Research Article
Modified Logistic Regression Models Using Gene Coexpression and Clinical Features to Predict Prostate Cancer Progression
Table 1
Logistic regression models that included TSP-selected gene pairs and different combinations of clinical variables.
| Model number | Patient’s age | Gleason score | Tumor percentage | Fusion ERG arrangement | TSP genes |
| 1.1 | | | | | X | 1.2 | X | | | | X | 1.3 | | X | | | X | 1.4 | | | X | | X | 1.5 | | | | X | X | 1.6 | X | X | | | X | 1.7 | X | | X | | X | 1.8 | X | | | X | X | 1.9 | | X | X | | X | 1.10 | | X | | X | X | 1.11 | | | X | X | X | 1.12 | X | X | X | | X | 1.13 | X | X | | X | X | 1.14 | X | | X | X | X | 1.15 | | X | X | X | X | 1.16 | X | X | X | X | X |
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