河北医科大学学报 ›› 2024, Vol. 45 ›› Issue (2): 135-140.doi: 10.3969/j.issn.1007-3205.2024.02.003

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结肠癌患者550例3年期生存分析及预后影响因素回归模型构建

  

  1. 河北省石家庄市人民医院消化内科,河北 石家庄 050011

  • 出版日期:2024-02-25 发布日期:2024-02-06
  • 作者简介:赵树巧(1975-),女,河北石家庄人,河北省石家庄市人民医院副主任医师,医学学士,从事消化内科疾病诊断治疗研究。
  • 基金资助:
    河北省医学科学研究课题项目(20221693)

Analysis of 3-year survival of 550 patients with colon cancer and construction of regression model of prognostic factors

  1. Department of Gastroenterology, Shijiazhuang People′s Hospital, Hebei Province, Shjiazhuang 050011, China

  • Online:2024-02-25 Published:2024-02-06

摘要: 目的 探讨结肠癌患者550例3年期生存情况及预后影响因素,并构建回归模型。
方法 回顾性分析我院接受手术治疗后出院的结肠癌患者550例的临床资料,根据随访3年后是否存活将其分为预后不良组(死亡,134例)和预后良好组(生存,416例)。统计3年期生存情况,比较2组临床资料,并采用多因素Cox回归分析法分析影响结肠癌患者预后的危险因素,构建Cox回归模型。
结果 随访3年后,550例结肠癌患者有416例生存,3年生存率为75.64%。预后不良组年龄>60岁、分化程度低、腺鳞癌、未分化癌、Dukes分期C期、D期、右半结肠癌、有家族史、有并发症、有淋巴结转移、血清癌胚抗原水平异常、手术中间入路、淋巴结清扫个数<12个、术中出血量≥200 mL的患者占比分别为79.85%、48.25%、14.18%、10.45%、33.58%、65.67%、85.82%、22.39%、95.52%、59.96%、71.64%、67.16%、58.96%、89.55%,均高于预后良好组的52.40%、16.59%、1.20%、1.44%、2.64%、0.00%、41.83%、9.13%、84.62%、28.37%、31.25%、33.17%、41.11%、9.86%;已婚的患者占比为24.63%,低于预后良好组的75.48%(P<0.05)。多因素Cox回归分析结果显示,年龄>60岁、Dukes分期C、D期、右半结肠癌、有淋巴结转移、术中出血量≥200 mL是结肠癌患者预后不良的独立危险因素(P<0.05)。并构建预测模型结果显示,内部验证一致性指数为0.852(95%CI:0.819~0.885),校正曲线显示预测值与观察值具有良好的一致性。
结论 年龄>60岁、Dukes分期C、D期、右半结肠癌、有淋巴结转移、淋巴结清扫个数<12个、术中出血量≥200 mL是结肠癌患者预后不良的危险因素,其Cox回归模型有效且拟合效果较好,临床针对伴有以上情况的患者可给予相应的治疗及干预措施,以改善预后。


关键词: 结肠肿瘤, 预后, 模型构建

Abstract: Objective To investigate the 3-year survival and prognostic factors of 550 patients with colon cancer, and to construct a regression model. 
Methods The clinical data of 550 patients with colon cancer who was discharged from our hospital after surgical treatment were retrospectively analyzed.  They were divided into the poor prognosis group (death, n=134) and the good prognosis group (survival, n=416) according to whether they survived at 3 years after follow-up. The 3-year survival was recorded, and the clinical data of the two groups were compared. Multivariate Cox regression analysis was used to analyze the risk factors affecting the prognosis of colon cancer patients, and a Cox regression model was constructed. 
Results At 3 years after follow-up, 416 of the 550 patients with colon cancer survived, and the 3-year survival rate was 75.64%. The proportion of patients with age >60 years, low differentiation, adenosquamous cell carcinoma, undifferentiated carcinoma, Dukes stage C and D, right colon cancer, family history, presence of complications, lymph node metastasis, the abnormal level of serum carcinoembryonic antigen, intermediate surgical approach, number of lymph node dissections <12, and intraoperative bleeding ≥ 200 mL in the good prognosis group were 79.85%, 48.25%, 14.18%, 10.45%, 33.58%, 65.67%, 85.82%, 22.39%, 95.52%, 59.96%, 71.64%, 67.16%, 58.96%, and 89.55%, respectively, which were higher than those (52.40%, 16.59%, 1.20%, 1.44%, 2.64%, 0.00%, 41.83%, 9.13%, 84.62%, 28.37%, 31.25%, 33.17%, 41.11%, and 9.86%) in the poor prognosis group; the proportion of married patients was 24.63%, which was lower than that (75.48%) in the poor prognosis group (P<0.05). Multivariate Cox regression analysis showed that age >60 years, Dukes stage C and D, right colon cancer, lymph node metastasis and intraoperative bleeding ≥ 200 mL were independent risk factors for poor prognosis of patients with colon cancer (P<0.05). The results of the prediction model constructed showed that the internal validation consistency index (C-inex) was 0.852 (95%CI: 0.819-0.885), and the correction curve showed that the predicted value was in good agreement with the observed value. 
Conclusion Age >60 years, Dukes stage C and D, right colon cancer, lymph node metastasis, number of lymph node dissections <12, and intraoperative bleeding ≥ 200 mL are risk factors for poor prognosis in patients with colon cancer. The Cox regression model is effective and has a good fitting effect. The patients with the above conditions can be given corresponding treatment and intervention measures to improve the prognosis.


Key words: colonic neoplasms, prognosis, model construction