Skip to main content
. 2014 Jan 22;9(1):e85249. doi: 10.1371/journal.pone.0085249

Table 1. Multivariate progression and survival analysis in patients with bladder cancer.

Dataset Endpoint Clinical variables* Multivariate analysis (P<0.05) Final model
CNUH (N = 165) Progression CCP score, stage, grade, BCG therapy, chemotherapy, age, gender - CCP score, stage
Lindgren (N = 97) Progression CCP score, grade - CCP score
Dyrskjot (N = 162) PFS CCP score, stage, grade, CIS diagnosis, BCG/MMC treatment, age, gender CCP score CCP score
Blaveri (N = 78) OS CCP score, grade, stage, surgery, age, gender CCP score CCP score
CNUH (N = 165) DSS CCP score, stage, grade, BCG therapy, chemotherapy. age gender Stage, age Stage, age
Dyrskjot (N = 155) DSS CCP score, stage, grade, CIS diagnosis, cystectomy following TURBT, BCG/MMC treatment, age, gender CCP score, CIS diagnosis CCP score, CIS, age
Lindgren (N = 156) DSS CCP score, stage, grade, cystectomy following TURBT, age, gender Stage Stage
MSKCC (N = 87) OS CCP score, stage, grade, age, gender CCP score, stage, grade Stage, grade
*

Variables include the following (see Tables S6–S7 in File S4 for complete multivariate analysis):

Stage: Ta-T1 vs. T2–T4 (CNUH, Dyrksjot - DSS, Lindgren, and MSKCC) and T1 vs. Ta (Dyrskjot -PFS);

Grade: high vs. low (CNUH, Lindgren, Blaveri, MSKCC); high vs. low vs. PUNLMP (Dyrskjot).

Surgery: cystectomy vs. transurethral resection of the bladder.

Abbreviations: PFS, progression-free survival; OS, overall survival; DSS, disease-specific survival.

Final model is constructed from forward step-wise regression of significant variables (P<0.05).