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  • Naghavi, Mohsen, et al. (författare)
  • Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013
  • 2015
  • Ingår i: The Lancet. - : Elsevier. - 1474-547X .- 0140-6736. ; 385:9963, s. 117-171
  • Tidskriftsartikel (refereegranskat)abstract
    • Background Up-to-date evidence on levels and trends for age-sex-specifi c all-cause and cause-specifi c mortality is essential for the formation of global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013) we estimated yearly deaths for 188 countries between 1990, and 2013. We used the results to assess whether there is epidemiological convergence across countries. Methods We estimated age-sex-specifi c all-cause mortality using the GBD 2010 methods with some refinements to improve accuracy applied to an updated database of vital registration, survey, and census data. We generally estimated cause of death as in the GBD 2010. Key improvements included the addition of more recent vital registration data for 72 countries, an updated verbal autopsy literature review, two new and detailed data systems for China, and more detail for Mexico, UK, Turkey, and Russia. We improved statistical models for garbage code redistribution. We used six different modelling strategies across the 240 causes; cause of death ensemble modelling (CODEm) was the dominant strategy for causes with sufficient information. Trends for Alzheimer's disease and other dementias were informed by meta-regression of prevalence studies. For pathogen-specifi c causes of diarrhoea and lower respiratory infections we used a counterfactual approach. We computed two measures of convergence (inequality) across countries: the average relative difference across all pairs of countries (Gini coefficient) and the average absolute difference across countries. To summarise broad findings, we used multiple decrement life-tables to decompose probabilities of death from birth to exact age 15 years, from exact age 15 years to exact age 50 years, and from exact age 50 years to exact age 75 years, and life expectancy at birth into major causes. For all quantities reported, we computed 95% uncertainty intervals (UIs). We constrained cause-specific fractions within each age-sex-country-year group to sum to all-cause mortality based on draws from the uncertainty distributions. Findings Global life expectancy for both sexes increased from 65.3 years (UI 65.0-65.6) in 1990, to 71.5 years (UI 71.0-71.9) in 2013, while the number of deaths increased from 47.5 million (UI 46.8-48.2) to 54.9 million (UI 53.6-56.3) over the same interval. Global progress masked variation by age and sex: for children, average absolute diff erences between countries decreased but relative diff erences increased. For women aged 25-39 years and older than 75 years and for men aged 20-49 years and 65 years and older, both absolute and relative diff erences increased. Decomposition of global and regional life expectancy showed the prominent role of reductions in age-standardised death rates for cardiovascular diseases and cancers in high-income regions, and reductions in child deaths from diarrhoea, lower respiratory infections, and neonatal causes in low-income regions. HIV/AIDS reduced life expectancy in southern sub-Saharan Africa. For most communicable causes of death both numbers of deaths and age-standardised death rates fell whereas for most non-communicable causes, demographic shifts have increased numbers of deaths but decreased age-standardised death rates. Global deaths from injury increased by 10.7%, from 4.3 million deaths in 1990 to 4.8 million in 2013; but age-standardised rates declined over the same period by 21%. For some causes of more than 100 000 deaths per year in 2013, age-standardised death rates increased between 1990 and 2013, including HIV/AIDS, pancreatic cancer, atrial fibrillation and flutter, drug use disorders, diabetes, chronic kidney disease, and sickle-cell anaemias. Diarrhoeal diseases, lower respiratory infections, neonatal causes, and malaria are still in the top five causes of death in children younger than 5 years. The most important pathogens are rotavirus for diarrhoea and pneumococcus for lower respiratory infections. Country-specific probabilities of death over three phases of life were substantially varied between and within regions. Interpretation For most countries, the general pattern of reductions in age-sex specifi c mortality has been associated with a progressive shift towards a larger share of the remaining deaths caused by non-communicable disease and injuries. Assessing epidemiological convergence across countries depends on whether an absolute or relative measure of inequality is used. Nevertheless, age-standardised death rates for seven substantial causes are increasing, suggesting the potential for reversals in some countries. Important gaps exist in the empirical data for cause of death estimates for some countries; for example, no national data for India are available for the past decade.
