TY - JOUR
T1 - Noninvasive computed tomography-based risk stratification of lung adenocarcinomas in the national lung screening trial
AU - Maldonado, Fabien
AU - Duan, Fenghai
AU - Raghunath, Sushravya M.
AU - Rajagopalan, Srinivasan
AU - Karwoski, Ronald A.
AU - Garg, Kavita
AU - Greco, Erin
AU - Nath, Hrudaya
AU - Robb, Richard A.
AU - Bartholmai, Brian J.
AU - Peikert, Tobias
N1 - Publisher Copyright:
Copyright © 2015 by the American Thoracic Society.
PY - 2015/9/15
Y1 - 2015/9/15
N2 - Rationale: Screening for lung cancer using low-dose computed tomography (CT) reduces lung cancer mortality. However, in addition to a high rate of benign nodules, lung cancer screening detects a large number of indolent cancers that generally belong to the adenocarcinoma spectrum. Individualized management of screen-detected adenocarcinomas would be facilitated by noninvasive risk stratification. Objectives: To validate that Computer-Aided Nodule Assessment and Risk Yield (CANARY), a novel image analysis software, successfully risk stratifies screen-detected lung adenocarcinomas based on clinical disease outcomes. Methods: We identified retrospective 294 eligible patients diagnosed with lung adenocarcinoma spectrum lesions in the low-dose CT arm of the National Lung Screening Trial. The last low-dose CT scan before the diagnosis of lung adenocarcinoma was analyzed using CANARY blinded to clinical data. Based on their parametric CANARY signatures, all the lung adenocarcinoma nodules were risk stratified into three groups. CANARY risk groups were compared using survival analysis for progression-free survival. Measurements and Main Results: A total of 294 patients were included in the analysis. Kaplan-Meier analysis of all the 294 adenocarcinoma nodules stratified into the Good, Intermediate, and Poor CANARY risk groups yielded distinct progression-free survival curves (P,0.0001). This observation was confirmed in the unadjusted and adjusted (age, sex, race, and smoking status) progression-free survival analysis of all stage I cases. Conclusions: CANARY allows the noninvasive risk stratification of lung adenocarcinomas into three groups with distinct post-treatment progression-free survival. Our results suggest that CANARY could ultimately facilitate individualized management of incidentally or screen-detected lung adenocarcinomas.
AB - Rationale: Screening for lung cancer using low-dose computed tomography (CT) reduces lung cancer mortality. However, in addition to a high rate of benign nodules, lung cancer screening detects a large number of indolent cancers that generally belong to the adenocarcinoma spectrum. Individualized management of screen-detected adenocarcinomas would be facilitated by noninvasive risk stratification. Objectives: To validate that Computer-Aided Nodule Assessment and Risk Yield (CANARY), a novel image analysis software, successfully risk stratifies screen-detected lung adenocarcinomas based on clinical disease outcomes. Methods: We identified retrospective 294 eligible patients diagnosed with lung adenocarcinoma spectrum lesions in the low-dose CT arm of the National Lung Screening Trial. The last low-dose CT scan before the diagnosis of lung adenocarcinoma was analyzed using CANARY blinded to clinical data. Based on their parametric CANARY signatures, all the lung adenocarcinoma nodules were risk stratified into three groups. CANARY risk groups were compared using survival analysis for progression-free survival. Measurements and Main Results: A total of 294 patients were included in the analysis. Kaplan-Meier analysis of all the 294 adenocarcinoma nodules stratified into the Good, Intermediate, and Poor CANARY risk groups yielded distinct progression-free survival curves (P,0.0001). This observation was confirmed in the unadjusted and adjusted (age, sex, race, and smoking status) progression-free survival analysis of all stage I cases. Conclusions: CANARY allows the noninvasive risk stratification of lung adenocarcinomas into three groups with distinct post-treatment progression-free survival. Our results suggest that CANARY could ultimately facilitate individualized management of incidentally or screen-detected lung adenocarcinomas.
KW - Image analysis
KW - Individualized medicine
KW - Lung adenocarcinoma
KW - Risk stratification
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U2 - 10.1164/rccm.201503-0443OC
DO - 10.1164/rccm.201503-0443OC
M3 - Article
C2 - 26052977
AN - SCOPUS:84942274744
SN - 1073-449X
VL - 192
SP - 737
EP - 744
JO - American journal of respiratory and critical care medicine
JF - American journal of respiratory and critical care medicine
IS - 6
ER -