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Table 2 The results from the OPLS-DA and statistical analyses

From: Molecular response to induction chemotherapy and its correlation with treatment outcome in head and neck cancer patients by means of NMR-based metabolomics

OPLS-DA model diagnostics

Predictive component

R2X

R2Y

Q2

 

0.0995

0.477

0.28

Orthogonal components

R2X(o)

  
 

0.548

  
 

0.107

  

cv-ANOVA p value

0.0001

  

Misclassification table

 

Members

Correct

 

preCHT

1

100%

 

postCHT

23

100%

 

List of the important metabolites from the OPLS-DA model

Name

ppm

p(corr)

p value

Median ratio [%]

Metabolites increased after induction chemotherapy

1

Lipids

0.9

0.76

< 0.000

12.73

  

1.3

0.57

< 0.000

18.58

  

5.3

0.69

< 0.000

17.38

Metabolites decreased after induction chemotherapy

2

Alanine

1.48

0.33

0.0008

14.21

3

NAG

2.07

0.12

0.0002

9.03

4

Glucose

3.24

0.31

0.04

9.4

  

3.42

0.43

0.042

8.11

  

3.44

0.48

0.038

8.46

  

3.51

0.43

0.036

9.54

  

3.56

0.46

0.04

9.33

  

3.72

0.55

0.039

9.59

  

3.76

0.43

0.031

8.3

  

3.83

0.39

0.019

8.57

  

3.9

0.48

0.028

9.34

  

5.2

0.32

0.025

9.57

  1. R2X — an amount of variation in the data that is correlated to class separation; R2Y — a fraction of the class membership (Y) variation modeled using the data matrix (X), this parameter tells how good is the separation between two classes; R2X(o) — an amount of variation in the data that is uncorrelated (orthogonal) to the class separation; Q2 — a predictive ability of the OPLS-DA model; p(corr) — describes reliability of a variable, the closer to one the better; p value – from the WSR test, Median ratio — shows the between class differences in the peak integrals and is calculated as: 100 - (lower median)/(higher median)*100. NAG — N-acetyl-glycoprotein.