Predicting high-risk human papillomavirus infection, progression of cervical intraepithelial neoplasia, and prognosis of cervical cancer with a panel of 13 biomarkers tested in multivariate modeling
Autor: | Margherita, Branca, Marco, Ciotti, Colomba, Giorgi, Donatella, Santini, Luigi, Di Bonito, Silvano, Costa, Arrigo, Benedetto, Donatella, Bonifacio, Paola, Di Bonito, Pierluigi, Paba, Luisa, Accardi, Stina, Syrjänen, Cartesio, Favalli, Kari, Syrjänen, L, Accardi |
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Přispěvatelé: | M., Branca, M., Ciotti, C., Giorgi, D., Santini, DI BONITO, Luigi, S., Costa, A., Benedetto, Bonifacio, Daniela, P., Di Bonito, P., Paba, L., Accardi, S., Syrjanen, C., Favalli, K., Syrjanen, Zanconati, Fabrizio |
Rok vydání: | 2008 |
Předmět: |
Ribosomal Proteins
Pathology medicine.medical_specialty Survival Vascular Endothelial Growth Factor C receptors Uterine Cervical Neoplasms Biology cervical intraepithelial neoplasia Cervical intraepithelial neoplasia Sensitivity and Specificity Pathology and Forensic Medicine Receptors Laminin models laminin Predictive Value of Tests medicine Biomarkers Tumor Humans Telomerase reverse transcriptase theoretical Cervical cancer Oncogenic human papillomavirus Biomarker Progression Receiver operating characteristic Oncogenic human papillomaviru Papillomavirus Infections Obstetrics and Gynecology Cancer Odds ratio Models Theoretical medicine.disease Prognosis Uterine Cervical Dysplasia tumor markers Predictive value of tests Multivariate Analysis Disease Progression Biomarker (medicine) Settore MED/40 - Ginecologia e Ostetricia Female sensitivity and specificity prognosis multivariate analysis female predictive value of tests humans models theoretical papillomavirus infections disease progression vascular endothelial growth factor c tumor markers biological receptors laminin uterine cervical neoplasms biological |
Zdroj: | International journal of gynecological pathology : official journal of the International Society of Gynecological Pathologists. 27(2) |
ISSN: | 1538-7151 |
Popis: | Comprehensive multivariate models were used to disclose whether any of our previously analyzed 13 markers would be independent predictors of intermediate end point markers in cervical carcinogenesis. The expression of the following biomarkers, E-cadherin, extracellular signal-regulated kinase 1, 67-kd laminin receptor (LR67), matrix metalloproteinase 2, tissue inhibitor of metalloproteinase 2, nuclear factor-kappaB, nm23-H1, p16, proliferating cell nuclear antigen, survivin, human telomerase reverse transcriptase, topoisomerase 2alpha, and vascular endothelial growth factor (VEGF) C in 150 cervical cancer (CC) and 152 cervical intraepithelial neoplasia (CIN) lesions were determined immunohistochemically. Multivariate models were constructed to test predictive power of the markers for 3 outcomes: (1) high-grade CIN, (2) high-risk human papillomavirus (HR-HPV), and (3) CC survival. Performance indicators were calculated and compared by the areas under receiver operating characteristic (ROC) curve. Three marker panels were identified consisting of 5 independent predictors of CIN2 (E-cadherin, extracellular signal-regulated kinase 1, LR67, topoisomerase 2alpha, and VEGF-C), 3 predictors of HR-HPV (survivin, p16, and human telomerase reverse transcriptase), and 2 predictors of CC survival (nm23-H1 and tissue inhibitor of metalloproteinase 2). In predicting CIN2, the best balance between sensitivity (SE) and specificity (SP) was obtained by combining the 2 most powerful predictors in panel 1 (VEGF-C and LR67), giving the area under ROC curve, 0.897 (95% confidence interval [CI], 0.847-0.947); odds ratio, 86.27 (95% CI, 19.71-377.47); SE, 86.0%; SP, 93.3%; positive predictive value (PPV), 99.1%; and negative predictive value (NPV), 43.1%. In a hypothetical screening setting (10,000 women; CIN2 prevalence, 1%), this marker combination should theoretically detect CIN2 with 86.0% SE, 100% SP, 99.1% PPV, and 99.6% NPV, area under ROC curve of 0.930 (95% CI, 0.909-0.951), and odds ratio, 29998.0 (95% CI, 7,879.0-37,338.0). Combining 2 markers (LR67 and VEGF-C) enables accurate detection of high-grade CIN in a clinical setting. However, testing the performance of this marker combination in a screening setting necessitates their analysis in cytological samples. |
Databáze: | OpenAIRE |
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