ROC-Analysis Derived Immunohistochemical P53 Cut-Off Scores as an Adjunct to Routine Histopathology for Better Diagnostic Compartmentalisation of Cervical Lesions

OBJECTIVE: The aim of this study was to evaluate the predictive value of Immunohistochemical p53 cut-off scores as an adjunct to routine histopathology for better diagnosis of cervical lesions. MATERIALS AND METHODS: Prospective study carried out for 1 year. After ethical approval and informed consent, a total of 100 cervical tissue samples were analyzed; chronic cervicitis (CC)-15, cervical intraepithelial neoplasia (CIN)-40, and squamous cell carcinoma cervix (SCC)-45 (FIGO 2018 clinical staging). After routine processing of tissue specimen, hematoxylin and eosin (HE) staining was done. Grading of cervical precancerous lesions (CIN) was done as per World Health Organisation criteria as CIN 1,2 or 3. Broder’s grading was assigned for every SCC sample. RESULTS: Mean p53 scores of CC, CIN, and SCC cases were 0.0, 1.70, and 4.38, respectively, CIN 1, 2, and 3 were 1.07, 1.63, and 2.22, respectively. SCC was differentiated from CIN3 with p53 ≥4.5 as predictor for SCC, sensitivity and specificity were 57.8% and 88.9%, respectively. Overall diagnostic accuracy of the proposed scoring system for differentiating CC, CIN, and SCC was 61%, while the accuracy of previous methods of interpreting p53 immunoreactivity as immunoscore >2 or arbitrary cut-off of >10% cells with nuclear positivity was only 48%. CONCLUSION: ROC-derived immunoscore cut-offs can provide the much-needed objectivity and optimal decision thresholds to immunohistochemistry interpretation.