ArticleAsian Pacific journal of cancer prevention : APJCP2026
Prediction Score of Cervical Intraepithelial Neoplasia Grade II or Higher (CIN2+) in Patients with Low-Grade Cytology (ASC-US, LSIL) and HPV- Negative or Non-type 16/18 High-Risk HPV-Positive Results.
Article in Asian Pacific journal of cancer prevention : APJCP, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectiveThe aim of this study was to identify and quantify the risk factors with the greatest impact on the development of CIN2+ in patients with low-grade cytology and either HPV-negative or high-risk HPV-positive (non-16/18) results. The secondary aim was to develop and validate a multiparameter, risk-based prediction system. MATERIALS AND
methodsThis retrospective cohort study was conducted in the Department of Obstetrics and Gynecology at Thammasat University Hospital between January 2021 and December 2024. Women who underwent cervical cancer screening and had a report of low-grade cytological abnormalities (ASC-US or LSIL), with either non-16/18 high-risk HPV infection or a negative HPV test, were included.
resultsA total of 480 participants were included. The mean age of participants was 40.7 years. The prevalence of CIN2+ was 15.6% (75/480). The predictive model was developed by incorporating six factors: having three or more deliveries, six or more lifetime sexual partners, smoking, no cervical screening within five years, lack of HPV vaccination, and high-risk HPV positivity (non-16/18). Subjects with a score of 5 or more out of 14 points were classified as high-risk and recommended to undergo colposcopy within four weeks. The model demonstrated a sensitivity of 97.3% and a negative predictive value (NPV) of 98.6%.
conclusionThe risk factors for CIN2+ included having three or more deliveries, six or more lifetime sexual partners, smoking, no cervical screening within the past five years, lack of HPV vaccination, and high-risk HPV positivity (non-16/18). The predictive model demonstrated a sensitivity of 97.3% and a negative predictive value (NPV) of 98.6%.
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