Table 2. Results of applying RF to predict outcome of paclitaxel therapy.
| Type of treatment | Survival years (as
threshold) |
# Patients |
K (number of genes
to be used in random selection) |
Accuracy (True
Positive - TP) (%) |
Precision | F-Measure | MCC 1 | AUC 2 |
|---|---|---|---|---|---|---|---|---|
| Chemotherapy
(CT) |
3 | 53 | 7 | 56.6 | 0.510 | 0.524 | -0.095 | 0.441 |
| 4 | 7 | 69.8 | 0.698 | 0.698 | 0.396 | 0.700 | ||
| 5 | 19 | 66.0 | 0.645 | 0.636 | 0.230 | 0.653 | ||
| Hormone therapy
(HT) |
3 | 420 | 19 | 85.5 | 0.731 | 0.788 | 0.000 | 0.606 |
| 4 | 9 | 78.6 | 0.715 | 0.706 | 0.069 | 0.559 | ||
| 5 | 9 | 71.0 | 0.634 | 0.627 | 0.059 | 0.632 | ||
| CT and/or HT | 3 | 504 | 9 | 82.7 | 0.685 | 0.749 | 0.000 | 0.506 |
| 4 | 19 | 73.6 | 0.647 | 0.648 | 0.039 | 0.527 | ||
| 5 | 7 | 65.3 | 0.602 | 0.593 | 0.086 | 0.588 |
1MCC: Matthews Correlation Coefficient. 2AUC: Area under receiver operating curve; both Discovery and Validation patient datasets analyzed. RF predictions done using a gene panel consisting of 19 genes ( ABCB1, ABCB11, ABCC1, ABCC10, BAD, BBC3, BCL2, BCL2L1, BMF, CYP2C8, CYP3A4, MAP2, MAP4, MAPT, NR1I2, SLCO1B3, TUBB1, TUBB4A, TUBB4B).