1 resultado para Diseases in art
em Collection Of Biostatistics Research Archive
Filtro por publicador
- Repository Napier (1)
- Rhode Island School of Design (8)
- ABACUS. Repositorio de Producción Científica - Universidad Europea (1)
- Aberdeen University (1)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (4)
- Aquatic Commons (11)
- ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha (1)
- Archimer: Archive de l'Institut francais de recherche pour l'exploitation de la mer (3)
- Archive of European Integration (3)
- Aston University Research Archive (6)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (34)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (14)
- Biblioteca Digital de Teses e Dissertações Eletrônicas da UERJ (2)
- Bioline International (5)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (115)
- Boston University Digital Common (2)
- Brock University, Canada (3)
- Brunel University (1)
- Bucknell University Digital Commons - Pensilvania - USA (1)
- Bulgarian Digital Mathematics Library at IMI-BAS (4)
- CaltechTHESIS (1)
- Cambridge University Engineering Department Publications Database (3)
- CentAUR: Central Archive University of Reading - UK (28)
- Chinese Academy of Sciences Institutional Repositories Grid Portal (5)
- Cochin University of Science & Technology (CUSAT), India (4)
- Coffee Science - Universidade Federal de Lavras (1)
- Collection Of Biostatistics Research Archive (1)
- Comissão Econômica para a América Latina e o Caribe (CEPAL) (1)
- CORA - Cork Open Research Archive - University College Cork - Ireland (3)
- Corvinus Research Archive - The institutional repository for the Corvinus University of Budapest (1)
- Dalarna University College Electronic Archive (1)
- Digital Archives@Colby (2)
- Digital Commons @ DU | University of Denver Research (53)
- Digital Commons at Florida International University (8)
- Digital Peer Publishing (2)
- DigitalCommons@The Texas Medical Center (16)
- DigitalCommons@University of Nebraska - Lincoln (2)
- DRUM (Digital Repository at the University of Maryland) (1)
- Duke University (5)
- eResearch Archive - Queensland Department of Agriculture; Fisheries and Forestry (21)
- FAUBA DIGITAL: Repositorio institucional científico y académico de la Facultad de Agronomia de la Universidad de Buenos Aires (2)
- FUNDAJ - Fundação Joaquim Nabuco (3)
- Glasgow Theses Service (1)
- Greenwich Academic Literature Archive - UK (1)
- Helda - Digital Repository of University of Helsinki (16)
- Illinois Digital Environment for Access to Learning and Scholarship Repository (2)
- Indian Institute of Science - Bangalore - Índia (11)
- Instituto Nacional de Saúde de Portugal (2)
- Instituto Politécnico de Viseu (2)
- Instituto Politécnico do Porto, Portugal (4)
- Lume - Repositório Digital da Universidade Federal do Rio Grande do Sul (1)
- Memoria Académica - FaHCE, UNLP - Argentina (3)
- Memorial University Research Repository (1)
- National Center for Biotechnology Information - NCBI (11)
- Nottingham eTheses (1)
- Portal de Revistas Científicas Complutenses - Espanha (9)
- QSpace: Queen's University - Canada (1)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (31)
- Queensland University of Technology - ePrints Archive (123)
- RCAAP - Repositório Científico de Acesso Aberto de Portugal (1)
- Repositório Alice (Acesso Livre à Informação Científica da Embrapa / Repository Open Access to Scientific Information from Embrapa) (2)
- Repositório Científico do Instituto Politécnico de Lisboa - Portugal (3)
- Repositório digital da Fundação Getúlio Vargas - FGV (1)
- Repositório Digital da Universidade Municipal de São Caetano do Sul - USCS (1)
- Repositório Institucional da Universidade de Aveiro - Portugal (2)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (82)
- Research Open Access Repository of the University of East London. (1)
- Royal College of Art Research Repository - Uninet Kingdom (2)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (4)
- Savoirs UdeS : plateforme de diffusion de la production intellectuelle de l’Université de Sherbrooke - Canada (1)
- Scielo España (1)
- Scientific Open-access Literature Archive and Repository (1)
- South Carolina State Documents Depository (1)
- Universidad del Rosario, Colombia (7)
- Universidad Politécnica de Madrid (8)
- Universidade Complutense de Madrid (3)
- Universidade de Lisboa - Repositório Aberto (3)
- Universidade Federal do Pará (2)
- Universidade Federal do Rio Grande do Norte (UFRN) (1)
- Universitat de Girona, Spain (2)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (3)
- Université de Lausanne, Switzerland (7)
- Université de Montréal, Canada (5)
- University of Connecticut - USA (1)
- University of Michigan (87)
- University of Queensland eSpace - Australia (22)
- University of Southampton, United Kingdom (2)
- University of Washington (3)
- WestminsterResearch - UK (3)
- Worcester Research and Publications - Worcester Research and Publications - UK (6)
Resumo:
Mendelian models can predict who carries an inherited deleterious mutation of known disease genes based on family history. For example, the BRCAPRO model is commonly used to identify families who carry mutations of BRCA1 and BRCA2, based on familial breast and ovarian cancers. These models incorporate the age of diagnosis of diseases in relatives and current age or age of death. We develop a rigorous foundation for handling multiple diseases with censoring. We prove that any disease unrelated to mutations can be excluded from the model, unless it is sufficiently common and dependent on a mutation-related disease time. Furthermore, if a family member has a disease with higher probability density among mutation carriers, but the model does not account for it, then the carrier probability is deflated. However, even if a family only has diseases the model accounts for, if the model excludes a mutation-related disease, then the carrier probability will be inflated. In light of these results, we extend BRCAPRO to account for surviving all non-breast/ovary cancers as a single outcome. The extension also enables BRCAPRO to extract more useful information from male relatives. Using 1500 familes from the Cancer Genetics Network, accounting for surviving other cancers improves BRCAPRO’s concordance index from 0.758 to 0.762 (p = 0.046), improves its positive predictive value from 35% to 39% (p < 10−6) without impacting its negative predictive value, and improves its overall calibration, although calibration slightly worsens for those with carrier probability < 10%. Copyright c 2000 John Wiley & Sons, Ltd.