  • Forouzanfar, Mohammad H., et al. (författare)
  • Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015 : a systematic analysis for the Global Burden of Disease Study 2015
  • 2016
  • Ingår i: The Lancet. - : Elsevier. - 0140-6736 .- 1474-547X. ; 388:10053, s. 1659-1724
  • Tidskriftsartikel (refereegranskat)abstract
    • Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors-the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57.8% (95% CI 56.6-58.8) of global deaths and 41.2% (39.8-42.8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211.8 million [192.7 million to 231.1 million] global DALYs), smoking (148.6 million [134.2 million to 163.1 million]), high fasting plasma glucose (143.1 million [125.1 million to 163.5 million]), high BMI (120.1 million [83.8 million to 158.4 million]), childhood undernutrition (113.3 million [103.9 million to 123.4 million]), ambient particulate matter (103.1 million [90.8 million to 115.1 million]), high total cholesterol (88.7 million [74.6 million to 105.7 million]), household air pollution (85.6 million [66.7 million to 106.1 million]), alcohol use (85.0 million [77.2 million to 93.0 million]), and diets high in sodium (83.0 million [49.3 million to 127.5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Copyright (C) The Author(s). Published by Elsevier Ltd.
  • Antoniou, A. C., et al. (författare)
  • Common variants in LSP1, 2q35 and 8q24 and breast cancer risk for BRCA1 and BRCA2 mutation carriers
  • 2009
  • Ingår i: Human Molecular Genetics. - [Antoniou, Antonis C.; McGuffog, Lesley; Peock, Susan; Cook, Margaret; Frost, Debra; Oliver, Clare; Platte, Radka; Pooley, Karen A.; Easton, Douglas F.] Univ Cambridge, Dept Publ Hlth & Primary Care, Canc Res UK Genet Epidemiol Unit, Cambridge, England. [Sinilnikova, Olga M.; Leone, Melanie] Univ Lyon, CNRS, Hosp Civils Lyon,Ctr Leon Berard,UMR5201, Unite Mixte Genet Constitut Canc Frequents, Lyon, France. [Healey, Sue; Spurdle, Amanda B.; Beesley, Jonathan; Chen, Xiaoqing; Chenevix-Trench, Georgia] Queensland Inst Med Res, Brisbane, Qld 4029, Australia. [Nevanlinna, Heli; Heikkinen, Tuomas] Univ Helsinki, Cent Hosp, Dept Obstet & Gynecol, FIN-00290 Helsinki, Finland. [Simard, Jacques] Univ Laval, Quebec City, PQ, Canada. [Simard, Jacques] Univ Quebec, Ctr Hosp, Canada Res Chair Oncogenet, Canc Genom Lab, Quebec City, PQ, Canada. Peter MacCallum Canc Inst, Melbourne, Vic 3002, Australia. [Neuhausen, Susan L.; Ding, Yuan C.] Univ Calif Irvine, Dept Epidemiol, Irvine, CA USA. [Couch, Fergus J.; Wang, Xianshu; Fredericksen, Zachary] Mayo Clin, Rochester, MN USA. [Peterlongo, Paolo; Peissel, Bernard; Radice, Paolo] Fdn IRCCS Ist Nazl Tumori, Milan, Italy. [Peterlongo, Paolo; Radice, Paolo] Fdn Ist FIRC Oncol Molecolare, Milan, Italy. [Bonanni, Bernardo; Bernard, Loris] Ist Europeo Oncol, Milan, Italy. [Viel, Alessandra] IRCCS, Ctr Riferimento Oncol, Aviano, Italy. [Bernard, Loris] Cogentech, Consortium Genom Technol, Milan, Italy. [Szabo, Csilla I.] Mayo Clin, Coll Med, Dept Lab Med & Pathol, Rochester, MN USA. [Foretova, Lenka] Masaryk Mem Canc Inst, Dept Canc Epidemiol & Genet, Brno, Czech Republic. [Zikan, Michal] Charles Univ Prague, Dept Biochem & Expt Oncol, Fac Med 1, Prague, Czech