miR-Test: A Blood Test for Lung Cancer Early Detection
| Autor: | Pier Paolo Di Fiore, Matteo Jacopo Marzi, Patrick Maisonneuve, Francesco Nicassio, Francesca Montani, Giuseppina Bonizzi, Massimo Bellomi, Raffaella Bertolotti, Fabio Dezi, Rose Mary Carletti, Fabrizio Bianchi, Giulia Veronesi, Cristiano Rampinelli, Elisa Dama, Lorenzo Spaggiari |
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| Přispěvatelé: | Montani, F, Marzi, Mj, Dezi, F, Dama, E, Carletti, Rm, Bonizzi, G, Bertolotti, R, Bellomi, M, Rampinelli, C, Maisonneuve, P, Spaggiari, L, Veronesi, G, Nicassio, F, Di Fiore, Pp, Bianchi, F |
| Rok vydání: | 2015 |
| Předmět: |
Adult
Male Oncology Cancer Research medicine.medical_specialty Lung Neoplasms Population Sensitivity and Specificity Predictive Value of Tests Internal medicine Biomarkers Tumor medicine Humans Blood test Lung cancer education Early Detection of Cancer Aged education.field_of_study Cancer Death Rate medicine.diagnostic_test business.industry Smoking Cancer Middle Aged medicine.disease Confidence interval Surgery MicroRNAs Area Under Curve Population Surveillance Predictive value of tests Female Tomography X-Ray Computed business Lung cancer screening |
| Zdroj: | JNCI: Journal of the National Cancer Institute. 107 |
| ISSN: | 1460-2105 0027-8874 |
| Popis: | Lung cancer is the leading cause of cancer death worldwide. Low-dose computed tomography screening (LDCT) was recently shown to anticipate the time of diagnosis, thus reducing lung cancer mortality. However, concerns persist about the feasibility and costs of large-scale LDCT programs. Such concerns may be addressed by clearly defining the target "high-risk" population that needs to be screened by LDCT. We recently identified a serum microRNA signature (the miR-Test) that could identify the optimal target population. Here, we performed a large-scale validation study of the miR-Test in high-risk individuals (n = 1115) enrolled in the Continuous Observation of Smoking Subjects (COSMOS) lung cancer screening program. The overall accuracy, sensitivity, and specificity of the miR-Test are 74.9% (95% confidence interval [CI] = 72.2% to 77.6%), 77.8% (95% CI = 64.2% to 91.4%), and 74.8% (95% CI = 72.1% to 77.5%), respectively; the area under the curve is 0.85 (95% CI = 0.78 to 0.92). These results argue that the miR-Test might represent a useful tool for lung cancer screening in high-risk individuals. |
| Databáze: | OpenAIRE |
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