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11 results on '"Stanford Prevention Research Center"'

1. First-in-Human Study of Utomilumab, a 4-1BB/CD137 Agonist, in Combination with Rituximab in Patients with Follicular and Other CD20+ Non-Hodgkin Lymphomas

Author

Craig Davis, Nancy L. Bartlett, Roch Houot, Aron Thall, Ronald Levy, Keith A. Ching, Leslie Popplewell, Sandip Pravin Patel, Adrian Woolfson, Bo Huang, Ying Chen, Xinmeng J. Mu, Ajay K. Gopal, Caron A. Jacobson, Kolette D. Fly, Shibing Deng, University of Washington [Seattle], Stanford Prevention Research Center, Stanford Medicine, Stanford University-Stanford University, CHU Pontchaillou [Rennes], Centre d'Investigation Clinique [Rennes] (CIC), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), Etablissement français du sang [Rennes] (EFS Bretagne), Microenvironment, Cell Differentiation, Immunology and Cancer (MICMAC), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Moores Cancer Center [La Jolla], UC San Diego School of Medicine, City of Hope National Medical Center, Dana-Farber Cancer Institute [Boston], Pfizer Oncology, Washington University School of Medicine in St. Louis, Washington University in Saint Louis (WUSTL), N.A., Université de Rennes (UR)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), School of Medicine [Univ California San Diego] (UC San Diego), University of California [San Diego] (UC San Diego), University of California (UC)-University of California (UC)-University of California [San Diego] (UC San Diego), and University of California (UC)-University of California (UC)

Subjects
0301 basic medicine, Cancer Research, medicine.medical_specialty, [SDV]Life Sciences [q-bio], Gastroenterology, 03 medical and health sciences, 0302 clinical medicine, Pharmacokinetics, immune system diseases, hemic and lymphatic diseases, Internal medicine, medicine, Adverse effect, CD20, biology, business.industry, medicine.disease, 3. Good health, Lymphoma, 030104 developmental biology, Oncology, Tolerability, 030220 oncology & carcinogenesis, Pharmacodynamics, biology.protein, Rituximab, Refractory Follicular Lymphoma, business, medicine.drug
Abstract

Purpose: In this phase I study (NCT01307267), we evaluated safety, pharmacokinetics, clinical activity, and pharmacodynamics of treatment with utomilumab plus rituximab in patients with relapsed/refractory follicular lymphoma (FL) and other CD20+ non-Hodgkin lymphomas (NHL). Patients and Methods: Primary objectives were to assess treatment safety and tolerability for estimating the MTD, using a modified time-to-event continual reassessment method, and selecting the recommended phase II dose (RP2D). Results: Sixty-seven patients received utomilumab (0.03–10.0 mg/kg every 4 weeks) and rituximab (375 mg/m2 weekly) in the dose-escalation groups or utomilumab (1.2 mg/kg every 4 weeks) plus rituximab in the dose-expansion cohort. No patient experienced dose-limiting toxicity. The MTD for utomilumab in combination with rituximab was not reached and estimated to be ≥10 mg/kg every 4 weeks. The majority of the utomilumab treatment-related adverse events (AE) were grade 1 to 2; the most common AE was fatigue (16.4%). The pharmacokinetics of utomilumab in combination with rituximab was linear in the 0.03 to 10 mg/kg dose range. A low incidence (1.5%) of treatment-induced antidrug antibodies against utomilumab was observed. The objective response rate was 21.2% (95% CI, 12.1%–33.0%) in all patients with NHL, including four complete and 10 partial responses. Analysis of paired biopsies from a relapsed/refractory FL patient with complete response showed increased T-cell infiltration and cytotoxic activity in tumors. Biomarker correlations with outcomes suggested that clinical benefit may be contingent on patient immune function. Conclusions: Utomilumab in combination with rituximab demonstrated clinical activity and a favorable safety profile in patients with CD20+ NHLs.

Published
2020

2. Sustainable Diets for Cardiovascular Disease Prevention and Management

Author

Matthew J. Landry, Anthony Crimarco, Claire Bladier, Andrea S. Mendoza-Vasconez, Christopher D. Gardner, Stanford Prevention Research Center, Stanford Medicine, Stanford University-Stanford University, Direction de l'Evaluation des Risques (DER), Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES), and This work was supported by a training grant from the National Heart, Lung, and Blood Institute [T32 HL007034].

