Individualized prediction of survival benefit from primary tumor resection for patients with unresectable metastatic colorectal cancer

• Main Authors: Yi Yang, Yujie Lu, Wen Jiang, Jinzhou Zhu, Su Yan
• Format: Article
• Language: English
• Published: BMC 2020-08-01
• Series: World Journal of Surgical Oncology
• Subjects: Nomogram; Survival; SEER; Colorectal cancer; Metastasis; Primary tumor resection
• Online Access: http://link.springer.com/article/10.1186/s12957-020-01972-y

Abstract Background The impact of primary tumor resection (PTR) on the prognosis of unresectable metastatic colorectal cancer (mCRC) patients remains debatable. We aimed to develop several prognostic nomograms which could be useful in predicting whether patients might benefit from PTR or not. Methods Patients diagnosed as mCRC without resected metastasis were identified from the Surveillance Epidemiology and End Results database and randomly assigned into two groups: a training cohort (6369 patients) and a validation cohort (2774 patients). Univariate and multivariable Cox analyses were performed to identify the independent predictors and construct nomograms that could independently predict the overall survival (OS) of unresectable mCRC patients in PTR and non-PTR groups, respectively. The performance of these nomograms was assessed by the concordance index (C-index), calibration curves, and decision curve analysis (DCA). Results Based on the result of univariate and multivariable Cox analyses, two nomograms were respectively constructed to predict the 1-year OS rates of unresectable mCRC patients when receiving PTR and not. The first one included age, gender, tumor grade, proximal colon, N stage, CEA, chemotherapy, radiotherapy, histology type, brain metastasis, liver metastasis, lung metastasis, and bone metastasis. The second nomogram included age, race, tumor grade, primary site, CEA, chemotherapy, brain metastasis, and bone metastasis. These nomograms showed favorable sensitivity with the C-index range of 0.700–0.725. The calibration curves and DCAs also exhibited adequate fit and ideal net benefits in prognosis prediction and clinical application. Conclusions These practical prognosis nomograms could assist clinicians in making appropriate treatment decisions to effectively manage the disease.