Preferences Toward Attributes of Disease-Modifying Therapies: The Role of Nurses in Multiple Sclerosis Care : Journal of Neuroscience Nursing

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Preferences Toward Attributes of Disease-Modifying Therapies: The Role of Nurses in Multiple Sclerosis Care

del Río-Muñoz, Beatriz; Azanza-Munarriz, Cristina; Becerril-Ríos, Noelia; Goicochea-Briceño, Haydee; Horno, Rosalía; Lendínez-Mesa, Alejandro; Sánchez-Franco, César; Sarmiento, Mònica; Bueno-Gil, Guillermo; Medrano, Nicolás; Maurino, Jorge

Author Information
Journal of Neuroscience Nursing: October 2022 - Volume 54 - Issue 5 - p 220-225
doi: 10.1097/JNN.0000000000000661

Abstract

Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system that mainly affects young people and is associated with physical and cognitive impairment and loss of functional autonomy.1,2 The spectrum of disease-modifying therapies (DMTs) has grown substantially in the last 10 years, allowing for individualized disease management and more ambitious therapeutic goals.3,4 In this context, nurses have an essential role in identifying the perceptions and needs of patients and caregivers at all stages of the disease according to the Neuman system model.5,6 They usually participate in patient education and aspects related to disease care as well as on how treatments are administered, the importance of adherence, and potential side effects.5–11 In addition, their close and frequent interaction with patients gives them the opportunity to detect more subtle symptoms that are often overlooked in follow-up office visits by neurologists.12,13

Although nurses cannot prescribe DMTs, understanding their treatment preferences and priorities may help to improve their role in a complicated treatment landscape with different side effect profiles and safety monitoring needs.3,14 The aim of this study was to assess nurses' preferences toward relapsing-remitting MS treatments according to different attributes of efficacy, safety, and mode of administration.

Methods

This is a multicenter, noninterventional, cross-sectional, Web-based study conducted in collaboration with the Sociedad Española de Enfermería Neurológica. Nurses with experience managing MS patients received an email from the Sociedad Española de Enfermería Neurológica with the invitation to participate in the study. This email included a link to access the study website. This study was approved by the Hospital Universitario Clínico San Carlos (Madrid, Spain) research board. A written informed consent was obtained from all participants.

Conjoint analysis is a well-established and validated approach to assess the value that people allocate to the different characteristics of medical interventions.15,16 Preference elicitation using conjoint analysis has been studied in MS involving different healthcare professionals and patients.17–19

Treatment attributes and levels were originally designed by our research team of 7 nurses specialized in MS after reviewing clinical trials and patient preference research literature.14,19,20 Prevention of disability progression, preservation of cognitive function, route and frequency of administration, and side effect risk and safety monitoring were the 5 attributes selected (Supplemental Digital Content 1, available at https://links.lww.com/JNN/A420). An orthogonal design was applied to design 8 simulated treatment options containing unique combinations of attributes and levels (Supplemental Digital Content 2, available at https://links.lww.com/JNN/A421). Participants ranked treatment options from 1 (most preferred) to 8 (least preferred).

In addition, participants had to answer questions related to sociodemographic and professional practice characteristics, and completed questionnaires to measure nurses' attitude toward the adoption of medical innovations, coping strategies, workplace burnout, and healthcare-related regret.21–24 The Evidence-Based Practice Attitude Scale is a high–psychometric-quality instrument used to measure attitudes toward adopting new treatments, interventions, and practices among healthcare providers.21 It consists of 15 items rated on a 5-point Likert-type scale, ranging from 0 (not at all) to 4 (to a very great extent). Higher scores indicate a more positive attitude toward innovations. The Brief-COPE is a validated 28-item questionnaire designed to measure effective and ineffective ways to cope with a stressful life event.22 Higher scores indicate increased utilization of the specific coping strategy. Occupational burnout was assessed using the 9 items of the emotional exhaustion dimension of the Maslach Burnout Inventory-Human Services Survey.23 A score of 27 or greater indicates high emotional exhaustion. The 10-item Regret Intensity Scale is a validated tool used to assess regret caused by a past event, covering affective, physical, and cognitive aspects.24,25 Higher scores indicate higher regret intensity.

