TY - JOUR
T1 - Noninvasive risk stratification of lung adenocarcinoma using quantitative computed tomography
AU - Raghunath, Sushravya
AU - Maldonado, Fabien
AU - Rajagopalan, Srinivasan
AU - Karwoski, Ronald A.
AU - DePew, Zackary S.
AU - Bartholmai, Brian J.
AU - Peikert, Tobias
AU - Robb, Richard A.
N1 - Publisher Copyright:
Copyright © 2014 by the International Association for the Study of Lung Cancer.
PY - 2014/11/1
Y1 - 2014/11/1
N2 - Introduction: Lung cancer remains the leading cause of cancer-related deaths in the United States and worldwide. Adenocarcinoma is the most common type of lung cancer and encompasses lesions with widely variable clinical outcomes. In the absence of noninvasive risk stratification, individualized patient management remains challenging. Consequently a subgroup of pulmonary nodules of the lung adenocarcinoma spectrum is likely treated more aggressively than necessary. Methods: Consecutive patients with surgically resected pulmonary nodules of the lung adenocarcinoma spectrum (lesion size ≤3 cm, 2006-2009) and available presurgical high-resolution computed tomography (HRCT) imaging were identified at Mayo Clinic Rochester. All cases were classified using an unbiased Computer-Aided Nodule Assessment and Risk Yield (CANARY) approach based on the quantification of presurgical HRCT characteristics. CANARY-based classification was independently correlated to postsurgical progression-free survival. Results: CANARY analysis of 264 consecutive patients identified three distinct subgroups. Independent comparisons of 5-year disease-free survival (DFS) between these subgroups demonstrated statistically significant differences in 5-year DFS, 100%, 72.7%, and 51.4%, respectively (p = 0.0005). Conclusions: Noninvasive CANARY-based risk stratification identifies subgroups of patients with pulmonary nodules of the adenocarcinoma spectrum characterized by distinct clinical outcomes. This technique may ultimately improve the current expert opinion-based approach to the management of these lesions by facilitating individualized patient management.
AB - Introduction: Lung cancer remains the leading cause of cancer-related deaths in the United States and worldwide. Adenocarcinoma is the most common type of lung cancer and encompasses lesions with widely variable clinical outcomes. In the absence of noninvasive risk stratification, individualized patient management remains challenging. Consequently a subgroup of pulmonary nodules of the lung adenocarcinoma spectrum is likely treated more aggressively than necessary. Methods: Consecutive patients with surgically resected pulmonary nodules of the lung adenocarcinoma spectrum (lesion size ≤3 cm, 2006-2009) and available presurgical high-resolution computed tomography (HRCT) imaging were identified at Mayo Clinic Rochester. All cases were classified using an unbiased Computer-Aided Nodule Assessment and Risk Yield (CANARY) approach based on the quantification of presurgical HRCT characteristics. CANARY-based classification was independently correlated to postsurgical progression-free survival. Results: CANARY analysis of 264 consecutive patients identified three distinct subgroups. Independent comparisons of 5-year disease-free survival (DFS) between these subgroups demonstrated statistically significant differences in 5-year DFS, 100%, 72.7%, and 51.4%, respectively (p = 0.0005). Conclusions: Noninvasive CANARY-based risk stratification identifies subgroups of patients with pulmonary nodules of the adenocarcinoma spectrum characterized by distinct clinical outcomes. This technique may ultimately improve the current expert opinion-based approach to the management of these lesions by facilitating individualized patient management.
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U2 - 10.1097/JTO.0000000000000319
DO - 10.1097/JTO.0000000000000319
M3 - Article
C2 - 25170645
AN - SCOPUS:84925803639
SN - 1556-0864
VL - 9
SP - 1698
EP - 1703
JO - Journal of Thoracic Oncology
JF - Journal of Thoracic Oncology
IS - 11
ER -