Evidence map›Paper›PMID 40998429›Full record

Observational studyBMJ open2025

Single-centre, prospective cohort to predict optimal individualised treatment response in multiple sclerosis (POINT-MS): a cohort profile.

Ronja Christensen, Alessandro Cruciani, Sarmad Al-Araji, Alessia Bianchi, Declan Chard, Samih Fourali, Weaam Hamed, Ahmed Hammam, Anna He, Baris Kanber and 18 more

Abstract readObservational Study
In one paragraph

Observational study in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Data-Driven Fatigue Trajectories in Multiple Sclerosis and Their Predictors.Neurology(R) neuroimmunology & neuroinflammation · 2026
    Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

28 authors.

Ronja ChristensenUCL Queen Square Institute of Neurology, UCL, London, UK ronja.christensen@ucl.ac.uk.ORCID http://orcid.org/0000-0002-5101-0896
Alessandro CrucianiQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Sarmad Al-ArajiQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Alessia BianchiQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Declan ChardQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Samih FouraliQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Weaam HamedQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Ahmed HammamQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Anna HeQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Baris KanberQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Davide MaccarroneQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Marcello MocciaQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Suraya MohamudQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Riccardo NistriQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Anestis PassalisQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.ORCID http://orcid.org/0009-0008-9031-1107
Valeria PozzilliQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Ferran Prados CarrascoQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Eirini SamdanidouQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Joy SongQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Jed WingroveQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Charmaine YamQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Marios YiannakasQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Alan J ThompsonQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Ahmed ToosyQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Yael HacohenQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Frederik BarkhofQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
Olga CiccarelliQueen Square MS Centre, Department of Neuroinflammation, UCL, London, UK.
POINT-MS Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeMultiple sclerosis (MS) is a chronic neurological condition that affects approximately 150 000 people in the UK and presents a significant healthcare burden, including the high costs of disease-modifying treatments (DMTs). DMTs have substantially reduced the risk of relapse and moderately reduced disability progression. Patients exhibit a wide range of responses to available DMTs. The Predicting Optimal INdividualised Treatment response in MS (POINT-MS) cohort was established to predict the individual treatment response by integrating comprehensive clinical phenotyping with imaging, serum and genetic biomarkers of disease activity and progression. Here, we present the baseline characteristics of the cohort and provide an overview of the study design, laying the groundwork for future analyses.

participantsPOINT-MS is a prospective, observational research cohort and biobank of 781 adult participants with a diagnosis of MS who consented to study enrolment on initiation of a DMT at the Queen Square MS Centre (National Hospital of Neurology and Neurosurgery, University College London Hospital NHS Trust, London) between 01/07/2019 and 31/07/2024. All patients were invited for clinical assessments, including the expanded disability status scale (EDSS) score, brief international cognitive assessment for MS and various patient-reported outcome measures (PROMs). They additionally underwent MRI at 3T, optical coherence tomography and blood tests (for genotyping and serum biomarkers quantification), at baseline (i.e., within 3 months from commencing a DMT), and between 6-12 (re-baseline), 18-24, 30-36, 42-48 and 54-60 months after DMT initiation. FINDINGS TO DATE: 748 participants provided baseline data. They were mostly female (68%) and White (75%) participants, with relapsing-remitting MS (94.3%), and with an average age of 40.8 (±10.9) years and a mean disease duration of 7.9 (±7.4) years since symptom onset. Despite low disability (median EDSS 2.0), cognitive impairment was observed in 40% of participants. Most patients (98.4%) had at least one comorbidity. At study entry, 59.2% were treatment naïve, and 83.2% initiated a high-efficacy DMT. Most patients (76.4%) were in either full- or part-time employment. PROMs indicated heterogeneous impairments in physical and mental health, with a greater psychological than physical impact and with low levels of fatigue. When baseline MRI scans were compared with previous scans (available in 668 (89%) patients; mean time since last scan 9±8 months), 26% and 8.5% of patients had at least one new brain or spinal cord lesion at study entry, respectively. Patients showed a median volume of brain lesions of 6.14 cm FUTURE PLANS: Modelling with both standard statistics and machine learning approaches is currently planned to predict individualised treatment response by integrating all the demographic, socioeconomic, clinical data with imaging, genetic and serum biomarkers. The long-term output of this research is a stratification tool that will guide the selection of DMTs in clinical practice on the basis of the individual prognostic profile. We will complete long-term follow-up data in 4 years (January 2029). The biobank and MRI repository will be used for collaborative research on the mechanisms of disability in MS.

Indexed as

Multiple SclerosisAdultBiomarkersDisability EvaluationDisease ProgressionFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedPatient Reported Outcome MeasuresPrecision MedicineProspective StudiesTreatment OutcomeBiomarkersClinical Decision-MakingCognitionDrug UtilizationMagnetic Resonance ImagingMultiple sclerosis

Identifiers

PMID40998429
PMCPMC12481372

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.