Statistical Analysis

The ordinary least squares method was used to estimate parameters. Results were summarized in terms of utilities (profits), relative (overall), and individual importance assigned to each attribute. The Kendall correlation coefficient between real ranges and those predicted by the model was used to assess the goodness of fit of the model. The relative importance of each factor was obtained by dividing the importance of a factor by the sum of all individual importance scores. A model fits the data well if the differences between the observed values and the predicted values are small and unbiased. The closer the coefficient is to 1, the better the model.

An exploratory k-means cluster analysis based on individual profits to different attributes was used to identify possible profiles of nurses with similar preferences. Differences in sociodemographic and professional practice characteristics as well as behavioral factors were assessed between clusters.

Results

Overall, 331 nurses were invited to participate, 130 initiated the study (39.3%), and 98 completed the study (29.6%). The mean (SD) age was 44.7 (9.8) years, and 91.8% were female. Almost 50% worked at a hospital-based outpatient clinic with a mean (SD) time of experience managing MS of 7.5 (5.4) years. Main demographic and professional practice characteristics are shown in Table 1.

TABLE 1 - Demographic and Professional Practice Characteristics of the Sample
N = 98
Sex Female, n (%) 90 (91.8)
Age, y Mean (SD) 44.7 (9.8)
>40, n (%) 65 (66.3)
Work experience, y As a hospital nurse, mean (SD) 21.1 (9.9)
Managing patients with MS, mean (SD) 7.5 (5.4)
Work setting Outpatient clinic, n (%) 48 (49.0)
IV center, n (%) 33 (33.7)
MS patients managed per week Mean (SD) 23.9 (22.6)
Training and professional activities Participation in MS clinical trials, n (%) 61 (62.2)
Authorship of scientific manuscripts/abstracts in peer-reviewed journals/congresses, n (%) 73 (74.5)
Attendance to MS training activities in the last 2 y, n (%) 89 (90.8)
Abbreviations: IV, intravenous; MS, multiple sclerosis.

Treatment option E was the most chosen by the participants. Nurses prioritized the preservation of cognition (38.6%), followed by preventing disability progression (35.2%) and side effect risk and safety monitoring (13.5%). Similar values were obtained with average importance (Table 2). Preserving cognition and preventing disability progression also were the most preferred attributes according to the utilities scores (Table 2). Overall, mode of administration was the least preferred attribute, although self-administration and administration over longer periods were the most valued in these 2 dimensions. Pearson R and Kendall τ coefficients showed a high correlation: 1000 (P < .001) and 1000 (P < .001), respectively. Estimated utilities were consistent across the sample according to sociodemographic and professional practice characteristics.

TABLE 2 - Utility Scores and Importance Assigned to Each Attribute and Level
Utility Estimation (SE) Importance (Relative) Importance (Averaged)
Cognition
 No cognitive impairment 1.245 (0.040) 38.6% 32.7%
 Cognitive impairment −1.245 (0.040)
Disease progression
 No progression in 2 y 1.133 (0.040) 35.2% 31.7%
 Progression in 2 y −1.133 (0.040)
Safety and nurse monitoring
 Infrequent but severe AE plus monitoring 1–2 times a month −0.434 (0.040) 13.5% 14.2%
 Frequent but mild-moderate AE plus monitoring every 3–6 mo 0.434 (0.040)
Route of administration
 Self-administered 0.240 (0.040) 7.4% 10.0%
 Hospital administration −0.240 (0.040)
Frequency of administration
 At least twice a month −0.143 (0.053) 5.3% 11.4%
 Monthly −0.056 (0.062)
 Every 6 mo 0.199 (0.062)
Abbreviation: AE, adverse effect.
Positive values indicate a greater preference for an attribute.

Two participant clusters were identified based on the prioritization assigned to each attribute. Cluster 1 included 78 (79.6%) nurses prioritizing treatments that preserve cognition and prevent disability progression. Cluster 2 included 20 nurses prioritizing route and frequency of administration of treatments. Cluster 1 participants showed a higher intensity of regret compared with cluster 2 participants (mean [SD] 10-item Regret Intensity Scale score, 2.2 [0.9] and 1.6 [0.7], respectively; P = .01) (Supplemental Digital Content 3, available at https://links.lww.com/JNN/A422). Cluster 2 nurses managed a higher mean rate of MS patients per week compared with patients with other neurological diseases than cluster 1 participants (58.5% and 42.6%, respectively; P = .04) and also showed a higher level of denial (mean [SD] Brief COPE denial score, 1.9 [2.1] and 0.9 [1.2], respectively; P = .008) (Supplemental Digital Content 3, available at https://links.lww.com/JNN/A422). No other differences in demographic, professional practice, and behavioral characteristics were found between groups.

