Journal of Probability and Statistics / 2012 / Article / Tab 1

Research Article

Clustering-Based Method for Developing a Genomic Copy Number Alteration Signature for Predicting the Metastatic Potential of Prostate Cancer

Table 1

Clinical And histological characteristics of samples used to validate the metastatic potential score model.

CaseControl

𝑛 1339
Age
 Mean59.559.1
 Median6158
 Standard deviation7.17.3
 Range46–6746–73
Race
 Asian0 (0%)1 (1.9%)
 Black1 (1.9%)4 (7.7%)
 Unknown0 (0%)2 (3.8%)
 White Non-Hispanic12 (23.1%)32 (61.5%)
Clinical stage
 T1C4 (7.7%)23 (44.2%)
 T25 (9.6%)16 (30.8%)
 T34 (7.7%)0 (0%)
 T40 (0%)0 (0%)
Biopsy Gleason score
 50 (0%)0 (0%)
 64 (7.7%)26 (50%)
 77 (13.5%)10 (19.2%)
 82 (3.8%)2 (3.8%)
 90 (0%)1 (1.9%)
Prediagnosis biopsy PSA (ng/mL)
 Median6.95.6
 <42 (3.8%)6 (11.5%)
 4–106 (11.5%)24 (46.2%)
 >104 (7.7%)7 (13.5%)
Pretreatment PSA (ng/mL)
 Median12.85.6
 <42 (3.8%)7 (13.5%)
 4–104 (7.7%)26 (50%)
 >107 (13.5%)6 (11.5%)

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