Institution
Fred Hutchinson Cancer Research Center
Nonprofit•Cape Town, South Africa•
About: Fred Hutchinson Cancer Research Center is a nonprofit organization based out in Cape Town, South Africa. It is known for research contribution in the topics: Population & Transplantation. The organization has 12322 authors who have published 30954 publications receiving 2288772 citations. The organization is also known as: Fred Hutch & The Hutch.
Topics: Population, Transplantation, Cancer, Breast cancer, Prostate cancer
Papers published on a yearly basis
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728 citations
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VU University Medical Center1, Hannover Medical School2, University of Birmingham3, University of Rome Tor Vergata4, King's College London5, Cardiff University6, National Institutes of Health7, University of Texas MD Anderson Cancer Center8, Radboud University Nijmegen9, University of Oxford10, Fred Hutchinson Cancer Research Center11, University of Washington12, NewYork–Presbyterian Hospital13
TL;DR: The objective of this work was to identify key clinical and scientific issues in the measurement and application of MRD in AML, to achieve consensus on these issues, and to provide guidelines for the current and future use of MRd in clinical practice.
726 citations
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TL;DR: The Trans‐Proteomic Pipeline is described, which makes use of open XML file formats for storage of data at the raw spectral data, peptide, and protein levels, and enables uniform analysis and exchange of MS/MS data generated from a variety of different instruments, and assigned peptides using a range of different database search programs.
Abstract: The analysis of tandem mass (MS/MS) data to identify and quantify proteins is hampered by the heterogeneity of file formats at the raw spectral data, peptide identification, and protein identification levels. Different mass spectrometers output their raw spectral data in a variety of proprietary formats, and alternative methods that assign peptides to MS/MS spectra and infer protein identifications from those peptide assignments each write their results in different formats. Here we describe an MS/MS analysis platform, the Trans-Proteomic Pipeline, which makes use of open XML file formats for storage of data at the raw spectral data, peptide, and protein levels. This platform enables uniform analysis and exchange of MS/MS data generated from a variety of different instruments, and assigned peptides using a variety of different database search programs. We demonstrate this by applying the pipeline to data sets generated by ThermoFinnigan LCQ, ABI 4700 MALDI-TOF/TOF, and Waters Q-TOF instruments, and searched in turn using SEQUEST, Mascot, and COMET.
726 citations
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University of Southern California1, Fred Hutchinson Cancer Research Center2, Georgetown University3, QIMR Berghofer Medical Research Institute4, German Cancer Research Center5, University of Cologne6, University of Hawaii at Manoa7, Roswell Park Cancer Institute8, University of Copenhagen9, Mayo Clinic10, Duke University11, University of North Carolina at Chapel Hill12, Harvard University13, Dartmouth College14, University of California, Irvine15, University College London16, University of Giessen17, University of California, Los Angeles18, University of Duisburg-Essen19, University of British Columbia20, University of Texas Health Science Center at Houston21, Memorial Sloan Kettering Cancer Center22, Yale University23
TL;DR: In this paper, the association between self-reported endometriosis and risk of ovarian cancer was found to be a risk factor for epithelial ovarian cancer; however, whether this risk extends to all invasive histological subtypes or borderline tumours is not clear.
