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Volume 15
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10.3390/diagnostics15172200
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Clinical and Virological Profiles Associated with CINTEC® PLUS Positivity: A Data-Driven Clustering and Modeling Study

by
Iulian-Valentin Munteanu
1,
Demetra Socolov
2,*,
Razvan Socolov
2,
Ana-Maria Adam
1,
Gigi Adam
3,
Ingrid-Andrada Vasilache
2,
Petronela Vicoveanu
4,
Valeriu Harabor
1,
Anamaria Harabor
1 and
Alina-Mihaela Calin
1
1
Clinical and Surgical Department, Faculty of Medicine and Pharmacy, ‘Dunarea de Jos’ University, 800216 Galati, Romania
2
Department of Mother and Child Care, “Grigore T. Popa” University of Medicine and Pharmacy Iasi, 700115 Iasi, Romania
3
Department of Pharmaceutical Sciences, Faculty of Medicine and Pharmacy, ‘Dunarea de Jos’ University, 800216 Galati, Romania
4
Department of Mother and Newborn Care, Faculty of Medicine and Biological Sciences, ‘Ștefan cel Mare’ University, 720229 Suceava, Romania
*
Author to whom correspondence should be addressed.
Diagnostics 2025, 15(17), 2200; https://doi.org/10.3390/diagnostics15172200
Submission received: 22 July 2025 / Revised: 18 August 2025 / Accepted: 28 August 2025 / Published: 29 August 2025
(This article belongs to the Special Issue Diagnosis and Management of Gynecological Cancers: Third Edition)
Versions Notes

Abstract

Background/Objectives: The diagnostic performance of CINtec® PLUS can be influenced by numerous patient characteristics and risk factors. The aim of this retrospective study was to evaluate and model the risk factors associated with CINtec® PLUS test positivity in patients undergoing cervical cancer screening and to assess their predictive performance for the prediction of cervical intraepithelial neoplasia (CIN) 2/3 using an unsupervised machine learning-based model. Methods: Medical data of 134 patients with human papillomavirus (HPV) infection who underwent CINtec® PLUS testing were used to model the impact of risk factors on dual-stain cytology positivity and to evaluate the predictive performance for CIN2/3. Results: The gradient boosting classifier for the prediction of CINtec® PLUS positivity using clinical risk factors had a precision of 75%, an overall accuracy of 0.62, and an area under the curve (AUC) value of 0.77. Body mass index and age were the most important variables in this model. HSIL, ASC-US, and other high-risk HPV strains increased the likelihood of a positive outcome. Overall AUC values for a positive test alone were 0.74 and 0.69 for CIN2 and CIN3 prediction, respectively. For CIN2 prediction, the XGBoost model performed well, with 71% sensitivity, 85% specificity, and an AUC value of 0.90. However, the model had 96% sensitivity, 25% specificity, and 0.58 AUC for CIN3 prediction. Conclusions: Patient characteristics and risk factors can influence CINtec® PLUS positivity rates and they need to be carefully considered before choosing a specific management.
Keywords: dual-stain cytology; CINtec® PLUS positivity; XGBoost; modeling; clinical risk profile; clusters dual-stain cytology; CINtec® PLUS positivity; XGBoost; modeling; clinical risk profile; clusters

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MDPI and ACS Style

Munteanu, I.-V.; Socolov, D.; Socolov, R.; Adam, A.-M.; Adam, G.; Vasilache, I.-A.; Vicoveanu, P.; Harabor, V.; Harabor, A.; Calin, A.-M. Clinical and Virological Profiles Associated with CINTEC® PLUS Positivity: A Data-Driven Clustering and Modeling Study. Diagnostics 2025, 15, 2200. https://doi.org/10.3390/diagnostics15172200

AMA Style

Munteanu I-V, Socolov D, Socolov R, Adam A-M, Adam G, Vasilache I-A, Vicoveanu P, Harabor V, Harabor A, Calin A-M. Clinical and Virological Profiles Associated with CINTEC® PLUS Positivity: A Data-Driven Clustering and Modeling Study. Diagnostics. 2025; 15(17):2200. https://doi.org/10.3390/diagnostics15172200

Chicago/Turabian Style

Munteanu, Iulian-Valentin, Demetra Socolov, Razvan Socolov, Ana-Maria Adam, Gigi Adam, Ingrid-Andrada Vasilache, Petronela Vicoveanu, Valeriu Harabor, Anamaria Harabor, and Alina-Mihaela Calin. 2025. "Clinical and Virological Profiles Associated with CINTEC® PLUS Positivity: A Data-Driven Clustering and Modeling Study" Diagnostics 15, no. 17: 2200. https://doi.org/10.3390/diagnostics15172200

APA Style

Munteanu, I.-V., Socolov, D., Socolov, R., Adam, A.-M., Adam, G., Vasilache, I.-A., Vicoveanu, P., Harabor, V., Harabor, A., & Calin, A.-M. (2025). Clinical and Virological Profiles Associated with CINTEC® PLUS Positivity: A Data-Driven Clustering and Modeling Study. Diagnostics, 15(17), 2200. https://doi.org/10.3390/diagnostics15172200

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