Objective: To identify risk factors associated with cancer-specific survival and develop a predictive model for patients undergoing primary hepatic resection for metastatic colorectal cancer.
Background: No published studies investigated collectively the inter-relation of factors related to patient cancer-specific survival after hepatectomy for metastatic colorectal cancer.
Methods: Clinical, pathologic, and complete follow-up data were prospectively collected from 929 consecutive patients undergoing primary (n = 925) or repeat hepatic resection (n = 80) for colorectal liver metastases at a tertiary referral center from 1987 to 2005. Parametric survival analysis was used to identify predictors of cancer-specific survival and develop a predictive model. The model was validated using measures of discrimination and calibration.
Results: Postoperative mortality and morbidity were 1.5% and 25.9%, respectively. 5-year and 10-year cancer-specific survival were 36% and 23%. On multivariate analysis, 7 risk factors were found to be independent predictors of poor survival: number of hepatic metastases >3, node positive primary, poorly differentiated primary, extrahepatic disease, tumor diameter > or =5 cm, carcinoembryonic antigen level >60 ng/mL, and positive resection margin. The first 6 of these criteria were used in a preoperative scoring system and the last 6 in the postoperative setting. Patients with the worst postoperative prognostic criteria had an expected median cancer-specific survival of 0.7 years and a 5-year cancer-specific survival of 2%. Conversely, patients with the best prognostic postoperative criteria had an expected median cancer-specific survival of 7.4 years and a 5-year cancer-specific survival of 64%. When tested both predictive models fitted the data well with no significant differences between observed and predicted outcomes (P > 0.05).
Conclusion: Resection of liver metastases provides good long-term cancer-specific survival benefit, which can be quantified pre- or postoperatively using the criteria described. The "Basingstoke Predictive Index" may be used for risk-stratifying patients who may benefit from intensive surveillance and selection for adjuvant therapy and trials.