Recursive Partitioning Analysis for Local Control Achieved With Stereotactic Body Radiation Therapy for the Liver, Spine, or Lymph Nodes - Roman O. Kowalchuk, MD; Michael R. Waters, MD, PhD; Sunil W. Dutta, MD; Marie L. Mack, BS; K. Martin Richardson, MS; Kelly Spencer, MS; Kara D. Romano, MD; James M. Larner, MD; Jason P. Sheehan, MD, PhD; C. Ronald Kersh, MD (Advances in Radiation Oncology, 2021)
Purpose: This study aims to develop a local control risk stratification using recursive partitioning analysis (RPA) for patients receiving stereotactic body radiation therapy (SBRT) for metastatic cancer. Methods and Materials: A single institutional database of 397 SBRT treatments to the liver, spine, and lymph nodes was constructed. All treatments required imaging follow-up to assess for local control. Cox proportional hazards analysis was implemented before the decision tree analysis. The data were split into training (70%), validation (10%), and testing (20%) sets for RPA to optimize the training set. Results: In the study, 361 treatments were included in the local control analysis. Two-year local control was 71%. A decision tree analysis was used and the resulting model demonstrated 93.10% fidelity for the validation set and 87.67% for the test set. RPA class 3 was composed of patients with non-small cell lung cancer (NSCLC) primary tumors and treatment targets other than the cervical, thoracic, and lumbar spines. RPA class 2 included patients with primary cancers other than NSCLC or breast and treatments targets of the sacral spine or liver. RPA class 1 consisted of all other patients (including lymph node targets and patients with primary breast cancer). Classes 3, 2, and 1 demonstrated 3-year local controls rates of 29%, 50%, and 83%, respectively. On subgroup analysis using the Kaplan-Meier method, treatments for lymph nodes and primary ovarian disease demonstrated improved local control relative to other treatment targets (P < .005) and primary disease sites (P < .005), respectively. Conclusions: A local control risk stratification model for SBRT to sites of metastatic disease was developed. Treatment target and primary tumor were identified as critical factors determining local control. NSCLC primary lesions have increased local failure for targets other than the cervical, thoracic, or lumbar spines, and improved local control was identified for lymph node sites and breast or ovarian primary tumors.