Subjects
Healthy eating pattern, MESH: Food Supply, Natural resource economics, Biodiversity, Context (language use), Cardiovascular disease prevention, 030204 cardiovascular system & hematology, Food Supply, 03 medical and health sciences, 0302 clinical medicine, MESH: Diet, Economic cost, Health care, Food choice, Humans, Medicine, 030212 general & internal medicine, Dietary patterns, 2. Zero hunger, MESH: Humans, Land use, business.industry, MESH: Cardiovascular Diseases, MESH: Diet, Healthy, 15. Life on land, Diet, Plant-based diets, 3. Good health, Sustainability, Cardiovascular Diseases, 13. Climate action, Agriculture, Diet, Healthy, Cardiology and Cardiovascular Medicine, business, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition
Abstract

Healthy dietary patterns are recommended for prevention of cardiovascular disease, which remains the leading cause of morbidity and mortality globally. In this review, we discuss dietary patterns that are not only optimal for CVD prevention and management but also sustainable in maximizing health, environmental, and economic benefits. The growing literature on sustainable diets in the context of environmental sustainability includes subtopics of climate change, land use, biodiversity loss, freshwater use, and reactive nitrogen emissions. Similarly, economic sustainability, beyond the retail cost of food, extends to healthcare costs and the economic costs of environmental destruction related to current agricultural practices and food choices. Dietary patterns that are high in plant foods and low in animal foods could maximize health, environmental, and economic benefits; however, questions remain about how to best promote these patterns to achieve wider adoption in an environmentally and economically sustainable way.

Published
2021

3. Dietary Protein and Amino Acids in Vegetarian Diets-A Review

Author

François Mariotti, Christopher D. Gardner, Physiologie de la Nutrition et du Comportement Alimentaire (PNCA), AgroParisTech-Institut National de la Recherche Agronomique (INRA), Stanford University [Stanford], Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Department of Medicine, Stanford Prevention Research Center, Stanford University School of Medicine [CA, USA]-Stanford University School of Medicine [CA, USA], and Stanford University

Subjects
0301 basic medicine, Amino acid deficiency, High energy, vegetarian diet, lcsh:TX341-641, 030209 endocrinology & metabolism, Review, Biology, Vegetarian diets, 03 medical and health sciences, 0302 clinical medicine, Environmental health, adults, Humans, 2. Zero hunger, chemistry.chemical_classification, adequacy, amino acids, 030109 nutrition & dietetics, Nutrition and Dietetics, Health professionals, Diet, Vegetarian, Nutritional Requirements, Vegan Diet, Nutritional status, protein requirement, vegan diet, protein intake, 3. Good health, Amino acid, Dietary protein, chemistry, Dietary Proteins, protein, lcsh:Nutrition. Foods and food supply, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition, Food Science
Abstract

International audience; While animal products are rich in protein, the adequacy of dietary protein intake from vegetarian/vegan diets has long been controversial. In this review, we examine the protein and amino acid intakes from vegetarian diets followed by adults in western countries and gather information in terms of adequacy for protein and amino acids requirements, using indirect and direct data to estimate nutritional status. We point out that protein-rich foods, such as traditional legumes, nuts and seeds, are sufficient to achieve full protein adequacy in adults consuming vegetarian/vegan diets, while the question of any amino acid deficiency has been substantially overstated. Our review addresses the adequacy in changes to protein patterns in people newly transitioning to vegetarian diets. We also specifically address this in older adults, where the issues linked to the protein adequacy of vegetarian diets are more complex. This contrasts with the situation in children where there are no specific concerns regarding protein adequacy because of their very high energy requirements compared to those of protein. Given the growing shifts in recommendations from nutrition health professionals for people to transition to more plant-based, whole-food diets, additional scientific evidence-based communications confirming the protein adequacy of vegetarian and vegan diets is warranted.

Published
2019

4. Classification and Evolution of Human Papillomavirus Genome Variants: Alpha-5 (HPV26, 51, 69, 82), Alpha-6 (HPV30, 53, 56, 66), Alpha-11 (HPV34, 73), Alpha-13 (HPV54) and Alpha-3 (HPV61)

Author

Ann W. Hsing, Mark Schiffman, Kathryn Anastos, Paul K.S. Chan, Patti E. Gravitt, Robert D. Burk, Michel Segondy, Vikrant V. Sahasrabuddhe, Rolando Herrero, Zigui Chen, Rob DeSalle, Department of Microbiology, the University of Hong Kong, The University of Hong Kong (HKU), National Cancer Institute [Bethesda] (NCI-NIH), National Institutes of Health [Bethesda] (NIH), Proyecto Epidemiológico Guanacaste, Fundación INCIENSA, San José, Costa Rica, Prevention and Implementation Group, International Agency for Research on Cancer, World Health Organization, France, The Sackler Institute of Comparative Genomics, American Museum of Natural History, Albert Einstein College of Medicine [New York], Pathogénèse et contrôle des infections chroniques (PCCI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre Hospitalier Universitaire de Montpellier (CHU Montpellier )-Université de Montpellier (UM), Milken Institute School of Public Health, The George Washington University (GW), Stanford Prevention Research Center, Stanford Medicine, and Stanford University-Stanford University

