We analyzed outcomes after lung stereotactic body radiotherapy (SBRT) for early-stage non–small-cell lung carcinoma in patients by histology and KRAS mutation status. Histology was not associated with outcomes, but KRAS mutation was associated with lower freedom from recurrence on univariable analysis and decreased cancer-specific survival on multivariable analysis. Given the small sample sizes, these results are hypothesis generating, and further study of SBRT outcomes by tumor genotype in larger data sets is needed.
Background
We analyzed outcomes after lung stereotactic body radiotherapy (SBRT) for early-stage non–small cell lung-carcinoma (NSCLC) by histology and KRAS genotype.
Patients and Methods
We included 75 patients with 79 peripheral tumors treated with SBRT (18 Gy × 3 or 10 to 12 Gy × 5) at our institution from 2009 to 2012. Genotyping for KRAS mutations was performed in 10 patients. Outcomes were analyzed by the Kaplan-Meier method/Cox regression, or cumulative incidence method/Fine-Gray analysis.
Results
The median patient age was 74 (range, 46 to 93) years, and Eastern Cooperative Oncology Group performance status was 0 to 1 in 63%. Tumor histology included adenocarcinoma (44%), squamous cell carcinoma (25%), and NSCLC (18%). Most tumors were T1a (54%). Seven patients had KRAS-mutant tumors (9%). With a median follow-up of 18.8 months among survivors, the 1-year estimate of overall survival was 88%, cancer-specific survival (CSS) 92%, primary tumor control 94%, and freedom from recurrence (FFR) 67%. In patients with KRAS-mutant tumors, there was a significantly lower tumor control (67% vs. 96%; P = .04), FFR (48% vs. 69%; P = .03), and CSS (75% vs. 93%; P = .05). On multivariable analysis, histology was not associated with outcomes, but KRAS mutation (hazard ratio, 10.3; 95% confidence interval, 2.3–45.6; P = .0022) was associated with decreased CSS after adjusting for age.
Conclusion
In this SBRT series, histology was not associated with outcomes, but KRAS mutation was associated with lower FFR on univariable analysis and decreased CSS on multivariable analysis. Because of the small sample size, these hypothesis-generating results need to be studied in larger data sets.