Novel Nomograms Individually Predicting Overall Survival of Non-metastatic Colon Cancer Patients

Abstract

Background: This study aimed to develop an effective prognostic nomogram for predicting non-metastatic colon cancer. Methods: The Surveillance, Epidemiology, and End Results program was utilized to analyze patients who underwent surgical therapy (25,350 for training, 10,860 for validation). Nomograms were created depending upon multivariate analysis in the training cohort and were compared to current American Joint Committee on Cancer (AJCC) classifications. Areas under the receiver-operating characteristic curves (AUCs), Akaike's information criterions (AICs), and calibration curves were used. The clinical benefit was measured using decision curve analyses (DCAs). The validation cohort was used to validate the results. Results: Nomogram 1 included age, gender, histological grade, T stage, number of retrieved lymph nodes, tumor size, and N stage. Nomogram 2 included age, gender, histological grade, T stage, number of retrieved lymph nodes, tumor size, and number of positive lymph nodes. The prognostic discrimination of nomogram 1 (AUC, 0.729, 95% CI, 0.723-0.736) was better than that of nomogram 2 (AUC, 0.704, 95% CI, 0.698-0.710, p < 0.001) in five-year overall survival in the training cohort. Nomogram 1 (AIC, 137,319) also showed superior model-fitting compared to nomogram 2 (AIC, 137,453). Similarity, nomogram 1 was better than the AJCC 6th and 8th TNM classifications. DCA revealed that nomogram 1 had a superior net benefit than other models. These findings were validated using the validation cohort. Conclusions: The proposed nomogram 1 was a better prognostic prediction model with better discrimination and superior model-fitting for patients with non-metastatic colon cancer, which might prove to be clinically helpful.

Keywords: colon cancer; nomogram; overall survival; prediction model; prognosis.

Figure 1

Flow chart for patient selection and study development.

Figure 2

Nomograms predicting three- and five-year overall survival (OS). For each patient, corresponding clinicopathological feature points were calculated and summed up to obtain total points. Predicted three- and five-year OS can be estimated based on total points for each patient. (A) Nomogram 1: variables included age, gender, histological grade, AJCC 8th T stage, tumor size, retrieved lymph nodes, and AJCC 8th N stage; (B) Nomogram 2: variables included age, gender[[Inline Image]], histological grade, AJCC 8th T stage, tumor size, RLNs, and number of positive lymph nodes.

Figure 3

Kaplan–Meier survival curve based on the AJCC 6th TNM and AJCC 8th TNM classifications. (A) Kaplan–Meier survival curves based on AJCC 6th TNM classification in the training cohort. (B) Kaplan–Meier survival curves based on AJCC 8th TNM classification in the training cohort. (C) Kaplan–Meier survival curves based on AJCC 6th TNM classification in the validation cohort. (D) Kaplan–Meier survival curves based on AJCC 8th TNM classification in the validation cohort.

Figure 4

Time-dependent areas under receiver-operating characteristic (ROC) curves (AUCs) in training and validation cohorts for three- and five-year OS. In training cohort, (A, B) were nomogram 1 for three- and five-year OS, respectively. (C, D) were nomogram 2 for three- and five-year OS, respectively. (E, F) were AJCC 8th TNM classification for three- and five-year OS, respectively. (G, H) were AJCC 6th TNM classification for three- and five-year OS, respectively. In validation cohort, (I, J) were nomogram 1 for three- and five-year OS, respectively. (K, L) were nomogram 2 in three- and five-year OS, respectively. (M, N) were AJCC 8th TNM classification for three- and five-year OS, respectively. (O, P) were AJCC 6th TNM classification for three- and five-year OS, respectively.

Figure 5

Calibration curve for predicting patient survival at (A) three and (B) five years in the training cohort and at (C) three and (D) five years in the validation cohort. Nomogram-predicted probability of OS is plotted on the x-axis; actual OS is plotted on the y-axis. Shorter distance between two curves indicates higher accuracy.

Figure 6

Decision curve analysis of training and validation cohorts for three- and five-year OS. Decision curve analysis was used to compare clinical net benefits between nomograms and conventional staging systems in terms of three-year OS for (A) training and (C) validation cohorts and five-year OS for (B) training and (D) validation cohorts. For decision curve analysis, horizontal solid black line assumed no patients would die and dotted gray line assumed all patients would die.