Subjects
0301 basic medicine, food.ingredient, Alpha (ethology), Genome, Viral, Alphapapillomavirus, Biology, Genome, Article, Evolution, Molecular, 03 medical and health sciences, food, Phylogenetics, Virology, Genetic variation, Humans, Human papillomavirus, Phylogeny, Genetics, Phylogenetic tree, Papillomavirus Infections, Genetic Variation, 030104 developmental biology, Capsid, [SDV.MP.VIR]Life Sciences [q-bio]/Microbiology and Parasitology/Virology, Female
Abstract

International audience; HPV variants from the same type can be classified into lineages and sublineages based on the complete genome differences and the phylogenetic topologies. We examined nucleotide variations of twelve HPV types within the species Alpha-5 (HPV26, 51, 69, 82), Alpha-6 (HPV30, 53, 56, 66), Alpha-11 (HPV34, 73), Alpha-13 (HPV54) and Alpha-3 (HPV61) by analyzing 1432 partial sequences and 181 complete genomes from multiple geographic populations. The inter-lineage and inter-sublineage mean differences of HPV variants ranged between 0.9-7.3% and 0.3-0.9%, respectively. The heterogeneity and phylogenies of HPV isolates indicate an independent evolutionary history for each type. The noncoding regions were the most variable regions whereas the capsid proteins were relatively conserved. Certain variant lineages and/or sublineages were geographically-associated. These data provide the basis to further classify HPV variants and should foster future studies on the evolution of HPV genomes and the associations of HPV variants with cancer risk.

Published
2018

5. A meta-analysis of genome-wide association studies identifies novel variants associated with osteoarthritis of the hip

