Skip to main content
Top

05-07-2018 | Rheumatoid arthritis | Article

Perspectives of patients, first-degree relatives and rheumatologists on preventive treatments for rheumatoid arthritis: a qualitative analysis

Journal: BMC Rheumatology

Authors: Sarah Munro, Luke Spooner, Katherine Milbers, Marie Hudson, Cheryl Koehn, Mark Harrison

Publisher: BioMed Central

Abstract

Background

There is growing evidence that it may be possible to identify people at high risk of developing rheumatoid arthritis (RA). Assuming that effective interventions were available, this could mean that treatments introduced in the pre-symptomatic phase could prevent or delay the onset of the disease. Our study aimed to identify the potential attributes involved in decision-making around whether or not to take preventive treatment for RA, in order to inform the development of a discrete choice experiment (DCE) to ascertain consumer preferences for a preventive treatment program for RA.

Methods

We conducted a focus group study to develop conceptual attributes, refine their meaning, and develop levels. Participants included RA patients, first-degree relatives of RA patients, and rheumatologists who were 18 years of age and over, could read and speak English, and could provide informed consent. Candidate attributes were refined through iterative rounds of data collection and analysis. All focus groups were audio-recorded and transcribed, and then analyzed using the Framework Method to identify, compare, and contrast key conceptual attributes.

Results

Attributes identified from analysis included: accuracy of the test, certainty in estimates, method of administration, risk of RA and risk of reduction with treatment, risk and seriousness of side effects, person recommending the test, and opinion of the health care professional. Patients with RA, first-degree relatives of patients, and rheumatologists all valued the accuracy of testing due to concerns about false positives, and valued certainty in estimates of the test and preventive treatment. Patients and first-degree relatives desired this evidence from a range of sources, including discussions with people with the disease and health care professionals, and their preferences were modified by the strength of recommendation from their health care professional.

