Related Experiment Video
Updated: May 5, 2026

Chromogenic In Situ Hybridization as a Tool for HPV-Related Head and Neck Cancer Diagnosis
Published on: June 14, 2019
The Performance of Modified Swede Colposcopic Index to Predict High Grade Cervical Intraepithelial Neoplasia and
Nutchar Klangprapan1, Nopporn Rodpenpear2
1Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Police general hospital, Rajprasong Intersection Pathuwan Bangkok, Thailand.
Objective:
The primary objective is to examine the external validity of the modified Swede colposcopic index (MSCI) for predicting cervical intraepithelial neoplasia grade 2-3, including cancer (CIN2+), and to evaluate inter-rater and intra-rater reliability as a secondary objective in women with abnormal cervical cancer screening.
Methods:
We conducted a prospective study to predict CIN2+ in women aged 25-65 years with abnormal cervical cancer screening results (atypical squamous cells of undetermined significance (ASC-US) or higher and/or high-risk HPV infection). All participants were previously undiagnosed with CIN2+. We evaluated the effectiveness of MSCI in detecting CIN2+ using sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).
Results:
A total of 118 women were included in this study. Gynecologic oncologists using the MSCI achieved a sensitivity of 46.9%, specificity of 87.2%, PPV of 57.7%, NPV of 81.5%, and accuracy of 76.27%. Inter-rater reliability for the MSCI was good (ICC=0.77, 95%confidence interval=0.67-0.84), and intra-rater reliability was excellent (ICC=0.98, 95%confidence interval =0.97-0.99).
Conclusion:
In a real-world clinical setting, studies have demonstrated that MSCI exhibits high specificity while maintaining acceptable sensitivity.
More Related Videos
03:05Author Spotlight: Advancing Early Detection and Treatment of Gastrointestinal Tumors
Published on: February 16, 2024
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025