Patient preferences for maintenance therapy in Crohn’s disease: A discrete-choice experiment

Autoři: Glen S. Hazlewood aff001;  Gyanendra Pokharel aff002;  Robert Deardon aff002;  Deborah A. Marshall aff001;  Claire Bombardier aff004;  George Tomlinson aff004;  Christopher Ma aff006;  Cynthia H. Seow aff001;  Remo Panaccione aff006;  Gilaad G. Kaplan aff001
Působiště autorů: Department of Medicine and Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada aff001;  Department of Mathematics and Statistics, University of Calgary, Calgary, Alberta, Canada aff002;  Department of Production of Animal Health, Faculty of Veterinary Medicine, University of Calgary, Calgary, Alberta, Canada aff003;  Department of Medicine and Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, Ontario, Canada aff004;  Toronto General Research Institute, University Health Network, Toronto, Ontario, Canada aff005;  Inflammatory Bowel Disease Unit, Division of Gastroenterology and Hepatology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada aff006
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
doi: 10.1371/journal.pone.0227635



To quantify patient preferences for maintenance therapy of Crohn’s disease and understand the impact on treatment selection.


We conducted a discrete-choice experiment in patients with Crohn’s disease (n = 155) to measure the importance of attributes relevant to choosing between different medical therapies for maintenance of Crohn’s disease. The attributes included efficacy and withdrawals due to adverse events, as well as dosing and other rare risks of treatment. From the discrete-choice experiment we estimated the part-worth (importance) of each attribute level, and explored preference heterogeneity through latent class analysis. We then used the part-worths to apply weights across each outcome from a prior network meta-analysis to estimate patients’ preferred treatment in pairwise comparisons and for the overall group of treatments.


The discrete-choice experiment revealed that maintaining remission was the most important attribute. Patients would accept a rare risk of infection or cancer for a 14% absolute increased chance of remission. Latent class analysis demonstrated that 45% of the cohort was risk averse, either to adverse events or requiring a course of prednisone. When these preferences were used in modelling studies to compare pairs of treatments, there was a ≥ 78% probability that all biologic treatments were preferred to azathioprine and methotrexate, based on the balance of benefits and harms. When comparing all treatments, adalimumab was preferred by 53% of patients, who were motivated by efficacy, and vedolizumab was preferred by 30% who were driven by the preference to avoid risks. However, amongst biologic treatment options, there was considerable uncertainty regarding the preferred treatment at the individual patient level.


Patients with Crohn’s disease from our population were, on average, focused on the benefits of treatment, supporting intensive treatment approaches aimed at maintaining remission. Important preference heterogeneity was identified, however, highlighting the importance of shared decision making when selecting treatments.

Klíčová slova:

Adverse events – Blood counts – Cancer treatment – Crohn's disease – Gastroenterology and hepatology – Methotrexate – Network analysis – Toxicity


1. Coward S, Clement F, Benchimol EI, Bernstein CN, Avina-Zubieta JA, Bitton A, et al. Past and Future Burden of Inflammatory Bowel Diseases Based on Modeling of Population-Based Data. Gastroenterology. 2019;156(5):1345–53 e4. Epub 2019/01/15. doi: 10.1053/j.gastro.2019.01.002 30639677.

2. Ng SC, Shi HY, Hamidi N, Underwood FE, Tang W, Benchimol EI, et al. Worldwide incidence and prevalence of inflammatory bowel disease in the 21st century: a systematic review of population-based studies. Lancet. 2018;390(10114):2769–78. Epub 2017/10/21. doi: 10.1016/S0140-6736(17)32448-0 29050646.

3. Kaplan GG. The global burden of IBD: from 2015 to 2025. Nat Rev Gastroenterol Hepatol. 2015;12(12):720–7. Epub 2015/09/02. doi: 10.1038/nrgastro.2015.150 26323879.

4. Molodecky NA, Soon IS, Rabi DM, Ghali WA, Ferris M, Chernoff G, et al. Increasing incidence and prevalence of the inflammatory bowel diseases with time, based on systematic review. Gastroenterology. 2012;142(1):46–54 e42; quiz e30. Epub 2011/10/18. doi: 10.1053/j.gastro.2011.10.001 22001864.

5. Peyrin-Biroulet L, Sandborn W, Sands BE, Reinisch W, Bemelman W, Bryant RV, et al. Selecting Therapeutic Targets in Inflammatory Bowel Disease (STRIDE): Determining Therapeutic Goals for Treat-to-Target. Am J Gastroenterol. 2015;110(9):1324–38. Epub 2015/08/26. doi: 10.1038/ajg.2015.233 26303131.

6. Singh S, Fumery M, Sandborn WJ, Murad MH. Systematic review and network meta-analysis: first- and second-line biologic therapies for moderate-severe Crohn's disease. Aliment Pharmacol Ther. 2018. Epub 2018/06/20. doi: 10.1111/apt.14852 29920733.

7. Bewtra M, Fairchild AO, Gilroy E, Leiman DA, Kerner C, Johnson FR, et al. Inflammatory Bowel Disease Patients' Willingness to Accept Medication Risk to Avoid Future Disease Relapse. Am J Gastroenterol. 2015;110(12):1675–81. Epub 2015/10/21. doi: 10.1038/ajg.2015.321 26482859.

8. Hazlewood GS. Measuring Patient Preferences: An Overview of Methods with a Focus on Discrete Choice Experiments. Rheum Dis Clin North Am. 2018;44(2):337–47. Epub 2018/04/07. doi: 10.1016/j.rdc.2018.01.009 29622300.

