A model of multiple tumor marker for lymph node metastasis assessment in colorectal cancer: a retrospective study

PeerJ

article

Jiangping Fu¹  Mengjie Tu¹  Yin Zhang³  Yan Zhang⁴  Jiasi Wang⁵  Zhaoping Zeng¹  Jie Li¹  Fanxin Zeng¹ 

[1] Department of Clinical Research Center, Dazhou Central Hospital;National Center for International Research of Biological Targeting Diagnosis and Therapy, Guangxi Key Laboratory of Biological Targeting Diagnosis and Therapy Research, Collaborative Innovation Center for Targeting Tumor Diagnosis and Therapy, Guangxi Medical University;Department of Oncology, Dazhou Central Hospital;Department of Thoracic Oncology, Cancer Center, State Key Laboratory of Biotherapy, West China Hospital, West China Medical School, Sichuan University;Department of Clinical Laboratory, Dazhou Central Hospital

关键词: Colorectal cancer;    Tumor markers;    Nomogram;    Assessment model;    Lymph node metastasis;   

DOI  :  10.7717/peerj.13196

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

Background Assessment of colorectal cancer (CRC) lymph node metastasis (LNM) is critical to the decision of surgery, prognosis, and therapy strategy. In this study, we aimed to develop and validate a multiple tumor marker nomogram for predicting LNM in CRC patients. Methods A total of 674 patients who met the inclusion criteria were collected and randomly divided into primary cohort and internal test cohort at a ratio of 7:3. An external test cohort enrolled 178 CRC patients from the West China Hospital. Clinicopathologic variables were obtained from electronic medical records. The least absolute shrinkage and selection operator (LASSO) and interquartile range analysis were carried out for variable dimensionality reduction and feature selection. Multivariate logistic regression analysis was conducted to develop predictive models of LNM. The performance of the established models was evaluated by the receiver operating characteristic (ROC) curve, calibration belt, and clinical usefulness. Results Based on minimum criteria, 18 potential features were reduced to six predictors by LASSO and interquartile range in the primary cohort. The model demonstrated good discrimination and ROC curve (AUC = 0.721 in the internal test cohort, AUC = 0.758 in the external test cohort) in LNM assessment. Good calibration was shown for the probability of CRC LNM in the internal and external test cohorts. Decision curve analysis illustrated that multi-tumor markers nomogram was clinically useful. Conclusions The study proposed a reliable nomogram that could be efficiently and conveniently utilized to facilitate the assessment of individually-tailored LNM in patients with CRC, complementing imaging and biopsy tests.

【 授权许可】

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