Hostname: page-component-8448b6f56d-gtxcr Total loading time: 0 Render date: 2024-04-24T16:41:21.333Z Has data issue: false hasContentIssue false
  • English
  • Français

PATIENT PRIORITIES FOR TREATMENT ATTRIBUTES IN ADJUNCTIVE DRUG THERAPY OF SEVERE HYPERCHOLESTEROLEMIA IN GERMANY: AN ANALYTIC HIERARCHY PROCESS

Part of: Special Collection - Methods

Published online by Cambridge University Press:  10 July 2018

Axel C. Mühlbacher ,
Anika Kaczynski ,
Franz-Werner Dippel  and
Susanne Bethge
Axel C. Mühlbacher
Affiliation:
Hochschule Neubrandenburg; Gesellschaft für empirische Beratung GmbH (GEB)muehlbacher@hs-nb.de
Anika Kaczynski
Affiliation:
Hochschule Neubrandenburg
Franz-Werner Dippel
Affiliation:
Sanofi Deutschland GmbH, Evidenzbasierte Medizin
Susanne Bethge
Affiliation:
Hochschule Neubrandenburg
Get access Rights & Permissions [Opens in a new window]

Abstract

Objectives:

Severe hypercholesterolemia is a major cause of death in coronary heart disease. New adjunctive drug therapies have passed authorization processes and been launched recently. So far it is not known which properties of the new treatment options generate the highest benefit for patients. The aim was to evaluate patient priorities in the field of adjunctive drug therapy with apheresis. Therapy characteristics were examined as to their relevance to hypercholesterolemia patients.

Methods:

To identify all potential patient-relevant treatment characteristics, a systematic literature review and ten interviews with patients were conducted. Seven key characteristics were identified from the patient perspective. Patients’ priorities were elicited using an analytic hierarchy process (AHP).

Results:

In total, N = 61 patients diagnosed with severe hypercholesterolemia and undergoing apheresis participated in the study. The analysis showed predominance for the attribute “reduction of LDL-C level in blood” (Wglobal:0.362). The “risk of myopathy” (Wglobal:0.164), “risk of neurocognitive impairment” (Wglobal:0.161) and “frequency of apheresis” (Wglobal:0.119) were ranked second, third and fourth. Subgroup analyses revealed that “frequency of apheresis” is of greater importance to younger patients, men and/or patients who indicated a reduction in quality of life due to apheresis.

Conclusions:

The essential decision criteria for optimal therapy from the patients’ perspective were obtained. “Reduction of lipoprotein in blood” was ranked highest compared with the “mode of administration” and “side effects” characteristics. The study offers a transparent approach for the identification of patient priorities for adjunctive PCSK9-inhibitor therapy in apheresis-treated hypercholesterolemia. The project can be used by healthcare decision makers to understand the importance of each patient-relevant endpoint.

