Procedure-Specific Risk Prediction for Recurrence in Patients Undergoing Lobectomy or Sublobar Resection for Small (≤2 cm) Lung Adenocarcinoma: An International Cohort Analysis.
Academic Article
Overview
abstract
INTRODUCTION: This work was performed to develop and validate procedure-specific risk prediction for recurrence following resection for early-stage lung adenocarcinoma (ADC) and investigate risk prediction utility in identifying patients who may benefit from adjuvant chemotherapy (ACT). METHODS: In patients who underwent resection for small (≤2 cm) lung ADC (lobectomy, 557; sublobar resection, 352), an association between clinicopathologic variables and risk of recurrence was assessed by a competing risks approach. Procedure-specific risk prediction was developed based on multivariable regression for recurrence. External validation was conducted using cohorts (N = 708) from Japan, Taiwan, and Germany. The accuracy of risk prediction was measured using a concordance index. We applied the lobectomy risk prediction approach to a propensity score-matched cohort of patients with stage II-III disease (n = 316, after matching) with or without ACT and compared lung cancer-specific survival between groups among low- or high-risk scores. RESULTS: Micropapillary pattern, solid pattern, lymphovascular invasion, and necrosis were involved in the risk prediction following lobectomy, and micropapillary pattern, spread through air spaces, lymphovascular invasion, and necrosis following sublobar resection. Both internal and external validation showed good discrimination (concordance index in lobectomy and sublobar resection: internal, 0.77 and 0.75, respectively; and external, 0.73 and 0.79, respectively). In the stage II-III propensity score-matched cohort, among high-risk patients, ACT significantly reduced the risk of lung cancer-specific death (subhazard ratio 0.43, p = 0.001), but not among low-risk patients. CONCLUSIONS: Procedure-specific risk prediction for patients with resected small lung ADC can be used to better prognosticate and stratify patients for further interventions.
