Screening for Pancreatic Adenocarcinoma in BRCA2 Mutation Carriers: Results of a Disease Simulation Model

Abstract

Background: BRCA2 mutation carriers are at increased risk for multiple cancers including pancreatic adenocarcinoma (PAC). Our goal was to compare the effectiveness of different PAC screening strategies in BRCA2 mutation carriers, from the standpoint of life expectancy. Methods: A previously published Markov model of PAC was updated and extended to incorporate key aspects of BRCA2 mutation carrier status, including competing risks of breast- and ovarian-cancer specific mortality. BRCA2 mutation carriers were modeled and analyzed as the primary cohort for the analysis. Additional higher risk BRCA2 cohorts that were stratified according to the number of first-degree relatives (FDRs) with PAC were also analyzed. For each cohort, one-time screening and annual screening were evaluated, with screening starting at age 50 in both strategies. The primary outcome was net gain in life expectancy (LE) compared to no screening. Sensitivity analysis was performed on key model parameters, including surgical mortality and MRI test performance. Findings: One-time screening at age 50 resulted in a LE gain of 3.9 days for the primary BRCA2 cohort, and a gain of 5.8 days for those with BRCA2 and one FDR. Annual screening resulted in LE loss of 12.9 days for the primary cohort and 1.3 days for BRCA2 carriers with 1 FDR, but resulted in 20.6 days gained for carriers with 2 FDRs and 260 days gained for those with 3 FDRs. For patients with ≥3 FDRs, annual screening starting at an earlier age (i.e. 35–40) was optimal. Interpretation: Among BRCA2 mutation carriers, aggressive screening regimens may be ineffective unless additional indicators of elevated risk (e.g., 2 or more FDRs) are present. More clinical studies are needed to confirm these findings. Funding: American Cancer Society – New England Division – Ellison Foundation Research Scholar Grant (RSG-15-129-01-CPHPS).

Keywords

• Pancreatic cancer
• BRCA2 mutation
• Cancer screening
• Simulation disease modeling