Development and validation of a nomogram for predicting survival in patients with gastrointestinal stromal tumours.

Background: This study aimed to develop and validate nomograms for predicting long-term overall survival (OS) and cancer-specific survival (CSS) in gastrointestinal stromal tumours (GISTs).

Methods: Patients diagnosed with GISTs between 2004 and 2015 were selected for the study from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were randomly separated into the training set and the validation set. Multivariate analysis was used on the training set to obtain independent prognostic factors to build nomograms for predicting 3- and 5-year OS and CSS. The discrimination and calibration plots were used to evaluate the predictive accuracy of the nomograms.

Results: Data for a total of 5622 patients with GISTs were collected from the SEER database. Nomograms were established based on variables that were significantly associated with OS and CSS identified by the Cox regression model. The nomograms for predicting OS and CSS displayed better discrimination power than did the SEER stage and Tumour-Node-Metastasis (TNM) staging systems (7th edition) in the training set and validation set. Calibration plots of the nomograms indicated that OS and CSS closely corresponded to actual observation.

Conclusions: The nomograms were able to more accurately predict 3- and 5-year OS and CSS of patients with GISTs than were existing models.