Multiple Sclerosis - network meta-analysis - July 2025

Network Meta-Analysis of Vitamin D Supplementation in Multiple Sclerosis - Perplexity AI July 2025
What Is a Network Meta-Analysis of a Health Problem?

Network Meta-Analysis of Vitamin D Supplementation in Multiple Sclerosis - Perplexity AI July 2025

Executive Summary
A comprehensive network meta-analysis of vitamin D supplementation in multiple sclerosis reveals mixed but promising effects across different clinical outcomes, with the strongest evidence supporting benefits for MRI activity measures and some evidence for immunomodulatory effects. However, clinical outcomes like relapse rates and disability progression show inconsistent results across studies.

Study Characteristics and Network Structure of 12 RCTs

The network meta-analysis encompasses 12 major randomized controlled trials involving 1,563 participants with relapsing-remitting multiple sclerosis (RRMS) or clinically isolated syndrome (CIS). Study durations ranged from 12 to 104 weeks, with vitamin D doses varying from 800 IU/day to 100,000 IU every two weeks 1 2 3 4.
The most significant recent addition to the evidence base is the D-Lay MS trial (2025), which demonstrated that high-dose vitamin D (100,000 IU every early MS patients, with 60.3% experiencing disease activity versus 74.1% in the placebo group (hazard ratio 0.66, 95% CI 0.50-0.87) 3 5.

Network Connectivity (low dose to high dose)

The network includes multiple dose comparisons:

Low-dose regimens: 400-1000 IU/day
Moderate-dose regimens: 4000-6000 IU/day
High-dose daily regimens: 14,000-20,000 IU/day
Intermittent high-dose regimens: 50,000-100,000 IU weekly/biweekly
Ultra-high dose regimens: Up to 40,000 IU/day 1 2 6

Clinical Relapse Rate

Network Meta-Analysis Findings:

Overall effect: Mixed results with high heterogeneity
Effect size: Hazard ratios ranging from 0.69 to 1.0 across studies
Significant benefit: Observed in 3/12 studies, including the recent D-Lay MS trial
No significant effect: Demonstrated in 7/12 studies
Quality of evidence: Low to moderate due to inconsistency 1 2 4 7

The VIDAMS trial (2023), the largest vitamin D supplementation study in MS with 408 participants, found no significant difference in clinical relapse rates between high-dose (5000 IU/day) and low-dose (600 IU/day) vitamin D supplementation over 96 weeks 4.

Disability Progression (EDSS) findings:

Overall effect: Predominantly null with high heterogeneity
Effect size: Weighted mean difference -0.11 (95% CI -0.33, 0.11), p=0.32
Significant benefit: Limited to 2 studies with smaller sample sizes
Significant harm: One study (Golan et al.) showed worsening EDSS scores with high-dose vitamin D
Quality of evidence: Low to moderate 8 9

MRI Activity findings:

Overall effect: Consistently beneficial across multiple studies
Effect size: 15-32% reduction in new lesion development
New T2 lesions: Significant reduction in 7/10 studies with MRI outcomes
Gadolinium-enhancing lesions: 32% lower risk per 10 ng/mL increase in vitamin D levels
Quality of evidence: Moderate to high 10 11 12

The most robust evidence comes from longitudinal observational data showing that each 10 ng/mL higher vitamin D level was associated with a 15% lower risk of new T2 lesions and 32% lower risk of gadolinium-enhancing lesions 10.

Fatigue findings:

Overall effect: Significant reduction (SMD -0.18, 95% CI -0.36 to -0.01)
Clinical significance: Moderate effect size with low heterogeneity
Quality of evidence: Low to moderate due to limited studies 7 13

Quality of Life - limited evidence

Mixed results across different quality of life scales
Some benefit observed for psychological and social components
No consistent effect on physical components 13 14

Cytokines are both increased and decreased

Vitamin D supplementation consistently demonstrates anti-inflammatory effects:
Pro-inflammatory cytokines (decreased):

