ArticleFrontiers in oncology2026
Risk-stratified surveillance after LEEP: a nomogram integrating HPV persistence, margin status, and clinical factors to predict CIN2+ recurrence.
Article in Frontiers in oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Impact of Body Mass Index on Clinical Outcomes of LLETZ.Journal of clinical medicine · 2026Article
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10 authors.
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Abstract
Background: Cervical intraepithelial neoplasia (CIN) recurrence after loop electrosurgical excision procedure (LEEP) remains a clinically consequential barrier to cervical cancer prevention, and risk stratification tools tailored to real-world practice are limited in China. This study developed and internally validated a clinical prediction nomogram for histologically confirmed CIN2+ recurrence after LEEP. Methods: A retrospective single-center cohort was assembled of women treated with LEEP for CIN2+ between January 2018 and October 2024. Candidate predictors included demographic and reproductive factors, smoking, HPV vaccination, prior cervical treatment, transformation zone type, LEEP pathology (including adenocarcinoma Results: Among 2,230 women (median follow-up 31.8 months, IQR 19.6-43.5), 334 developed CIN2+ recurrence (15.0%), with a median time to recurrence of 15.6 months (IQR 8.2-24.3). Persistent HPV infection occurred in 50.6% of women with recurrence versus 23.1% without recurrence ( Conclusion: In a contemporary Chinese single-center cohort, genotype-defined persistent HPV infection and margin burden were dominant determinants of CIN2+ recurrence after LEEP, with vaccination status and NLR providing additional stratification. The resulting nomogram offers a pragmatic framework for risk-adapted surveillance, pending external multicenter validation.
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