Author

William E R Ollier, Gillian A. Wallis, Unnur Styrkarsdottir, Nicholas G. Martin, P. Eline Slagboom, Mike R. Reed, Helgi Jonsson, J. Mark Wilkinson, John P. A. Ioannidis, Aime Keis, Yolande F. M. Ramos, Daniel S. Evans, Penelope A. Lind, Stuart H. Ralston, Thorvaldur Ingvarsson, Andrew McCaskie, Konstantinos K. Tsilidis, Evangelos Evangelou, Kay Chapman, Tim D. Spector, Aaron G. Day-Williams, L. Stefan Lohmander, Aspasia Tsezou, Ashok Rai, Rob G H H Nelissen, Kari Stefansson, Cristina Rodriguez-Fontenla, Sarah Metrustry, Andres Metspalu, Kalliope Panoutsopoulou, Albert Hofman, Hanneke J. M. Kerkhof, John Loughlin, Panos Deloukas, Joyce B. J. van Meurs, Ana M. Valdes, Evangelia E. Ntzani, Lorraine Southam, José A. Riancho, J. Christiaan Keurentjes, Francisco J. Blanco, Gudmar Thorleifsson, Peter M. Nilsson, Ingrid Meulenbelt, Lili Milani, Fernando Rivadeneira, Michael C. Nevitt, Nicholas Bellamy, Nancy E Lane, Unnur Thorsteinsdottir, Grant W. Montgomery, Michael Doherty, Tõnu Esko, Ingileif Jonsdottir, Nigel K Arden, Hafdis T. Helgadottir, André G. Uitterlinden, Antonio Gonzalez, Steffan D. Bos, Margreet Kloppenburg, Andrew Carr, Eleftheria Zeggini, Gunnar Engström, N Aslam, Fraser Birrell, Neeta Parimi, Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece Department of Twin Research & Genetic Epidemiology, King's College London, London, UK. 2Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands. 3Department of Population Genetics, deCODE Genetics, Reykjavik, Iceland. 4Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece. 5Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands Netherlands Consortium for Healthy Ageing, The Netherlands. 6Estonian Genome Center, University of Tartu, Tartu, Estonia Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia. 7California Pacific Medical Center Research Institute, San Francisco, USA. 8Department of Twin Research & Genetic Epidemiology, King's College London, London, UK. 9Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton, UK. 10Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands. 11NIHR Biomedical Research Unit and ARUK Centre of excellence for Sport, Exercise and Osteoarthritis, University of Oxford, Oxford, UK MRC Epidemiology Resource Centre, University of Southampton, Southampton, UK. 12Worcestershire Royal Hospital, Worcestershire Acute Hospitals NHS Trust, Worcester, UK. 13Centre of National Research on Disability and Rehabilitation Medicine, The University of Queensland, Brisbane, Australia. 14Musculoskeletal Research Group, Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, UK Wansbeck General Hospital, Northumbria Healthcare NHS Foundation Trust, Ashington, UK. 15Rheumatology Division, Instituto de Investigación Biomédica-Hospital Universitario A Coruña, A Corunna, Spain. 16NIHR Biomedical Research Unit and ARUK Centre of excellence for Sport, Exercise and Osteoarthritis, University of Oxford, Oxford, UK. 17Department of Academic Rheumatology, University of Nottingham, Nottingham, UK. 18Department of Clinical Sciences Malmo, Lund University, Malmo, Sweden. 19Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands. 20Department of Orthopedic Surgery, Akureyri Hospital, Akureyri, Iceland School of Health Sciences, University of Akureyri, Akureyri, Iceland. 21Department of Medicine, The National University Hospital of Iceland, Reykjavik, Iceland Faculty of Medicine, University of Iceland, Reykjavik, Iceland. 22Department of Public Health, University of Tartu, Tartu, Estonia Orthopedic Surgeons, Elva Hospital, Elva, Estonia. 23Department of Orthopedics, Leiden University Medical Center, Leiden, The Netherlands. 24Department of Rheumatology, Leiden University Medical Center, Leiden, The Netherlands. 25Department of Quantitative Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia. 26Musculoskeletal Research Group, Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, UK. 27Department of Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia. 28Estonian Genome Center, University of Tartu, Tartu, Estonia. 29Department of Molecular Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia. 30Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California, USA. 31Centre for Integrated Genomic Medical Research, University of Manchester, Manchester, UK. 32Worcestershire Acute Hospitals NHS Trust, Worcester, UK. 33Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK. 34Wansbeck General Hospital, Northumbria Healthcare NHS Foundation Trust, Ashington, UK. 35Department of Internal Medicine, Hospital U.M. Valdecilla-IFIMAV, University of Cantabria, Santander, Spain. 36Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands. 37Laboratorio Investigacion 10 and Rheumatology Unit, Instituto de Investigacion Sanitaria-Hospital Clinico Universitario de Santiago, Santiago de Compostela, Spain. 38Department of Population Genetics, deCODE Genetics, Reykjavik, Iceland Department of Medicine, The National University Hospital of Iceland, Reykjavik, Iceland. 39Department of Biology, University of Thessaly, Medical School, Larissa, Greece. 40Wellcome Trust Centre for Cell-Matrix Research, University of Manchester, Manchester, UK. 41Department of Human Metabolism, University of Sheffield, Sheffield, UK. 42Department of Medicine, University of California at Davis, Sacramento, USA. 43Research Unit for Musculoskeletal Function and Physiotherapy, and Department of Orthopedics and Traumatology, University of Southern Denmark, Odense, Denmark Department of Clinical Sciences Lund, Lund University, Lund, Sweden. 44Department of Population Genetics, deCODE Genetics, Reykjavik, Iceland Faculty of Medicine, University of Iceland, Reykjavik, Iceland. 45Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece Stanford Prevention Research Center, Stanford University School of Medicine, Stanford, USA. 46Department of Twin Research & Genetic Epidemiology, King's College London, London, UK Department of Academic Rheumatology, University of Nottingham, Nottingham, UK., arcOGEN Consortium, Universidad de Cantabria, Medical Oncology, Epidemiology, and Internal Medicine

Subjects
Male, Aging, Epidemiology, Genome-wide association study, Calcium-Calmodulin-Dependent Protein Kinase Type 2/genetics, Bioinformatics, Osteoarthritis, Hip, Nuclear Receptor Coactivator 3, Gene Frequency, Grupo de Ascendencia Continental Europea, Immunology and Allergy, Medicine, 2.1 Biological and endogenous factors, Osteoarthritis, Hip/genetics, Aetiology, European Continental Ancestry Group/genetics, Gene polymorphism, Single Nucleotide, Protein-Tyrosine Kinases, Protein-Serine-Threonine Kinases, 3. Good health, Slitgigt, 1117 Public Health And Health Services, 1107 Immunology, Nuclear Receptor Coactivator 3/genetics, Female, arcOGEN Consortium, Frecuencia de los Genes, Protein-Serine-Threonine Kinases/genetics, Clinical Sciences, Immunology, European Continental Ancestry Group, Predisposición Genética a la Enfermedad, Single-nucleotide polymorphism, Locus (genetics), Protein Serine-Threonine Kinases, Public Health And Health Services, Polymorphism, Single Nucleotide, General Biochemistry, Genetics and Molecular Biology, Immediate early protein, White People, Proteína Quinasa Tipo 2 Dependiente de Calcio Calmodulina, Estudio de Asociación del Genoma Completo, Immediate-Early Proteins, Sex Factors, Rheumatology, Gene Polymorphism, Osteoarthritis, Genetics, Humans, Genetic Predisposition to Disease, Polymorphism, Allele frequency, Genetic association, Rheumatology and Autoimmunity, Homeodomain Proteins, Hip, Protein-Tyrosine Kinases/genetics, business.industry, Whites, Arthritis, Prevention, Human Genome, 1103 Clinical Sciences, Clinical and Epidemiological Research, Arfgengi, Immediate-Early Proteins/genetics, Arthritis & Rheumatology, Minor allele frequency, Musculoskeletal, Mjaðmir, HMGN Proteins, Osteoartritis de la Cadera, Homeodomain Proteins/genetics, business, Calcium-Calmodulin-Dependent Protein Kinase Type 2, HMGN Proteins/genetics, Genome-Wide Association Study
Abstract

