Decision Making in Multiple Sclerosis Care Under Uncertainty

Study Overview
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Brief Summary
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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
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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.

Official Title
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Decision Making in Multiple Sclerosis Care Under Uncertainty

Conditions
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Multiple Sclerosis

Intervention / Treatment
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* Other: Quantitative risk


Participation Criteria
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Eligibility Criteria
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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

Ages Eligible for Study
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Minimum Age: 23 Years
Maximum Age: 80 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Other
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: Double


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Quantitative risk estimation<br>Participants will be exposed to case-scenarios. Each case scenario provides a description of the current clinical situation (e.g. patient age, current treatment, number of relapses, current EDSS, MRI findings, etc). In addition, participants will see a squared box indicating the probability of risk progression (20%, 25%, 85%, 90%). This information may or may not be accurate to reflect potential errors of risk prediction tools. | Other: Quantitative risk<br>* 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.<br>|
| Active Comparator: Qualitative risk estimation<br>Participants will be exposed to the same case-scenarios as the intervention arm. Each case scenario provides a description of the current clinical situation (e.g. patient age, current treatment, number of relapses, current EDSS, MRI findings, etc). In addition, participants will see a squared box indicating a qualitative probability of risk progression (low, high). This information may or may not be accurate to reflect potential errors of risk prediction tools. | Other: Quantitative risk<br>* 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.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Therapeutic inertia score | The 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) | At the completion of the study, an estimated 90 minutes | 
| Accuracy of treatment decisions | Comparison 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. | At the completion of the study, an estimated 90 minutes | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Therapeutic decisions under fatigue | Given 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). | At the completion of the study, an estimated 90 minutes | 
| Prevalence of therapeutic inertia (TI) | Comparison 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) | At the completion of the study, an estimated 90 minutes | 
| Factors associated with therapeutic decisions | Participants 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] | At the completion of the study, an estimated 90 minutes | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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decision making, therapeutic, disease modifying agents, monoclonal antobodies, physicians, neurologists, uncertainty, neuroeconomics