Dataset Information

Development and validation of prognostic nomograms for patients with colon neuroendocrine neoplasms.

ABSTRACT:

Background

Colon neuroendocrine neoplasms (NENs) have one of the poorest median overall survival (OS) rates among all NENs. The American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) staging system-currently the most commonly used prediction model-has limited prediction accuracy because it does not include parameters such as age, sex, and treatment. The aim of this study was to construct nomograms containing various clinically important parameters to predict the prognosis of patients with colon NENs more accurately.

Methods

Using the Surveillance, Epidemiology, and End Results (SEER) database, we performed a retrospective analysis of colon NENs diagnosed from 1975 to 2016. Data were collected from 1196 patients; almost half were female (617/1196, 51.6%), and the average age was 61.94 ± 13.05 years. Based on the age triple cut-off values, there were 396 (33.1%), 408 (34.1%), and 392 (32.8%) patients in age groups 0-55 years, 55-67 years, and ≥ 68 years, respectively. Patients were randomized into training and validation cohorts (3:1). Independent prognostic factors were used for construction of nomograms to precisely predict OS and cancer-specific survival (CSS) in patients with colon NENs.

Results

Multivariate analysis showed that age ≥ 68 years, sex, tumor size, grade, chemotherapy, N stage, and M stage were independent predictors of OS. In the validation cohort, the Concordance index (C-index) values of the OS and CSS nomograms were 0.8345 (95% confidence interval [CI], 0.8044-0.8646) and 0.8209 (95% CI, 0.7808-0.861), respectively. C-index also indicated superior performance of both nomograms (C-index 0.8347 for OS and 0.8668 for CSS) compared with the AJCC TNM classification (C-index 0.7159 for OS and 0.7366 for CSS).

Conclusions

We established and validated new nomograms for more precise prediction of OS and CSS in patients with colon NENs to facilitate individualized clinical decisions.

SUBMITTER: Xu R

PROVIDER: S-EPMC8349494 | biostudies-literature |

REPOSITORIES: biostudies-literature

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