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files. This article is open access. Osteoarthritis (OA) is the most common form of arthritis with a clear genetic component. To identify novel loci associated with hip OA we performed a meta-analysis of genome-wide association studies (GWAS) on European subjects. We performed a two-stage meta-analysis on more than 78,000 participants. In stage 1, we synthesised data from eight GWAS whereas data from 10 centres were used for 'in silico' or 'de novo' replication. Besides the main analysis, a stratified by sex analysis was performed to detect possible sex-specific signals. Meta-analysis was performed using inverse-variance fixed effects models. A random effects approach was also used. We accumulated 11,277 cases of radiographic and symptomatic hip OA. We prioritised eight single nucleotide polymorphism (SNPs) for follow-up in the discovery stage (4349 OA cases); five from the combined analysis, two male specific and one female specific. One locus, at 20q13, represented by rs6094710 (minor allele frequency (MAF) 4%) near the NCOA3 (nuclear receptor coactivator 3) gene, reached genome-wide significance level with p=7.9×10(-9) and OR=1.28 (95% CI 1.18 to 1.39) in the combined analysis of discovery (p=5.6×10(-8)) and follow-up studies (p=7.3×10(-4)). We showed that this gene is expressed in articular cartilage and its expression was significantly reduced in OA-affected cartilage. Moreover, two loci remained suggestive associated; rs5009270 at 7q31 (MAF 30%, p=9.9×10(-7), OR=1.10) and rs3757837 at 7p13 (MAF 6%, p=2.2×10(-6), OR=1.27 in male specific analysis). Novel genetic loci for hip OA were found in this meta-analysis of GWAS. info:eu-repo/grantAgreement/EC/FP7/200800 info:eu-repo/grantAgreement/EC/FP7/286213

Published
2014

6. Non-randomised Ebola trials-lessons for optimal outbreak research

Author

Bates, Matthew, Zumla, Alimuddin, Ippolito, Giuseppe, Lanini, Simone, Brouqui, Philippe, Di Caro, Antonino, Vairo, Francesco, Fusco, Francesco Maria, Krishna, Sanjeev, Capobianchi, Maria Rosaria, Kyobe-Bosa, Henry, Puro, Vincenzo, Woelfel, Roman, Avsic-Zupanc, Tatjana, Ioannidis, John P. A., Portella, Gina, Kremsner, Peter, Dar, Osman, University College of London [London] (UCL), Department for Infectious Diseases, National Institute for Infectious Diseases ‘‘Lazarro Spallanzani’’, Unité de Recherche sur les Maladies Infectieuses et Tropicales Emergentes (URMITE), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR48, INSB-INSB-Centre National de la Recherche Scientifique (CNRS), Hôpital Nord [CHU - APHM], Laboratory of microbiology and biorepository, INMI L. Spallanzani, Clinical Department, Institute for Infection and Immunity [Londres, UK], St George's, University of London, Laboratory of virology, 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, Institut des sciences biologiques (INSB-CNRS)-Institut des sciences biologiques (INSB-CNRS)-Centre National de la Recherche Scientifique (CNRS), and University of Ioannina

Subjects
[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases, ComputingMilieux_MISCELLANEOUS
Abstract

International audience; no abstract

Published
2016

7. Age at menopause, reproductive history, and venous thromboembolism risk among postmenopausal women: the Women's Health Initiative Hormone Therapy clinical trials

