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已发表论文
高级别鳞状上皮内病变（HSIL）阳性疾病风险列线图模型：一项单中心回顾性分析
Authors Wu QZ, Lin MH, Zheng JR, Weng XQ, Zheng LL, Mao YY
Received 18 August 2025
Accepted for publication 25 October 2025
Published 4 November 2025 Volume 2025:17 Pages 4091—4101
DOI https://doi.org/10.2147/IJWH.S561459
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Matteo Frigerio
Qiu-Zhen Wu,1 Mao-Hua Lin,1 Jian-Rui Zheng,1 Xiu-Qing Weng,1 Li-Li Zheng,2,* Ying-Yu Mao1,*
1Department of Pathology, Mindong Hospital Affiliated to Fujian Medical University, Fuan, 355000, People’s Republic of China; 2Department of Gynecology, Mindong Hospital Affiliated to Fujian Medical University, Fuan, 355000, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Ying-Yu Mao, Department of Pathology, Mindong Hospital Affiliated to Fujian Medical University, Fuan, 355000, People’s Republic of China, Tel +86-18596659660, Fax +86-593-8981236, Email myy905@qq.com Li-Li Zheng, Department of Gynecology, Mindong Hospital Affiliated to Fujian Medical University, Fuan, 355000, People’s Republic of China, Tel +86-15080352165, Fax +86-593-8981915, Email 470326165@qq.com
Purpose: To develop and validate a nomogram for predicting high-grade squamous intraepithelial lesions or worse (HSIL+), incorporating results from ThinPrep cytologic test (TCT) and Aptima HPV E6/E7 mRNA (AHPV) testing.
Patients and Methods: This diagnostic study consecutively enrolled 3,202 patients referred for colposcopy due to abnormal cervical screening results. All participants underwent colposcopy with biopsy (targeted and/or endocervical) to obtain a definitive histopathological result, which served as the reference standard. The cohort was randomly split into training (70%) and validation (30%) sets. A binary logistic regression model was developed, and a nomogram was constructed. Model performance was evaluated using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA).
Results: The final multivariate model was defined by the equation: Logit(P) = − 4.014 + 1.677 × OHR + 2.917 × HPV16 + 1.938 × HPV18/45 + 2.343 × HPV(16+18/45) + 0.326 × ASC-US + 1.676 × ASC-H + 1.161 × LSIL + 1.593 × AGC + 4.939 × ≥HSIL. A nomogram was developed using the R rms package. The model demonstrated excellent discrimination in internal validation, with areas under the ROC curves (AUCs) of 0.843 (95% CI: 0.824– 0.863) in the training set and 0.833 (95% CI: 0.813– 0.873) in the validation set, along with good calibration. DCA confirmed its clinical utility across a risk threshold of 2%– 50%.
Conclusion: The developed logistic-nomogram provides an accurate and practical tool for predicting HSIL+, potentially aiding in individualized clinical management.
Keywords: cervical cancer screening, TCT, AHPV, HSIL+, nomogram
1Department of Pathology, Mindong Hospital Affiliated to Fujian Medical University, Fuan, 355000, People’s Republic of China; 2Department of Gynecology, Mindong Hospital Affiliated to Fujian Medical University, Fuan, 355000, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Ying-Yu Mao, Department of Pathology, Mindong Hospital Affiliated to Fujian Medical University, Fuan, 355000, People’s Republic of China, Tel +86-18596659660, Fax +86-593-8981236, Email myy905@qq.com Li-Li Zheng, Department of Gynecology, Mindong Hospital Affiliated to Fujian Medical University, Fuan, 355000, People’s Republic of China, Tel +86-15080352165, Fax +86-593-8981915, Email 470326165@qq.com
Purpose: To develop and validate a nomogram for predicting high-grade squamous intraepithelial lesions or worse (HSIL+), incorporating results from ThinPrep cytologic test (TCT) and Aptima HPV E6/E7 mRNA (AHPV) testing.
Patients and Methods: This diagnostic study consecutively enrolled 3,202 patients referred for colposcopy due to abnormal cervical screening results. All participants underwent colposcopy with biopsy (targeted and/or endocervical) to obtain a definitive histopathological result, which served as the reference standard. The cohort was randomly split into training (70%) and validation (30%) sets. A binary logistic regression model was developed, and a nomogram was constructed. Model performance was evaluated using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA).
Results: The final multivariate model was defined by the equation: Logit(P) = − 4.014 + 1.677 × OHR + 2.917 × HPV16 + 1.938 × HPV18/45 + 2.343 × HPV(16+18/45) + 0.326 × ASC-US + 1.676 × ASC-H + 1.161 × LSIL + 1.593 × AGC + 4.939 × ≥HSIL. A nomogram was developed using the R rms package. The model demonstrated excellent discrimination in internal validation, with areas under the ROC curves (AUCs) of 0.843 (95% CI: 0.824– 0.863) in the training set and 0.833 (95% CI: 0.813– 0.873) in the validation set, along with good calibration. DCA confirmed its clinical utility across a risk threshold of 2%– 50%.
Conclusion: The developed logistic-nomogram provides an accurate and practical tool for predicting HSIL+, potentially aiding in individualized clinical management.
Keywords: cervical cancer screening, TCT, AHPV, HSIL+, nomogram