Utility of Noncancerous Chest CT Features for Predicting Overall Survival and Noncancer Death in Patients With Stage I Lung Cancer Treated With Stereotactic Body Radiotherapy.

Abstract

BACKGROUND. Noncancerous imaging markers can be readily derived from pre-treatment diagnostic and radiotherapy planning chest CT examinations. OBJECTIVE. The purpose of this article was to explore the ability of noncancerous features on chest CT to predict overall survival (OS) and noncancer-related death in patients with stage I lung cancer treated with stereotactic body radiation therapy (SBRT). METHODS. This retrospective study included 282 patients (168 female, 114 male; median age, 75 years) with stage I lung cancer treated with SBRT between January 2009 and June 2017. Pretreatment chest CT was used to quantify coronary artery calcium (CAC) score, pulmonary artery (PA)-to-aorta ratio, emphysema, and body composition in terms of the cross-sectional area and attenuation of skeletal muscle and subcutaneous adipose tissue at the T5, T8, and T10 vertebral levels. Associations of clinical and imaging features with OS were quantified using a multivariable Cox proportional hazards (PH) model. Penalized multivariable Cox PH models to predict OS were constructed using clinical features only and using both clinical and imaging features. The models' discriminatory ability was assessed by constructing time-varying ROC curves and computing AUC at prespecified times. RESULTS. After a median OS of 60.8 months (95% CI, 55.8-68.0), 148 (52.5%) patients had died, including 83 (56.1%) with noncancer deaths. Higher CAC score (11-399: hazard ratio [HR], 1.83 [95% CI, 1.15-2.91], p = .01; ≥ 400: HR, 1.63 [95% CI, 1.01-2.63], p = .04), higher PA-to-aorta ratio (HR, 1.33 [95% CI, 1.16-1.52], p < .001, per 0.1-unit increase), and lower thoracic skeletal muscle index (HR, 0.88 [95% CI, 0.79-0.98], p = .02, per 10-cm2/m2 increase) were independently associated with shorter OS. Discriminatory ability for 5-year OS was greater for the model including clinical and imaging features than for the model including clinical features only (AUC, 0.75 [95% CI, 0.68-0.83] vs 0.61 [95% CI, 0.53-0.70]; p < .01). The model's most important clinical or imaging feature according to mean standardized regression coefficients was the PA-to-aorta ratio. CONCLUSION. In patients undergoing SBRT for stage I lung cancer, higher CAC score, higher PA-to-aorta ratio, and lower thoracic skeletal muscle index independently predicted worse OS. CLINICAL IMPACT. Noncancerous imaging features on chest CT performed before SBRT improve survival prediction compared with clinical features alone.