Author

Geneviève Plu-Bureau, Barbara B. Cochrane, Marianne Canonico, Marcia L. Stefanick, JoAnn E. Manson, Pierre-Yves Scarabin, Mary Jo O'Sullivan, Centre de recherche en épidémiologie et santé des populations (CESP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris-Sud - Paris 11 (UP11)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Université Paris Descartes - Paris 5 (UPD5), Recherche en épidémiologie et biostatistique, Université Paris-Sud - Paris 11 (UP11)-Institut National de la Santé et de la Recherche Médicale (INSERM), Maison du patrimoine Oral de Bourgogne (Anost) (MPOB), Stanford Prevention Research Center, Stanford Medicine, Stanford University-Stanford University, University of Washington [Seattle], Departments of Ophthalmology and Microbiology and Molecular Genetics, Harvard Medical School [Boston] (HMS), National Heart, Lung, and Blood Institute, Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Paris-Sud - Paris 11 (UP11)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM), SZTAJNBOK, Pascale, Centre de recherche en épidémiologie et santé des populations ( CESP ), Université de Versailles Saint-Quentin-en-Yvelines ( UVSQ ) -Université Paris-Sud - Paris 11 ( UP11 ) -Assistance publique - Hôpitaux de Paris (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale ( INSERM ), Université Paris Descartes - Paris 5 ( UPD5 ), Université Paris-Sud - Paris 11 ( UP11 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Maison du patrimoine Oral de Bourgogne ( MPO ), Maison du patrimoine Oral de Bourgogne, Stanford University School of Medicine, and Harvard Medical School [Boston] ( HMS )

Subjects
MESH : Venous Thromboembolism, MESH: Reproductive History, MESH: Menopause, medicine.medical_treatment, MESH : Aged, 030204 cardiovascular system & hematology, MESH: Venous Thromboembolism, MESH: Pregnancy, 0302 clinical medicine, MESH : Child, MESH: Risk Factors, Pregnancy, Risk Factors, MESH: Child, MESH : Female, 030212 general & internal medicine, Child, Reproductive History, MESH: Aged, Clinical Trials as Topic, MESH : Estrogen Replacement Therapy, MESH: Middle Aged, Obstetrics, Women's Health Initiative, Hazard ratio, Estrogen Replacement Therapy, MESH : Menopause, Age Factors, MESH : Menarche, Obstetrics and Gynecology, [ SDV.SPEE ] Life Sciences [q-bio]/Santé publique et épidémiologie, Venous Thromboembolism, MESH : Adult, Middle Aged, MESH : Risk Factors, 3. Good health, MESH : Women's Health, Menopause, Postmenopause, Parity, MESH : Ovariectomy, MESH: Menarche, MESH : Postmenopause, Menarche, Female, MESH: Postmenopause, Adult, medicine.medical_specialty, MESH: Clinical Trials as Topic, Adolescent, Ovariectomy, MESH: Ovariectomy, Article, 03 medical and health sciences, MESH : Adolescent, MESH : Reproductive History, medicine, Humans, MESH : Middle Aged, cardiovascular diseases, MESH : Parity, Aged, MESH: Adolescent, MESH: Age Factors, Gynecology, MESH: Humans, Proportional hazards model, business.industry, MESH : Humans, MESH: Parity, Oophorectomy, MESH: Adult, equipment and supplies, medicine.disease, MESH: Estrogen Replacement Therapy, MESH : Clinical Trials as Topic, MESH : Pregnancy, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Women's Health, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, MESH : Age Factors, Hormone therapy, business, MESH: Women's Health, MESH: Female
Abstract

International audience; This study aims to investigate venous thromboembolism (VTE) risk in relation to age at menopause, age at menarche, parity, bilateral oophorectomy, and time since menopause, as well as any interaction with randomized hormone therapy (HT) assignment, among postmenopausal women. Using pooled data from the Women's Health Initiative HT clinical trials including 27,035 postmenopausal women aged 50 to 79 years who had no history of VTE, we assessed the risk of VTE in relation to age at menopause, age at menarche, parity, bilateral oophorectomy, and time since menopause by Cox proportional hazards models. Linear trends, quadratic relationships, and interactions of reproductive life characteristics with HT on VTE risk were systematically tested. During follow-up, 426 women reported a first VTE, including 294 non-procedure-related events. No apparent interaction of reproductive life characteristics with HT assignment on VTE risk was detected, and there was not a significant association between VTE and age at menarche, age at menopause, parity, oophorectomy, or time since menopause. However, analyses restricted to non-procedure-related VTE showed a U-shaped relationship between age at menopause and thrombotic risk that persisted after multivariable analysis (P < 0.01). Compared with women aged 40 to 49 years at menopause, those who had early menopause (age 55 y) had a significantly increased VTE risk (hazard ratio [95% CI]: 1.8 [1.2-2.7] and 1.5 [1.0-2.4], respectively). Reproductive life characteristics have little association with VTE and do not seem to influence the effect of HT on thrombotic risk among postmenopausal women. Nevertheless, early and late onset of menopause might be newly identified risk factors for non-procedure-related VTE.

