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B. Bartholmai
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ORAL 24 - CT Detected Nodules - Predicting Biological Outcome (ID 122)
- Event: WCLC 2015
- Type: Oral Session
- Track: Screening and Early Detection
- Presentations: 1
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ORAL24.06 - Stratification of Lung Adenocarcinomas in the National Lung Screening Trial (ID 102)
11:39 - 11:50 | Author(s): B. Bartholmai
- Abstract
- Presentation
Background:
Screening for lung cancer with low-dose computed tomography (LDCT) was shown to reduce lung cancer mortality. However, lung cancer screening also detects indolent cancers of unclear clinical significance, which generally belong to the adenocarcinoma spectrum. The individualized management of these more indolent cancers may be facilitated by non-invasive risk stratification. We present our validation study of CANARY (Computer-Aided Nodule Assessment and Risk Yield), a novel LDCT-based software, used to stratify adenocarcinoma nodules in three groups with distinct outcomes.
Methods:
All individuals in the LDCT arm of the National Lung Screening Trial (NLST) with adenocarcinoma were identified. The last LDCT data available were analyzed blinded to clinical data. Using CANARY, all lung adenocarcinoma nodules were classified as Good (G), Intermediate (I) and Poor (P) based on previously established radiologic signatures. This classification was then used for survival analysis using progression-free survival
Results:
LDCT datasets of 294 patients with resected adenocarcinomas with available outcome data were included in the blinded CANARY analysis. Kaplan-Meier analysis of all the 294 adenocarcinoma nodules stratified into G, I and P CANARY classes yielded distinct progression-free survival curves (P < 0.0001). A similar separation was seen with adjusted progression-free survival curves, after adjustment for, age, gender, race and smoking status for all pathological stage I cases.
Conclusion:
CANARY allows the non-invasive risk stratification of lung adenocarcinomas into three groups with distinct post-surgical disease-free survival. Our results suggest that CANARY could facilitate individualized management of incidentally- or screen-detected lung adenocarcinomas.
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