BACKGROUND: While several prognostic models have been developed to predict survival of patients who undergo hepatectomy for metastatic colorectal cancer (mCRC), few data exist to predict survival after recurrence. We sought to develop a model that predicts survival for patients who have developed recurrence following hepatectomy for mCRC. METHODS: A retrospective analysis was performed on data from consecutive patients that underwent hepatectomy for mCRC. Clinicopathologic data, recurrence patterns, and outcomes were analyzed. Kaplan-Meier survival analysis and univariate and multivariate analyses were performed. An integer-based model was created to predict the patterns of recurrence and survival after recurrence. RESULTS: This analysis included 280 patients with a median follow-up of 50.1 months. Of these, 53% underwent major hepatectomy and 87% had negative margins. Recurrent disease developed in 63% of patients. After hepatectomy, factors associated with short disease-free interval (DFI) and overall survival (OS) included CEA > 200 ng/ml (P < 0.0005), >1 metastasis (P < 0.0005), and a high Fong score (P < 0.0005). After recurrence, the pattern of recurrence was a strong predictor of OS (P < 0.0005). Independent predictors of the pattern of recurrence on multivariate analysis include CEA > 200 ng/ml, tumor size >5 cm, and >1 liver metastasis. A simple predictive scoring system was developed from the beta coefficients of this analysis that correlated with recurrence pattern (P < 0.0005). CONCLUSIONS: After hepatectomy, survival of patients with recurrent mCRC is strongly predicted by the patterns of recurrence, and the recurrence pattern can be predicted with a simple model. This can also be extended to create a scoring system that estimates expected survival.
BACKGROUND: While several prognostic models have been developed to predict survival of patients who undergo hepatectomy for metastatic colorectal cancer (mCRC), few data exist to predict survival after recurrence. We sought to develop a model that predicts survival for patients who have developed recurrence following hepatectomy for mCRC. METHODS: A retrospective analysis was performed on data from consecutive patients that underwent hepatectomy for mCRC. Clinicopathologic data, recurrence patterns, and outcomes were analyzed. Kaplan-Meier survival analysis and univariate and multivariate analyses were performed. An integer-based model was created to predict the patterns of recurrence and survival after recurrence. RESULTS: This analysis included 280 patients with a median follow-up of 50.1 months. Of these, 53% underwent major hepatectomy and 87% had negative margins. Recurrent disease developed in 63% of patients. After hepatectomy, factors associated with short disease-free interval (DFI) and overall survival (OS) included CEA > 200 ng/ml (P < 0.0005), >1 metastasis (P < 0.0005), and a high Fong score (P < 0.0005). After recurrence, the pattern of recurrence was a strong predictor of OS (P < 0.0005). Independent predictors of the pattern of recurrence on multivariate analysis include CEA > 200 ng/ml, tumor size >5 cm, and >1 liver metastasis. A simple predictive scoring system was developed from the beta coefficients of this analysis that correlated with recurrence pattern (P < 0.0005). CONCLUSIONS: After hepatectomy, survival of patients with recurrent mCRC is strongly predicted by the patterns of recurrence, and the recurrence pattern can be predicted with a simple model. This can also be extended to create a scoring system that estimates expected survival.
Authors: Jason W Denbo; Suguru Yamashita; Guillaume Passot; Michael Egger; Yun S Chun; Scott E Kopetz; Dipen Maru; Kristoffer Watten Brudvik; Steven H Wei; Claudius Conrad; Jean-Nicolas Vauthey; Thomas A Aloia Journal: J Gastrointest Surg Date: 2016-06-22 Impact factor: 3.452
Authors: Alyson L Mahar; Carolyn Compton; Susan Halabi; Kenneth R Hess; Martin R Weiser; Patti A Groome Journal: J Surg Oncol Date: 2017-08-02 Impact factor: 3.454
Authors: K Homayounfar; A Bleckmann; L C Conradi; T Sprenger; T Lorf; M Niessner; C O Sahlmann; J Meller; T Liersch; B M Ghadimi Journal: Int J Colorectal Dis Date: 2013-02-01 Impact factor: 2.571