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Decision Making in Multiple Sclerosis Care Under Uncertainty

Decision Making in Multiple Sclerosis Care Under Uncertainty

Status
UNKNOWN
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT04035720
Enrollment
450
Registered
2019-07-29
Start date
2019-07-06
Completion date
2021-12-22
Last updated
2019-07-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Multiple Sclerosis

Keywords

decision making, therapeutic, disease modifying agents, monoclonal antobodies, physicians, neurologists, uncertainty, neuroeconomics

Brief summary

The main objectives of this study are: i) To determine patient-level, physician-level and health system factors influencing therapeutic decisions in multiple sclerosis (MS) care by applying conjoint discrete experiments. ii) To determine the prevalence of therapeutic inertia among participating neurologists. iii) To compare clinical judgement vs. a qualitative or quantitative approach when assessing for a given case-scenario. iv) To evaluate the influence of decision fatigue in treatment decisions.

Detailed description

The landscape of MS care is changing. Currently, there are over 15 disease modifying agents (DMTs) available to treat MS, with varying availability around the world. Significant heterogeneity exists in the efficacy and risks associated with these therapies. Neurologists caring for MS patients face important choices in each medical encounter: 1) continue with the same management, 2) initiate or escalate therapy for a more effective or safer agent, or 3) consider a reassessment within months under the uncertainty of the current status of the patient. Limited information on how physicians weigh in different factors when making therapeutic decisions. Physicians (cognitive biases affecting decision making) and health system (e.g. access to an infusion center) factors are the most responsible causes of practice gaps in MS care. The physician's component is the least studied. Therapeutic inertia (TI) is a common phenomenon in MS care defined as lack of treatment initiation or escalation (e.g. switch interferons or glatiramer to fingolimod /alemtuzumab /natalizumab/ocrelizumab/ etc.) when recommended by guidelines or evidence of disease progression. This phenomenon leads to poorer patient's outcomes, greater disability, and diminished quality of life. Goals of the study: i) to determine what are the most relevant factors influencing therapeutic decisions among neurologists with expertise in MS care; ii) to asses whether physicians rely on medical information provided in a case scenario versus a quantitative or qualitative estimation of disease progression based on hypothetical models.

Interventions

OTHERQuantitative risk

Participants will be able to see a square box that represent the estimated risk of disease progression. They will have to elect making a therapeutic decision based on the description of the case-scenario or based on the estimated prediction as represented in the square box.

Sponsors

Hoffmann-La Roche
CollaboratorINDUSTRY
University of Toronto
CollaboratorOTHER
Unity Health Toronto
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
OTHER
Masking
DOUBLE (Subject, Investigator)

Eligibility

Sex/Gender
ALL
Age
23 Years to 80 Years
Healthy volunteers
No

Inclusion criteria

* Actively practicing neurologist * Expertise in treating patients with multiple sclerosis (at least 12 per year) * Clinical setting: academic or community institutions, private practice or outpatient clinic * Certified physicians in their specialty * Online consent to participate in the study

Design outcomes

Primary

MeasureTime frameDescription
Therapeutic inertia scoreAt the completion of the study, an estimated 90 minutesThe therapeutic inertia (TI) score is based on our previous work published elsewhere (see references). It is based on the sum number of case-scenarios that required treatment escalation over the total number of presented scenarios (10). Range: 0 (lowest value) to 10 (maximal value). The higher value represents the higher level of therapeutic inertia. There is no subscale. This measurement has been previously reported (Saposnik et al. JAMA Netw Open. 2019 Jul 3;2(7):e197093. doi: 10.1001/jamanetworkopen.2019.7093; Saposnik et al. MDM Policy Pract. 2019 Jun 21;4(1):2381468319855642. doi: 10.1177/2381468319855642)
Accuracy of treatment decisionsAt the completion of the study, an estimated 90 minutesComparison of discordant pairs in each arm: Using chi-square (parametric) test, there will be a comparison between groups (intervention vs. control) in the proportion of participants who made accurate therapeutic decisions.

Secondary

MeasureTime frameDescription
Therapeutic decisions under fatigueAt the completion of the study, an estimated 90 minutesGiven that participants will be exposed to several case-scenarios, a comparison of therapeutic inertia will be conducted between the first half and the second half of case scenarios as previously reported (Saposnik et al. Front Neurol. 2017 Aug 21;8:430. doi: 10.3389/fneur.2017.00430. eCollection 2017).
Prevalence of therapeutic inertia (TI)At the completion of the study, an estimated 90 minutesComparison of treatment decisions using a binary definition of therapeutic inertia (TI). Lack of treatment escalation in at least one case-scenario (out of the total) will be considered as TI present as previously reported ((Saposnik et al. JAMA Netw Open. 2019 Jul 3;2(7):e197093. doi: 10.1001/jamanetworkopen.2019.7093; Saposnik et al. MDM Policy Pract. 2019 Jun 21;4(1):2381468319855642. doi: 10.1177/2381468319855642)
Factors associated with therapeutic decisionsAt the completion of the study, an estimated 90 minutesParticipants will be exposed to 12 pairs of case-scenarios as per the discrete choice design. Participants have to choose the ideal case-scenario (e.g. A, B or neither- but they cannot choose both) for escalating treatment. Each pair of case-scenarios represent a comprehensive combination of possible variables. The most common factors associated with treatment escalation will be assessed based on these experimental design. A weighted estimate will be calculated for each collected variable. See details in Discrete Choice Experiment Response Rates: A Meta-analysis.Watson V et al. Health Econ. (2017) and Saposnik et al.Stroke. 2019 Jul 22:STROKEAHA119025631. doi: 10.1161/STROKEAHA.119.025631. \[Epub ahead of print\]

Countries

Canada

Contacts

Primary ContactGustavo Saposnik, MD, MSc,
saposnikg@smh.ca4168645155
Backup ContactRoula Raptis, Msc
RaptisS@smh.ca416-864-6060

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026