Table 3

Performance of predictive models for classification of clinico-pathological characteristics in normal mucosa tissue.

CHARACTERISTICS

¹Advanced Dukes'

stage

Poorly differentiated

Lymph node

involvement

Invasiveness

²Disease recurrence

Number of features

7

5

3

6

7

Positive prediction rate

8/13

8/14

11/14

3/7

0/5

Sensitivity

0.615

0.571

0.786

0.429

0.000

³CI

0.322-0.849

0.296-0.812

0.488-0.943

0.116-0.798

0.000-0.537

Positive predictive value

0.500

0.444

0.733

0.500

0.000

CI

0.255-0.749

0.224-0.686

0.448-0.911

0.139-0.860

0.000-0.945

Negative prediction rate

12/20

9/19

15/19

23/26

25/26

Specificity

0.600

0.474

0.789

0.885

0.962

CI

0.364-0.800

0.252-0.705

0.539-0.930

0.687-0.970

0.784-0.998

Negative predictive value

0.706

0.600

0.833

0.852

0.833

CI

0.440-0.886

0.329-0.825

0.577-0.956

0.654-0.951

0.645-0.937

Absolute error

0.394

0.485

0.212

0.212

0.194

⁴ROC error

0.392

0.477

0.212

0.343

0.519

Fisher's exact test

P = 0.139

P = 0.267

P = 0.001

P = 0.082

P = 0.839

¹Includes Dukes' C1 and C2; ² Median follow-up time for recurrent disease patients: 33 months; median follow-up time for disease-free patient: 27 months (analysis excludes patients who died through surgical complications - see Table 1); ³CI = 95% confidence interval; ⁴ROC = receiver-operator characteristics

The KNN algorithm [29] was used in 'leave-one-out' cross-validation prediction with the number of features (marker peaks) specified. Marker peaks were selected using a t-test statistic except for lymph node involvement and invasiveness characteristics of tumour tissue where the SNR test statistic was used.

Liao et al. BMC Cancer 2010 10:410   doi:10.1186/1471-2407-10-410