9. Bridges JF, Hauber AB, Marshall D, Lloyd A, Prosser LA, Regier DA, et al. Conjoint Analysis Applications in Health-a Checklist: A Report of the ISPOR Good Research Practices for Conjoint Analysis Task Force. Value Health. 2011;14(4):403–13. Epub 2011/06/15. doi: 10.1016/j.jval.2010.11.013 21669364.

10. Hazlewood GS, Rezaie A, Borman M, Panaccione R, Ghosh S, Seow CH, et al. Comparative effectiveness of immunosuppressants and biologics for inducing and maintaining remission in Crohn's disease: a network meta-analysis. Gastroenterology. 2015;148(2):344–54 e5; quiz e14-5. doi: 10.1053/j.gastro.2014.10.011 25448924.

11. Hazlewood GS, Bombardier C, Tomlinson G, Thorne C, Bykerk VP, Thompson A, et al. Treatment preferences of patients with early rheumatoid arthritis: a discrete-choice experiment. Rheumatology (Oxford). 2016;55(11):1959–68. doi: 10.1093/rheumatology/kew280 27477807.

12. Lighthouse Studio v9.0 (Formerly SSIWeb). Orem, Utah: Sawtooth Software, Inc.; 2016. Available from:

13. Lennard-Jones JE. Classification of inflammatory bowel disease. Scand J Gastroenterol Suppl. 1989;170:2–6; discussion 16–9. Epub 1989/01/01. doi: 10.3109/00365528909091339 2617184.

14. Hazlewood GS, Bombardier C, Tomlinson G, Marshall D. A Bayesian model that jointly considers comparative effectiveness research and patients' preferences may help inform GRADE recommendations: an application to rheumatoid arthritis treatment recommendations. J Clin Epidemiol. 2018;93:56–65. doi: 10.1016/j.jclinepi.2017.10.003 29051108.

15. Johnson FR, Yang JC, Reed SD. The Internal Validity of Discrete Choice Experiment Data: A Testing Tool for Quantitative Assessments. Value Health. 2019;22(2):157–60. Epub 2019/02/04. doi: 10.1016/j.jval.2018.07.876 30711059.

16. Brooks S, Gelman A. General Methods for Monitoring Convergence of Iterative Simulations. J Comput Graph Stat. 1998;7(4):434–55.

17. CENTOCOR INC. Remicade (infliximab) [package insert]. Revised June 2018 Nov 21, 2019. Available from:

18. Abbvie Inc. Humira (adalimumab) [package insert]. Nov 21, 2019; (Revised June 2018). Available from:

19. Quezada SM, McLean LP, Cross RK. Adverse events in IBD therapy: the 2018 update. Expert Rev Gastroenterol Hepatol. 2018;12(12):1183–91. Epub 2019/02/23. doi: 10.1080/17474124.2018.1545574 30791788.

20. Moran GW, Dubeau MF, Kaplan GG, Yang H, Seow CH, Fedorak RN, et al. Phenotypic features of Crohn's disease associated with failure of medical treatment. Clin Gastroenterol Hepatol. 2014;12(3):434–42 e1. Epub 2013/08/28. doi: 10.1016/j.cgh.2013.08.026 23978351.

21. Elwyn G, Lloyd A, Joseph-Williams N, Cording E, Thomson R, Durand MA, et al. Option Grids: shared decision making made easier. Patient Educ Couns. 2013;90(2):207–12. Epub 2012/08/03. doi: 10.1016/j.pec.2012.06.036 22854227.

22. Casellas F, Herrera-de Guise C, Robles V, Navarro E, Borruel N. Patient preferences for inflammatory bowel disease treatment objectives. Dig Liver Dis. 2017;49(2):152–6. Epub 2016/10/09. doi: 10.1016/j.dld.2016.09.009 27717791.

23. Bewtra M, Johnson FR. Assessing patient preferences for treatment options and process of care in inflammatory bowel disease: a critical review of quantitative data. Patient. 2013;6(4):241–55. Epub 2013/10/16. doi: 10.1007/s40271-013-0031-2 24127239; PubMed Central PMCID: PMC3865778.

24. Johnson FR, Hauber B, Ozdemir S, Siegel CA, Hass S, Sands BE. Are gastroenterologists less tolerant of treatment risks than patients? Benefit-risk preferences in Crohn's disease management. J Manag Care Pharm. 2010;16(8):616–28. Epub 2010/09/28. doi: 10.18553/jmcp.2010.16.8.616 20866166.

25. Almario CV, Keller MS, Chen M, Lasch K, Ursos L, Shklovskaya J, et al. Optimizing Selection of Biologics in Inflammatory Bowel Disease: Development of an Online Patient Decision Aid Using Conjoint Analysis. Am J Gastroenterol. 2018;113(1):58–71. Epub 2017/12/06. doi: 10.1038/ajg.2017.470 29206816.

26. Scott FI, Johnson FR, Bewtra M, Brensinger CM, Roy JA, Reed SD, et al. Improved Quality of Life With Anti-TNF Therapy Compared With Continued Corticosteroid Utilization in Crohn's Disease. Inflamm Bowel Dis. 2019;25(5):925–36. Epub 2018/12/12. doi: 10.1093/ibd/izy321 30535149.

27. Bewtra M, Reed SD, Johnson FR, Scott FI, Gilroy E, Sandler RS, et al. Variation Among Patients With Crohn's Disease in Benefit vs Risk Preferences and Remission Time Equivalents. Clin Gastroenterol Hepatol. 2019. Epub 2019/05/18. doi: 10.1016/j.cgh.2019.05.010 31100456.

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2020 Číslo 1