CNS Open Data
Latest UpdatesOpen DatasetsClinical TrialsResearch GuidesTrend ReportsGlossaryData SourcesAbout

Medical & Academic Disclaimer: CNS Open Data is an academic neuroinformatics platform indexing open research datasets, preprints, and clinical trial pipelines for researchers and data scientists. Content on this site does not constitute medical advice, clinical diagnosis, or treatment recommendations.

CNS Open Data— Open Science Portal for Central Nervous System Research|Research Guides|Trend Reports|Glossary|Ranking|Open Datasets|About|Privacy Policy|Contact
AlzforumOpenNeuroDANDI ArchiveAgora (AMP-AD)
HomeClinical Trial & PipelineMSBase & BigMS Harmonized Cohort: Quantifying Progression Independent of Relapse Activity (PIRA) Under High-Efficacy DMTs
MS Data AllianceMultiple SclerosisClinical Trial & PipelineFAIR Metadata / APIDUA / Approval Req
MSBase DUA / Academic Consortium

MSBase & BigMS Harmonized Cohort: Quantifying Progression Independent of Relapse Activity (PIRA) Under High-Efficacy DMTs

August 1, 2026
Kalincik T, Butzkueven H, Tur C, MSBase Study Group
DOI: 10.1001/jamaneurol.2022.4655

Study Design & Technical Specifications

Sample Size / Cohort

48,000+ Longitudinal MS Patients

Subject / Study Model

Human Clinical Cohort

Analytical Modalities

Longitudinal EDSSClinical MetricsOMOP CDM

Primary Abstract & Repository Description

Source: MS Data Alliance
Multi-center longitudinal real-world evidence study evaluating roving-baseline EDSS trajectories, Relapse-Associated Worsening (RAW) versus PIRA rates, and early anti-CD20 / natalizumab intervention across harmonized international MS registries.
CNS Open Data Deep Research Brief

Editorial Critique, Methodological Value & Reusability Guide

Structured via CNS Domain Knowledge Engine

1. Scientific Context & Premise

Primary Premise (MS Data Alliance): "Multi-center longitudinal real-world evidence study evaluating roving-baseline EDSS trajectories, Relapse-Associated Worsening (RAW) versus PIRA rates, and early anti-CD20 / natalizumab intervention across harmonized international MS registries." Within Multiple Sclerosis (MS), this work examines Multiple Sclerosis, PIRA, EDSS, MSBase, Real-World Evidence in relation to paramagnetic rim lesions (PRLs), T2/FLAIR lesion volume, oligoclonal bands, EBV titers, and EDSS progression metrics. Authored by Kalincik T, Butzkueven H, Tur C.

2. Study Architecture & Findings

Study Architecture: Human Clinical Cohort (48,000+ Longitudinal MS Patients) utilizing Longitudinal EDSS, Clinical Metrics, OMOP CDM [DOI: 10.1001/jamaneurol.2022.4655]. Key reported conclusion: "Multi-center longitudinal real-world evidence study evaluating roving-baseline EDSS trajectories, Relapse-Associated Worsening (RAW) versus PIRA rates, and early anti-CD20 / natalizumab intervention across harmonized international MS registries."

3. Secondary Analysis & Reusability

Secondary Analysis Applications: (1) Cross-referencing Longitudinal EDSS, Clinical Metrics, OMOP CDM variables (Multiple Sclerosis, PIRA, EDSS, MSBase, Real-World Evidence) against open repositories in Multiple Sclerosis (MS); (2) Benchmarking feature distributions and effect sizes reported in "MSBase & BigMS Harmonized Cohort: Quantifying Progression Independent of Relapse"; (3) Informing cohort stratification and endpoint selection.

4. Methodological Caveats & Governance

Methodological Note: When integrating these Longitudinal EDSS, Clinical Metrics, OMOP CDM findings, account for cohort-specific inclusion criteria (48,000+ Longitudinal MS Patients), potential site/instrument batch effects, and repository license terms (MSBase DUA / Academic Consortium).

Related CNS Open Data Research Playbooks & Methodology Guides
Multiple Sclerosis (MS) Open Data Guide: Federated Real-World Data (OMOP CDM) & MRI Lesion Analysis
10 min read • Open Playbook
Advanced MS Neuroimaging Pipeline: Automated Lesion Segmentation, Paramagnetic Rim Lesions (PRLs) & Spinal Cord Atrophy Quantification
14 min read • Open Playbook

Data Access, Reproducibility & Analysis Starter Guide

FAIR Open Science & Clinical Metadata Verification Protocol

FAIR Metadata / API

Quick Data Access & Structured Export

Open the primary repository directly or download structured metadata (JSON / CSV) in one click.

