Video-Assisted Thoracoscopic Lobectomy for Lung Cancer: Current Practice Patterns and Predictors of Adoption

Abstract

Video-assisted thoracoscopic surgery (VATS) lobectomy has been shown to be a safe, minimally invasive approach for the surgical management of lung cancer. Despite evidence supporting oncologic efficacy, recent reports indicate that less than half of lobectomies are performed by VATS. We examined nationwide lobectomy practice patterns to identify specific predictors for VATS adoption. Premier hospital data (2010 to 2014) were used to identify open and VATS lobectomy procedures performed for the treatment of primary lung cancer. Propensity score method was used to match VATS and open operations (1:1) on clinical characteristics. Variables associated with VATS lobectomy were assessed by logistic regression to evaluate independent predictors. Secondary outcomes included postoperative complications, readmission, and mortality. Patients with primary lung cancer (n= 17,304) that underwent VATS (n= 6,670, 38.5%) or open (n= 10,634, 61.5%) lobectomy were identified; 6,670 patients in each group were matched for analysis. VATS performance increased significantly from 2010 to 2014, (39.6% versus 43.8%, p= 0.0004), particularly for thoracic surgeons (50.3% versus 54.7%, p < 0.0001), those performing 15 or more lobectomies per year (53.6% versus 59.8%, p<0.0001), and for surgeons practicing in the Northeast (54.8% versus 59.9%, p= 0.0001). Independent predictors of VATS utilization included surgeon volume and specialty training, hospital type and size, and region. Multivariate analysis demonstrated a significant association between VATS and surgeon volume, independent of specialty. National rates of VATS lobectomy continue to increase, particularly for thoracic surgeons, high-volume surgeons, and surgeons in the Northeast. Surgeon volume and specialty are strong independent predictors of VATS lobectomy. Efforts that support centralization of care may improve VATS lobectomy rates and decrease the regional variability identified in this analysis.