Published
2013

8. 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

9. Strengthening the reporting of genetic risk prediction studies: the GRIPS statement

Author

A Cecile J W, Janssens, John P A, Ioannidis, Cornelia M, van Duijn, Julian, Little, Muin J, Khoury, Epidemiology, Department of Epidemiology, 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, Epidemiology and Community Medicine, University of Ottawa [Ottawa], Office of Public Health Genomics, and Centers for Disease Control and Prevention

Subjects
Epidemiology, Statement (logic), Applied psychology, Psychological intervention, Genome-wide association study, Disease, Strengthening the reporting of observational studies in epidemiology, 0302 clinical medicine, Multidisciplinary approach, Health care, Medicine, Genetics(clinical), Genetic risk, General Environmental Science, 0303 health sciences, GRIPS, Genomics, General Medicine, Reporting guideline, 3. Good health, Systematic review, Risk analysis (engineering), 030220 oncology & carcinogenesis, DOAJ:Health Sciences, Cardiology and Cardiovascular Medicine, Genetic Markers, medicine.medical_specialty, Guidelines as Topic, Human genomics, Disclosure, Genetics and Genomics/Complex Traits, Guidelines, Risk Assessment, Education, Molecular Genetics, 03 medical and health sciences, Genetic, SDG 3 - Good Health and Well-being, Drugs: Cardiovascular System, Correspondence, Genetics, Humans, Genetic Testing, Molecular Biology, Developing Countries, Genetic testing, Genetic association, Models, Statistical, Public health, lcsh:R, Methodology, Genetic risk models, lcsh:RA1-1270, Guideline, body regions, Epidemiologic Studies, Genetic epidemiology, Reporting, Public Health and Epidemiology/Preventive Medicine, Observational study, Gene Discovery, Research design, Public Health and Epidemiology/Screening, Operations research, lcsh:Medicine, 030204 cardiovascular system & hematology, Bioinformatics, Guidelines and Guidance, Risk model, Risk Factors, 030212 general & internal medicine, Genetics (clinical), Framingham Risk Score, medicine.diagnostic_test, lcsh:Public aspects of medicine, General Engineering, Risk factor (computing), Risk prediction, Checklist, Predictive factor, Policy, Research Design, Practice Guidelines as Topic, Molecular Medicine, Psychology, Risk assessment, Genetic Research, Digital content, Genetic counseling, MEDLINE, Internal Medicine, Research Methods & Reporting, Genetic Predisposition to Disease, 030304 developmental biology, Publishing, Actuarial science, Models, Genetic, Extramural, Genome, Human, business.industry, Research, Genetics and Genomics, DOAJ:Public Health, General Earth and Planetary Sciences, Interdisciplinary Communication, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Artificial intelligence, Public Health and Epidemiology/Epidemiology, business, Forecasting, Genome-Wide Association Study
Abstract

The recent successes of genome-wide association studies and the promises of whole genome sequencing fuel interest in the translation of this new wave of basic genetic knowledge to health care practice. Knowledge about genetic risk factors may be used to target diagnostic, preventive, and therapeutic interventions for complex disorders based on a person's genetic risk, or to complement existing risk models based on classical nongenetic factors, such as the Framingham risk score for cardiovascular disease. Implementation of genetic risk prediction in health care requires a series of studies that encompass all phases of translational research,1,2 starting with a comprehensive evaluation of genetic risk prediction. With increasing numbers of discovered genetic markers that can be used in future genetic risk prediction studies, it is crucial to enhance the quality of the reporting of these studies, since valid interpretation could be compromised by the lack of reporting of key information. Information that is often missing includes details in the description of how the study was designed and conducted (eg, how genetic variants were selected and coded, how risk models or genetic risk scores were constructed, and how risk categories were chosen), or how the results should be interpreted. An appropriate assessment of the study's strengths and weaknesses is not possible without this information. There is ample evidence that prediction research often suffers from poor design and bias, and these may also have an impact on the results of the studies and on models of disease outcomes based on these studies.3–5 Although most prognostic studies published to date claim significant results,6,7 very few translate to clinically useful applications. Just as for observational epidemiological studies,8 poor reporting complicates the use of the specific study for research, clinical, or public health purposes and hampers the …

Published
2011

10. Preventable breast cancer is postmenopausal

Author

Seyed Mohsen Mousavi, Asta Försti, Kari Hemminki, Jan Sundquist, Division of Molecular Genetic Epidemiology, German Cancer Research Center - Deutsches Krebsforschungszentrum [Heidelberg] (DKFZ), Center for Primary Care Research, Lund University [Lund], Center for Family and Community Medicine, karolinska institute, Stanford Prevention Research Center, Stanford Medicine, Stanford University-Stanford University, Cancer Research Center of Cancer Institute, and Tehran University of Medical Sciences

