Evidence map›Paper›PMID 39643805›Full record

ArticlePharmacoEconomics2025

Value of Innovative Multiple Myeloma Treatments from Patient and Healthcare Provider Perspectives: Evidence from a Discrete Choice Experiment.

Sakil Syeed, Chia Jie Tan, Amandeep Godara, Kyna Gooden, Derek Tang, Samantha Slaff, Yu-Hsuan Shih, Surachat Ngorsuraches, Nathorn Chaiyakunapruk

Abstract read
In one paragraph

Article in PharmacoEconomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Sakil SyeedDepartment of Pharmacotherapy, The University of Utah College of Pharmacy, 30 S 2000 E, Salt Lake City, UT, 84112, USA.ORCID 0000-0002-1814-5852
Chia Jie TanDepartment of Pharmacotherapy, The University of Utah College of Pharmacy, 30 S 2000 E, Salt Lake City, UT, 84112, USA.ORCID 0000-0003-2452-0556
Amandeep GodaraDivision of Hematology and Hematologic Malignancies, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA.ORCID 0000-0003-1943-4442
Kyna GoodenGlobal Health Economics and Outcomes Research, Bristol Myers Squibb, Princeton, NJ, USA.
Derek TangGlobal Health Economics and Outcomes Research, Bristol Myers Squibb, Princeton, NJ, USA.
Samantha SlaffGlobal Health Economics and Outcomes Research, Bristol Myers Squibb, Princeton, NJ, USA.
Yu-Hsuan ShihGlobal Health Economics and Outcomes Research, Bristol Myers Squibb, Princeton, NJ, USA.ORCID 0000-0002-9823-3771
Surachat NgorsurachesHealth Outcomes Research and Policy, Auburn University Harrison College of Pharmacy, Auburn, AL, USA.ORCID 0000-0002-2327-224X
Nathorn ChaiyakunaprukDepartment of Pharmacotherapy, The University of Utah College of Pharmacy, 30 S 2000 E, Salt Lake City, UT, 84112, USA. nathorn.chaiyakunapruk@utah.edu.ORCID 0000-0003-4572-8794

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough innovation generally provides measurable improvements in disease characteristics and patient survival, some benefits can remain unclear. This study aimed to investigate patient and healthcare provider (HCP) preferences for the innovative attributes of multiple myeloma (MM) treatments.

methodsA cross-sectional, web-based, discrete choice experiment (DCE) survey was conducted among 200 patients with MM and 30 HCPs of patients with MM in the USA. A literature review, followed by interviews with patients with MM and HCPs, was undertaken to select five attributes (progression-free survival [PFS], chance of severe side effects, how patients live with MM treatments, scientific innovation, and monthly out-of-pocket [OOP] cost) and their levels. A Bayesian efficient design was used to generate DCE choice sets. Each choice set comprised two hypothetical MM treatment alternatives described by the selected attributes and their levels. Each patient and HCP was asked to choose a preferred alternative from each of the 11 choice sets. Mixed logit and latent class models were developed to estimate patient and HCP preferences for the treatment attributes.

resultsOverall, patients and HCPs preferred increased PFS, less chance of severe side effects, a treatment that offered life without treatment, scientific innovation, and lower OOP cost. From patients' perspectives, PFS had the highest conditional relative importance (44.7%), followed by how patients live with MM treatments (21.6%) and scientific innovation (16.0%).

conclusionsIn addition to PFS, patients and HCPs also valued innovative MM treatments that allowed them to live without treatments and/or offered scientific innovation. These attributes should be considered when evaluating MM treatments.

Indexed as

Choice BehaviorHealth PersonnelMultiple MyelomaPatient PreferenceAdultAgedBayes TheoremCross-Sectional StudiesFemaleHealth ExpendituresHumansMaleMiddle AgedProgression-Free SurvivalSurveys and QuestionnairesUnited States

Identifiers

PMID39643805
PMCPMC11929691

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.