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Oncology

Evaluating process utilities for the treatment burden of chemotherapy in multiple myeloma in Japan: a time trade-off valuation study

ORCID Icon, , , & ORCID Icon
Pages 565-573 | Received 13 Oct 2022, Accepted 29 Mar 2023, Published online: 12 Apr 2023
 

Abstract

Aims

This study estimated the “process utilities” of treatment options for patients with relapsed/refractory multiple myeloma (RRMM) in Japan using the time trade-off (TTO) method. Chimeric antigen receptor (CAR) T cell immunotherapy is available for patients with RRMM who are triple-class exposed (TCE) after treatment with immunomodulatory agents, proteasome inhibitors, and anti-CD38 monoclonal antibodies. However, the impact of available treatment options on health state utilities has not been well characterized, particularly in relation to process utilities.

Methods

Eight vignettes of health states and daily activity restrictions related to each of the following RRMM therapies were prepared: no treatment, CAR T cell therapy with idecabtagene vicleucel (ide-cel), regular intravenous infusion, and oral administration. A face-to-face survey of healthy Japanese adults who were representative of the general population was conducted. The TTO method was used to evaluate each vignette and to generate utility scores for each treatment regimen.

Results

Three hundred and nineteen respondents participated in the survey (mean age: 44 years [range: 20–64]; female: 50%). Utility scores for no treatment, ide-cel, oral pomalidomide, and dexamethasone (Pd) therapy ranged from ∼0.7 to 0.8. Utility scores for regular intravenous infusion regimens ranged from 0.50 to 0.56. There was a difference of ∼0.2 between the utility scores for no treatment/ide-cel/oral administration and regular intravenous infusions.

Conclusions

Differences in treatment administration across RRMM therapies showed a substantial impact on health state utilities. When quantifying the value of treatments, process utility gains should be considered as an independent factor in health technology assessments.

JEL CLASSIFICATION CODES:

Transparency

Declaration of funding

This work was supported by Bristol Myers Squibb K.K. The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Declaration of financial/other relationships

TI received grants from Bristol Myers Squibb, Janssen, Pfizer, and Takeda, and honoraria from Bristol Myers Squibb, Janssen, Ono, Sanofi, and Takeda outside of this work. MN is an employee of and shareholder in Bristol Myers Squibb K.K. TM is an employee of CRECON Medical Assessment Inc., which received payment for these works from Bristol Myers Squibb K.K. FM received consultation fees from Bristol Myers Squibb K.K. SI received honoraria from Bristol Myers Squibb, Celgene, Janssen, Ono, Sanofi, and Takeda, and research grants from AbbVie, Amgen, Bristol Myers Squibb, Caelum, Chugai, Daiichi Sankyo, Janssen, Ono, Otsuka, Pfizer, and Takeda, outside of this work.

Author contributions

All authors contributed to the conception and design of the study and the data analysis and interpretation. Acquisition of data was conducted by MN, TM, and FM. All authors critically revised the manuscript for intellectual content and gave final approval of the version to be published. All authors agree to be accountable for all aspects of the work.

Acknowledgements

The authors received writing and editorial assistance in the preparation of this manuscript from Eilish McBurnie, of Excerpta Medica, funded by Bristol Myers Squibb.

Data availability statement

BMS policy on data sharing may be found at https://www.bms.com/researchers-and-partners/independent-research/data-sharing-request-process.html.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.