Table 3.
PCA analysis of the nine Weiss parameters gave the best fitting model of four components. PCA analysis was performed by SPSS 26.00 on data from the ACC cohort (n = 79). Pattern matrix related to a 4-component model, after Varimax rotation and missing pairwise
| Weiss parameter | Component 1 | Component 2 | Component 3 | Component 4 |
|---|---|---|---|---|
| Necrosis | 0.801 | |||
| Venous invasion | 0.744 | |||
| Sinusoidal invasion | 0.808 | |||
| Capsular invasion | 0.654 | |||
| Diffuse architecture | 0.646 | |||
| Atypical mitosis | 0.879 | |||
| > 5 mitoses per 50 high-power fields (10 mm2) | 0.657 | |||
| Nuclear atypia | 0.590 | |||
| Clear cells ≤ 25% | 0.836 |
Data are expressed as correlation values between parameters and components > 0.450, and are indicated in descending order. Barlett’s test value for adequacy = 0.548 and significance of the correlation matrix p < 0.001. Descending weight of the single components from Component 1 to 4 for covering variance of Weiss score