Predictors of Survival and Disease-Free Survival in Patients With Resected N1 Non-Small Cell Lung Cancer

Academic Article

Abstract

  • Background: Factors that predict poor survival or increased risk of recurrence for patients with N1 disease may be dependent on tumor characteristics. Methods: This study was a retrospective review of a prospective database of consecutive patients who had clinical or pathologic N1 non-small cell lung cancer (NSCLC) who underwent preoperative 2-[(18)F] fluoro-2-deoxy-D-glucose (FDG)-positron emission tomography (PET) scans and complete resection with thoracic lymphadenectomy. Results: There were 135 patients (88 men). The 5-year disease-free rate was 55%. Kaplan-Meier analysis showed that poor differentiation (p = 0.036), multiple N1 stations (p = 0.010), and the lack of adjuvant chemotherapy (p = 0.039) were all associated with a shorter 5-year disease-free rate. Multivariate disease-free analysis demonstrated that only multiple stations (p = 0.002) were independently associated with recurrence. The overall 5-year survival was 48%. Univariate analysis showed that multiple nodes within one station (p = 0.016), multiple station involvement (p = 0.041), and lack of adjuvant chemotherapy (p = 0.039) and moderate-to-poor tumor differentiation (p = 0.046) were associated with decreased survival. Multivariate analysis found that multiple stations, multiple nodes, and lack of adjuvant chemotherapy were independent predictors of poor survival. Integrated PET-computed tomography (CT) was significantly more sensitive for staging N1 disease than dedicated FDG-PET (p = 0.032). Neoadjuvant chemotherapy given to 48 nonrandomized patients did not seem to impact disease recurrence or overall 5-year survival rates (p = 0.349). Conclusions: Factors that predict a poor outcome in patients with resected N1 NSCLC are the involvement of multiple N1 stations, multiple N1 nodes, and the lack of adjuvant chemotherapy. Integrated PET-CT is more sensitive for detecting N1 disease then dedicated PET. These data may influence preoperative or postoperative therapy, or both. © 2007 The Society of Thoracic Surgeons.
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    Author List

  • Cerfolio RJ; Bryant AS
  • Start Page

  • 182
  • End Page

  • 190
  • Volume

  • 84
  • Issue

  • 1