Crowdsourcing the General Public for Large Scale Molecular Pathology Studies in Cancer.

Autor:	Candido Dos Reis FJ; Department of Oncology, University of Cambridge, Cambridge, UK ; Department of Gynecology and Obstetrics, Ribeirao Preto School of Medicine, University of Sao Paulo, Ribeirao Preto, Brazil., Lynn S; Department of Physics (Astrophysics), University of Oxford, Oxford, UK., Ali HR; Cancer Research UK, Cambridge Institute, Cambridge, UK., Eccles D; University of Southampton, Southampton, UK., Hanby A; University of Leeds, Leeds, UK., Provenzano E; Addenbrookes Hospital NHS Trust, Cambridge, UK., Caldas C; Cancer Research UK, Cambridge Institute, Cambridge, UK., Howat WJ; Cancer Research UK, Cambridge Institute, Cambridge, UK., McDuffus LA; Cancer Research UK, Cambridge Institute, Cambridge, UK., Liu B; Cancer Research UK, Cambridge Institute, Cambridge, UK., Daley F; Institute of Cancer Research, London, UK., Coulson P; Institute of Cancer Research, London, UK., Vyas RJ; Cancer Research UK, London, UK., Harris LM; Cancer Research UK, London, UK., Owens JM; Cancer Research UK, London, UK., Carton AF; Cancer Research UK, London, UK., McQuillan JP; Cancer Research UK, London, UK., Paterson AM; Cancer Research UK, London, UK., Hirji Z; Cancer Research UK, London, UK., Christie SK; Cancer Research UK, London, UK., Holmes AR; Cancer Research UK, London, UK., Schmidt MK; Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands., Garcia-Closas M; Institute of Cancer Research, London, UK., Easton DF; Department of Oncology, University of Cambridge, Cambridge, UK ; Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK., Bolla MK; Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK., Wang Q; Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK., Benitez J; Human Genotyping (CEGEN) Unit, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain ; Biomedical Network on Rare Diseases (CIBERER), Madrid, Spain., Milne RL; Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia ; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Australia., Mannermaa A; Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Finland., Couch F; Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA., Devilee P; Department of Human Genetics & Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands., Tollenaar RA; Department of Surgical Oncology, Leiden University Medical Center, Leiden, The Netherlands., Seynaeve C; Department of Medical Oncology, Family Cancer Clinic, Erasmus MC Cancer Institute, Rotterdam, The Netherlands., Cox A; Sheffield Cancer Research, Department of Oncology, University of Sheffield, Sheffield, UK., Cross SS; Academic Unit of Pathology, Department of Neuroscience, University of Sheffield, Sheffield, UK., Blows FM; Department of Oncology, University of Cambridge, Cambridge, UK., Sanders J; Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands., de Groot R; Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands., Figueroa J; National Cancer Institute, USA., Sherman M; National Cancer Institute, USA., Hooning M; Department of Medical Oncology, Family Cancer Clinic, Erasmus MC Cancer Institute, Rotterdam, The Netherlands., Brenner H; Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany ; Division of Preventive Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany ; German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany., Holleczek B; Saarland Cancer Registry, Saarbrücken, Germany., Stegmaier C; Saarland Cancer Registry, Saarbrücken, Germany., Lintott C; Department of Physics (Astrophysics), University of Oxford, Oxford, UK., Pharoah PD; Department of Oncology, University of Cambridge, Cambridge, UK ; Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Jazyk:	angličtina
Zdroj:	EBioMedicine [EBioMedicine] 2015 May 09; Vol. 2 (7), pp. 681-9. Date of Electronic Publication: 2015 May 09 (Print Publication: 2015).
DOI:	10.1016/j.ebiom.2015.05.009
Abstrakt:	Background: Citizen science, scientific research conducted by non-specialists, has the potential to facilitate biomedical research using available large-scale data, however validating the results is challenging. The Cell Slider is a citizen science project that intends to share images from tumors with the general public, enabling them to score tumor markers independently through an internet-based interface. Methods: From October 2012 to June 2014, 98,293 Citizen Scientists accessed the Cell Slider web page and scored 180,172 sub-images derived from images of 12,326 tissue microarray cores labeled for estrogen receptor (ER). We evaluated the accuracy of Citizen Scientist's ER classification, and the association between ER status and prognosis by comparing their test performance against trained pathologists. Findings: The area under ROC curve was 0.95 (95% CI 0.94 to 0.96) for cancer cell identification and 0.97 (95% CI 0.96 to 0.97) for ER status. ER positive tumors scored by Citizen Scientists were associated with survival in a similar way to that scored by trained pathologists. Survival probability at 15 years were 0.78 (95% CI 0.76 to 0.80) for ER-positive and 0.72 (95% CI 0.68 to 0.77) for ER-negative tumors based on Citizen Scientists classification. Based on pathologist classification, survival probability was 0.79 (95% CI 0.77 to 0.81) for ER-positive and 0.71 (95% CI 0.67 to 0.74) for ER-negative tumors. The hazard ratio for death was 0.26 (95% CI 0.18 to 0.37) at diagnosis and became greater than one after 6.5 years of follow-up for ER scored by Citizen Scientists, and 0.24 (95% CI 0.18 to 0.33) at diagnosis increasing thereafter to one after 6.7 (95% CI 4.1 to 10.9) years of follow-up for ER scored by pathologists. Interpretation: Crowdsourcing of the general public to classify cancer pathology data for research is viable, engages the public and provides accurate ER data. Crowdsourced classification of research data may offer a valid solution to problems of throughput requiring human input.
Databáze:	MEDLINE
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