Subjects
Adult, Cancer Research, medicine.medical_specialty, Time Factors, Emigrants and Immigrants, Breast Neoplasms, Ethnic origin, Risk Assessment, White People, Danish, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Breast cancer, Age Distribution, Asian People, Risk Factors, Epidemiology, Ethnic differences, medicine, Humans, 030212 general & internal medicine, Environmental effect, Risk factor, Aged, Sweden, business.industry, Incidence (epidemiology), Incidence, Incidence change, Age Factors, Cancer, Middle Aged, medicine.disease, language.human_language, 3. Good health, Surgery, Postmenopause, Oncology, Databases as Topic, Age-incidence, 030220 oncology & carcinogenesis, language, Female, Breast disease, business, Demography
Abstract

International audience; Breast cancer incidence has markedly increased in Western countries for reasons that are not entirely understood. We characterized periodic and age-specific incidence trends of breast cancer in immigrants who migrated from low incidence areas to Sweden. The incidence in immigrants was compared to that in native Swedes and standardized incidence ratios (SIRs) were calculated, based on the Swedish Family-Cancer Database. Age-specific incidence data for low and high incidence populations were obtained from Cancer Incidence in Five Continents IX and NORDCAN. For immigrants from the seven lowest countries/regions 535 breast cancers were identified; the SIRs ranging from 0.45 for Turkish to 0.70 for Greek women. The SIR increased somewhat with the length of stay in Sweden, from 0.55 for stay between 0 and 10 years to 0.59 for a stay of 20+ years. The age-specific incidence curves for these immigrants were superimposable upon the earliest Swedish (year 1960) or Danish (1943) rates. These rates differed from the current Swedish rates by a much lower postmenopausal component. Large incidence differences were also observed between white Californians and immigrants from China and Korea. Our results show that the main difference between high and low incidence areas is in postmenopausal cancer which has increased preferentially during the past century. Immigrants from low risk areas to Sweden show age-specific incidence patterns of Swedes half a century ago. These differences offer opportunities for the identification of factors underlying breast cancer etiology and tools for prevention.

Published
2010

11. Breast cancer risk in women who fulfill high-risk criteria: at what age should surveillance start?

Author

Justo Lorenzo Bermejo, Jan Sundquist, Andreas Brandt, Kari Hemminki, Division of Molecular Genetic Epidemiology, German Cancer Research Center - Deutsches Krebsforschungszentrum [Heidelberg] (DKFZ), Institute of Medical Biometry and Informatics, University Hospital Heidelberg, Center for Primary Care Research, Lund University [Lund], Stanford Prevention Research Center, Stanford Medicine, and Stanford University-Stanford University

Subjects
Oncology, Cancer Research, medicine.medical_specialty, Age of onset, Psychological intervention, Breast Neoplasms, 03 medical and health sciences, 0302 clinical medicine, Breast cancer, Risk Factors, Internal medicine, medicine, Humans, Mass Screening, Genetic Predisposition to Disease, Registries, Family history, 030304 developmental biology, Proportional Hazards Models, Hereditary breast cancer, 0303 health sciences, Hereditary breast–ovarian cancer syndrome, Proportional hazards model, business.industry, Hazard ratio, Age Factors, Middle Aged, medicine.disease, 3. Good health, Pedigree, 030220 oncology & carcinogenesis, Relative risk, Female, Clinical risk criteria, business, Familial breast cancer, Demography
Abstract

International audience; Family history is a strong predictor of hereditary breast cancer, particularly when it includes cases of early onset or bilateral breast cancers and multiple cases of breast or ovarian cancers. This article provides relative risks and cumulative risks of breast cancer in women whose family history indicates high risk. Specifically, the aim was to determine how many years earlier the high-risk women reach the cumulative risk of women without family history at the age at which screening in average-risk women is initiated. The women of the nation-wide Swedish Family-Cancer Database were classified according to clinical criteria based on family history suggesting high risk for hereditary breast ovarian cancer syndrome. The relative risks of breast cancer were calculated as hazard ratio using Cox regression. Cumulative risks of breast cancer were estimated with a stratified Cox model based on Tsiatis' method. The hazard ratios of breast cancer for the considered criteria ranged from 1.50 to 5.99. The cumulative risks ranged from 1 to 10% by age 50 years. The age to reach the same cumulative risk as women lacking a family history at the age of 50 years ranged between 32.0 and 40.8 years. Relative and cumulative risks of women at high risk of breast cancer associated with different clinical criteria were diverse, which may be helpful in considering when current clinical criteria are revised. According to the present results, current recommendations of starting clinical interventions 10 years earlier in high-risk women, based on expert opinions, appear justified at least for the largest high-risk groups.

Published
2009

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