The role of PAX1 and JAM3 methylation in predicting the pathological upgrading of cervical intraepithelial neoplasia before conization DOI
Xiaoyan Chen,

Hubin Xu,

Lei Zhao

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: April 17, 2025

Abstract Objective:To explore the effect of PAX1 and JAM3 gene methylation on pathological upgrading before conization. Methods:A total 549 patients who underwent colposcopy at our hospital were enrolled for analysis from December 2020 to April 2022. results in preoperative cervical exfoliated cells collected. Univariate multivariate logistic regression conducted identify independent risk factors influencing conization, aiming establish a prediction model. Results: A 88 finally included statistical according inclusion exclusion criteria. Based univariate analysis, ∆Ct (P=0.016, OR: 0.784, 95%CI: 0.644-0.956) canal lesions (P=0.048, 3.469, 1.014-11.870) identified as Using above results, we established model plotted receiver operator characteristic curve (ROC). The area under (AUC) was calculated when Youden index maximized with an AUC value 0.818 (95%CI: 0.720-0.916), specificity 94.4%, sensitivity 60%. cut-off determined 4 .34 maximizing index. Conclusion:PAX1 could be promising triage marker predicting CIN We found that if △Ct is lower than 4.34, it highly suggestive upgrading.

Language: Английский

The role of PAX1 and JAM3 methylation in predicting the pathological upgrading of cervical intraepithelial neoplasia before conization DOI
Xiaoyan Chen,

Hubin Xu,

Lei Zhao

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: April 17, 2025

Abstract Objective:To explore the effect of PAX1 and JAM3 gene methylation on pathological upgrading before conization. Methods:A total 549 patients who underwent colposcopy at our hospital were enrolled for analysis from December 2020 to April 2022. results in preoperative cervical exfoliated cells collected. Univariate multivariate logistic regression conducted identify independent risk factors influencing conization, aiming establish a prediction model. Results: A 88 finally included statistical according inclusion exclusion criteria. Based univariate analysis, ∆Ct (P=0.016, OR: 0.784, 95%CI: 0.644-0.956) canal lesions (P=0.048, 3.469, 1.014-11.870) identified as Using above results, we established model plotted receiver operator characteristic curve (ROC). The area under (AUC) was calculated when Youden index maximized with an AUC value 0.818 (95%CI: 0.720-0.916), specificity 94.4%, sensitivity 60%. cut-off determined 4 .34 maximizing index. Conclusion:PAX1 could be promising triage marker predicting CIN We found that if △Ct is lower than 4.34, it highly suggestive upgrading.

Language: Английский

Citations

0