Abstract: Summary Background Endometriosis is a risk factor for epithelial ovarian cancer; however, whether this risk extends to all invasive histological subtypes or borderline tumours is not clear. We undertook an international collaborative study to assess the association between endometriosis and histological subtypes of ovarian cancer. Methods Data from 13 ovarian cancer case–control studies, which were part of the Ovarian Cancer Association Consortium, were pooled and logistic regression analyses were undertaken to assess the association between self-reported endometriosis and risk of ovarian cancer. Analyses of invasive cases were done with respect to histological subtypes, grade, and stage, and analyses of borderline tumours by histological subtype. Age, ethnic origin, study site, parity, and duration of oral contraceptive use were included in all analytical models. Findings 13 226 controls and 7911 women with invasive ovarian cancer were included in this analysis. 818 and 738, respectively, reported a history of endometriosis. 1907 women with borderline ovarian cancer were also included in the analysis, and 168 of these reported a history of endometriosis. Self-reported endometriosis was associated with a significantly increased risk of clear-cell (136 [20·2%] of 674 cases vs 818 [6·2%] of 13 226 controls, odds ratio 3·05, 95% CI 2·43–3·84, p Interpretation Clinicians should be aware of the increased risk of specific subtypes of ovarian cancer in women with endometriosis. Future efforts should focus on understanding the mechanisms that might lead to malignant transformation of endometriosis so as to help identify subsets of women at increased risk of ovarian cancer. Funding Ovarian Cancer Research Fund, National Institutes of Health, California Cancer Research Program, California Department of Health Services, Lon V Smith Foundation, European Community's Seventh Framework Programme, German Federal Ministry of Education and Research of Germany, Programme of Clinical Biomedical Research, German Cancer Research Centre, Eve Appeal, Oak Foundation, UK National Institute of Health Research, National Health and Medical Research Council of Australia, US Army Medical Research and Materiel Command, Cancer Council Tasmania, Cancer Foundation of Western Australia, Mermaid 1, Danish Cancer Society, and Roswell Park Alliance Foundation.
726 citations
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TL;DR: This commentary considers the amassed evidence that shows that self-report dietary intake data can successfully be used to inform dietary guidance and public health policy and 7 specific recommendations for collecting, analyzing, and interpreting self- report dietary data are provided.
Abstract: Recent reports have asserted that, because of energy underreporting, dietary self-report data suffer from measurement error so great that findings that rely on them are of no value. This commentary considers the amassed evidence that shows that self-report dietary intake data can successfully be used to inform dietary guidance and public health policy. Topics discussed include what is known and what can be done about the measurement error inherent in data collected by using self-report dietary assessment instruments and the extent and magnitude of underreporting energy compared with other nutrients and food groups. Also discussed is the overall impact of energy underreporting on dietary surveillance and nutritional epidemiology. In conclusion, 7 specific recommendations for collecting, analyzing, and interpreting self-report dietary data are provided: (1) continue to collect self-report dietary intake data because they contain valuable, rich, and critical information about foods and beverages consumed by populations that can be used to inform nutrition policy and assess diet-disease associations; (2) do not use self-reported energy intake as a measure of true energy intake; (3) do use self-reported energy intake for energy adjustment of other self-reported dietary constituents to improve risk estimation in studies of diet-health associations; (4) acknowledge the limitations of self-report dietary data and analyze and interpret them appropriately; (5) design studies and conduct analyses that allow adjustment for measurement error; (6) design new epidemiologic studies to collect dietary data from both short-term (recalls or food records) and long-term (food-frequency questionnaires) instruments on the entire study population to allow for maximizing the strengths of each instrument; and (7) continue to develop, evaluate, and further expand methods of dietary assessment, including dietary biomarkers and methods using new technologies.
725 citations
Authors
Showing all 12368 results
Name | H-index | Papers | Citations |
---|---|---|---|
Walter C. Willett | 334 | 2399 | 413322 |
Robert Langer | 281 | 2324 | 326306 |
Meir J. Stampfer | 277 | 1414 | 283776 |
JoAnn E. Manson | 270 | 1819 | 258509 |
David J. Hunter | 213 | 1836 | 207050 |
Peer Bork | 206 | 697 | 245427 |
Eric Boerwinkle | 183 | 1321 | 170971 |
Ruedi Aebersold | 182 | 879 | 141881 |
Bruce M. Psaty | 181 | 1205 | 138244 |
Aaron R. Folsom | 181 | 1118 | 134044 |
David Baker | 173 | 1226 | 109377 |
Frederick W. Alt | 171 | 577 | 95573 |
Lily Yeh Jan | 162 | 467 | 73655 |
Yuh Nung Jan | 162 | 460 | 74818 |
Charles N. Serhan | 158 | 728 | 84810 |