S-GRAS score performs better than a model from SEER for patients with adrenocortical carcinoma

Abstract

Purpose To externally validate the performance of the S-GRAS score and a model from the Surveillance, Epidemiology, and End Results (SEER) database in a Chinese cohort of patients with adrenocortical carcinoma (ACC). Methods We first developed a model using data from the SEER database, after which we retrospectively reviewed 51 ACC patients hospitalized between 2013 and 2018, and we finally validated the model and S-GRAS score in this Chinese cohort. Results Patient age at diagnosis, tumor size, TNM stage, and radiotherapy were used to construct the model, and the Harrell’s C-index of the model in the training set was 0.725 (95% CI: 0.682–0.768). However, the 5-year area under the curve (AUC) of the model in the validation cohort was 0.598 (95% CI: 0.487–0.708). The 5-year AUC of the ENSAT stage was 0.640 (95% CI: 0.543–0.737), but the Kaplan–Meier curves of stages I and II overlapped in the validation cohort. The resection status (P = 0.066), age (P=0.68), Ki67 (P = 0.69), and symptoms (P = 0.66) did not have a significant impact on cancer-specific survival in the validation cohort. In contrast, the S-GRAS score group showed better discrimination (5-year AUC: 0.683, 95% CI: 0.602–0.764) than the SEER model or the ENSAT stage. Conclusion The SEER model showed favorable discrimination and calibration ability in the training set, but it failed to distinguish patients with various prognoses in our institution. In contrast, the S-GRAS score could effectively stratify patients with different outcomes.