Republic. [Claes, Kathleen] Ghent Univ Hosp, Ctr Med Genet, B-9000 Ghent, Belgium. [Greene, Mark H.; Mai, Phuong L.] US Natl Canc Inst, Clin Genet Branch, Rockville, MD USA. [Rennert, Gad; Lejbkowicz, Flavio] CHS Natl Canc Control Ctr, Haifa, Israel. [Rennert, Gad; Lejbkowicz, Flavio] Carmel Hosp, Dept Community Med & Epidemiol, Haifa, Israel. [Rennert, Gad; Lejbkowicz, Flavio] B Rappaport Fac Med, Haifa, Israel. [Andrulis, Irene L.; Glendon, Gord] Canc Care Ontario, Ontario Canc Genet Network, Toronto, ON M5G 2L7, Canada. [Andrulis, Irene L.] Mt Sinai Hosp, Fred A Litwin Ctr Canc Genet, Samuel Lunenfeld Res Inst, Toronto, ON, Canada. [Andrulis, Irene L.] Univ Toronto, Dept Mol Genet, Toronto, ON, Canada. [Gerdes, Anne-Marie; Thomassen, Mads] Odense Univ Hosp, Dept Biochem Pharmacol & Genet, DK-5000 Odense, Denmark. [Sunde, Lone] Aarhus Univ Hosp, Dept Clin Genet, DK-8000 Aarhus, Denmark. [Caligo, Maria A.] Univ Pisa, Div Surg Mol & Ultrastructural Pathol, Dept Oncol, Pisa, Italy. [Caligo, Maria A.] Pisa Univ Hosp, Pisa, Italy. [Laitman, Yael; Kontorovich, Tair; Cohen, Shimrit; Friedman, Eitan] Chaim Sheba Med Ctr, Susanne Levy Gertner Oncogenet Unit, IL-52621 Tel Hashomer, Israel. [Kaufman, Bella] Chaim Sheba Med Ctr, Inst Oncol, IL-52621 Tel Hashomer, Israel. [Kaufman, Bella; Friedman, Eitan] Tel Aviv Univ, Sackler Sch Med, IL-69978 Tel Aviv, Israel. [Dagan, Efrat; Baruch, Ruth Gershoni] Rambam Med Ctr, Genet Inst, Haifa, Israel. [Harbst, Katja] Lund Univ, Dept Oncol, S-22100 Lund, Sweden. [Barbany-Bustinza, Gisela; Rantala, Johanna] Karolinska Univ Hosp, Dept Clin Genet, Stockholm, Sweden. [Ehrencrona, Hans] Uppsala Univ, Dept Genet & Pathol, Uppsala, Sweden. [Karlsson, Per] Sahlgrenska Univ, Dept Oncol, Gothenburg, Sweden. [Domchek, Susan M.; Nathanson, Katherine L.] Univ Penn, Philadelphia, PA 19104 USA. [Osorio, Ana; Benitez, Javier] Ctr Invest Biomed Red Enfermedades Raras CIBERERE, Inst Salud Carlos III, Madrid, Spain. [Osorio, Ana; Benitez, Javier] Spanish Natl Canc Ctr CNIO, Human Canc Genet Programme, Human Genet Grp, Madrid, Spain. [Blanco, Ignacio] Catalan Inst Oncol ICO, Canc Genet Counseling Program, Barcelona, Spain. [Lasa, Adriana] Hosp Santa Creu & Sant Pau, Genet Serv, Barcelona, Spain. [Hamann, Ute] Deutsch Krebsforschungszentrum, Neuenheimer Feld 580 69120, D-6900 Heidelberg, Germany. [Hogervorst, Frans B. L.] Netherlands Canc Inst, Dept Pathol, Family Canc Clin, NL-1066 CX Amsterdam, Netherlands. [Rookus, Matti A.] Netherlands Canc Inst, Dept Epidemiol, Amsterdam, Netherlands. [Collee, J. Margriet] Erasmus Univ, Dept Clin Genet, Rotterdam Family Canc Clin, Med Ctr, NL-3000 DR Rotterdam, Netherlands. [Devilee, Peter] Dept Genet Epidemiol, Leiden, Netherlands. [Wijnen, Juul] Leiden Univ, Med Ctr, Ctr Human & Clin Genet, Leiden, Netherlands. [Ligtenberg, Marjolijn J.] Radboud Univ Nijmegen, Med Ctr, Dept Human Genet, NL-6525 ED Nijmegen, Netherlands. [van der Luijt, Rob B.] Univ Utrecht, Med Ctr, Dept Clin Mol Genet, NL-3508 TC Utrecht, Netherlands. [Aalfs, Cora M.] Univ Amsterdam, Acad Med Ctr, Dept Clin Genet, NL-1105 AZ Amsterdam, Netherlands. [Waisfisz, Quinten] Vrije Univ Amsterdam, Med Ctr, Dept Clin Genet, Amsterdam, Netherlands. [van Roozendaal, Cornelis E. P.] Univ Med Ctr, Dept