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PLoS One. 2012;7(3):e31989. doi: 10.1371/journal.pone.0031989. Epub 2012 Mar 9.

Molecular prognostic prediction for locally advanced nasopharyngeal carcinoma by support vector machine integrated approach.

Author information

1
Department of Medical Oncology, the Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, People's Republic of China.

Abstract

BACKGROUND:

Accurate prognostication of locally advanced nasopharyngeal carcinoma (NPC) will benefit patients for tailored therapy. Here, we addressed this issue by developing a mathematical algorithm based on support vector machine (SVM) through integrating the expression levels of multi-biomarkers.

METHODOLOGY/PRINCIPAL FINDINGS:

Ninety-seven locally advanced NPC patients in a randomized controlled trial (RCT), consisting of 48 cases serving as training set and 49 cases as testing set of SVM models, with 5-year follow-up were studied. We designed SVM models by selecting the variables from 38 tissue molecular biomarkers, which represent 6 tumorigenesis signaling pathways, and 3 EBV-related serological biomarkers. We designed 3 SVM models to refine prognosis of NPC with 5-year follow-up. The SVM1 displayed highly predictive sensitivity (sensitivity, specificity were 88.0% and 81.9%, respectively) by integrating the expression of 7 molecular biomarkers. The SVM2 model showed highly predictive specificity (sensitivity, specificity were 84.0% and 94.5%, respectively) by grouping the expression level of 12 molecular biomarkers and 3 EBV-related serological biomarkers. The SVM3 model, constructed by combination SVM1 with SVM2, displayed a high predictive capacity (sensitivity, specificity were 88.0% and 90.3%, respectively). We found that 3 SVM models had strong power in classification of prognosis. Moreover, Cox multivariate regression analysis confirmed these 3 SVM models were all the significant independent prognostic model for overall survival in testing set and overall patients.

CONCLUSIONS/SIGNIFICANCE:

Our SVM prognostic models designed in the RCT displayed strong power in refining patient prognosis for locally advanced NPC, potentially directing future target therapy against the related signaling pathways.

PMID:
22427815
PMCID:
PMC3302890
DOI:
10.1371/journal.pone.0031989
[Indexed for MEDLINE]
Free PMC Article

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