Discussion

Current management of MS poses many challenges for healthcare professionals.5,6,26 By focusing on coordinating the care of MS patients throughout the disease trajectory, nurses can capture different types of information and support neurologists in the treatment decision-making process.5,6,27,28

In this study, preserving cognition and delaying disability progression were the most chosen DMT attributes among nurses with experience managing MS in Spain. The importance of understanding perspectives toward MS DMTs has been explored mainly in patients.19 Research on treatment preferences among healthcare professionals caring for MS has been less studied. Tencer et al29 found that reducing the rate of brain volume loss was the most important treatment attribute among 101 neurologists from the United Kingdom, followed by risk of infections and progression of disability at 2 years. Delaying disease progression was the most prioritized treatment attribute in a study involving 65 hospital pharmacists in Spain, followed by preserving quality of life and cognition.18

There are very few studies of therapeutic goals aimed at understanding the perspective of nurses caring for MS patients, and they are mainly oriented toward their perception of tolerability of different drugs and advantages of autoinjectors.30–32 Péloquin et al8 investigated knowledge and attitudes regarding MS care among 135 nurses from France, Germany, Italy, Spain, Canada, United States, and the United Kingdom. Participants reported knowledge gaps on new DMTs available (51%), treatment sequencing (46%), and detection of treatment failure (52%). Most participants also reported difficulties interpreting certain neurological assessments and outcomes (eg, Timed 25-Foot Walk Test, no evidence of disease activity, no evidence of progression or active disease).7 In a study with nurses and neurologists from the Netherlands, risk of life-threatening or severely disabling adverse events was the most important attribute in treatment decision, followed by effects on disability, frequency of relapses, and quality of life.17 Both groups did not differ significantly in their perspective about which attributes were most important for making decisions, with statistical differences only being found in 2 low prioritized attributes (costs were ranked higher by neurologists and drug interactions were ranked higher by nurses).17

These results show that all healthcare professionals involved in MS care in Spain are aligned on the increasing importance of impacting disease progression with the goal of preventing disability. In our study, we found that a subset of nurses (20.4%) prioritized route and frequency of administration as the most important attributes of treatments. They had a higher rate of MS patients managed per week and a higher coping component of denial compared with those participants who prioritized efficacy attributes. We hypothesize that a higher workload may have influenced this preference for treatment options that are easier to administer and/or have lower safety monitoring requirements.

Our study has limitations that deserve mention. First, the limited availability of studies on treatment preferences in MS nurses determined that the selection of treatment attributes and levels in this study was based primarily on previous studies conducted in patients and neurologists. Second, the selection of few treatment attributes to avoid complex study design and difficulty in selecting preferences could have caused omitted variable bias owing to exclusion of additional key attributes already identified in previous studies, such as the relapse prevention rate.33 Third, nurses are not the final decision-makers in prescribing MS treatments, and we have not captured their knowledge of the different efficacy and safety characteristics of currently available agents. Finally, nurses may have different responsibilities and activities in MS care depending on the country where they work. Therefore, these results may not necessarily be representative in other countries.

Conclusion

This study showed that preserving cognitive function and reducing disability progression are the most valued DMT attributes among nurses caring for patients with MS. The understanding of nurses' preferences may support their role in the multidisciplinary management of MS facilitating shared decision making by patients and neurologists.

Acknowledgments

The authors are most grateful to the Sociedad Española de Enfermería Neurológica and all nurses who participated in the study.

