摘要
目的:探讨肌层浸润性膀胱癌根治术预后相关因素。方法:回顾性分析156例腹腔镜下根治性膀胱全切除术及盆腔淋巴结清扫术后肌层浸润性膀胱癌患者生存数据,选择17种可能对预后产生影响的因素,采用Kaplan-Meier法及Cox比例风险模型统计分析。结果:单因素分析示年龄、肿瘤T分期、有无淋巴结转移、肾积水、是否侵犯输尿管下段、是否侵犯淋巴脉管、是否行新辅助化疗、术后辅助放化疗对患者预后的影响差异有统计学意义(P<0.05)。多因素分析示年龄(P<0.001)、肿瘤T分期(P=0.003)、淋巴结转移(P=0.031)、新辅助化疗(P=0.015)为肌层浸润性膀胱癌根治术预后影响因素。结论:年龄、肿瘤T分期、淋巴结转移为影响肌层浸润性膀胱癌根治术患者生存的独立危险因素。新辅助化疗是肌层浸润性膀胱癌根治术预后保护因素。
Objective:To explore the prognosis factors of radical cystectomy in patients with muscle-invasive bladder cancer.Methods:We retrospectively collected 156 patients clinical,pathological and survival data with muscle-invasive bladder cancer undergoing laparoscopic radical cystectomy and pelvic lymphadenectomy.17 non-repetitive clinical factors that may affect prognosis were selected for survival analysis,including gender,age,nationality,smoking,tumor staging,pathological grade,etc.Kaplan-Meier method and Cox proportional hazard model were used to statistically analyse the prognostic factors.Results:Univariate analysis showed that age,T stage,lymph node metastasis,hydronephrosis,infringement of lower ureter,invasion of lymphatic vessels,neoadjuvant chemotherapy,postoperative chemoradiotherapy were prognosis factors(P<0.05).Multivariate analysis by the Cox proportional hazard model showed age(P<0.001),T stage(P=0.003),lymph node metastasis(P=0.031),neoadjuvant chemotherapy(P=0.015)were the prognostic factors(P<0.05)of radical cystectomy in patients with muscle-invasive bladder cancer.Conclusion:Age,T stage,lymph node metastasis were the independent risk factors affecting survival of patients with muscle-invasive bladder cancer.Neoadjuvant chemotherapy was the protective factor for prognosis.
作者
斯热努尔·艾合买提
张瑞丽
魏媛
包永星
Sirenuer·Aihemaiti;Zhang Ruili;Wei Yuan;Bao Yongxing(Department of Tumor Center,First Affiliated Hospital of Xinjiang Medical University,Xinjiang Urumqi 830054,China)
出处
《现代肿瘤医学》
CAS
2020年第17期2995-2999,共5页
Journal of Modern Oncology
基金
国家自然科学基金地区科学基金项目(编号:81760452)
新疆维吾尔自治区自然科学基金青年项目(编号:2019D01B49)。
关键词
肌层浸润性膀胱癌
预后因素
COX比例风险模型
muscle-invasive bladder cancer
prognostic factor
Cox proportional hazard model