Construction of a prognostic nomogram for predicting the postoperative metastasis risk of patients with non-metastatic color-ectal cancer / 临床检验杂志

ABSTRACT

Objective To construct a prognostic nomogram for predicting the prognosis of patients with colorectal cancer ( CRC) , and verify its accuracy. Methods The clinical pathologic data from 438 CRC patients hospitalized in the Third Affiliated Hospital of Soo-chow University during January 2006 and May 2013 were retrospectively analyzed. The independent risk factors for predicting the prog-nosis of CRC were determined by the univariate and multivariate regression model. The prognostic nomogram was established by the R-language software. Then, the nomograms of postoperative 3-year and 5-year disease free survivals ( DFS) were drawn, and compared with the actual status. The internal validation and accuracy of the nomogram were determined by the Bootstrap method and the calculat-ed concordance index ( C-index) , respectively. The sensitivity and specificity of the nomogram for predicting the 3-year and 5-year DFS were compared with those of TNM system established by the American Joint Committee On Cancer (AJCC) (7th ed.) by using the time-dependent ROC curve. Results Among 438 CRC patients, the metastasis of CRC occurred in 233 patients, including 105 liver metas-tasis and 57 lung metastasis. Multivariate COX regression analysis showed that tumor differentiation degree, TNM stage, serum CEA level, serum CA19-9 level, neutrophil lymphocyte ratio ( NLR) and P53 level were the independent risk factors of CRC. The C-index of the constructed nomogram for predicting the survival rate of CRC patients was 0.678. The predicted 3-year and 5-year DFS by the no-mogram were highly coincident with the actual status. The analysis results of the time-dependent ROC curve showed that the sensitivity and specificity of the established nomogram for predicting the postoperative 3-year and 5-year DFS were higher than those of AJCC-TNM stage.Conclusion The established nomogram may accurately predict the prognosis of CRC patients, which may be helpful for clinicians to follow up or make beneficial treatment for CRC patients.