Keywords

Analytic Hierarchy Process (AHP)Patient prioritiesSevere hypercholesterolemiaLipoprotein apheresisAdjunctive drug therapy
Type
Method
Information
International Journal of Technology Assessment in Health Care , Volume 34 , Issue 3 , 2018 , pp. 267 - 275
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1.Robinson, JG, Farnier, M, Krempf, M, et al. Efficacy and safety of alirocumab in reducing lipids and cardiovascular events. N Engl J Med. 2015;372:1489–1499.Google Scholar
2.Bruckert, E, Saheb, S, Bonté, JR, Coudray-Omnès, C. Daily life, experience and needs of persons suffering from homozygous familial hypercholesterolaemia: Insights from a patient survey. Atheroscler Suppl. 2014;15:46–51.Google Scholar
3.Goldberg, AC, Hopkins, PN, Toth, PP, et al. Familial hypercholesterolemia: screening, diagnosis and management of pediatric and adult patients: Clinical guidance from the National Lipid Association Expert Panel on Familial Hypercholesterolemia. J Clin Lipidol. 2011;5:133–140.Google Scholar
4.Stefanutti, C, Julius, U. Lipoprotein apheresis: State of the art and novelties. Atheroscler Suppl. 2013;14:19–27.Google Scholar
5.Wang, A, Richhariya, A, Gandra, SR, et al. Systematic review of low-density lipoprotein cholesterol apheresis for the treatment of familial hypercholesterolemia. J Am Heart Assoc. 2016;5:e003294.Google Scholar
6.Stein, EA, Gipe, D, Bergeron, J, et al. Effect of a monoclonal antibody to PCSK9, REGN727/SAR236553, to reduce low-density lipoprotein cholesterol in patients with heterozygous familial hypercholesterolaemia on stable statin dose with or without ezetimibe therapy: A phase 2 randomised controlled trial. Lancet. 2012;380:29–36.Google Scholar
7.Roth, EM, Bujas-Bobanovic, M, Louie, MJ, Cariou, B. Patient and physician perspectives on mode of administration of the PCSK9 monoclonal antibody alirocumab, an injectable medication to lower LDL-C levels. Clin Ther. 2015;37:1945–1954.e6.Google Scholar
8.Cannon, C, Cariou, B, Blom, D, et al. Efficacy and safety of alirocumab in high cardiovascular risk patients with inadequately controlled hypercholesterolaemia on maximally tolerated doses of statins: The ODYSSEY COMBO II randomized controlled trial. Eur Heart J. 2015;36:1186–1194.Google Scholar
9.Roth, EM, Taskinen, M-R, Ginsberg, HN, et al. Monotherapy with the PCSK9 inhibitor alirocumab versus ezetimibe in patients with hypercholesterolemia: Results of a 24 week, double-blind, randomized Phase 3 trial. Int J Cardiol. 2014;176:55–61.Google Scholar
10.Mühlbacher, AC, Juhnke, C. Patient preferences versus physicians’ judgement: Does it make a difference in healthcare decision making? Appl Health Econ Health Policy. 2013;11:163–180.Google Scholar
11.Mühlbacher, AC, Bridges, JF, Bethge, S, et al. Preferences for antiviral therapy of chronic hepatitis C: A discrete choice experiment. Eur J Health Econ. 2017;18:155–165.Google Scholar
12.Mühlbacher, AC, Johnson, FR. Choice experiments to quantify preferences for health and healthcare: State of the practice. Appl Health Econ Health Policy. 2016;14:253–266.Google Scholar
13.Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen (IQWiG), General methods, version 5.0 / 10.07.2017. 2017, Köln.Google Scholar
14.U.S. Department of Health and Human Services FDA Center for Drug Evaluation and Research, U.S. Department of Health and Human Services FDA Center for Biologics Evaluation and Research, and U.S. Department of Health and Human Services FDA Center for Devices and Radiological Health, Guidance for industry: Patient-reported outcome measures: use in medical product development to support labeling claims: Draft guidance. Health Qual Life Outcomes. 2006;4:79.Google Scholar
15.Ho, M, Saha, A, McCleary, KK, et al. A framework for incorporating patient preferences regarding benefits and risks into regulatory assessment of medical technologies. Value Health. 2016;19:746–750.Google Scholar
16.Sloane, EB, Liberatore, MJ, Nydick, RL. Medical decision support using the Analytic Hierarchy Process. J Healthc Inf Manag. 2002;16:38–43.Google Scholar
17.Saaty, TL. How to make a decision: The analytic hierarchy process. Eur J Oper Res. 1990;48:9–26.Google Scholar
18.Dolan, JG. Medical decision making using the analytic hierarchy process choice of initial antimicrobial therapy for acute pyelonephritis. Med Decis Making. 1989;9:51–56.Google Scholar
19.Thokala, P, Devlin, N, Marsh, K, et al. Multiple criteria decision analysis for health care decision making—An introduction: Report 1 of the ISPOR MCDA Emerging Good Practices Task Force. Value Health. 2016;19:1–13.Google Scholar
20.Marsh, K, IJzerman, M, Thokala, P, et al. Multiple criteria decision analysis for health care decision making—Emerging good practices: Report 2 of the ISPOR MCDA Emerging Good Practices Task Force. Value Health. 2016;19:125–137.Google Scholar
21.Saaty, TL. The analytic hierarchy process. Planning, priority setting, resource allocation. 2nd ed. New York: McGraw-Hill; 1980: XIII, 287 S.Google Scholar
22.Cuchel, M, Bruckert, E, Ginsberg, HN, et al. Homozygous familial hypercholesterolaemia: New insights and guidance for clinicians to improve detection and clinical management. A position paper from the Consensus Panel on Familial Hypercholesterolaemia of the European Atherosclerosis Society. Eur Heart J. 2014;35:2146–2157.Google Scholar
23.Rosada, A, Kassner, U, Banisch, D, et al. Quality of life in patients treated with lipoprotein apheresis. J Clin Lipidol. 2016;10:323–329.e6.Google Scholar
24.Baigent, C, Blackwell, L, Emberson, J, et al. Efficacy and safety of more intensive lowering of LDL cholesterol: A meta-analysis of data from 170,000 participants in 26 randomised trials. Lancet. 2010;376:1670–1681.Google Scholar
25.Blom, DJ, Hala, T, Bolognese, M, et al. A 52-week placebo-controlled trial of evolocumab in hyperlipidemia. N Engl J Med. 2014;370:1809–1819.Google Scholar
26.Koren, MJ, Giugliano, RP, Raal, FJ, et al. Efficacy and safety of longer-term administration of evolocumab (AMG 145) in patients with hypercholesterolemia 52-week results from the open-label study of long-term evaluation against LDL-C (OSLER) randomized trial. Circulation. 2014;129:234–243.Google Scholar
27.Raal, FJ, Honarpour, N, Blom, DJ, et al. Inhibition of PCSK9 with evolocumab in homozygous familial hypercholesterolaemia (TESLA Part B): A randomised, double-blind, placebo-controlled trial. Lancet. 2015;385:341–350.Google Scholar
28.Schwartz, C, Bode, R, Repucci, N, et al. The clinical significance of adaptation to changing health: A meta-analysis of response shift. Qual Life Res. 2006;15:1533–1550.Google Scholar
29.Belton, V, Gear, T. On a short-coming of Saaty's method of analytic hierarchies. Omega (Westport). 1983;11:228–230.Google Scholar
30.Triantaphyllou, E, Mann, SH. An evaluation of the eigenvalue approach for determining the membership values in fuzzy sets. Fuzzy Sets Syst. 1990;35:295–301.Google Scholar
31.Dyer, JS. Remarks on the analytic hierarchy process. Manage Sci. 1990;36:249–258.Google Scholar
32.Schmidt, K, Aumann, I, Hollander, I, Damm, K, von der Schulenburg, J-MG. Applying the analytic hierarchy process in healthcare research: A systematic literature review and evaluation of reporting. BMC Med Inf Decis Making. 2015;15:112.Google Scholar
Supplementary material: File

Mühlbacher et al. supplementary material

Figures S1-S2 and Table S1

Download Mühlbacher et al. supplementary material(File)
File 47.5 KB
Supplementary material: File

Mühlbacher et al. supplementary material

Mühlbacher et al. supplementary material 1

Download Mühlbacher et al. supplementary material(File)
File 34.3 KB