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. 2025 Apr 22;20(4):e0322168.
doi: 10.1371/journal.pone.0322168. eCollection 2025.

Assessing therapeutic decisions in generalized myasthenia gravis: Study protocol

Gerardo Gutiérrez-Gutiérrez  1 , Rocío Gómez-Ballesteros  2 , Javier Sotoca  3 , Adrián Ares  4 , Ramón Villaverde  5 , Virginia Reyes  6 , Thaís Armangué  7 , Elisa Salas  2 , Paola Díaz-Abós  2 , Pablo Rebollo  8 , Mónica Sarmiento  8 , Iratxe Escobar  2 , Jorge Maurino  2 , Luis Querol  9
Affiliations

Assessing therapeutic decisions in generalized myasthenia gravis: Study protocol

Gerardo Gutiérrez-Gutiérrez et al. PLoS One. .

Abstract

Background: The therapeutic landscape in generalized myasthenia gravis (gMG) has been continuously evolving in recent years, with over five products approved, each with different efficacy, safety, and administration profiles. With the availability of new targeted treatments, physicians are faced with the challenge of therapeutic decision-making tailored to traditional therapeutic goals, individual preferences, and personal experience, seeking optimal disease control with a positive safety profile. In this context of uncertainty and multiple novel choices, this study aims to provide insights into the preferred treatment choices of neurologists managing gMG and to identify demographic, professional or behavioral factors influencing the decision-making process.

Methods: This is a non-interventional, cross-sectional, web-based study involving 150 neurologists treating gMG patients in collaboration with the Spanish Society of Neurology. The primary endpoint will be to assess preferences for different gMG treatment attributes using a conjoint analysis to create hypothetical treatment scenarios. Therapeutic inertia, described as the lack of treatment initiation or intensification when therapeutic goals are not met, will be evaluated as a secondary endpoint through 7 case scenarios simulating real gMG clinical practice situations. Neurologists will also answer a survey composed of demographic, professional, and behavioral characteristics (user resistance behavior, care-related regret, burnout, risk attitude, empathy, work fulfilment, and personality traits) to recognize possible factors influencing decisions.

Conclusions: The study findings will contribute to better understanding of decision-making in gMG under a changing therapeutic landscape with multiple new targeted options, and will identify which factors have a role in affecting those decisions.

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Conflict of interest statement

I have read the journal's policy and the authors of this manuscript have the following competing interests: GGG has received compensation for consulting services from CSL Behring, Biogen, Alter, Takeda, Akcea, Lupin Neuroscience, Roche, Alexion, and Argenx; congresses support from Alter, Esteve, Sanofi-Genzyme, Pfizer, and UCB Pharma; has scientific relation with Lilly, Alexion, Genzyme, Takeda, Biogen, Pfizer, and Alter; books with Exeltis, Alter, Esteve, Andrómaco, and Bristol-Myers; and has received grants and awards from Lilly, UCB Pharma, and CSL Behring. RGB, ES, PDA, IE and JM are employees of Roche Pharma Spain. JS has received travel/congress support and compensation for consulting services from Roche, Biogen, UCB, and Argenx. AA has received speaking honoraria, consultation services compensation, or travel support for congress and scientific meetings attendance from Almirall, Bayer, Biogen, BMS, Janssen, Merck, Novartis, Roche, Sanofi, and Teva. MS and PB are employees of IQVIA Spain, the contract research organization selected by Roche for this study. LQ received speaker honoraria from Merck, Sanofi, Roche, Biogen, Grifols and CSL Behring; provided expert testimony for Grifols, Johnson & Johnson, Annexon Pharmaceuticals, Sanofi, Novartis, Takeda, and CSL-Behring; and received research funds from Roche, UCB, and Grifols. The rest of the authors declare no conflict of interest for this work. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Figures

Fig 1
Fig 1. PROMPT-MG study flow.
Fig 2
Fig 2. Conjoint Analysis process general overview.
IV, intravenous; m, months; MG-ADL, Myasthenia Gravis–specific Activities of Daily Living; SC, subcutaneous; SPSS, Statistical Package for Social Sciences w, weeks.
Fig 3
Fig 3. Step-by-Step Overview of completing the Conjoint Analysis (CA) in the eCRF.
It is a simplified representation of the eCRF screen sequence that neurologist participants must follow and complete, guided by the specific instructions displayed on each screen. The ellipsis symbol (…) indicates that the actual eCRF screens contain additional information or content not shown here. CA, conjoint analysis; eCRF, electronic Case Report Form; IV, intravenous; MG, myasthenia gravis; MG-ADL, Myasthenia Gravis–specific Activities of Daily Living scale; SC, subcutaneous.
See this image and copyright information in PMC

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