Background: Several studies suggest that test characteristics for the fecal immunochemical test (FIT) differ by gender, triggering a debate on whether men and women should be screened differently. We used the microsimulation model MISCAN-Colon to evaluate whether screening stratified by gender is cost-effective. Methods: We estimated gender-specific FIT characteristics based on first-round positivity and detection rates observed in a FIT screening pilot (CORERO-1). Subsequently, we used the model to estimate harms, benefits, and costs of 480 genderspecific FIT screening strategies and compared them with uniform screening. Results: Biennial FIT screening from ages 50 to 75 was less effective in women than men [35.7 vs. 49.0 quality-adjusted life years (QALY) gained, respectively] at higher costs (€42, 161 vs. -€5, 471, respectively). However, the incremental QALYs gained and costs of annual screening compared with biennial screening were more similar for both genders (8.7 QALYs gained and €26, 394 for women vs. 6.7 QALYs gained and €20, 863 for men). Considering all evaluated screening strategies, optimal gender-based screening yielded at most 7% more QALYs gained than optimal uniform screening and even resulted in equal costs and QALYs gained from a willingness- to-pay threshold of €1, 300. Conclusions: FIT screening is less effective in women, but the incremental cost-effectiveness is similar in men and women. Consequently, screening stratified by gender is not more costeffective than uniform FIT screening. Impact: Our conclusions support the current policy of uniform FIT screening. Cancer Epidemiol Biomarkers Prev; 26(8); 1328-36.

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Persistent URL dx.doi.org/10.1158/1055-9965.EPI-16-0786, hdl.handle.net/1765/100943
Journal Cancer Epidemiology, Biomarkers & Prevention
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Citation
van der Meulen, M.P, Kapidzic, A, van Leerdam, M.E, Van Der Steen, A, Kuipers, E.J, Spaander, M.C.W, … Lansdorp-Vogelaar, I. (2017). Do men and women need to be screened differently with fecal immunochemical testing? A cost-effectiveness analysis. Cancer Epidemiology, Biomarkers & Prevention, 26(8), 1328–1336. doi:10.1158/1055-9965.EPI-16-0786