Radiological lymph‐node size improves the prognostic value of systemic inflammation index in rectal cancer with pathologically negative nodes

医学 结直肠癌 淋巴结 全身炎症 内科学 放射性武器 癌症 淋巴 索引(排版) 炎症 肿瘤科 病理 放射科 计算机科学 万维网
作者
Shaoyong Peng,Xiaoxia Liu,Yingjie Li,Huichuan Yu,Yumo Xie,Xiaolin Wang,Jiaming Zhou,Mingxuan Zhu,Yanxin Luo,Meijin Huang
出处
期刊:Cancer Medicine [Wiley]
卷期号:12 (9): 10303-10314 被引量:2
标识
DOI:10.1002/cam4.5761
摘要

Abstract Background The relationship between the radiological lymph node (rLN) size and survival outcome in node‐negative rectal cancer is still uncertain. In this study, we aimed to explore the role of enlarged rLN in predicting the survival of node‐negative rectal cancers. Methods We retrospectively reviewed the records of 722 node‐negative rectal cancer who underwent curative resection. Factors associated with DFS (disease‐free survival) and CSS (cancer‐specific survival) were assessed with univariate and multivariate analysis. Survival analysis was performed according to presence with or without enlarged rLN. Combining rLN with NLR as a new index‐inflammation immune score (IIS) for predicting survival. Comparing different models to assess the predictive powers. Results A total of 119 patients had tumor recurrence and 73 patients died due to cancer. Patients with enlarged rLN (≥5 mm) was significantly associated with better DFS (HR:0.517, 95%CI:0.339–0.787, p = 0.002) and CSS (HR:0.43, 95%CI:0.242–0.763, p = 0.004). The risk factors of recurrence were rLN, neutrophil‐lymphocyte ratio (NLR), CEA level, and distance from the anal verge. The risk of recurrence increased by 1.88‐ and 2.83‐fold for the high score in IIS compared with the low and intermediate score group (All p < 0.001). Similarly, the high score in IIS also increased the risk of cancer‐specific death. In the model comparison, the AIC and LR were improved by including the rLN into the NLR model for DFS and CSS prediction (All p < 0.05). Conclusions Node‐negative rectal cancer patients with enlarged rLN had a better survival outcome. IIS might be a more comprehensive and complete inflammation immune index for survival prediction.
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