Abstract
BACKGROUND: The current nodal (pN) classification still has limitations in stratifying the prognosis of small cell lung cancer (SCLC) patients with pathological classifications T1-2N0-2M0. Thus. This study aimed to develop and validate a modified nodal classification based on a multicenter cohort. MATERIALS AND METHODS: We collected 1156 SCLC patients with pathological classifications T1-2N0-2M0 from the Surveillance, Epidemiology, and End Results database and a multicenter database in China. The X-tile software was conducted to determine the optimal cutoff points of the number of examined lymph nodes (ELNs) and lymph node ratio (LNR). The Kaplan-Meier method, the Log-rank test, and the Cox regression method were used in this study. We classified patients into three pathological N modification categories, new pN#1 (pN0-#ELNs > 3), new pN#2 (pN0-#ELNs ≤ 3 or pN1-2-#LNR ≤ 0.14), and new pN#3 (N1-2-#LNR > 0.14). The Akaike information criterion (AIC), Bayesian Information Criterion, and Concordance index (C-index) were used to compare the prognostic, predictive ability between the current pN classification and the new pN component. RESULTS: The new pN classification had a satisfactory effect on survival curves (Log-rank P < 0.001). After adjusting for other confounders, the new pN classification could be an independent prognostic indicator. Besides, the new pN component had a much more accurate predictive ability in the prognostic assessment for SCLC patients of pathological classifications T1-2N0-2M0 compared with the current pN classification in the SEER database (AIC: 4705.544 vs. 4731.775; C-index: 0.654 vs. 0.617, P < 0.001). Those results were validated in the MCDB from China. CONCLUSIONS: The multicenter cohort developed and validated a modified nodal classification for SCLC patients with pathological category T1-2N0-2M0 after surgery. Besides, we propose that an adequate lymph node dissection is essential; surgeons should perform and consider the situation of ELNs and LNR when they evaluate postoperative prognoses of SCLC patients.