References

1. McGinley MP, Goldschmidt CH, Rae-Grant AD. Diagnosis and treatment of multiple sclerosis: a review. JAMA. 2021;325(8):765–779. doi:10.1001/jama.2020.26858
2. Maurino J, Martínez-Ginés ML, García-Domínguez JM, et al. Workplace difficulties, health-related quality of life, and perception of stigma from the perspective of patients with multiple sclerosis. Mult Scler Relat Disord. 2020;41:102046. doi:10.1016/j.msard.2020.102046
3. Linker RA, Chan A. Navigating choice in multiple sclerosis management. Neurol Res Pract. 2019;1:5. doi:10.1186/s42466-019-0005-5
4. Tsantes E, Curti E, Collura F, Bazzurri V, Fiore A, Granella F. Five- and seven-year prognostic value of new effectiveness measures (NEDA, MEDA and six-month delayed NEDA) in relapsing-remitting multiple sclerosis. J Neurol Sci. 2020;414:116827. doi:10.1016/j.jns.2020.116827
5. Meehan M, Doody O. The role of the clinical nurse specialist multiple sclerosis, the patients' and families' and carers' perspective: an integrative review. Mult Scler Relat Disord. 2020;39:101918. doi:10.1016/j.msard.2019.101918
6. Soelberg Sorensen P, Giovannoni G, Montalban X, Thalheim C, Zaratin P, Comi G. The multiple sclerosis care unit. Mult Scler. 2019;25(5):627–636. doi:10.1177/1352458518807082
7. Weilenmann M, Händler-Schuster D, Petry H, Zanolari D, Schmid-Mohler G, Beckmann S. Patient satisfaction with the quality of counseling provided by advanced practice nurses specialized in multiple sclerosis: a quantitative analysis. J Neurosci Nurs. 2021;53(2):99–103. doi:10.1097/JNN.0000000000000578
8. Péloquin S, Schmierer K, Leist TP, Oh J, Murray S, Lazure P. Challenges in multiple sclerosis care: results from an international mixed-methods study. Mult Scler Relat Disord. 2021;50:102854. doi:10.1016/j.msard.2021.102854
9. Schmid F, Rogan S, Glässel A. A Swiss health care professionals' perspective on the meaning of interprofessional collaboration in health care of people with MS—a focus group study. Int J Environ Res Public Health. 2021;18(12):6537. doi:10.3390/ijerph18126537
10. Cameron E, Rog D, McDonnell G, Overell J, Pearson O, French DP. Factors influencing multiple sclerosis disease-modifying treatment prescribing decisions in the United Kingdom: a qualitative interview study. Mult Scler Relat Disord. 2019;27:378–382. doi:10.1016/j.msard.2018.11.023
11. Price E, Lucas R, Lane J. Experiences of healthcare for people living with multiple sclerosis and their healthcare professionals. Health Expect. 2021;24(6):2047–2056. doi:10.1111/hex.13348
12. Parker LS, Topcu G, De Boos D, das Nair R. The notion of "invisibility" in people's experiences of the symptoms of multiple sclerosis: a systematic meta-synthesis. Disabil Rehabil. 2021;43(23):3276–3290. doi:10.1080/09638288.2020.1741698
13. Marck CH, Hunter A, Butler E, et al. Assessment and treatment of depression in people with multiple sclerosis: a qualitative analysis of specialist clinicians' experiences. Mult Scler Relat Disord. 2022;57:103362. doi:10.1016/j.msard.2021.103362
14. Lucchetta RC, Leonart LP, Becker J, Pontarolo R, Fernandez-Llimós F, Wiens A. Safety outcomes of disease-modifying therapies for relapsing-remitting multiple sclerosis: a network meta-analysis. Mult Scler Relat Disord. 2019;35:7–15. doi:10.1016/j.msard.2019.06.036
15. Bridges JF, Hauber AB, Marshall D, 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):403–413. doi:10.1016/j.jval.2010.11.013
16. Farley K, Thompson C, Hanbury A, Chambers D. Exploring the feasibility of conjoint analysis as a tool for prioritizing innovations for implementation. Implement Sci. 2013;8:56. doi:10.1186/1748-5908-8-56
17. Kremer IEH, Evers SMAA, Jongen PJ, Hiligsmann M. Comparison of preferences of healthcare professionals and MS patients for attributes of disease-modifying drugs: a best-worst scaling. Health Expect. 2018;21(1):171–180. doi:10.1111/hex.12599
