Table 2. Performance validation of TMB estimation using derived TMB cut-off value of 10 mutations/Mb for the small gene panel from 406 NSCLC patients.
| Method | TP | TN | FP | FN | Sensitivity | Specificity | PPV | MCC |
|---|---|---|---|---|---|---|---|---|
| NaiveBayes | 59 | 291 | 13 | 43 | 57.8% | 95.7% | 81.9% | 60.8% |
| BayesNet | 72 | 280 | 24 | 30 | 70.6%# | 92.1% | 75.0% | 64.0% |
| Logistic* | 69 | 289 | 15 | 33 | 67.6% | 95.1% | 82.1% | 67.1% |
| LogitBoost | 65 | 289 | 15 | 37 | 63.7% | 95.1% | 81.3% | 64.1% |
| RandomForest | 63 | 284 | 20 | 39 | 61.8% | 93.4% | 75.9% | 59.4% |
| SVM* | 67 | 293 | 11 | 35 | 65.7% | 96.4%# | 85.9%# | 68.3%# |
| MultiClassClassifier* | 69 | 289 | 15 | 33 | 67.6% | 95.1% | 82.1% | 67.1% |
*, methods in bold represent the most suitable method for TMB estimation; #, values in bold indicate the highest value for sensitivity, specificity, PPV, or MCC. NSCLC, non-small cell lung cancer; TMB, tumor mutation burden; TP, true positive; FP, false positive; TN, true negative; FN, false negative; PPV, positive predictive value; MCC, Matthew’s correlation coefficient.