Decision Making in Multiple Sclerosis Care Under Uncertainty

July 24, 2019 updated by: Unity Health Toronto

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.

Study Overview

Status

Unknown

Conditions

Intervention / Treatment

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.

Study Type

Interventional

Enrollment (Anticipated)

450

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • Ontario
      • Toronto, Ontario, Canada, M5B 1X2
        • Recruiting
        • St. Michael's Hospital
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

23 years to 80 years (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Description

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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Other
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Double

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Quantitative risk estimation
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.
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.
Active Comparator: Qualitative risk estimation
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.
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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Therapeutic inertia score
Time Frame: At the completion of the study, an estimated 90 minutes

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
Time Frame: At the completion of the study, an estimated 90 minutes
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
Time Frame: At the completion of the study, an estimated 90 minutes
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)
Time Frame: At the completion of the study, an estimated 90 minutes
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
Time Frame: At the completion of the study, an estimated 90 minutes

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

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

July 6, 2019

Primary Completion (Anticipated)

July 21, 2021

Study Completion (Anticipated)

December 22, 2021

Study Registration Dates

First Submitted

March 25, 2019

First Submitted That Met QC Criteria

July 24, 2019

First Posted (Actual)

July 29, 2019

Study Record Updates

Last Update Posted (Actual)

July 29, 2019

Last Update Submitted That Met QC Criteria

July 24, 2019

Last Verified

July 1, 2019

More Information

Terms related to this study

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

No

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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