4.5 Article

Cost-Effectiveness of Colorectal Cancer Screening in High-Risk Spanish Patients: Use of a Validated Model to Inform Public Policy

Journal

CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION
Volume 19, Issue 11, Pages 2765-2776

Publisher

AMER ASSOC CANCER RESEARCH
DOI: 10.1158/1055-9965.EPI-10-0530

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Funding

  1. NIH [R01 CA101849-01A1]
  2. Government of Aragon, Spain

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Background: The European Community has made a commitment to colorectal cancer (CRC) screening, but regional considerations may affect the design of national screening programs. We developed a decision analytic model tailored to a pilot screening program for high-risk persons in Spain with the aim of informing public policy decisions. Materials and Methods: We constructed a decision analytic Markov model based on our validated model of CRC screening that reflected CRC epidemiology and costs in persons with first-degree relatives with CRC in Aragon, Spain, and superimposed colonoscopy every 5 or 10 years from ages 40 to 80 years. The pilot program's preliminary clinical results and our modeling results were presented to regional health authorities. Results: In the model, without screening, 88 CRC cases occurred per 1,000 persons from age 40 to 85 years. In the base case, screening reduced this by 72% to 77% and gained 0.12 discounted life years per person. Screening every 10 years was cost saving, and screening every 5 years versus every 10 years cost 7,250 euros per life year gained. Based on these savings, 36 to 39 euros per person per year could go toward operating costs while maintaining a neutral budget. If screening costs doubled, screening remained highly cost-effective but no longer cost saving. These results contributed to the health authorities' decision to expand the pilot program to the entire region in 2009. Conclusions: Colonoscopic screening of first-degree relatives of persons with CRC may be cost saving in public systems like that of Spain. Decision analytic modeling tailored to regional considerations can inform public policy decisions. Impact: Tailored decision analytic modeling can inform regional policy decisions on cancer screening. Cancer Epidemiol Biomarkers Prev; 19(11); 2765-76. (C)2010 AACR.

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