基于 SEER 数据库和中国人群的直肠癌远处转移风险因素评估及预后预测模型的建立和验证研究。

Evaluation of Risk Factors, and Development and Validation of Prognostic Prediction Models for Distant Metastasis in Patients With Rectal Cancer: A Study Based on the SEER Database and a Chinese Population.

机构信息

College of First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China.

Oncology Laboratory, Weifang Traditional Chinese Hospital, Weifang, China.

出版信息

Cancer Control. 2024 Jan-Dec;31:10732748241303650. doi: 10.1177/10732748241303650.

DOI:10.1177/10732748241303650

PMID:39579008

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11585045/

Abstract

PURPOSE

This study aimed to construct a prediction model regarding risk factors and prognostic factors for distant metastasis of T1-T3 stage rectal cancer. For this purpose, a population-based retrospective cohort study was conducted.

METHODS

Data on 7872 patients diagnosed with rectal cancer between 2004 and 2020 were obtained from the Surveillance, Epidemiology, and End Results database, of whom 746 had distant metastases at diagnosis. Independent risk factors for distant metastasis of rectal cancer were determined using univariate and multivariate logistic regression analyses. Cox proportional hazards regression analyses clarified the independent prognostic factors for distant metastases of rectal cancer. A 7:3 randomization process was used to place all patients into the training and internal validation groups. Furthermore, we retrospectively collected clinical data from 226 patients who had both rectal cancer and distant metastases between 2012 and 2024 at the Weifang Hospital of Traditional Chinese Medicine. We used the calibration curve, DCA curve, C-index, and area under the curve (AUC) to assess the discriminatory and pre-precision qualities of the models.

RESULTS

The multivariate logistic regression analysis identified race, tumor grade, T stage, N stage, radiotherapy, chemotherapy, surgery, tumor size, and histological subtype as risk factors for distant metastases in rectal cancer, with AUC values for both training and validation sets exceeding 0.8. Using Cox regression analysis, we determined that the age, sex, tumor size, surgery, chemotherapy, and radiotherapy were independent predictors of distant metastasis of rectal cancer. In the prognostic model, the C-index of the training cohort was 0.687 (95% CI: 0.6615-0.7125), that of the internal validation cohort was 0.692 (95% CI: 0.6508-0.7332), and that of the external validation cohort was 0.704 (0.6785-0.7295).

CONCLUSION

Our nomogram can predict risk factors and analyze the 1-, 2-, and 3 year prognosis of distant metastases in patients with rectal cancer, providing valuable guidance for future clinical work.

摘要

目的

本研究旨在构建 T1-T3 期直肠癌远处转移的风险因素和预后因素预测模型。为此，进行了一项基于人群的回顾性队列研究。

方法

从监测、流行病学和最终结果数据库中获取了 2004 年至 2020 年间诊断为直肠癌的 7872 例患者的数据，其中 746 例在诊断时发生远处转移。使用单因素和多因素逻辑回归分析确定直肠癌远处转移的独立风险因素。Cox 比例风险回归分析明确了直肠癌远处转移的独立预后因素。采用 7:3 的随机化过程将所有患者分为训练组和内部验证组。此外，我们回顾性地收集了 2012 年至 2024 年期间在潍坊市中医院同时患有直肠癌和远处转移的 226 例患者的临床数据。我们使用校准曲线、DCA 曲线、C 指数和曲线下面积（AUC）来评估模型的判别和预测精度。

结果

多因素逻辑回归分析确定了种族、肿瘤分级、T 分期、N 分期、放疗、化疗、手术、肿瘤大小和组织学亚型是直肠癌远处转移的风险因素，训练集和验证集的 AUC 值均超过 0.8。使用 Cox 回归分析，我们确定年龄、性别、肿瘤大小、手术、化疗和放疗是直肠癌远处转移的独立预测因素。在预后模型中，训练队列的 C 指数为 0.687（95%CI：0.6615-0.7125），内部验证队列为 0.692（95%CI：0.6508-0.7332），外部验证队列为 0.704（0.6785-0.7295）。