FDG PET/CT Overcomes Discordance Between Clinical and Pathologic TNM Classification of Small-size Primary Lung Cancer: Influence on Postoperative Prognosis

Introduction: We aimed to determine the concordance between the clinical stage (c-stage) and pathologic stage (p-stage) for patients with small-size lung cancer. Additionally we searched for prognostic factors other than the TNM stage.

Patients and methods: We retrospectively reviewed the preoperative multidetector computed tomography (CT) and positron emission tomography/CT reports, surgical records, and pathologic reports of patients with primary lung cancer ≤ 3 cm. The Union for International Cancer Control TNM seventh edition classification of c-stage and p-stage were compared. The tumors were classified into multiple subgroups by concordance or discordance between the c-stage and p-stage. Disease-free survival (DFS) was assessed using survival analysis to assess the tumor characteristics that were predictive of prognosis.

Results: A total of 289 surgically resected primary lung cancers were evaluated. The concordance between c-stage and p-stage was 65.4%, with moderate reproducibility (kappa coefficient, 0.467). The upstaging rate from c-stage I to p-stage II-IV was 9.4%, and these patients had significantly worse DFS than those with a concordant stage I classification (P < .001). The main reason for upstaging was an underestimation of metastases to the hilar lymph nodes (n = 7) or mediastinal lymph nodes (n = 11). A multivariate Cox proportional hazards model showed that the significant predictive factors for DFS were p-stage (hazard ratio, 1.342; P = .003) and maximum standardized uptake value on positron emission tomography/CT (hazard ratio, 12.162; P = .001).

Conclusion: The concordance rate between c-stage and p-stage for small primary lung cancers had moderate reproducibility. Discordance between c-stage I and p-stage II-IV significantly affected DFS. The maximum standardized uptake value of the primary lesion was an independent prognostic factor, and combining it with c-stage might improve the prediction of therapeutic outcomes.