Clin Genet, Maastricht, Netherlands. [Evans, D. Gareth; Lalloo, Fiona] Cent Manchester Univ Hosp, NHS Fdn Trust, Manchester Acad Hlth Sci Ctr, Manchester, Lancs, England. [Eeles, Rosalind] Inst Canc Res, Translat Canc Genet Team, London SW3 6JB, England. [Eeles, Rosalind] Royal Marsden NHS Fdn Trust, London, England. [Izatt, Louise] Guys Hosp, Clin Genet, London SE1 9RT, England. [Davidson, Rosemarie] Ferguson Smith Ctr Clin Genet, Glasgow, Lanark, Scotland. [Chu, Carol] Yorkshire Reg Genet Serv, Leeds, W Yorkshire, England. [Eccles, Diana] Princess Anne Hosp, Wessex Clin Genet Serv, Southampton, Hants, England. [Cole, Trevor] Birmingham Womens Hosp Healthcare, NHS Trust, W Midlands Reg Genet Serv, Birmingham, W Midlands, England. [Hodgson, Shirley] Univ London, Dept Canc Genet, St Georges Hosp, London, England. [Godwin, Andrew K.; Daly, Mary B.] Fox Chase Canc Ctr, Philadelphia, PA 19111 USA. [Stoppa-Lyonnet, Dominique] Univ Paris 05, Paris, France. [Stoppa-Lyonnet, Dominique] Inst Curie, INSERM U509, Serv Genet Oncol, Paris, France. [Buecher, Bruno] Inst Curie, Dept Genet, Paris, France. [Bressac-de Paillerets, Brigitte; Remenieras, Audrey; Lenoir, Gilbert M.] Inst Cancrol Gustave Roussy, Dept Genet, Villejuif, France. [Bressac-de Paillerets, Brigitte] Inst Cancerol Gustave Roussy, INSERM U946, Villejuif, France. [Caron, Olivier] Inst Cancerol Gustave Roussy, Dept Med, Villejuif, France. [Lenoir, Gilbert M.] Inst Cancerol Gustave Roussy, CNRS FRE2939, Villejuif, France. [Sevenet, Nicolas; Longy, Michel] Inst Bergonie, Lab Genet Constitutionnelle, Bordeaux, France. [Longy, Michel] Inst Bergonie, INSERM U916, Bordeaux, France. [Ferrer, Sandra Fert] Hop Hotel Dieu, Ctr Hosp, Lab Genet Chromosom, Chambery, France. [Prieur, Fabienne] CHU St Etienne, Serv Genet Clin Chromosom, St Etienne, France. [Goldgar, David] Univ Utah, Dept Dermatol, Salt Lake City, UT 84112 USA. [Miron, Alexander; Yassin, Yosuf] Dana Farber Canc Inst, Boston, MA 02115 USA. [John, Esther M.] No Calif Canc Ctr, Fremont, CA USA. [John, Esther M.] Stanford Univ, Sch Med, Stanford, CA 94305 USA. [Buys, Saundra S.] Univ Utah, Hlth Sci Ctr, Huntsman Canc Inst, Salt Lake City, UT USA. [Hopper, John L.] Univ Melbourne, Melbourne, Australia. [Terry, Mary Beth] Columbia Univ, New York, NY USA. [Singer, Christian; Gschwantler-Kaulich, Daphne; Staudigl, Christine] Med Univ Vienna, Div Special Gynecol, Dept OB GYN, Vienna, Austria. [Hansen, Thomas V. O.] Univ Copenhagen, Rigshosp, Dept Clin Biochem, DK-2100 Copenhagen, Denmark. [Barkardottir, Rosa Bjork] Landspitali Univ Hosp, Dept Pathol, Reykjavik, Iceland. [Kirchhoff, Tomas; Pal, Prodipto; Kosarin, Kristi; Offit, Kenneth] Mem Sloan Kettering Canc Ctr, Dept Med, Clin Genet Serv, New York, NY 10021 USA. [Piedmonte, Marion] Roswell Pk Canc Inst, GOG Stat & Data Ctr, Buffalo, NY 14263 USA. [Rodriguez, Gustavo C.] Evanston NW Healthcare, NorthShore Univ Hlth Syst, Evanston, IL 60201 USA. [Wakeley, Katie] Tufts Univ, New England Med Ctr, Boston, MA 02111 USA. [Boggess, John F.] Univ N Carolina, Chapel Hill, NC 27599 USA. [Basil, Jack] St Elizabeth Hosp, Edgewood, KY 41017 USA. [Schwartz, Peter E.] Yale Univ, Sch Med, New Haven, CT 06510 USA. [Blank, Stephanie V.] New York Univ, Sch Med, New