Evaluation of combined pathological responses in primary tumor and lymph nodes following neoadjuvant chemoimmunotherapy in non-small cell lung cancer

Abstract

BackgroundInconsistent pathological responses of tumor and lymph nodes (LNs) were frequently observed in non-small cell lung cancer (NSCLC) receiving neoadjuvant chemoimmunotherapy. However, there is a lack of studies to report the prognostic significance and the relevant clinicopathological factors of tumor-nodal inconsistent responses after neoadjuvant immunotherapy or chemoimmunotherapy. Therefore, this study aimed to depict the inconsistent pathological combined tumor-nodal responses in NSCLC patients after neoadjuvant chemoimmunotherapy as well as the underlying clinical significance. MethodsA total of 81 node-positive NSCLC patients who underwent neoadjuvant chemoimmunotherapy were eligible for inclusion. Demographic, radiologic, and pathological features of patients were recorded. Patients with pathological complete response of both tumor (ypT(pCR)) and LNs (ypN0) were classified into the combined good responder group and the relevant clinicopathological features were evaluated. The event-free survival (EFS) outcome was analyzed using Kaplan-Meier analysis. ResultsThe ypN0 and ypT(pCR) rates were 74.1 % and 42.0 %, respectively. A significant correlation was observed between ypT(pCR) and ypN0 (P = 0.003), but inconsistent responses remained. The combined responses of the primary tumor and LNs demonstrated a significant association with the prognosis outcome (P = 0.005). Notably,patients who received at least twice of their infusions of immune checkpoint inhibitors after 15:30 had a worse prognosis (P = 0.015). ConclusionA significant but not absolute correlation was observed between good tumor response and good nodal response in NSCLC patients after neoadjuvant chemoimmunotherapy, but inconsistent responses were also found. The combination of tumor and nodal responses is significantly associated with prognosis and combined good responder can be used as a reliable prognosis predictor.