BACKGROUND: Colon cancer (CC) is one of the most common cancers of the digestive tract, the third most common cancer worldwide, and the second most common cause of cancer-related deaths. Previous studies have demonstrated a higher risk of lymph node metastasis (LNM) in young patients with CC. It might be reasonable to treat patients with early-onset locally advanced CC with extended lymph node dissection. However, few studies have focused on early-onset CC (ECC) patients with LNM. At present, the methods of predicting and evaluating the prognosis of ECC patients with LNM are controversial. AIM: To compare the prognostic values of four lymph node staging indices and establish the best nomogram for patients with ECC. METHODS: From the data of patients with CC obtained from the Surveillance, Epidemiology, and End Results (SEER) database, data of young patients with ECC (≤ 50 years old) was screened. Patients with unknown data were excluded from the study, while the remaining patients were included. The patients were randomly divided into a training group (train) and a testing group (test) in the ratio of 7:3, while building the model. The model was constructed by the training group and verified by the testing group. Using multiple Cox regression models to compare the prediction efficiency of LNM indicators, nomograms were built based on the best model selected for overall survival (OS) and cause-specific survival (CSS). In the two groups, the performance of the nomogram was evaluated by constructing a calibration plot, time-dependent area under the curve (AUC), and decision curve analysis. Finally, the patients were grouped based on the risk score predicted by the prognosis model, and the survival curve was constructed after comparing the survival status of the high and low-risk groups. RESULTS: Records of 26922 ECC patients were screened from the SEER database. N classification, positive lymph nodes (PLN), lymph node ratio (LNR) and log odds of PLN (LODDS) were considered to be independent predictors of OS and CSS. In addition, independent risk factors for OS included gender, race, marital status, primary site, histology, grade, T, and M classification, while the independent prognostic factors for CSS included race, marital status, primary site, grade, T, and M classification. The prediction model including LODDS is composed of minimal Akaike information criterion, maximal concordance indexes, and AUCs. Factors including gender, race, marital status, primary site, histology, grade, T, M classification, and LODDS were integrated into the OS nomogram, while race, marital status, primary site, grade, T, M classification, and LODDS were included into the CSS nomogram. The nomogram representing both cohorts had been successfully verified in terms of prediction accuracy and clinical practicability. CONCLUSION: LODDS is superior to N-stage, PLN, and LNR of ECC. The nomogram containing LODDS might be helpful in tumor evaluation and clinical decision-making, since it provides an appropriate prediction of ECC.