SPINCOMS Biomarker Study

Not Applicable

Active, not recruiting

• Conditions: Multiple Sclerosis
• Interventions: Device: SOMAscan

• Registration Number: NCT04496830
• Lead Sponsor: Washington University School of Medicine

Brief Summary

To determine if biomarker-based CSF testing is reliably detecting differences between patients with Multiple Sclerosis (MS), different MS-subtypes, and other central nervous system (CNS) diseases. This study will also look to identify biomarkers that could be used for the prediction, at the time of diagnosis, of the future disease clinical course and response to therapy. The SOMAscan assay will be used for CSF samples analysis.

Detailed Description

Using machine learning, the investigators have developed from SOMAScan:

1. 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);

2. A molecular test that differentiates relapsing-remitting MS from progressive MS variants (AUROC of 0.91); and

3. 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, this 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.

Basic Information
|
Recruitment & Eligibility
|
Study & Design
|
Trial Locations

Study Timeline

• Study Start: 2020-06-15
• Study First Submitted: 2020-07-27
• Study First Submitted QC: 2020-07-30
• Study First Posted: 2020-08-03
• Status Verified: 2023-04
• Last Update Submitted: 2023-04-28
• Last Update Posted: 2023-05-01
• Primary Completion: 2023-12-01
• Study Completion: 2024-03-01

Recruitment & Eligibility

• Status: ACTIVE_NOT_RECRUITING
• Sex: All
• Target Recruitment: 160

Inclusion Criteria

Not provided

Read More

Exclusion Criteria

Not provided

Read More

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: PARALLEL

Arm && Interventions

Group	Intervention	Description
Non-Inflammatory Neurological Diseases	SOMAscan	* Clinical data questionnaire * CSF Analysis
Progressive Multiple Sclerosis	SOMAscan	* Blood sample collection * Vital signs, weight, height and BMI. * Complete neurological examination documented in NeurEx (recorded with an iPAD). * Clinical data questionnaire * 25FW \& non-dominant hand 9HPT (required for calculating CombiWISE \& MS-DSS). * Smartphone Apps (include 25FW, SDMT and tests that correlate highly w 9HPT - can be acquired in patient-autonomous manner with minimal assistance). * Optical Coherence Tomography (OCT) * CSF Analysis
Relapsing Remitting Multiple Sclerosis	SOMAscan	* Blood sample collection * Vital signs, weight, height and BMI. * Complete neurological examination documented in NeurEx (recorded with an iPAD). * Clinical data questionnaire * 25FW \& non-dominant hand 9HPT (required for calculating CombiWISE \& MS-DSS). * Smartphone Apps (include 25FW, SDMT and tests that correlate highly w 9HPT - can be acquired in patient-autonomous manner with minimal assistance). * Optical Coherence Tomography (OCT) * CSF Analysis
Other Non-Inflammatory Neurological Diseases	SOMAscan	* Clinical data questionnaire * CSF Analysis

Primary Outcome Measures

Name	Time	Method
Biomarker Predicted Outcomes against NeurEx-based outcomes	3 years	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).
MS Severity Model Analyses	3 years	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.

Trial Locations

Locations (1)

Washington University in St Louis; 🇺🇸 Saint Louis, Missouri, United States