York, NY 10016 USA. [Toland, Amanda E.] Ohio State Univ, Dept Internal Med, Columbus, OH 43210 USA. [Toland, Amanda E.] Ohio State Univ, Div Human Canc Genet, Ctr Comprehens Canc, Columbus, OH 43210 USA. [Montagna, Marco; Casella, Cinzia] IRCCS, Ist Oncologico Veneto, Immunol & Mol Oncol Unit, Padua, Italy. [Imyanitov, Evgeny N.] NN Petrov Inst Res Inst, St Petersburg, Russia. [Allavena, Anna] Univ Turin, Dept Genet Biol & Biochem, Turin, Italy. [Schmutzler, Rita K.; Versmold, Beatrix; Arnold, Norbert] Univ Cologne, Dept Obstet & Gynaecol, Div Mol Gynaeco Oncol, Cologne, Germany. [Engel, Christoph] Univ Leipzig, Inst Med Informat Stat & Epidemiol, Leipzig, Germany. [Meindl, Alfons] Tech Univ Munich, Dept Obstet & Gynaecol, Munich, Germany. [Ditsch, Nina] Univ Munich, Dept Obstet & Gynecol, Munich, Germany. Univ Schleswig Holstein, Dept Obstet & Gynaecol, Campus Kiel, Germany. [Niederacher, Dieter] Univ Duesseldorf, Dept Obstet & Gynaecol, Mol Genet Lab, Dusseldorf, Germany. [Deissler, Helmut] Univ Ulm, Dept Obstet & Gynaecol, Ulm, Germany. [Fiebig, Britta] Univ Regensburg, Inst Human Genet, Regensburg, Germany. [Suttner, Christian] Univ Heidelberg, Inst Human Genet, Heidelberg, Germany. [Schoenbuchner, Ines] Univ Wurzburg, Inst Human Genet, D-8700 Wurzburg, Germany. [Gadzicki, Dorothea] Med Univ, Inst Cellular & Mol Pathol, Hannover, Germany. [Caldes, Trinidad; de la Hoya, Miguel] Hosp Clinico San Carlos 28040, Madrid, Spain. : Oxford University Press. - 0964-6906 .- 1460-2083. ; 18:22, s. 4442-4456
  • Tidskriftsartikel (refereegranskat)abstract
    • Genome-wide association studies of breast cancer have identified multiple single nucleotide polymorphisms (SNPs) that are associated with increased breast cancer risks in the general population. In a previous study, we demonstrated that the minor alleles at three of these SNPs, in FGFR2, TNRC9 and MAP3K1, also confer increased risks of breast cancer for BRCA1 or BRCA2 mutation carriers. Three additional SNPs rs3817198 at LSP1, rs13387042 at 2q35 and rs13281615 at 8q24 have since been reported to be associated with breast cancer in the general population, and in this study we evaluated their association with breast cancer risk in 9442 BRCA1 and 5665 BRCA2 mutation carriers from 33 study centres. The minor allele of rs3817198 was associated with increased breast cancer risk only for BRCA2 mutation carriers [hazard ratio (HR) = 1.16, 95% CI: 1.07-1.25, P-trend = 2.8 × 10-4]. The best fit for the association of SNP rs13387042 at 2q35 with breast cancer risk was a dominant model for both BRCA1 and BRCA2 mutation carriers (BRCA1: HR = 1.14, 95% CI: 1.04-1.25, P = 0.0047; BRCA2: HR = 1.18 95% CI: 1.04-1.33, P = 0.0079). SNP rs13281615 at 8q24 was not associated with breast cancer for either BRCA1 or BRCA2 mutation carriers, but the estimated association for BRCA2 mutation carriers (per-allele HR = 1.06, 95% CI: 0.98-1.14) was consistent with odds ratio estimates derived from population-based case-control studies. The LSP1 and 2q35 SNPs appear to interact multiplicatively on breast cancer risk for BRCA2 mutation carriers. There was no evidence that the associations vary by mutation type depending on whether the mutated protein is predicted to be stable or not. 