Open Primary Data (MS Data Alliance)

This resource is indexed under FAIR (Findable, Accessible, Interoperable, and Reusable) open-science metadata standards, enabling programmatic cross-referencing across Europe PMC, Semantic Scholar, ClinicalTrials.gov, and CNS Open Data.

Programmatic Data Retrieval (Python Starter Code & Recommended SDKs)

Python Quickstart: Query Europe PMC & Semantic Scholar Metadata

# Fetch structured bibliographic & open-access data via Europe PMC REST API
import urllib.request
import urllib.parse
import json

query = "DOI:\"10.1001/jamaneurol.2022.4655\""
url = f"https://www.ebi.ac.uk/europepmc/webservices/rest/search?query={urllib.parse.quote(query)}&format=json&resultType=core"

with urllib.request.urlopen(url, timeout=10) as response:
    payload = json.loads(response.read().decode("utf-8"))
    results = payload.get("resultList", {}).get("result", [])
    if results:
        record = results[0]
        print("Title:", record.get("title"))
        print("Journal / Source:", record.get("journalTitle") or record.get("bookOrReportDetails"))
        print("Cited By Count:", record.get("citedByCount", 0))

Recommended Open-Source Software & SDKs

NiBabelPython SDK

Read and write access to NIfTI, GIFTI, and BIDS neuroimaging file formats in Python.

Scanpy (scverse)Python / AnnData

Scalable Python toolkit for analyzing AnnData (.h5ad) single-cell gene expression matrices.

Standardized 4-Step Workflow & Governance Checklist

Standardized Acquisition & Preprocessing Workflow

1. Programmatic Metadata & Full-Text OA Retrieval

Query Europe PMC or Crossref REST APIs using the persistent DOI/URL to retrieve structured XML full text, supplementary tables, and grant links.

2. Study Design & Cohort Eligibility Screening

Extract sample size, inclusion/exclusion criteria, and primary outcome endpoints for systematic review (PRISMA) inclusion.

3. Data Availability & Supplementary Repository Linkage

Locate accession numbers (GEO, SRA, OpenNeuro, DANDI, Zenodo, Figshare) referenced in the Data Availability section.

4. Citation Graph & Replication Tracking

Monitor supporting and contrasting citations over time to verify whether key findings have been independently replicated.

Reproducibility & Governance Checklist

  • Verify whether the source is a peer-reviewed journal publication or an unrefereed preprint before clinical citation.
  • Check supplementary data licenses (CC-BY / CC0) when extracting figures or summary statistics for meta-analyses.
  • Cross-reference NCT clinical trial identifiers when evaluating therapeutic efficacy or biomarker endpoints.

Tags & Modalities

Longitudinal EDSSClinical MetricsOMOP CDM#Multiple Sclerosis#PIRA#EDSS#MSBase#Real-World Evidence#Anti-CD20

Bibliometrics, Peer-Review Status & Citation Export

Cross-referenced via Semantic Scholar, Europe PMC & bioRxiv

1. Citation Metrics & Context Breakdown

0
Total Citations
0
Influential Citations

Citation Context Breakdown

Citation intent breakdown (Supporting vs. Contrasting) is currently accumulating in Semantic Scholar for this record. Researchers reusing this resource should cite the primary DOI/URL using the standardized formats below.

2. Peer-Review Validation & Revision History

Verified Publication / Open Dataset Record

Metadata and license integrity verified against primary repository records.

3. Standardized Academic Citation & BibTeX Export

Selected Format (APA)
Kalincik T et al. (2026). MSBase & BigMS Harmonized Cohort: Quantifying Progression Independent of Relapse Activity (PIRA) Under High-Efficacy DMTs. MS Data Alliance. https://doi.org/10.1001/jamaneurol.2022.4655
BibTeX Entry (LaTeX / Reference Managers)
@article{t2026msba,
  title = {MSBase & BigMS Harmonized Cohort: Quantifying Progression Independent of Relapse Activity (PIRA) Under High-Efficacy DMTs},
  author = {Kalincik T and Butzkueven H and Tur C and MSBase Study Group},
  year = {2026},
  journal = {MS Data Alliance},
  howpublished = {\url{https://www.msbase.org/}},
  doi = {10.1001/jamaneurol.2022.4655},
  note = {CNS Open Data: multiple_sclerosis}
}

Related Multiple Sclerosis Research & Datasets

Explore All Datasets
Clinical Trial & PipelineMS Data Alliance

MSDA: COVID19 GDSI LocalDashboard - Federated MS Data Toolkit

Official open-source repository and tool for Multiple Sclerosis federated research and data harmonization under MS-DATA-ALLIANCE.