Conclusions

The role of the person who recommends a test and the opinion of a health care professional are novel potential attributes involved in decisions around whether or not to take preventive treatment for RA, that have not been included in previous DCEs.
Literature
1.
Hemminki K, Li X, Sundquist J, Sundquist K. Familial associations of rheumatoid arthritis with autoimmune diseases and related conditions. Arthritis & Rheumatism. 2009;60(3):661–8.CrossRef
2.
Linos A, Worthington JW, O’Fallon M, Kurland LT. The epidemiology of rheumatoid arthritis in Rochester Minnesota: a study of incidence, prevalence, and Mortality. American Journal of Epidemiology. 1980;111(1):87–98.CrossRefPubMed
3.
Kvien TK, Uhlig T, Ødegard S, Heiberg MS. Epidemiological aspects of rheumatoid arthritis. Ann N Y Acad Sci. 2006;1069(1):212–22.CrossRefPubMed
4.
Humphreys JH, Verstappen SMM, Hyrich KL, Chipping JR, Marshall T, Symmons DPM. The incidence of rheumatoid arthritis in the UK: comparisons using the 2010 ACR/EULAR classification criteria and the 1987 ACR classification criteria. Results from the Norfolk arthritis register. Ann Rheum Dis. 2013;72(8):1315.CrossRefPubMed
5.
Costenbader KH, Feskanich D, Mandl LA, Karlson EW. Smoking intensity, duration, and cessation, and the risk of rheumatoid arthritis in women. Am J Med. 2006;119(6):503.e1–9.
6.
Källberg H, Ding B, Padyukov L, Bengtsson C, Rönnelid J, Klareskog L, et al. Smoking is a major preventable risk factor for rheumatoid arthritis estimations of risks after various exposures to cigarette smoke. Ann Rheum Dis. 2011;70(3):508–11.CrossRefPubMed
7.
Deane KD, O’Donnell CI, Hueber W, Majka DS, Lazar AA, Derber LA, et al. The number of elevated cytokines and chemokines in preclinical seropositive rheumatoid arthritis predicts time to diagnosis in an age-dependent manner. Arthritis Rheum. 2010;62(11):3161–72.CrossRefPubMedPubMedCentral
8.
Karlson EW, van Schaardenburg D, van der Helm-van Mil AH. Strategies to predict rheumatoid arthritis development in at-risk populations. Rheumatology. 2016;55(1):6–15.CrossRefPubMed
9.
Nielen MMJ, van Schaardenburg D, Reesink HW, Twisk JWR, van de Stadt RJ, van der Horst-Bruinsma IE, et al. Simultaneous development of acute phase response and autoantibodies in preclinical rheumatoid arthritis. Ann Rheum Dis. 2006;65(4):535.CrossRefPubMed
10.
Demoruelle MK, Deane KD. Treatment strategies in early rheumatoid arthritis and prevention of rheumatoid arthritis. Curr Rheumatol Rep. 2012;14(5):472–80.CrossRefPubMedPubMedCentral
11.
Nielen MMJ, van Schaardenburg D, Reesink HW, van de Stadt RJ, van der Horst-Bruinsma IE, de Koning MHMT, et al. Specific autoantibodies precede the symptoms of rheumatoid arthritis: a study of serial measurements in blood donors. Arthritis Rheum. 2004;50(2):380–6.CrossRefPubMed
12.
Sokolove J, Bromberg R, Deane KD, Lahey LJ, Derber LA, Chandra PE, et al. Autoantibody epitope spreading in the pre-clinical phase predicts progression to rheumatoid arthritis. PLoS ONE. 2012;7(5):e35296. Matloubian M, editorCrossRefPubMedPubMedCentral
13.
van Nies JAB, Krabben A, Schoones JW, TWJ H, Kloppenburg M, van der H Mil AHM. What is the evidence for the presence of a therapeutic window of opportunity in rheumatoid arthritis? A systematic literature review. Ann. Rheum. Dis. 2014;73(5):861–70.CrossRefPubMed
14.
Visser H, le Cessie S, Vos K, Breedveld FC, Hazes JMW. How to diagnose rheumatoid arthritis early: a prediction model for persistent (erosive) arthritis. Arthritis & Rheumatism. 2002;46(2):357–65.CrossRef
15.
Finckh A, Escher M, Liang MH, Bansback N. Preventive treatments for rheumatoid arthritis: issues regarding patient preferences. Curr Rheumatol Rep. 2016;18(8):51.CrossRefPubMed
16.
Falahee M, Simons G, Raza K, Stack RJ. Healthcare professionals’ perceptions of risk in the context of genetic testing for the prediction of chronic disease: a qualitative metasynthesis. J. Risk Res. 2018;21(2):129–66.CrossRef
17.
Bayliss K, Raza K, Simons G, Falahee M, Hansson M, Starling B, et al. Perceptions of predictive testing for those at risk of developing a chronic inflammatory disease: a meta-synthesis of qualitative studies. Journal of Risk Research. 2018;21(2):167–89.CrossRef
18.
