开发和验证用于结直肠癌肝肺转移患者的预后评分系统：一项回顾性研究。
Development and validation of a prognostic scoring system for patients with colorectal cancer hepato-pulmonary metastasis: a retrospective study.
机构信息
Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, Hubei, China.
出版信息
BMC Cancer. 2022 Jun 11;22(1):643. doi: 10.1186/s12885-022-09738-3.
BACKGROUND
Hepato-pulmonary metastasis of colorectal cancer (CRC) is a rare disease with poor prognosis. This study aims to establish a highly efficient nomogram model to predict overall survival (OS) and cancer-specific survival (CSS) in patients with colorectal cancer hepato-pulmonary metastasis (CRCHPM).
METHODS
We retrospectively analyzed the data of patients with CRCHPM from SEER database and Wuhan Union Hospital Cancer Center (WUHCC). A total of 1250 CRCHPM patients were randomly assigned to the training, internal validation, and external validation cohorts from 2010 to 2016.Univariate and multivariate cox analysis were performed to identify independent clinicopathological predictors of OS and CSS, and a nomogram was constructed to predict OS and CSS in CRCHPM patients.
RESULTS
A nomogram of OS was constructed based on seven independent predictors of age, degree of differentiation, T stage, chemotherapy, number of lsampled lymph nodes, number of positive lymph nodes, and tumor size. Nomogram showed favorable sensitivity in predicting OS at 1, 3 and 5 years, with area under the receiver operating characteristic curve (AUROC) values of 0.802, 0.759 and 0.752 in the training cohort;0.814, 0.769 and 0.716 in the internal validation cohort;0.778, 0.756 and 0.753 in the external validation cohort, respectively. A nomogram of CSS was constructed based on three independent predictors of T stage, chemotherapy, and tumor size. The AUROC values of 1, 3 and 5 years were 0.709,0.588,0.686 in the training cohort; 0.751, 0.648,0.666 in the internal validation cohort;0.781,0.588,0.645 in the external validation cohort, respectively. Calibration curves, Concordance index (C-index), and decision curve analysis (DCA) results revealed that using our model to predict OS and CSS is more efficient than other single clinicopathological characteristics.
CONCLUSION
A nomogram of OS and CSS based on clinicopathological characteristics can be conveniently used to predict the prognosis of CRCHPM patients.
背景
结直肠癌肝肺转移（CRC）是一种预后不良的罕见疾病。本研究旨在建立一种高效的列线图模型，以预测结直肠癌肝肺转移（CRCHPM）患者的总生存期（OS）和癌症特异性生存期（CSS）。
方法
我们回顾性分析了 SEER 数据库和武汉协和医院癌症中心（WUHCC）的 CRCHPM 患者数据。2010 年至 2016 年期间，共有 1250 例 CRCHPM 患者被随机分配到训练、内部验证和外部验证队列中。我们进行单变量和多变量 Cox 分析，以确定 OS 和 CSS 的独立临床病理预测因素，并构建列线图来预测 CRCHPM 患者的 OS 和 CSS。
结果
基于年龄、分化程度、T 分期、化疗、采样淋巴结数、阳性淋巴结数和肿瘤大小等 7 个独立预测因素，构建了 OS 列线图。列线图在预测 OS 方面具有良好的敏感性，在训练队列中的 1、3 和 5 年时的 AUC 值分别为 0.802、0.759 和 0.752；内部验证队列中分别为 0.814、0.769 和 0.716；外部验证队列中分别为 0.778、0.756 和 0.753。基于 T 分期、化疗和肿瘤大小等 3 个独立预测因素，构建了 CSS 列线图。在训练队列中，1、3 和 5 年时的 AUC 值分别为 0.709、0.588 和 0.686；内部验证队列中分别为 0.751、0.648 和 0.666；外部验证队列中分别为 0.781、0.588 和 0.645。校准曲线、一致性指数（C 指数）和决策曲线分析（DCA）结果表明，使用我们的模型预测 OS 和 CSS 比其他单一临床病理特征更有效。
结论
基于临床病理特征的 OS 和 CSS 列线图可方便地用于预测 CRCHPM 患者的预后。
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