Validation of the 7th TNM classification for non-small cell lung cancer: a retrospective analysis on prognostic implications for operated node-negative cases.

BACKGROUND

The 7th TNM staging system for non-small cell lung cancer (NSCLC) developed by the International Association for the study of Lung Cancer (IASLC) has been applied in Sweden since the beginning of the year 2010. The aim of this retrospective study was to evaluate the prognostic role of the 7th TNM staging system in a surgical Swedish patient cohort with node-negative NSCLC.

MATERIAL AND METHODS

We collected data from stage I patients (pT1-2 pN0, 6th TNM system) who underwent surgery for NSCLC at Karolinska University Hospital from 1987 to 2002. Tumors were restaged according to the 7th TNM version. Cox multivariate survival analysis was implemented in order to determine the prognostic impact of pathological stage when classified according to either the 6th or the 7th TNM systems.

RESULTS

The patient population consisted of 452 subjects. Tumor size was ≤ 3 cm in 51% of cases. The predominant histology was adenocarcinoma (53%) and lobectomy was the most common surgical procedure (82% of patients). The five-year survival rate in patients with stage IA vs. IB (6th TNM) was 62% vs. 51%, respectively (log-rank p = 0.036). Corresponding figures for the 7th TNM system were 70% in stage IA-T1a, 51% in stage IA-T1b, 54% in stage IB, 51% in stage IIA and 35% in stage IIB (log-rank p = 0.002). On multivariate analysis, adjusted by age, gender, histology, kind of surgery, grade of differentiation and smoking status, pathological stage was an independent prognostic factor if classified according to the 7th TNM version (p = 0.001), but not if scored according to the 6th TNM edition (p = 0.090).

CONCLUSION

The 7th TNM classification system is a more accurate predictor of prognosis in stage I operated patients than the old classification. The new system should be implemented even on retrospective cohorts especially when investigating the prognostic implication of the expression of molecular biomarkers.