A genomic strategy to refine prognosis in early-stage non-small-cell lung cancer.

Journal Article (Journal Article)

BACKGROUND: Clinical trials have indicated a benefit of adjuvant chemotherapy for patients with stage IB, II, or IIIA--but not stage IA--non-small-cell lung cancer (NSCLC). This classification scheme is probably an imprecise predictor of the prognosis of an individual patient. Indeed, approximately 25 percent of patients with stage IA disease have a recurrence after surgery, suggesting the need to identify patients in this subgroup for more effective therapy. METHODS: We identified gene-expression profiles that predicted the risk of recurrence in a cohort of 89 patients with early-stage NSCLC (the lung metagene model). We evaluated the predictor in two independent groups of 25 patients from the American College of Surgeons Oncology Group (ACOSOG) Z0030 study and 84 patients from the Cancer and Leukemia Group B (CALGB) 9761 study. RESULTS: The lung metagene model predicted recurrence for individual patients significantly better than did clinical prognostic factors and was consistent across all early stages of NSCLC. Applied to the cohorts from the ACOSOG Z0030 trial and the CALGB 9761 trial, the lung metagene model had an overall predictive accuracy of 72 percent and 79 percent, respectively. The predictor also identified a subgroup of patients with stage IA disease who were at high risk for recurrence and who might be best treated by adjuvant chemotherapy. CONCLUSIONS: The lung metagene model provides a potential mechanism to refine the estimation of a patient's risk of disease recurrence and, in principle, to alter decisions regarding the use of adjuvant chemotherapy in early-stage NSCLC.

Full Text

Duke Authors

Cited Authors

  • Potti, A; Mukherjee, S; Petersen, R; Dressman, HK; Bild, A; Koontz, J; Kratzke, R; Watson, MA; Kelley, M; Ginsburg, GS; West, M; Harpole, DH; Nevins, JR

Published Date

  • August 10, 2006

Published In

Volume / Issue

  • 355 / 6

Start / End Page

  • 570 - 580

PubMed ID

  • 16899777

Electronic International Standard Serial Number (EISSN)

  • 1533-4406

Digital Object Identifier (DOI)

  • 10.1056/NEJMoa060467


  • eng

Conference Location

  • United States