Hepatic resection for noncolorectal nonendocrine liver metastases: Analysis of 1452 patients and development of a prognostic model

OBJECTIVE: To determine the utility of hepatic resection (HR) in the treatment of patients with noncolorectal nonendocrine liver metastases (NCNELM). SUMMARY BACKGROUND DATA: The place of HR in the treatment of NCNELM remains controversial, primarily due to the limitations of previously published reports and the heterogeneity of primary tumor sites and histologies. METHODS: A multivariate risk model was developed by analyzing prognostic factors and long-term outcomes in 1452 patients with NCNELM treated with HR at 41 centers from 1983 to 2004. RESULTS: Hepatic metastases were solitary in 56% and unilateral in 71% (mean diameter, 50.5 mm). Extrahepatic metastases were present in 22%. The most common primary sites were breast (32%), gastrointestinal (16%), and urologic (14%). The most common histologies were adenocarcinoma (60%), GIST/sarcoma (13.5%), and melanoma (13%). R0 resection was achieved in 83% of patients with a 60-day mortality rate of 2.3% and a major complication rate of 21.5%. Tumor recurred in 67% of patients (liver, 24%; extrahepatic, 18%; both, 25%). Overall and disease-free survivals at 5 years were 36% and 21% and at 10 years were 23% and 15%, respectively. In multivariate analysis, factors associated with poor prognosis were patient age >60 years, nonbreast origin, melanoma or squamous histology, disease-free interval <12 months, extrahepatic metastases, R2 resection, and major hepatectomy (all P ≤ 0.02). A prognostic model based on these factors effectively stratified patients into low-risk (0-3 points, 46% 5-year survival), mid-risk (4-6 points, 33% 5-year survival), and high-risk (>6 points, <10% 5-year survival) groups (P = 0.0001). DISCUSSION: HR for NCNELM is safe and effective, with outcomes mainly dependent on primary tumor site and histology. For individual patients, a statistical model based on key prognostic factors could validate the indication for hepatic resection by predicting long-term survivals.