Development and internal validation of individualized prediction models of overall survival and 6-month mortality among patients with synchronous early-onset colorectal liver metastases.

Background: Early-onset colorectal cancer with synchronous liver metastasis (EO-CRLM) is a growing concern with a grim prognosis.

Methods: EO-CRLM patients were identified from the National Cancer Database. Random survival forest model and random forest (RF) model were developed for the prediction of overall survival (OS) and 6-month mortality, respectively.

Results: The variables with top contributions for random survival forest model of OS included primary tumor resection, chemotherapy and bone metastases. The AUCs of 1-, 3- and 5-year OS were 0.787, 0.763 and 0.761, respectively. The individualized risk profile predicted by the models closely aligned with the actual survival outcomes observed for the patients. The variables with top contributions for RF model for 6-month mortality included chemotherapy, Charlson-Deyo comorbidity score and presence of tumor deposits. RF model for 6-month mortality resulted in an AUC of 0.821 in training set, 0.828 in cross-validation and 0.852 in testing cohort. RF models for OS and 6-month mortality exhibited great net benefit with favorable clinical utility.

Conclusion: The models generated in this study accurately identified EO-CRLM patients at risk of worse OS and short-term mortality, which may complement standard clinical assessment and aid in creation of advanced care planning.