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