Andrew Piscitello1, Leila Saoud2, A Mark Fendrick3, Bijan J Borah4, Kristen Hassmiller Lich5, Michael Matney2, A Burak Ozbay2, Marcus Parton2, Paul J Limburg6. 1. EmpiriQA, LLC, Long Grove, IL, United States of America. 2. Exact Sciences Corporation, Madison, WI, United States of America. 3. Division of Gastroenterology, University of Michigan, Ann Arbor, MI, United States of America. 4. Department of Health Services Research, Mayo Clinic, Rochester, MN, United States of America. 5. Department of Health Policy & Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America. 6. Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, United States of America.
Abstract
BACKGROUND: Real-world adherence to colorectal cancer (CRC) screening strategies is imperfect. The CRC-AIM microsimulation model was used to estimate the impact of imperfect adherence on the relative benefits and burdens of guideline-endorsed, stool-based screening strategies. METHODS: Predicted outcomes of multi-target stool DNA (mt-sDNA), fecal immunochemical tests (FIT), and high-sensitivity guaiac-based fecal occult blood tests (HSgFOBT) were simulated for 40-year-olds free of diagnosed CRC. For robustness, imperfect adherence was incorporated in multiple ways and with extensive sensitivity analysis. Analysis 1 assumed adherence from 0%-100%, in 10% increments. Analysis 2 longitudinally applied real-world first-round differential adherence rates (base-case imperfect rates = 40% annual FIT vs 34% annual HSgFOBT vs 70% triennial mt-sDNA). Analysis 3 randomly assigned individuals to receive 1, 5, or 9 lifetime (9 = 100% adherence) mt-sDNA tests and 1, 5, or 9 to 26 (26 = 100% adherence) FIT tests. Outcomes are reported per 1000 individuals compared with no screening. RESULTS: Each screening strategy decreased CRC incidence and mortality versus no screening. In individuals screened between ages 50-75 and adherence ranging from 10%a-100%, the life-years gained (LYG) for triennial mt-sDNA ranged from 133.1-300.0, for annual FIT from 96.3-318.1, and for annual HSgFOBT from 99.8-320.6. At base-case imperfect adherence rates, mt-sDNA resulted in 19.1% more LYG versus FIT, 25.4% more LYG versus HSgFOBT, and generally had preferable efficiency ratios while offering the most LYG. Completion of at least 21 FIT tests is needed to reach approximately the same LYG achieved with 9 mt-sDNA tests. CONCLUSIONS: Adherence assumptions affect the conclusions of CRC screening microsimulations that are used to inform CRC screening guidelines. LYG from FIT and HSgFOBT are more sensitive to changes in adherence assumptions than mt-sDNA because they require more tests be completed for equivalent benefit. At imperfect adherence rates, mt-sDNA provides more LYG than FIT or HSgFOBT at an acceptable tradeoff in screening burden.
RCT Entities:
BACKGROUND: Real-world adherence to colorectal cancer (CRC) screening strategies is imperfect. The CRC-AIM microsimulation model was used to estimate the impact of imperfect adherence on the relative benefits and burdens of guideline-endorsed, stool-based screening strategies. METHODS: Predicted outcomes of multi-target stool DNA (mt-sDNA), fecal immunochemical tests (FIT), and high-sensitivity guaiac-based fecal occult blood tests (HSgFOBT) were simulated for 40-year-olds free of diagnosed CRC. For robustness, imperfect adherence was incorporated in multiple ways and with extensive sensitivity analysis. Analysis 1 assumed adherence from 0%-100%, in 10% increments. Analysis 2 longitudinally applied real-world first-round differential adherence rates (base-case imperfect rates = 40% annual FIT vs 34% annual HSgFOBT vs 70% triennial mt-sDNA). Analysis 3 randomly assigned individuals to receive 1, 5, or 9 lifetime (9 = 100% adherence) mt-sDNA tests and 1, 5, or 9 to 26 (26 = 100% adherence) FIT tests. Outcomes are reported per 1000 individuals compared with no screening. RESULTS: Each screening strategy decreased CRC incidence and mortality versus no screening. In individuals screened between ages 50-75 and adherence ranging from 10%a-100%, the life-years gained (LYG) for triennial mt-sDNA ranged from 133.1-300.0, for annual FIT from 96.3-318.1, and for annual HSgFOBT from 99.8-320.6. At base-case imperfect adherence rates, mt-sDNA resulted in 19.1% more LYG versus FIT, 25.4% more LYG versus HSgFOBT, and generally had preferable efficiency ratios while offering the most LYG. Completion of at least 21 FIT tests is needed to reach approximately the same LYG achieved with 9 mt-sDNA tests. CONCLUSIONS: Adherence assumptions affect the conclusions of CRC screening microsimulations that are used to inform CRC screening guidelines. LYG from FIT and HSgFOBT are more sensitive to changes in adherence assumptions than mt-sDNA because they require more tests be completed for equivalent benefit. At imperfect adherence rates, mt-sDNA provides more LYG than FIT or HSgFOBT at an acceptable tradeoff in screening burden.
Authors: Douglas K Rex; Prasanna L Ponugoti; Cynthia S Johnson; Lisa Kittner; Randy J Yanda Journal: Gastrointest Endosc Date: 2017-05-04 Impact factor: 9.427
Authors: Amy B Knudsen; Ann G Zauber; Carolyn M Rutter; Steffie K Naber; V Paul Doria-Rose; Chester Pabiniak; Colden Johanson; Sara E Fischer; Iris Lansdorp-Vogelaar; Karen M Kuntz Journal: JAMA Date: 2016-06-21 Impact factor: 56.272
Authors: Ann G Zauber; Iris Lansdorp-Vogelaar; Amy B Knudsen; Janneke Wilschut; Marjolein van Ballegooijen; Karen M Kuntz Journal: Ann Intern Med Date: 2008-10-06 Impact factor: 25.391
Authors: L Hol; M E van Leerdam; M van Ballegooijen; A J van Vuuren; H van Dekken; J C I Y Reijerink; A C M van der Togt; J D F Habbema; E J Kuipers Journal: Gut Date: 2010-01 Impact factor: 23.059
Authors: Emily Weiser; Philip D Parks; Rebecca K Swartz; Jack Van Thomme; Philip T Lavin; Paul Limburg; Barry M Berger Journal: J Med Screen Date: 2020-02-13 Impact factor: 2.136
Authors: Marjolein J E Greuter; Johannes Berkhof; Karen Canfell; Jie-Bin Lew; Evelien Dekker; Veerle M H Coupé Journal: BMC Public Health Date: 2016-09-22 Impact factor: 3.295