Background
Linear discriminant analysis
Classification by machine learning
Methods
IHC-decision trees and linear discriminant analysis of the public DLBCL database
IHC-decision trees and LDA classification, comparative performance analysis
Classification of DLBCL in COO molecular subgroups by automatic classifiers
IHC-decision trees and machine learning classifiers, comparative performance analysis
Validation in a clinical sample set
Survival analysis
Results
Public database analysis
Clinical sample set characteristics
IHC-decision trees and classification by LDA, performance analysis
Algorithm | Antibody combination | Acc | Sens | Spec | PPV | NPV | LR+ | LR− | |
---|---|---|---|---|---|---|---|---|---|
IHC-decision trees | Nyman | 3,5 | 0.72 | 0.52 | 0.91 | 0.84 | 0.67 | 5.56 | 0.53 |
Colomo | 1,2,5 | 0.78 | 0.71 | 0.84 | 0.81 | 0.75 | 4.56 | 0.34 | |
Hans | 1,2,5 | 0.85 | 0.91 | 0.78 | 0.80 | 0.91 | 4.21 | 0.11 | |
Hans* | 1,5 | 0.82 | 0.94 | 0.70 | 0.75 | 0.92 | 3.14 | 0.09 | |
Choi | 1,2,3,4,5 | 0.88 | 0.94 | 0.84 | 0.84 | 0.93 | 5.70 | 0.08 | |
Choi* | 1,3,4,5 | 0.79 | 0.74 | 0.83 | 0.80 | 0.77 | 4.30 | 0.31 | |
VY3 | 1,2,3 | 0.88 | 0.92 | 0.84 | 0.85 | 0.92 | 5.92 | 0.09 | |
VY4 | 1,2,3,4 | 0.88 | 0.93 | 0.84 | 0.85 | 0.92 | 5.80 | 0.09 | |
Linear discriminant analysis | As in Hans* | 1,5 | 0.84 | 0.77 | 0.91 | 0.89 | 0.81 | 8.59 | 0.25 |
As in Nyman | 3,5 | 0.77 | 0.81 | 0.74 | 0.75 | 0.81 | 3.10 | 0.25 | |
As in VY3 | 1,2,3 | 0.89 | 0.87 | 0.91 | 0.90 | 0.88 | 9.19 | 0.15 | |
As in Hans/Colomo | 1,2,5 | 0.87 | 0.86 | 0.88 | 0.87 | 0.87 | 7.25 | 0.16 | |
– | 1,4,5 | 0.87 | 0.81 | 0.92 | 0.90 | 0.84 | 9.93 | 0.20 | |
As in VY4 | 1,2,3,4 | 0.87 | 0.84 | 0.90 | 0.89 | 0.86 | 8.24 | 0.17 | |
As in Choi* | 1,3,4,5 | 0.88 | 0.86 | 0.91 | 0.90 | 0.87 | 9.09 | 0.16 | |
As in Choi | 1,2,3,4,5 | 0.89 | 0.87 | 0.91 | 0.90 | 0.88 | 9.23 | 0.14 |
IHC-decision tree algorithms performance
Linear discriminant analysis performance
Antibody combination | Sens | Spec | COO | Constant | Antibody | |||||
---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | ||||||
CD10 | BCL6 | FOXP1 | GCET1 | MUM1 | ||||||
As in Nyman | 3,5 | 0.81 | 0.74 | GCB | − 0.57 | 2.47 | 1.11 | |||
Non-GCB | − 3.29 | 4.38 | 5.06 | |||||||
As in Hans and | 1,2,5 | 0.86 | 0.88 | GCB | − 4.21 | 5.01 | 7.00 | 1.05 | ||
As in Colomo | Non-GCB | − 3.09 | 0.20 | 4.99 | 5.69 | |||||
As in Hans* | 1,5 | 0.77 | 0.91 | GCB | − 2.29 | 6.53 | 2.11 | |||
Non-GCB | − 2.12 | 1.28 | 6.45 | |||||||
As in Choi | 1,2,3,4,5 | 0.87 | 0.91 | GCB | − 4.80 | 4.59 | 6.31 | 0.71 | 3.28 | 1.02 |
Non-GCB | − 3.98 | − 0.41 | 3.80 | 3.75 | 1.24 | 4.73 | ||||
As in Choi* | 1,3,4,5 | 0.86 | 0.91 | GCB | − 3.34 | 5.67 | 1.78 | 4.03 | 1.67 | |
Non-GCB | − 3.46 | 0.24 | 4.39 | 1.69 | 5.12 | |||||
As in VY3 | 1,2,3 | 0.87 | 0.91 | GCB | − 4.18 | 4.86 | 6.99 | 0.64 | ||
Non-GCB | − 2.90 | − 0.74 | 4.58 | 4.61 | ||||||
As in VY4 | 1,2,3,4 | 0.84 | 0.90 | GCB | − 4.75 | 4.49 | 6.44 | 0.91 | 3.26 | |
Non-GCB | − 2.97 | − 0.86 | 4.40 | 4.70 | 1.12 | |||||
– | 1,4,5 | 0.81 | 0.92 | GCB | − 3.14 | 6.01 | 3.93 | 2.22 | ||
Non-GCB | − 2.23 | 1.09 | 1.44 | 6.49 |
Machine learning algorithms performance analysis
Algorithm | Antibody combination | Acc | Sens | Spec | PPV | NPV | LR+ | LR− | |
---|---|---|---|---|---|---|---|---|---|
IHC-decision tree | Nyman | 3,5 | 0.79 | 0.65 | 0.95 | 0.93 | 0.71 | 12.47 | 0.37 |
Colomo | 1,2,5 | 0.84 | 0.77 | 0.91 | 0.91 | 0.79 | 8.98 | 0.25 | |
Hans | 1,2,5 | 0.89 | 0.95 | 0.83 | 0.86 | 0.94 | 5.52 | 0.06 | |
Hans* | 1,5 | 0.86 | 0.95 | 0.76 | 0.81 | 0.94 | 3.94 | 0.06 | |
Choi | 1,2,3,4,5 | 0.93 | 1.00 | 0.84 | 0.87 | 1.00 | 6.44 | 0.00 | |
Choi* | 1,3,4,5 | 0.83 | 0.79 | 0.86 | 0.86 | 0.79 | 5.73 | 0.24 | |
VY3 | 1,2,3 | 0.90 | 0.97 | 0.83 | 0.86 | 0.96 | 5.61 | 0.04 | |
VY4 | 1,2,3,4 | 0.90 | 0.97 | 0.83 | 0.86 | 0.96 | 5.61 | 0.04 | |
Machine learning | PV | 1,3,4,5 | 0.94 | 0.95 | 0.93 | 0.94 | 0.95 | 13.8 | 0.05 |
ANN | 1,2,3,4,5 | 0.94 | 0.95 | 0.93 | 0.94 | 0.95 | 13.8 | 0.05 | |
BS | 1,2,3,4,5 | 0.94 | 0.95 | 0.93 | 0.94 | 0.95 | 13.8 | 0.05 | |
SVM | 1,2,3,4,5 | 0.94 | 0.97 | 0.91 | 0.92 | 0.96 | 11.23 | 0.04 | |
SVM | 1,2,3,4 | 0.94 | 0.97 | 0.91 | 0.92 | 0.96 | 11.23 | 0.04 |