7/31/2022Read Analysis
Clinical Trial & PipelineMS Data Alliance

Global Data Sharing Initiative (GDSI): Containerized Federated Analysis Pipeline for MS Registries

International federated research initiative and containerized query framework allowing participating national MS registries to analyze disease-modifying therapy (DMT) safety, anti-CD20 outcomes, and PIRA progression without transferring identifiable patient data.

6/15/2026Read Analysis
Peer-Reviewed PaperEurope PMC

Multiple Sclerosis and Viruses: « Liaisons Dangereuses ».

Multiple sclerosis (MS) is a complex, multifactorial neurodegenerative disease with an aetiology that is still partially elusive. Several risk factors are associated with MS development including genetic predisposition and various environmental stressors; however, recently, viral infections have gained significant attention as a crucial environmental trigger. Despite the well-established link between Epstein-Barr virus (EBV) and MS susceptibility, a single-pathogen model fails to clearly characterise the molecular cascades driving the disease, suggesting that the transition from infection to autoimmune response involves more than one viral agent. In this review we examine the speculation that the interactions among different neurotropic viruses could serve a collective causative role in MS, which is under-researched in the literature at present. We summarise contradictory evidence on the role of different viral agents, including the Herpesviridae family (Human Cytomegalovirus, EBV, Herpes Simplex Viruses HSV-1 and HSV-2, and Varicella Zoster Virus), Paramyxoviridae family (Measles Virus and Rubella Virus), Influenza virus, SARS-CoV-2, and Human Endogenous Retroviruses (HERVs). Through interplay within shared molecular pathways, immune modulation, and activation of latent infections, these viruses may collectively influence the inflammatory and demyelinating processes that characterise MS. This review evaluates the etiological role of viral interplay in MS through the cumulative and interactive effects of these pathogens. The available epidemiological, immunological, and experimental data converge on the concept that viral co-exposures act synergistically to shape MS susceptibility in genetically predisposed individuals. Characterising these viral interactions presents a new research direction for the identification of novel biomarkers and the development of preventative strategies through the targeted control of viral networks.

11/1/2026Read Analysis
PreprintmedRxiv (Neurology)

CNM-Au8 Treatment Is Associated With Reduced Chronic Lesion Tissue Expansion in Relapsing-Remitting Multiple Sclerosis

BackgroundCNM-Au8, a catalytic nanocrystalline gold suspension, is proposed to support neuronal bioenergetics, but its effect on chronic lesion evolution in multiple sclerosis (MS) has not been reported. ObjectivesTo evaluate the effect of CNM-Au8 on chronic lesion tissue expansion (CLTE). Results...

9/25/2026Read Analysis
Database / PortalMS Data Alliance

MSDA Core Dataset (CDS): Standardized Global Real-World Data Harmonization Framework for Multiple Sclerosis

The MSDA Core Dataset (CDS) establishes a 44-variable international harmonization schema mapped to the OMOP Common Data Model, enabling privacy-preserving federated analytics across global Multiple Sclerosis registries.

8/12/2026Read Analysis
Database / PortalMS Data Alliance

MSDA Global Registry & Cohort Metadata Discovery Catalogue (BigMS Network)

A centralized metadata discovery catalogue indexing over 30 national and international MS registries (>120,000 patients), detailing variable availability for EDSS, relapse history, MRI, fluid biomarkers, and DUA governance.

7/24/2026Read Analysis

Active Clinical Trials & Pipeline in Multiple Sclerosis

View Clinical Pipeline
MSBASE-GLOBAMultiple Sclerosis

MSBase & BigMS Harmonized Cohort: Quantifying Progression Independent of Relapse Activity (PIRA) Under High-Efficacy DMTs

MS Data Alliance
MSDA-COVID19MSDA

Global Data Sharing Initiative (GDSI): Containerized Federated Analysis Pipeline for MS Registries

MS Data Alliance
MSDA-GH-GDSIMultiple Sclerosis

MSDA: GDSI Mock DataGenerator - GDSI Mock data generator

MS Data Alliance

Related Data & Resources

Open Datasets

Explore Related Datasets

Find neuroimaging or multi-omics datasets relevant to this topic.

Clinical Trials

View Clinical Pipeline

Check investigational drugs, clinical trials, and clinical guidelines.

Academic Research & Medical Information Disclaimer

This page provides structured scientific metadata, methodological critiques, and open-data reusability guidelines intended strictly for neuroscience researchers and data scientists. It does not constitute medical advice, clinical diagnosis, or treatment recommendations.

Was this resource helpful?

Help improve data curation by sharing your feedback.

Open Source