J Cancer 2020; 11(15):4366-4372. doi:10.7150/jca.40921 This issue Cite
Research Paper
1. Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Bejing, China
2. Department of Colorectal Surgery, the Second Affiliated Hospital of Harbin Medical University, Harbin, China
*Xu Guan and Chen-xi Ma contributed equally to this work
Background: The prognosis of synchronous bone metastasis (BM) in colorectal cancer (CRC) is poor and rarely concerned. A clinical tool to evaluate the prognosis and clinical outcomes for BM would be attractive in current clinical practice.
Methods: A total of 342 CRC patients with synchronous BM were identified from Surveillance, Epidemiology, and End Results (SEER) database. The cancer specific survival (CSS) was estimated with the Kaplan-Meier method. Prognostic factors were identified from multivariate Cox model, and the final clinical nomogram was developed to predict the CSS. The concordance index (C-index) was used to assess the discriminative ability. Calibration curves were provided to internally validate the performance of the nomogram.
Results: The nomogram finally consisted of 6 prognostic factors including age, tumor grade, AJCC N stage, carcinoembryonic antigen (CEA) levels, primary tumor resection and chemotherapy, which translated the effects of prognostic factors into certain scores to predict the 1-, 2- and 3-year CSS for the synchronous BM in CRC patients. The nomogram presented a good accuracy for predicting the CSS with the C-index of 0.742. The calibration of the nomogram predictions was also accurate.
Conclusions: This nomogram was accurate enough to predict the CSS of CRC patients with synchronous BM using readily available clinicopathologic factors and could provide individualized clinical decisions for both physicians and patients.
Keywords: colorectal cancer, bone metastasis, nomogram, prognostic factors, cancer specific survival, the Surveillance, Epidemiology, and End Results database