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Table 8 Effect of the inverse regression-based prediction and measurement error correction on Ki67 dichotomisation accuracy at various reference value cutoffs (n = 164)

From: A methodology to ensure and improve accuracy of Ki67 labelling index estimation by automated digital image analysis in breast cancer tissue

Method

Underestimated (%)

Overestimated (%)

Total misclassified (%)

Ki-67 cutoff >10%

   

Ki67-VE-median

16/148 (11)

2/16 (13)

18 (11)

Ki67-DIA-2

0/148 (0)

12/16 (75)

12 (7)

Ki67-DIA-2 corrected

0/148 (0)

9/16 (56)

9 (5)

Ki67-DIA-2 corrected <40*

2/148 (1)

6/16 (38)

8 (5)

Ki-67 cutoff >15%

   

Ki67-VE-median

22/136 (16)

1/28 (4)

23 (14)

Ki67-DIA-2

2/136 (1)

13/28 (46)

15 (9)

Ki67-DIA-2 corrected

3/136 (2)

11/28 (46)

14 (9)

Ki67-DIA-2 corrected <40*

5/136 (4)

6/28 (21)

11 (7)

Ki-67 cutoff >20%

   

Ki67-VE-median

28/123 (23)

1/41 (2)

29 (18)

Ki67-DIA-2

2/123 (2)

9/41 (22)

11 (7)

Ki67-DIA-2 corrected

2/123 (2)

12/41 (29)

14 (9)

Ki67-DIA-2 corrected <40*

6/123 (5)

6/41 (15)

12 (7)

  1. *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.