18. Martínez-López I, Maurino J, Sanmartín-Fenollera P, et al. Assessing pharmacists' preferences towards efficacy attributes of disease-modifying therapies in relapsing-remitting multiple sclerosis. Pharmacy. 2020;8(2):61. doi:10.3390/pharmacy8020061
19. Visser LA, Louapre C, Uyl-de Groot CA, Redekop WK. Patient needs and preferences in relapsing-remitting multiple sclerosis: a systematic review. Mult Scler Relat Disord. 2020;39:101929. doi:10.1016/j.msard.2020.101929
20. Uitdehaag BMJ. Disability outcome measures in phase III clinical trials in multiple sclerosis. CNS Drugs. 2018;32(6):543–558. doi:10.1007/s40263-018-0530-8
21. Santesson AHE, Bäckström M, Holmberg R, Perrin S, Jarbin H. Confirmatory factor analysis of the Evidence-Based Practice Attitude Scale (EBPAS) in a large and representative Swedish sample: is the use of the total scale and subscale scores justified?BMC Med Res Methodol. 2020;20(1):254. doi:10.1186/s12874-020-01126-4
22. Carver CS, Scheier MF, Weintraub JK. Assessing coping strategies: a theoretically based approach. J Pers Soc Psychol. 1989;56(2):267–283. doi:10.1037//0022-3514.56.2.267
23. Maslach C, Jackson SE, Leiter MP. Maslach Burnout Inventory Manual. 4th ed. Menlo Park, CA: Mind Garden, Inc; 2018.
24. Saposnik G, Bueno-Gil G, Sempere ÁP, et al. Regret and therapeutic decisions in multiple sclerosis care: literature review and research protocol. Front Neurol. 2021;12:675520. doi:10.3389/fneur.2021.675520
25. Courvoisier DS, Cullati S, Haller CS, et al. Validation of a 10-item care-related Regret Intensity Scale (RIS-10) for health care professionals. Med Care. 2013;51(3):285–291. doi:10.1097/MLR.0b013e318280f02c
26. Oreja-Guevara C, Potra S, Bauer B, et al. Joint healthcare professional and patient development of communication tools to improve the standard of MS care. Adv Ther. 2019;36(11):3238–3252. doi:10.1007/s12325-019-01071-9
27. Roman C, Menning K. Treatment and disease management of multiple sclerosis patients: a review for nurse practitioners. J Am Assoc Nurse Pract. 2017;29(10):629–638. doi:10.1002/2327-6924.12514
28. Robles-Sanchez MA, Cruz-Díaz V, Amil-Bujan P, Sastre-Garriga J, Ramió-Torrentà L, Bertran-Noguer C. An expert patient program as a tool to empower people with multiple sclerosis. J Neurosci Nurs. 2020;52(4):166–171. doi:10.1097/JNN.0000000000000514
29. Tencer T, Will O, Kumar J, Cambron-Mellott MJ, Mackie DS, Beusterien K. Patient and neurologist preferences in the UK for relapsing-remitting multiple sclerosis treatments: findings from a discrete choice experiment. Curr Med Res Opin. 2021;37(9):1589–1598. doi:10.1080/03007995.2021.1940911
30. Verdun di Cantogno E, Tomlinson M, Manuel L, Thakur K. Autoinjector preference in multiple sclerosis and the role of nurses in treatment decisions: results from an international survey in Europe and the USA. Pragmat Obs Res. 2014;5:53–64. doi:10.2147/POR.S72012
31. Campbell TL, Lefaux BJ, Mayer LL, et al. Nursing management of gastrointestinal adverse events associated with delayed-release dimethyl fumarate: a global Delphi approach. J Neurosci Nurs. 2020;52(2):72–77. doi:10.1097/JNN.0000000000000495
32. White S, Harris C, Allan M, et al. Global peginterferon beta-1a tolerability management best practices: a nurse-focused Delphi approach. Neurol Ther. 2021;10(1):251–263. doi:10.1007/s40120-021-00238-3
33. Coast J, Flynn TN, Salisbury C, Louviere J, Peters TJ. Maximising responses to discrete choice experiments: a randomised trial. Appl Health Econ Health Policy. 2006;5(4):249–260. doi:10.2165/00148365-200605040-00006
Keywords:

conjoint analysis; disease-modifying treatments; multiple sclerosis; nursing research; treatment preferences

Supplemental Digital Content

Copyright © 2022 The Authors. Published by Wolters Kluwer Health, Inc.