Table III.
Performance of OSCC biomarker candidates in the training set and result of five-fold cross-validation
| Training set | |||
|---|---|---|---|
|
| |||
| AUC | Sensitivity | Specificity | |
| Oxalate | 0.783 | 0.750 | 0.733 |
| Sarcosine | 0.678 | 0.958 | 0.333 |
| 3-Hydroxyisovaleric acid | 0.778 | 0.792 | 0.800 |
| Urea | 0.728 | 0.792 | 0.667 |
| Benzoic acid | 0.819 | 0.833 | 0.800 |
| Nonanoic acid | 0.978 | 0.917 | 0.933 |
| β-Alanine | 0.750 | 0.583 | 0.867 |
| Creatinine | 0.631 | 0.500 | 0.867 |
| Threo-β-Hydroxyaspartic acid | 0.803 | 0.708 | 0.933 |
| Phthalic acid | 0.783 | 0.750 | 0.733 |
| Hypoxanthine | 0.800 | 0.675 | 0.583 |
| 5-Dehydroquinic acid | 0.739 | 0.667 | 0.733 |
| Glucose | 0.925 | 0.917 | 0.867 |
| Sebacic acid | 0.747 | 0.747 | 0.933 |
| Galactose | 0.914 | 0.917 | 0.867 |
| Galactosamine | 0.808 | 0.958 | 0.600 |
| Glucarate | 0.744 | 0.917 | 0.533 |
| Cysteine+Cystine | 0.947 | 0.917 | 1.000 |
| 5-fold cross validation | |||
|---|---|---|---|
|
| |||
| AUC | Sensitivity | Specificity | |
| Oxalate | 0.780 | 0.863 | 0.633 |
| Sarcosine | 0.644 | 0.642 | 0.650 |
| 3-Hydroxyisovaleric acid | 0.775 | 0.747 | 0.850 |
| Urea | 0.723 | 0.800 | 0.650 |
| Benzoic acid | 0.823 | 0.842 | 0.800 |
| Nonanoic acid | 0.976 | 0.914 | 0.933 |
| β-Alanine | 0.740 | 0.695 | 0.783 |
| Creatinine | 0.644 | 0.568 | 0.850 |
| Threo-β-Hydroxyaspartic acid | 0.804 | 0.726 | 0.933 |
| Phthalic acid | 0.780 | 0.864 | 0.617 |
| Hypoxanthine | 0.654 | 0.589 | 0.783 |
| 5-Dehydroquinic acid | 0.729 | 0.674 | 0.733 |
| Glucose | 0.922 | 0.916 | 0.850 |
| Sebacic acid | 0.766 | 0.621 | 0.933 |
| Galactose | 0.914 | 0.926 | 0.850 |
| Galactosamine | 0.804 | 0.958 | 0.617 |
| Glucarate | 0.725 | 0.916 | 0.533 |
| Cysteine+Cystine | 0.946 | 0.916 | 0.983 |
Four metabolites (nonanoic acid, cysteine + cystine, glucose, and galactose) shows high potential as biomarker candidate (over 0.9 in AUC, over 90% in sensitivity). Result of five-fold cross-validation shows similar tendency with the training set.