4.6 Article

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

期刊

PEERJ
卷 10, 期 -, 页码 -

出版社

PEERJ INC
DOI: 10.7717/peerj.13196

关键词

Colorectal cancer; Tumor markers; Nomogram; Assessment model; Lymph node metastasis

资金

  1. National Natural Science Foundation of China [81902861]
  2. Innovative Scientific Research Project of Medical Youth in Sichuan Province [Q20073]
  3. Scientific Research Fund of Technology Bureau in Dazhou [19YYJC0010]
  4. Scientific Fund of Health Commission of Sichuan Province [18PJ040]

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This study developed and validated a multiple tumor marker nomogram for predicting lymph node metastasis in colorectal cancer (CRC) patients. The nomogram showed good discrimination and performance in assessing lymph node metastasis, and demonstrated good calibration and clinical usefulness.
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.

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