysis (engineering), Strengthening reporting genetic risk prediction studies GRIPS, Strengthening, Female, Data mining, Risk assessment, Psychology, Adult, Genetic Research, medicine.medical_specialty, MODELS, Guidelines as Topic, Disclosure, Guidelines, Risk Assessment, Article, EXPLANATION, Education, 03 medical and health sciences, Genetic, SDG 3 - Good Health and Well-being, Genetics, medicine, Humans, Genetic Predisposition to Disease, Genetic Testing, Elaboration, Genetic testing, Aged, 030304 developmental biology, Publishing, Models, Genetic, Genome, Human, business.industry, Public health, Methodology, Epidemiologic Studies, Reporting, MARKER, Genomics/*methods, Interdisciplinary Communication, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, business, computer, Strengths and weaknesses, Genome-Wide Association Study
Abstract

The rapid and continuing progress in gene discovery for complex diseases is fuelling interest in the potential application of genetic risk models for clinical and public health practice. The number of studies assessing the predictive ability is steadily increasing, but they vary widely in completeness of reporting and apparent quality. Transparent reporting of the strengths and weaknesses of these studies is important to facilitate the accumulation of evidence on genetic risk prediction. A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS), building on the principles established by prior reporting guidelines. These recommendations aim to enhance the transparency, quality and completeness of study reporting and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct or analysis. © 2011 The Authors. European Journal of Clinical Investigation © 2011 Stichting European Society for Clinical Investigation Journal Foundation.

Published
2011

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