A preliminary study of the potential of tree classifiers in triage of high-grade squamous intraepithelial lesions.

OBJECTIVE

To investigate the potential value of tree classifiers for the triage of high-grade squamous intraepithelial lesions.

STUDY

DESIGN

The dataset comprised 808 histologically confirmed cases having a complete range of the cytologic sample assessments--liquid-based cytology, reflex human papillomavirus (HPV) DNA test, E6/E7 HPV mRNA test, and p16 immunocytochemical examinations. Data include 488 histologically negative (cervical intraepithelial neoplasia [CIN] 1 and below) or clinically negative cases and 320 with histologic diagnosis of CIN 2 or worse. Cytologic diagnosis was made according to the criteria of the Bethesda System. Cases were classified in two groups according to histology: those with CIN 2 or worse and those with CIN 1 and below. Fifty percent were randomly selected as a training set and the remaining were as a test set.

RESULTS

Application of tree classifier on the test set gave correct classification of 66.9% for CIN 2 and above cases and 97.3% for CIN 1 and below, producing overall accuracy of 91.5%, outperforming cytologic diagnosis alone.

CONCLUSION

Application of tree classifiers, based on standard cytologic diagnosis and expression of studied biomarkers, produces improved classification results for cervical precancerous lesions and cancer diagnosis and