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  Crowdsourced analysis of clinical trial data to predict amyotrophic lateral sclerosis progression

Küffner, R., Zach, N., Norel, R., Hawe, J., Schoenfeld, D., Wang, L., et al. (2015). Crowdsourced analysis of clinical trial data to predict amyotrophic lateral sclerosis progression. Nature Biotechnology, 33(1), 51-57. doi:10.1038/nbt.3051.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002A-4785-8 Version Permalink: http://hdl.handle.net/21.11116/0000-0000-FAA2-F
Genre: Journal Article

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 Creators:
Küffner, R, Author
Zach, N, Author
Norel, R, Author
Hawe, J, Author
Schoenfeld, D, Author
Wang, L, Author
Li, G, Author
Fang, L, Author
Mackey, L, Author
Hardiman, O, Author
Cudkowicz, M, Author
Sherman, A, Author
Ertaylan, G, Author
Grosse-Wentrup, M1, Author              
Hothorn, T, Author
van Ligtenberg, J, Author
Macke, JH2, Author              
Meyer, T, Author
Schölkopf, B1, Author              
Tran, L, Author
Vaughan, R, AuthorStolovitzky, G, AuthorLeitner, ML, Author more..
Affiliations:
1Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497647              
2Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497805              

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 Abstract: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with substantial heterogeneity in its clinical presentation. This makes diagnosis and effective treatment difficult, so better tools for estimating disease progression are needed. Here, we report results from the DREAM-Phil Bowen ALS Prediction Prize4Life challenge. In this crowdsourcing competition, competitors developed algorithms for the prediction of disease progression of 1,822 ALS patients from standardized, anonymized phase 2/3 clinical trials. The two best algorithms outperformed a method designed by the challenge organizers as well as predictions by ALS clinicians. We estimate that using both winning algorithms in future trial designs could reduce the required number of patients by at least 20. The DREAM-Phil Bowen ALS Prediction Prize4Life challenge also identified several potential nonstandard predictors of disease progression including uric acid, creatinine and surprisingly, blood pressure, shedding light on ALS pathobiology. This analysis reveals the potential of a crowdsourcing competition that uses clinical trial data for accelerating ALS research and development.

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 Dates: 2015-01
 Publication Status: Published in print
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 Identifiers: DOI: 10.1038/nbt.3051
BibTex Citekey: KuffnerZNHSWLFMHCSEGHvMMSTVSL2014
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Title: Nature Biotechnology
Source Genre: Journal
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Pages: - Volume / Issue: 33 (1) Sequence Number: - Start / End Page: 51 - 57 Identifier: -