Thymomas and thymic carcinomas are rare epithelial tumors arising from the thymus gland in the anterior mediastinum. The exact incidence of thymomas is not well documented, but estimated at person-years. The rarity and morphological heterogeneity of these tumors have significantly contributed to difficulties in predicting the behaviour of these tumors. The primary endpoint was to determine whether the gene signature could accurately predict and 10-year metastasis-free survival, defined as time from diagnosis to the development of multifocal pleural/lung deposits or extrathoracic metastases. One of the primary reasons for choosing this endpoint is that evaluation of the mediastinum for recurrence, following surgery and radiation therapy, is difficult. The secondary endpoint was to perform comparative analyses with Masaoka staging system, completeness of resection, and the WHO histological type to determine whether it was an buy ROR gama modulator 1 independent predictor. Using a training set, multiple nonlinear predictive modeling methods were performed to assess the prognostic ability of the gene signature to identify the best classifier. In addition to RBM, partition tree analysis, K-nearest neighbor analysis, and distance scoring analysis were performed using the SAS-based JMP Genomics software. The area under the receiver operator characteristic curve was calculated for each analysis to assess the predictive probabilities of each method. Survival analysis was performed using Kaplan�CMeier plots and log-rank analysis. Cox regression analysis was performed using WinSTAT software for the variables age, gender, stage, WHO type, completeness of resection, autoimmune disease, and gene signature. Impact of chemotherapy was also analyzed. Using Win- STAT, 95 confidence interval ranges for hazard 1332295-35-8 ratios were calculated. Positive and negative predictive values were calculated for gene signature, staging system, and extent of resection to show the precision of each method for predicting which tumors are at low and high risk of metastasis. The NPV showed that the gene signature was more precise than staging and absence of residual disease for identifying low-risk patients. PPV was comparable between gene signature stage and presence of re
