Optimal management of colorectal liver metastases in older patients: a decision analysis. Issue 11 (24th June 2014)

• Record Type: Journal Article
• Authors: Yang, Simon; Alibhai, Shabbir M.H.; Kennedy, Erin D.; El‐Sedfy, Abraham; Dixon, Matthew; Coburn, Natalie; Kiss, Alex; Law, Calvin H.L.
• Is Part Of: HPB. Volume 16:Issue 11(2014:Nov.)
• Page Start: 1031
• Page End: 1042
• Publication Date: 2014-06-24
• Subjects: Liver -- Diseases -- Periodicals; Biliary tract -- Diseases -- Periodicals; Pancreas -- Diseases -- Periodicals; 616.362005
• DOI: 10.1111/hpb.12292
• Languages: English
• ISSNs: 1365-182X

Abstract

Abstract: Background: Comparative trials evaluating management strategies for colorectal cancer liver metastases (CLM) are lacking, especially for older patients. This study developed a decision‐analytic model to quantify outcomes associated with treatment strategies for CLM in older patients. Methods: A Markov‐decision model was built to examine the effect on life expectancy (LE) and quality‐adjusted life expectancy (QALE) for best supportive care (BSC), systemic chemotherapy (SC), radiofrequency ablation (RFA) and hepatic resection (HR). The baseline patient cohort assumptions included healthy 70‐year‐old CLM patients after a primary cancer resection. Event and transition probabilities and utilities were derived from a literature review. Deterministic and probabilistic sensitivity analyses were performed on all study parameters. Results: In base case analysis, BSC, SC, RFA and HR yielded LEs of 11.9, 23.1, 34.8 and 37.0 months, and QALEs of 7.8, 13.2, 22.0 and 25.0 months, respectively. Model results were sensitive to age, comorbidity, length of model simulation and utility after HR. Probabilistic sensitivity analysis showed increasing preference for RFA over HR with increasing patient age. Conclusions: HR may be optimal for healthy 70‐year‐old patients with CLM. In older patients with comorbidities, RFA may provide better LE and QALE. Treatment decisions in older cancer patients should account for patient age, comorbidities, local expertise and individual values.