- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT04496830
SPINCOMS Biomarker Study (SPINCOMS)
Cerebrospinal Fluid-biomarkers-based Diagnostic and Prognostic Models for Multiple Sclerosis
Study Overview
Detailed Description
Using machine learning, the investigators have developed from SOMAScan:
- A molecular diagnostic test that differentiates MS from other inflammatory and non-inflammatory central nervous system (CNS) diseases (area under receiver-operator characteristic curve-AUROC of 0.98);
- A molecular test that differentiates relapsing-remitting MS from progressive MS variants (AUROC of 0.91); and
- A molecular test that predicts future rates of disability progression, concordance coefficient of 0.425 (p<0.001).
Because these results are derived from a single research center (NIAID/NDS), it is imperative to determine their performance in real clinical practice settings as a necessary step for their potential regulatory approval.
Consequently, his application has 2 specific aims:
AIM 1. To independently validate afore-mentioned CSF-biomarker-based tests for their clinical value within the multicenter Spinal fluid Consortium for MS (SPINCOMS). In Aim 1, each of the 3 defined tests will be validated in 100 new SPINCOMS patients. To validate the prognostic test, 100 MS patients with CSF collected at least 3 years ago will be evaluated at follow-up examination with standardized clinical outcomes. CSF will be analyzed blinded using pre-defined statistical models.
AIM 2. To explore whether collected CSF-biomarkers point towards pathogenic heterogeneity that may predict patient-specific efficacy for different disease-modifying treatments (DMTs) or identify pathogenic mechanisms not targeted by current DMTs. In Aim 2, clustering analysis will assess pathogenic heterogeneity and explore potential predictors of response to therapy.
Study Type
Enrollment (Actual)
Phase
- Not Applicable
Contacts and Locations
Study Locations
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Missouri
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St Louis, Missouri, United States, 63110
- Washington University in St Louis
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Sampling Method
Study Population
Relapsing-remitting multiple sclerosis patients
Progressive multiple sclerosis patients
Patients with non-inflammatory neurological diseases (NIND): e.g., ischemic-gliotic changes, CADASIL and other leukodystrophies, migraines, ischemic spinal cord lesions.
Patients with other inflammatory neurological diseases (OIND):e.g. CNS Sjogren's, SLE, vasculitis, CNS infections, MOG-associated disorders, NMO spectrum disorders (NMOSD)
Description
MS Patients selection criteria
- Lumbar puncture (LP) in the untreated stage with cryopreserved CSF (serum/blood optional) with consent to use it for future research
- ≥ 3 and ≤ 10 years of follow-up from LP
- At time of LP untreated and not treated with steroid or off steroids ≥ one month
- Available/willing to come for in-person follow-up
- Available/willing to sign the NIH 09-I-0032 "Sample processing only" consent form
- Diagnosis of MS based on 2017 McDonald criteria at time of follow-up visit
Non-MS Patients selection criteria Required: 25 Non-Inflammatory Neurological Disease (NIND), 25 Other Inflammatory Neurological Disease (OIND)
- Lumbar puncture (LP) in the untreated stage with cryopreserved CSF (serum/blood optional) with consent to use it for future research
- ≥ 3 and ≤ 10 years of follow-up from LP
- At time of LP untreated and not treated with steroid or off steroids ≥ one month
- Up to date contact information
- Available/willing to sign the NIH 09-I-0032 "Sample processing only" consent form
- Diagnosis:
NIND: e.g., ischemic-gliotic changes, CADASIL and other leukodystrophies, migraines, ischemic spinal cord lesions etc OIND: e.g. CNS Sjogren's, SLE, vasculitis, CNS infections, MOG-associated disorders, NMO spectrum disorders (NMOSD)
Study Plan
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
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Relapsing Remitting Multiple Sclerosis
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Progressive Multiple Sclerosis
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Non-Inflammatory Neurological Diseases
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Other Non-Inflammatory Neurological Diseases
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What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Biomarker Predicted Outcomes against NeurEx-based outcomes
Time Frame: 3 years
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CSF-biomarker-predicted outcomes against measured NeurEx-based outcomes, considering a Bonferroni-adjusted significance level 0.05/3 = 0.017 (to adjust for 3 tests).
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3 years
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MS Severity Model Analyses
Time Frame: 3 years
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As secondary analyses of MS severity model,assessment of correlations between CSF-biomarker-predicted outcomes and more traditional MS outcomes.
Specifically, correlate CSF-biomarker-based scores of MS severity and MSSS, ARMSSS and by MS-DSS, calculated from the follow-up visit scores.
Based on power calculations, 100 relevant patients/classifier will provide > 90% power to externally validate all 3 Somascan CSF-biomarker-based models.
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3 years
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Collaborators and Investigators
Publications and helpful links
General Publications
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Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Actual)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Estimated)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- 202004205
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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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