Validated predictive model for treatment and prognosis of adrenocortical carcinoma.

ABSTRACT

BACKGROUND: Adrenocortical carcinoma has a poor prognosis and multiple clinical, pathological, and treatment variables. Currently, we lack a prognostic and treatment calculator to determine the survival and efficacy of adjuvant chemoradiation. We aimed to validate a calculator to assess prognosis and treatment. METHODS: We searched the National Cancer Database to identify patients with adrenocortical carcinoma surgically treated from 2004 to 2020 and randomly allocated them into a training (80%) or validation set (20%). We analyzed the variables of age; sex; Charlson Comorbidity Index; insurance status; tumor size; pathologic tumor, node, and metastasis categories; surgical margins; and use of chemotherapy and radiation therapy. We used Cox regression prediction models and bootstrap coefficients to generate a mathematical model to predict 5- and 10-year overall survival. After using the area under the curve analysis to assess the model's performance, we compared overall survival in the training and validation sets. RESULTS: Multivariable analysis of the 3,480 patients included in the study revealed that all variables were significant except sex (P < .05) and incorporated into a mathematical model. The area under the curve for 5- and 10-year overall survival was 0.68 and 0.70, respectively, for the training set and 0.70 and 0.72, respectively, for the validation set. For the bootstrap coefficients, the 5- and 10-year overall survival was 6.4% and 4.1%, respectively, above the observed mean. CONCLUSION: Our model predicts the overall survival of patients with adrenocortical carcinoma based on clinical, pathologic, and treatment variables and can assist in individualizing treatment.