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A two-stage approach for combining gene expression and mutation with clinical data improves survival prediction in myelodysplastic syndromes and ovarian cancer.

Publication ,  Journal Article
Li, Y; Zhang, X; Akinyemiju, T; Ojesina, AI; Szychowski, JM; Liu, N; Xu, B; Yi, N
Published in: J Bioinform Genom
September 2016

MOTIVATION: Many traditional clinical prognostic factors have been known for cancer for years, but usually provide poor survival prediction. Genomic information is more easily available now which offers opportunities to build more accurate prognostic models. The challenge is how to integrate them to improve survival prediction. The common approach of jointly analyzing all type of covariates directly in one single model may not improve the prediction due to increased model complexity and cannot be easily applied to different datasets. RESULTS: We proposed a two-stage procedure to better combine different sources of information for survival prediction, and applied the two-stage procedure in two cancer datasets: myelodysplastic syndromes (MDS) and ovarian cancer. Our analysis suggests that the prediction performance of different data types are very different, and combining clinical, gene expression and mutation data using the two-stage procedure improves survival prediction in terms of improved concordance index and reduced prediction error. AVAILABILITY AND IMPLEMENTATION: The two-stage procedure can be implemented in BhGLM package which is freely available at http://www.ssg.uab.edu/bhglm/. CONTACT: nyi@uab.edu.

Duke Scholars

Published In

J Bioinform Genom

DOI

ISSN

2530-1381

Publication Date

September 2016

Volume

1

Issue

1

Location

Spain
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Li, Y., Zhang, X., Akinyemiju, T., Ojesina, A. I., Szychowski, J. M., Liu, N., … Yi, N. (2016). A two-stage approach for combining gene expression and mutation with clinical data improves survival prediction in myelodysplastic syndromes and ovarian cancer. J Bioinform Genom, 1(1). https://doi.org/10.18454/jbg.2016.1.1.2
Li, Yan, Xinyan Zhang, Tomi Akinyemiju, Akinyemi I. Ojesina, Jeff M. Szychowski, Nianjun Liu, Bo Xu, and Nengjun Yi. “A two-stage approach for combining gene expression and mutation with clinical data improves survival prediction in myelodysplastic syndromes and ovarian cancer.J Bioinform Genom 1, no. 1 (September 2016). https://doi.org/10.18454/jbg.2016.1.1.2.
Li Y, Zhang X, Akinyemiju T, Ojesina AI, Szychowski JM, Liu N, Xu B, Yi N. A two-stage approach for combining gene expression and mutation with clinical data improves survival prediction in myelodysplastic syndromes and ovarian cancer. J Bioinform Genom. 2016 Sep;1(1).

Published In

J Bioinform Genom

DOI

ISSN

2530-1381

Publication Date

September 2016

Volume

1

Issue

1

Location

Spain