  • Antoniou, A. C., et al. (författare)
  • Common breast cancer susceptibility alleles and the risk of breast cancer for BRCA1 and BRCA2 mutation carriers : Implications for risk prediction
  • 2010
  • Ingår i: Cancer Research. - : American Association for Cancer Research. - 0008-5472 .- 1538-7445. ; 70:23, s. 9742-9754
  • Tidskriftsartikel (refereegranskat)abstract
    • The known breast cancer susceptibility polymorphisms in FGFR2, TNRC9/TOX3, MAP3K1, LSP1, and 2q35 confer increased risks of breast cancer for BRCA1 or BRCA2 mutation carriers. We evaluated the associations of 3 additional single nucleotide polymorphisms (SNPs), rs4973768 in SLC4A7/NEK10, rs6504950 in STXBP4/COX11, and rs10941679 at 5p12, and reanalyzed the previous associations using additional carriers in a sample of 12,525 BRCA1 and 7,409 BRCA2 carriers. Additionally, we investigated potential interactions between SNPs and assessed the implications for risk prediction. The minor alleles of rs4973768 and rs10941679 were associated with increased breast cancer risk for BRCA2 carriers (per-allele HR = 1.10, 95% CI: 1.03-1.18, P = 0.006 and HR = 1.09, 95% CI: 1.01-1.19, P = 0.03, respectively). Neither SNP was associated with breast cancer risk for BRCA1 carriers, and rs6504950 was not associated with breast cancer for either BRCA1 or BRCA2 carriers. Of the 9 polymorphisms investigated, 7 were associated with breast cancer for BRCA2 carriers (FGFR2, TOX3, MAP3K1, LSP1, 2q35, SLC4A7, 5p12, P = 7 × 10-11 - 0.03), but only TOX3 and 2q35 were associated with the risk for BRCA1 carriers (P = 0.0049, 0.03, respectively). All risk-associated polymorphisms appear to interact multiplicatively on breast cancer risk for mutation carriers. Based on the joint genotype distribution of the 7 risk-associated SNPs in BRCA2 mutation carriers, the 5% of BRCA2 carriers at highest risk (i.e., between 95th and 100th percentiles) were predicted to have a probability between 80% and 96% of developing breast cancer by age 80, compared with 42% to 50% for the 5% of carriers at lowest risk. Our findings indicated that these risk differences might be sufficient to influence the clinical management of mutation carriers.
  • Frangou, Sophia, et al. (författare)
  • Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3–90 years
  • 2021
  • Ingår i: Human Brain Mapping. - : John Wiley & Sons. - 1065-9471 .- 1097-0193.
  • Tidskriftsartikel (refereegranskat)abstract
    • Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3–90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.
  • Lozano, Rafael, et al. (författare)
  • Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017
  • 2018
  • Ingår i: The Lancet. - : Elsevier. - 1474-547X .- 0140-6736. ; , s. 2091-2138
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings: The global median health-related SDG index in 2017 was 59·4 (IQR 35·4–67·3), ranging from a low of 11·6 (95% uncertainty interval 9·6–14·0) to a high of 84·9 (83·1–86·7). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation: The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains—curative interventions in the case of NCDs—towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions—or inaction—today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030.
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