Novel nomograms to predict lymph node metastasis and liver metastasis in patients with early colon carcinoma

Abstract

Abstract Background Lymph node status and liver metastasis (LIM) are important in determining the prognosis of early colon carcinoma. We attempted to develop and validate nomograms to predict lymph node metastasis (LNM) and LIM in patients with early colon carcinoma. Methods A total of 32,819 patients who underwent surgery for pT1 or pT2 colon carcinoma were enrolled in the study based on their records in the SEER database. Risk factors for LNM and LIM were assessed based on univariate and multivariate binary logistic regression. The C-index and calibration plots were used to evaluate LNM and LIM model discrimination. The predictive accuracy and clinical values of the nomograms were measured by decision curve analysis. The predictive nomograms were further validated in the internal testing set. Results The LNM nomogram, consisting of seven features, achieved the same favorable prediction efficacy as the five-feature LIM nomogram. The calibration curves showed perfect agreement between nomogram predictions and actual observations. The decision curves indicated the clinical usefulness of the prediction nomograms. Receiver operating characteristic curves indicated good discrimination in the training set (area under the curve [AUC] = 0.667, 95% CI 0.661–0.673) and the testing set (AUC = 0.658, 95% CI 0.649–0.667) for the LNM nomogram and encouraging performance in the training set (AUC = 0.766, 95% CI 0.760–0.771) and the testing set (AUC = 0.825, 95% CI 0.818–0.832) for the LIM nomogram. Conclusion Novel validated nomograms for patients with early colon carcinoma can effectively predict the individualized risk of LNM and LIM, and this predictive power may help doctors formulate suitable individual treatments.

Keywords

• Colon carcinoma
• Lymph node metastasis
• Liver metastasis
• Nomogram
• Decision curve analysis
• Surveillance, epidemiology, and end results