Additional file 1: of Prediction of non-muscle invasive bladder cancer outcomes assessed by innovative multimarker prognostic models E. López de Maturana A. Picornell A. Masson-Lecomte M. Kogevinas M. Márquez A. Carrato A. Tardón J. Lloreta M. García-Closas D. Silverman N. Rothman S. Chanock F. Real M. Goddard N. Malats 10.6084/m9.figshare.c.3617993_D2.v1 https://springernature.figshare.com/articles/journal_contribution/Additional_file_1_of_Prediction_of_non-muscle_invasive_bladder_cancer_outcomes_assessed_by_innovative_multimarker_prognostic_models/4384328 Table S1. Clinico-pathological variables included in the predictive models for time to first recurrence (TFR) and time to progression (TP). Table S2. Summary of censored patients and events (%) for each event in each time interval defined for the statistical analyses. Table S3. Area under the ROC curve (AUC) and coefficient of determination (R probit 2 ) obtained for each testing set in the 10 fold-crossvalidation analyses of time to first recurrence. Table S4. Area under the ROC curve (AUC) and coefficient of determination (R probit 2 ) obtained for each testing set in the 10 fold-crossvalidation analyses of time to progression. Table S5. Area under the ROC curve (AUC) and coefficient of determination (R probit 2 ) obtained for each testing set in the 2 fold-crossvalidation analyses of time to progression in patients at high risk. Table S6. Area under the ROC curve (AUC) and coefficient of determination (R probit 2 ) obtained for each testing set in the 2 fold-crossvalidation analyses of time to progression in patients at low risk. Table S7. Coefficient of determination (R probit 2 ) obtained for each testing set in the 10 fold-crossvalidation analyses of time to first recurrence (TFR), time to progression (TP) in the whole cohort, and time to progression (TP) in the high and low risk cohorts (TPHiR and TPLR). (DOC 113 kb) 2016-06-03 05:00:00 Multimarker models Bayesian statistical learning method Bayesian regression Bayesian LASSO AUC-ROC Determination coefficient heritability Bladder cancer outcome Prognosis Recurrence Progression Genome-wide common SNP Illumina Infinium HumanHap 1 M array Predictive ability