Analysis of Sensitivity, Specificity, and Positive and Negative Predictive Values of Smear and Colposcopy in Diagnosis of Premalignant and Malignant Cervical Lesions.

BACKGROUND This study aimed to examine the positive and negative predictive value in the diagnosis of premalignant and malignant lesions of cervical colposcopy, the sensitivity and specificity of smear, and to evaluate the correlation with histopathology of abnormal cytology and colposcopy. MATERIAL AND METHODS The criteria for inclusion of patients with unhealthy cervix in the study were: Erosion, Chronic cervicitis, and Healed lacerations, Hypertrophied cervix, bleeding on touch, suspicious growth/ulcer/polyp on the cervix, and abnormal discharges from the cervix. Women with frank carcinoma cervix, pregnant females, patients with bleeding per vaginum at the time of examination, and those who had used vaginal medications, vaginal contraceptives or douches in the last 48 h of examination were excluded from the study. Demographic analysis was performed for 450 patients who were admitted to the clinic. Sensitivity, specificity, positive predictive value and negative predictive values of patients to identify cervical pathologies of smear and colposcopy were histopathologically calculated. The statistical software package SPSS 15.0 (SPSS Inc., Chicago, IL, USA) and Spearman's and Chi-Square tests were used for statistical analysis. RESULTS Sensitivity, specificity, PPD and NDP of smear were 0.57%, 0.76%, 0.26%, 0.92% respectively. Sensitivity, specificity, PPD and NDP of colposcopy were 0.92%, 0.67%, 0.52%, 0.96% respectively. A statistically significant correlation was found between abnormal cytology and histopathology, and abnormal colposcopy finding and histopathology. CONCLUSIONS Women with clinical diagnosis of unhealthy cervix should be evaluated by cytology to detect any premalignant or malignant lesions. It was concluded that Pap smear, colposcopy and histopathology should be collectively evaluated to evaluate cervical findings in low socio-economic regions.