Number of involved nodal stations predicts survival in small cell lung cancer.

BACKGROUND

In small cell lung cancer (SCLC), the pathological N category is identical to it in non-small cell lung cancer (NSCLC) and remains unchanged over a decade. Here we verified the discriminability of number of involved nodal stations (nS) in SCLC and compared its efficacy in predicting survival with currently used pathological nodal (pN) staging.

METHODS

We retrospectively analyzed the patients who received operations and were pathologically diagnosed as SCLC at Shanghai Pulmonary Hospital between 2009 and 2019. X-tile software was adopted to determine optimal cut-off values for nS groups. Kaplan-Meier method and Cox regression analysis were used to compare survival between different groups. Decision curve analysis (DCA) was employed to evaluate the standardized net benefit.

RESULTS

A total of 369 patients were included. The median number of sampled stations was 6 (range 3-11), and the median number of positive stations was 1 (range 0-7). The optimal cutoff for nS groups was: nS0 (no station involved), nS1-2 (one or two stations involved), and nS ≥ 3 (three or more stations involved). Overall survival (OS) and relapse-free survival (RFS) were statistically different among all adjacent categories within the nS classification (p < 0.001, for both OS and RFS between each two subgroups), but survival curves for subgroups in pN overlapped (OS, p = 0.067; RFS, p = 0.068, pN2 vs. pN1). After adjusting for other confounders, nS was a prognostic indicator for OS and RFS. The DCA revealed that nS had improved predictive capability than pN.

CONCLUSIONS

Our cohort study demonstrated that the nS might serve as a superior indicator to predict survival than pN in SCLC and was worth considering in the future definition of the N category.