Table_1_Novel Nomograms Individually Predicting Overall Survival of Non-metastatic Colon Cancer Patients.DOCX (49.55 kB)

Table_1_Novel Nomograms Individually Predicting Overall Survival of Non-metastatic Colon Cancer Patients.DOCX

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posted on 06.05.2020 by Jun-Peng Pei, Chun-Dong Zhang, Yu Liang, Cheng Zhang, Kun-Zhe Wu, Zhe-Ming Zhao, Dong-Qiu Dai

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.

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