Purpose: Recent screening trial results indicate that low-dose computed tomography (LDCT) reduces lung cancer mortality in high-risk patients. However, high false-positive rates, costs, and potential harms highlight the need for complementary biomarkers. The diagnostic performance of a noninvasive plasma microRNA signature classifier (MSC) was retrospectively evaluated in samples prospectively collected from smokers within the randomized Multicenter Italian Lung Detection (MILD) trial. Patients and Methods: Plasma samples from 939 participants, including 69 patients with lung cancer and 870 disease-free individuals (n = 652, LDCT arm; n = 287, observation arm) were analyzed by using a quantitative reverse transcriptase polymerase chain reaction-based assay for MSC. Diagnostic performance of MSC was evaluated in a blinded validation study that used prespecified risk groups. Results: The diagnostic performance of MSC for lung cancer detection was 87% for sensitivity and 81% for specificity across both arms, and 88% and 80%, respectively, in the LDCT arm. For all patients, MSC had a negative predictive value of 99% and 99.86% for detection and death as a result of disease, respectively. LDCT had sensitivity of 79% and specificity of 81% with a false-positive rate of 19.4%. Diagnostic performance of MSC was confirmed by time dependency analysis. Combination of both MSC and LDCT resulted in a five-fold reduction of LDCT false-positive rate to 3.7%. MSC risk groups were significantly associated with survival (χ12 = 49.53; P < .001). Conclusion: This large validation study indicates that MSC has predictive, diagnostic, and prognostic value and could reduce the false-positive rate of LDCT, thus improving the efficacy of lung cancer screening. © 2014 by American Society of Clinical Oncology.

Clinical utility of a plasma-based miRNA signature classifier within computed tomography lung cancer screening: A correlative MILD trial study / Sozzi, Gabriella; Boeri, Mattia; Rossi, Marta; Verri, Carla; Suatoni, Paola; Bravi, Francesca; Roz, Luca; Conte, Davide; Grassi, Michela; Sverzellati, Nicola; Marchiano, Alfonso; Negri, Eva; La Vecchia, Carlo; Pastorino, Ugo. - In: JOURNAL OF CLINICAL ONCOLOGY. - ISSN 0732-183X. - 32:8(2014), pp. 768-773. [10.1200/JCO.2013.50.4357]

Clinical utility of a plasma-based miRNA signature classifier within computed tomography lung cancer screening: A correlative MILD trial study

SVERZELLATI, Nicola;
2014-01-01

Abstract

Purpose: Recent screening trial results indicate that low-dose computed tomography (LDCT) reduces lung cancer mortality in high-risk patients. However, high false-positive rates, costs, and potential harms highlight the need for complementary biomarkers. The diagnostic performance of a noninvasive plasma microRNA signature classifier (MSC) was retrospectively evaluated in samples prospectively collected from smokers within the randomized Multicenter Italian Lung Detection (MILD) trial. Patients and Methods: Plasma samples from 939 participants, including 69 patients with lung cancer and 870 disease-free individuals (n = 652, LDCT arm; n = 287, observation arm) were analyzed by using a quantitative reverse transcriptase polymerase chain reaction-based assay for MSC. Diagnostic performance of MSC was evaluated in a blinded validation study that used prespecified risk groups. Results: The diagnostic performance of MSC for lung cancer detection was 87% for sensitivity and 81% for specificity across both arms, and 88% and 80%, respectively, in the LDCT arm. For all patients, MSC had a negative predictive value of 99% and 99.86% for detection and death as a result of disease, respectively. LDCT had sensitivity of 79% and specificity of 81% with a false-positive rate of 19.4%. Diagnostic performance of MSC was confirmed by time dependency analysis. Combination of both MSC and LDCT resulted in a five-fold reduction of LDCT false-positive rate to 3.7%. MSC risk groups were significantly associated with survival (χ12 = 49.53; P < .001). Conclusion: This large validation study indicates that MSC has predictive, diagnostic, and prognostic value and could reduce the false-positive rate of LDCT, thus improving the efficacy of lung cancer screening. © 2014 by American Society of Clinical Oncology.
2014
Clinical utility of a plasma-based miRNA signature classifier within computed tomography lung cancer screening: A correlative MILD trial study / Sozzi, Gabriella; Boeri, Mattia; Rossi, Marta; Verri, Carla; Suatoni, Paola; Bravi, Francesca; Roz, Luca; Conte, Davide; Grassi, Michela; Sverzellati, Nicola; Marchiano, Alfonso; Negri, Eva; La Vecchia, Carlo; Pastorino, Ugo. - In: JOURNAL OF CLINICAL ONCOLOGY. - ISSN 0732-183X. - 32:8(2014), pp. 768-773. [10.1200/JCO.2013.50.4357]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2809859
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