T1期结直肠癌淋巴结转移的危险因素分析及其列线图预测模型的应用价值  

Risk factors for lymph node metastasis in T1 colorectal cancer and application value of its nomogram prediction model

作　　者：庄奥博 朱德祥[1] 许平平[1] 易拓[1] 林奇[1] 韦烨[1] 许剑民[1] Zhuang Aobo;Zhu Dexiang;Xu Pingping;Yi Tuo;Lin Qi;Wei Ye;Xu Jianmin(Department of General Surgery,Zhongshan Hospital,Fudan University,Shanghai 200032,China)

机构地区：[1]复旦大学附属中山医院普通外科,上海200032

出　　处：《中华消化外科杂志》2021年第3期323-330,共8页Chinese Journal of Digestive Surgery

基　　金：国家自然科学青年基金项目(81602036);上海市科学技术委员会项目(17411951300)。

摘　　要：目的探讨T1期结直肠癌淋巴结转移的危险因素及其列线图预测模型的应用价值。方法采用回顾性病例对照研究方法。收集2008年6月至2019年12月复旦大学附属中山医院收治的914例行根治性切除术T1期结直肠癌病人的临床病理资料;男528例,女386例;中位年龄为63岁,年龄范围为25~87岁。观察指标:(1)T1期结直肠癌病人的临床病理资料。(2)随访情况。(3)淋巴结转移的影响因素分析。(4)列线图预测模型的建立及内部验证。病人术后定期随访,术后2年内每3个月随访1次,随后每6个月随访1次,术后随访5年,了解病人的肿瘤复发和生存情况。正态分布的计量资料以x±s表示,组间比较采用t检验;偏态分布的计量资料以M(范围)表示。计数资料以绝对数或百分比表示,组间比较采用χ2检验。采用Kaplan-Meier法计算生存率和绘制生存曲线。采用Log-rank检验进行生存分析。单因素和多因素分析均采用Logistic回归分析。根据多因素分析结果,应用R语言软件建立基于Logistic回归的淋巴结转移概率预测列线图。采用校准度曲线评价模型预测结局发生概率与实际观测概率一致程度,以一致性指数(C-index)表示。采用Bootstrap方法评价模型性能,得出校准度曲线。采用Hosmer-Lemeshow检验计算模型的拟合优度。结果 (1)T1期结直肠癌病人的临床病理资料:914例病人中,直接手术687例,内镜切除后补救手术227例;术后组织病理学检查证实均为pT1NxM0期结直肠癌;肿瘤长径为(2.3±1.2)cm;肿瘤病理学类型腺癌为865例,黏液性腺癌为49例;肿瘤分化程度为高中分化727例,低未分化187例;黏膜下浸润深度≥1 000 μm 633例,<1 000 μm 281例;神经脉管侵犯110例,未受侵犯804例;术中淋巴结清扫数目为13枚(1~48枚);N分期为N0期804例,N1期98例,N2期12例。无围术期死亡病人。(2)随访情况:914例病人中,886例获得术后随访,随访时间为25个月(1~129个月);随�Objective To investigate the risk factors for lymph node metastasis in T1 colorectal cancer and application value of its nomogram prediction model.Methods The retrospective case‐control study was conducted.The clinicopathological data of 914 patients with T1 colorectal cancer who underwent radical resection in the Zhongshan Hospital of Fudan University June 2008 to December 2019 were collected.There were 528 males and 386 females,aged from 25 to 87 years,with a median age of 63 years.Observation indicators:(1)clinicopathological data of patients with T1 colorectal cancer;(2)follow‐up;(3)analysis of influencing factors for lymph nodmetastasis;(4)development and internal validation of a nomogram predition model.Patients were regularlly followed up once three months within postoperative 2 years and once six months thereafter to detect tumor recurrence and survival.The endpoint of follow‐up was at postoperative 5 years.Measurement data with normal distribution were represented as Mean±SD,and comparison between groups was analyzed using the t test.Measurement data with skewed distribution were represented as M(range).Count data were described as absolute numbers or percentages,and comparison between groups was analyzed using the chi‐square test.The Kaplan‐Meier method was used to calculate survival rates and draw survival curves.The Log‐rank test was used for survival analysis.Univariate and multivariate analyses were performed using the Logistic regression analysis.Based on results of multivariate analysis,a Logistic regressional nomogram for prediction of lymph node metastasis probability was constructed using R language software.The calibration curve was used to evaluate the consistency between probability predicd by the nomogram model and actual observation probability,which was reprensented by a consistency index.The Bootstrap method was used for evaluation of the model performance to receive the calibration curve.The Hosmer‐Lemeshow test was used to calculate the goodness of fit in model.Results(1

关 键 词：结肠肿瘤 直肠肿瘤 T1期 淋巴结转移 预测模型 列线图 

分 类 号：R735.34[医药卫生—肿瘤]