AbstractGiven the unclear preference criteria for regorafenib in treating refractory metastatic colorectal cancer (mCRC), this study aimed to construct an algorithm in selecting right patients for regorafenib. This was a multicenter retrospective cohort study. Patients with pathology confirmed mCRC and administered with regorafenib for > 3 weeks were enrolled. Patients with good response were defined to have progression-free survival (PFS) of ≥ 4 months. The Kaplan–Meier plot was used to analyze survival. A Cox proportional hazards model was used to analyze univariate and multivariate prognostic factors and was visualized using forest plot. A clustering heatmap was used to classify patients according to responses. The decision tree and nomogram were used to construct the approaching algorithm. A total of 613 patients was analyzed. The median PFS and overall survival (OS) were 2.7 and 10.6 months, respectively. The partial response and stable disease rate are 2.4% and 36.4%. The interval between metastasis (M1) and regorafenib, metastatic status (number, liver, and brain), and CEA level were independent prognostics factors of PFS that classifies patients into three groups: good, bad and modest-1/modest-2 group with PFS > = 4 months rates of 51%, 20%, 39% and 30%, respectively. Results were used to develop the decision tree and nomogram for approaching patients indicated with regorafenib. The preference criteria for regorafenib in treating patients with refractory mCRC are small tumor burden (CEA), slow growth (interval between metastasis and regorafenib) and poor/scanty spread (metastatic status: number and sites of metastasis): The 3S rules.TRIAL registration ClinicalTrials.gov Identifier: NCT03829852; Date of first registration (February 11, 2019).
Enhanced Detection of Treatment Effects on Metastatic Colorectal Cancer with Volumetric CT Measurements for Tumor Burden Growth Rate Evaluation
