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预测早发性局部晚期结肠癌的生存和预后:一项回顾性观察研究。

Predicting survival and prognosis in early-onset locally advanced colon cancer: a retrospective observational study.

机构信息

Northern Jiangsu People's Hospital Affiliated to Yangzhou University, Yangzhou, 225001, China.

General Surgery Institute of Yangzhou, Yangzhou University, Yangzhou, 225001, China.

出版信息

Int J Colorectal Dis. 2023 Oct 7;38(1):250. doi: 10.1007/s00384-023-04543-1.

Abstract

OBJECTIVE

To predict cancer-specific survival, a refined nomogram model and brand-new risk-stratifying system were established to classify the risk levels of patients with early-onset locally advanced colon cancer (LACC).

METHODS

The clinical factors and survival outcomes of LACC cases from the SEER database from 2010 to 2019 were retrieved retrospectively. Early-onset and late-onset colon cancer were grouped according to the age (50 years old) at diagnosis. Differences between groups were compared to identify mutual significant variables. A multivariate Cox regression analysis was further performed and then constructed a nomogram. We compared it with the AJCC-TNM system. The external validation was performed for evaluation. Finally, a risk-stratifying system of patients with early-onset LACC was established.

RESULTS

A total of 32,855 LACC patients were enrolled in, 4548 (13.84%) patients were included in the early-onset LACC group, and 28,307 (86.16%) patients were included in the late-onset LACC group. The external validation set included 228 early-onset LACC patients. Early-onset colon cancers had poorer prognosis (T4, N2, TNM stage III, CEA, tumor deposit, and nerve invasion), and a higher proportion received radiotherapy and systemic therapy (P<0.001). In the survival analysis, cancer-specific survival (CSS) was better in patients with early-onset LACC than in those with late-onset LACC (P <0.001). This nomogram constructed based on the results of COX analysis showed better accuracy in CSS prediction of early-onset LACC patients than AJCC-TNM system in the training set and external validation set (0.783 vs 0.728; 0.852 vs 0.773).

CONCLUSION

We developed a novel nomogram model to predict CSS in patients with early-onset LACC it provided a reference in prognosis prediction and selection of individualized treatment, helping clinicians in decision-making.

摘要

目的

建立一个改良的列线图模型和全新的风险分层系统,以对早发性局部晚期结肠癌(LACC)患者的风险水平进行分类,从而预测癌症特异性生存。

方法

回顾性检索 2010 年至 2019 年 SEER 数据库中 LACC 病例的临床资料和生存结局。根据诊断时的年龄(50 岁)将早发性和晚发性结肠癌分为两组。比较组间差异,确定相互显著的变量。进一步进行多变量 Cox 回归分析,并构建列线图。与 AJCC-TNM 系统进行比较。进行外部验证评估。最后,建立早发性 LACC 患者的风险分层系统。

结果

共纳入 32855 例 LACC 患者,其中 4548 例(13.84%)为早发性 LACC 患者,28307 例(86.16%)为晚发性 LACC 患者。外部验证集包括 228 例早发性 LACC 患者。早发性结肠癌预后较差(T4、N2、TNM 分期 III 期、CEA、肿瘤沉积和神经侵犯),接受放疗和系统治疗的比例较高(P<0.001)。生存分析显示,早发性 LACC 患者的癌症特异性生存率(CSS)优于晚发性 LACC 患者(P<0.001)。基于 COX 分析结果构建的列线图在训练集和外部验证集中对早发性 LACC 患者 CSS 预测的准确性均优于 AJCC-TNM 系统(0.783 比 0.728;0.852 比 0.773)。

结论

我们开发了一种新的列线图模型,用于预测早发性 LACC 患者的 CSS,为预后预测和个体化治疗选择提供了参考,有助于临床医生做出决策。

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