Table 7.
Single and multiple linear inverse regression models to predict reference values as dependent variable (n = 164, P <0.0001 for all models and slope estimates)
| Variable | R-square | Intercept estimate | Intercept P | Slope estimate | Slope standardized estimate |
|---|---|---|---|---|---|
|
Single regression models:
|
|
|
|
|
|
| Ki67-DIA-2 |
0.90 |
-3.1183 |
0.0165 |
1.1878 |
0.9494 |
| Ki67-DIA-2 < 40* |
0.75 |
-4.3913 |
0.0085 |
1.1472 |
0.8688 |
| Ki67-DIA-1 |
0.89 |
5.0453 |
<0.0001 |
1.1309 |
0.9447 |
| Ki67-DIA-0 |
0.86 |
6.8232 |
<0.0001 |
1.2916 |
0.9278 |
| Ki67-VE-median |
0.86 |
8.3195 |
<0.0001 |
0.8572 |
0.9302 |
|
Multiple regression model
|
0.91 |
-0.3245 |
0.8096 |
|
|
| Ki67-DIA-2 |
|
|
|
0.8068 |
0.6448 |
| Ki67-VE-median | 0.2985 | 0.3239 |
*Ki67-DIA-2 < 40 - represents a regression model for Ki67-DIA-2 with only Ki67-Count less than 40% cases included in the analysis (n = 92). DIA, digital image analysis; VE, visual estimate.