医学
比例危险模型
内科学
癌症
肿瘤科
生存分析
淋巴结切除术
队列
流行病学
回顾性队列研究
阶段(地层学)
数据库
古生物学
生物
计算机科学
作者
Jian Xiao,Kuan Shen,Hao Fan,Gang Wang,Kanghui Liu,Yuanhang Wang,Xiang Ma,Peidong Ni,Zekuan Xu,Li Yang
标识
DOI:10.1177/10668969231152578
摘要
Background. Although tumor size is regarded as the “T” stage of the tumor-node-metastasis (TNM) staging system for many solid tumors, its prognostic impact in gastric cancer remains uncertain and conflicting. Methods. We enrolled 6960 eligible patients from the Surveillance, Epidemiology, and End Results (SEER) database. The X-tile program was used to select the best cut-off value of tumor size. Then, the Kaplan–Meier method and the Cox proportional hazards model were applied to examine the efficacy of tumor size on prognostic prediction for overall survival (OS) and gastric cancer-specific survival (GCSS). The presence of nonlinear association was determined by the restricted cubic spline (RCS) model. Results. Tumor size was divided into 3 groups: small size (≤2.5 cm), medium size (2.6-5.2 cm), and large size (≥5.3 cm). After adjusting by covariates such as depth of tumor infiltration, the large and medium groups showed a worse prognosis than the small group; however, no survival difference in OS was suggested between the medium and large groups. Similarly, although there was a nonlinear relationship between tumor size and survival, increasing tumor size did not show an independent negative effect on prognosis in the RCS analysis. However, the stratified analyses proposed this 3-way cut of tumor size in prognostic prediction for patients with both inadequate lymphadenectomy and negative nodal metastasis. Conclusions. Tumor size as a prognostic predictor may not have good clinical applicability in gastric cancer. Otherwise, it was recommended for patients with both insufficient examinations of lymph nodes and stage N0 disease.
科研通智能强力驱动
Strongly Powered by AbleSci AI