Validated predictive model for treatment and prognosis of adrenocortical carcinoma

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. (c) 2023 Elsevier Inc. All rights reserved.