Stack RJ, Stoffer M, Englbrecht M, Mosor E, Falahee M, Simons G, et al. Perceptions of risk and predictive testing held by the first-degree relatives of patients with rheumatoid arthritis in England, Austria and Germany: a qualitative study. BMJ Open. 2016;6(6):e010555.CrossRefPubMedPubMedCentral
19.
Falahee M, Simons G, Buckley CD, Hansson M, Stack RJ, Raza K. Patients’ perceptions of their relatives’ risk of developing rheumatoid arthritis and of the potential for risk communication, prediction, and modulation. Arthritis Care Res (Hoboken). 2017;69(10):1558–65.CrossRef
20.
Louviere J, Hensher D, Swait J. Stated choice Methods : analysis and applications. Cambridge: Cambridge University Press; 2000.
21.
Street DJ, Burgess L, Viney R, Louviere J. Designing Discrete Choice Experiments for Health Care. In: Ryan PM, M.Sc RKG, Amaya-Amaya RFM, editors. Using Discrete Choice Experiments to Value Health and Health Care. Dordrecht: Springer Netherlands; 2008. p. 47–72. (The Economics of Non-Market Goods and Resources).
22.
de Bekker-Grob EW, Ryan M, Gerard K. Discrete choice experiments in health economics: a review of the literature. Health Econ. 2012;21(2):145–72.CrossRefPubMed
23.
Clark MD, Determann D, Petrou S, Moro D, de Bekker-Grob EW. Discrete choice experiments in health economics: a review of the literature. PharmacoEconomics. 2014;32(9):883–902.CrossRefPubMed
24.
Ryan M, Gerard K, Amaya-Amaya M. Using discrete choice experiments to value health and health care. Dordrecht: Springer; 2008.
25.
Coast J, Al-Janabi H, Sutton EJ, Horrocks SA, Vosper AJ, Swancutt DR, et al. Using qualitative methods for attribute development for discrete choice experiments: issues and recommendations. Health Econ. 2012;21(6):730–41.CrossRefPubMed
26.
Augustovski F, Beratarrechea A, Irazola V, Rubinstein F, Tesolin P, Gonzalez J, et al. Patient preferences for biologic agents in rheumatoid arthritis: a discrete-choice experiment. Value Health. 2013;16(2):385–93.CrossRefPubMed
27.
Harrison M, Marra C, Shojania K, Bansback N. Societal preferences for rheumatoid arthritis treatments: evidence from a discrete choice experiment. Rheumatology. 2015;54(10):1816–25.CrossRefPubMed
28.
Gale NK, Heath G, Cameron E, Rashid S, Redwood S. Using the framework method for the analysis of qualitative data in multi-disciplinary health research. BMC Med Res Methodol. 2013;13(1):117.CrossRefPubMedPubMedCentral
29.
Leech NL, Onwuegbuzie AJ. An Array of qualitative data analysis tools: a call for data analysis triangulation. Sch Psychol Q. 2007;22(4):557–84.CrossRef
30.
Poulos C, Hauber AB, González JM, Turpcu A. Patients’ willingness to trade off between the duration and frequency of rheumatoid arthritis treatments. Arthritis Care Res. 2014;66(7):1008–15.CrossRef
31.
Kuijper TM, Folmer R, Stolk EA, Hazes JMW, Luime JJ. Doctors’ preferences in de-escalating DMARDs in rheumatoid arthritis: a discrete choice experiment. Arthritis Res. Ther. 2017;19(1):78.CrossRefPubMedPubMedCentral
32.
Novotny F, Haeny S, Hudelson P, Escher M, Finckh A. Primary prevention of rheumatoid arthritis: a qualitative study in a high-risk population. Joint Bone Spine. 2013;80(6):673–4.CrossRefPubMed
33.
Makoul G, Clayman ML. An integrative model of shared decision making in medical encounters. Patient Educ Couns. 2006;60(3):301–12.CrossRefPubMed
34.
Vass C, Rigby D, Payne K. The role of qualitative research methods in discrete choice experiments: a systematic review and survey of authors. Med Decis Mak. 2017;37(3):298–313.CrossRef
35.
Helter TM, Boehler CEH. Developing attributes for discrete choice experiments in health: a systematic literature review and case study of alcohol misuse interventions. J Subst Use. 2016;21(6):662–8.CrossRefPubMedPubMedCentral
36.
Vosper J, Coast J, Flynn T. Qualitative methods in discrete choice experiments: Two case studies. In: Coast J, editor. Qualitative methods for health economics. London: Rowman & Littlefield; 2017. p. 175–92.
37.
Coast J, Horrocks S. Developing attributes and levels for discrete choice experiments using qualitative methods. J. Health Serv. Res. Policy. 2007;12(1):25–30.CrossRefPubMed
38.
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. 2016;55(11):1959–68.CrossRefPubMed
39.
Saunders B, Sim J, Kingstone T, Baker S, Waterfield J, Bartlam B, et al. Saturation in qualitative research: exploring its conceptualization and operationalization. Qual Quant. 2017;52(4):1–15.