Author:
Dai Xuan,Dai Zhujiang,Fu Jihong,Liang Zhonglin,Du Peng,Wu Tingyu
Abstract
Abstract
Background
Microsatellite instability-high (MSI-H) tumors, with elevated tumor mutational burden and expression of neoantigens, represent a distinct immune-activated subpopulation in colorectal cancer (CRC), characterized by strong lymph node reaction, locally advanced tumor and higher total lymph nodes harvested (TLN), but less metastatic lymph nodes and fewer incidence of III-IV stage. Host immune response to tumor and lymph nodes may be an important prognostic factor. However, N stage and LNR (Lymph-Node Ratio) have limitations in predicting the prognosis of MSI-H patients. Negative lymph node count (NLC) provided a more precise representation of immune activation status and extent of tumor metastasis. The study aims to detect prognostic significance of NLC in MSI-H CRC patients, and compare it with N stage, TLN and LNR.
Methods
Retrospective data of 190 consecutive MSI-H CRC patients who received curative resection were collected. Survival analyses were performed using the Kaplan–Meier method. Clinicopathological variables including NLC, N stage, TLN and LNR were studied in univariate and multivariate COX regression analyses. ROC (receiver operating characteristic curve) and concordance index were employed to compare the differences in predictive efficacy between NLC, N stage, TLN and LNR.
Results
Patients with increased NLC experienced a significantly improved 5-years DFS and OS in Kaplan–Meier analysis, univariate analysis, and multivariate analysis, independent of potential confounders examined. Increased NLC corresponded to elevated 5-years DFS rate and 5-years OS rate. AUC (area under curve) and concordance index of NLC in DFS and OS predicting were both significantly higher than N stage, TLN and LNR.
Conclusions
Negative lymph node is an important independent prognostic factor for MSI-H patients. Reduced NLC is associated with tumor recurrence and poor survival, which is a stronger prognostic factor than N stage, TLN and LNR.
Funder
National Natural Science Foundation of China
Natural Science Foundation of Shanghai Municipality
Publisher
Springer Science and Business Media LLC