Residual disease and risk factors in patients with high-grade cervical intraepithelial neoplasia and positive margins after initial conization
Authors Fu Y, Chen C, Feng S, Cheng X, Wang X, Xie X, Lü W
Received 29 January 2015
Accepted for publication 9 March 2015
Published 21 May 2015 Volume 2015:11 Pages 851—856
Checked for plagiarism Yes
Review by Single-blind
Peer reviewer comments 2
Editor who approved publication: Professor Deyun Wang
Yunfeng Fu,1,2,* Chen Chen,3,* Suwen Feng,2 Xiaodong Cheng,2 Xinyu Wang,1,2 Xing Xie,1,2 Weiguo Lü2
1Department of Gynecology, Fourth Affiliated Hospital, School of Medicine, Zhejiang University, Yiwu, 2Department of Gynecologic Oncology, Women’s Hospital, School of Medicine, Zhejiang University, Hangzhou, 3Second Hospital of Shandong University, Jinan, People’s Republic of China
*These authors contributed equally to this work
Background: The purpose of this study was to determine the clinicopathologic predictors of residual disease in patients with high-grade cervical intraepithelial neoplasia (CIN) and margin involvement after initial conization.
Methods: Data from 145 patients who underwent subsequent surgery for high-grade CIN with positive margins were retrospectively analyzed.
Results: After subsequent surgery, residual disease was diagnosed in 47 (34.2%) patients, of whom five had invasive cervical carcinoma, 31 had CIN 3, nine had CIN 2, and two had CIN 1. Multivariate analysis revealed that only age ≥35 years (P=0.033), major abnormal cytology (P=0.002), and pre-cone high-risk human papillomavirus load ≥300 relative light units (P=0.011) were significant factors associated with residual disease.
Conclusion: Age ≥35 years, major abnormal cytology, and pre-cone high-risk human papillomavirus load ≥300 relative light units were the only significant factors predicting post-cone residual disease. Appropriate application of these predictive factors may avoid delayed treatment and overtreatment.
Keywords: cervical intraepithelial neoplasia, residual disease, conization, positive margin, predictor
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