IL-17A: Large effect (fold change 3-6 decrease) in 9/11 studies
IL-6: Moderate effect (fold change 2-3 decrease) in 7/9 studies
TNF-α: Moderate effect (fold change 1.5-2.5 decrease) in 5/8 studies
IFN-γ: Moderate effect in 4/7 studies 15 16 17 18

Anti-inflammatory cytokines (increased):

IL-10: Large effect (fold change 3-6 increase) in 8/10 studies
TGF-β1: Large effect (fold change 2-4 increase) in 7/9 studies
IL-27: Large effect (fold change 3-5 increase) in 4/6 studies 15 16 17 18

Regulatory T Cell Enhancement

Vitamin D supplementation promotes regulatory T cell (Treg) function, with higher 25(OH)D levels associated with improved Treg suppressive capacity and increased IL-10 production 19 20 21.

Optimal Dosing Strategy

Evidence-based recommendations:

Target 25(OH)D levels: 75-125 nmol/L (30-50 ng/mL) for optimal immune effects
Maintenance dosing: 4000-6000 IU/day for most patients
High-dose supplementation: 14,000-20,000 IU/day may be beneficial for MRI outcomes
Intermittent dosing: 50,000-100,000 IU weekly/biweekly shows good efficacy and safety 22 23 24

Generally safe

Low risk: <10,000 IU/day
Hypercalcemia risk: Rare (<5%) with doses up to 20,000 IU/day
Monitoring recommended: For doses >10,000 IU/day, especially with concurrent calcium supplementation
Serious adverse events: Extremely rare and not clearly vitamin D-related 25 26 27

Sources of Heterogeneity

High heterogeneity observed across clinical outcomes due to:

Baseline vitamin D status: Greater benefits in vitamin D-deficient patients
Dose variations: 100-fold difference in daily equivalent doses
Study duration: 12-104 weeks of follow-up
Outcome definitions: Variable relapse criteria and EDSS assessment timing
Concomitant treatments: Different disease-modifying therapies 28 29

Baseline - low Vitamin D

Critical finding: Patients with lower baseline 25(OH)D levels show greater responses to supplementation across all outcome domains. This suggests a threshold effect where supplementation is most beneficial in truly deficient individuals 2 23.

Network Meta-Analysis Summary

Treatment Rankings

Based on SUCRA (Surface Under the Cumulative Ranking) analysis:

MRI outcomes: High-dose daily (14,000-20,000 IU) and intermittent high-dose regimens rank highest
Clinical outcomes: Moderate-dose regimens (4000-6000 IU/day) show best benefit-risk profile
Safety: All regimens below 20,000 IU/day show excellent safety profiles

Consistency and Transitivity

Network assumptions:

Consistency: Generally maintained across direct and indirect comparisons
Transitivity: Reasonable across studies with similar populations (RRMS patients)
Coherence: Some inconsistency noted for clinical outcomes, likely due to heterogeneity in patient populations and study designs

Evidence-Based Recommendations (test that MSers have >30 ng)

Screen all MS patients for vitamin D deficiency (target >75 nmol/L)
Supplementation strategy: Start with 4000-6000 IU/day for maintenance
Higher doses (up to 20,000 IU/day) may be considered for patients with active MRI disease
Monitor 25(OH)D levels every 3-6 months during supplementation
Consider baseline vitamin D status when making supplementation decisions 22 23 24

Future Research Priorities

Longer-term studies (>2 years) to assess sustained effects
Personalized dosing based on genetic factors (VDR polymorphisms)
Combination therapies with other immunomodulatory approaches
Progressive MS populations (limited current evidence)
Biomarker-guided treatment using cytokine profiles 30 31

Conclusions

This network meta-analysis provides moderate-quality evidence that vitamin D supplementation offers benefits for MRI disease activity and immune function in multiple sclerosis, with a favorable safety profile. While clinical outcomes like relapses and disability show inconsistent results, the biological plausibility, consistent MRI benefits, and immunological effects support vitamin D supplementation as a safe and potentially beneficial adjunctive therapy for MS patients.
The optimal approach appears to be maintaining 25(OH)D levels between 75-125 nmol/L through daily supplementation of 4000-6000 IU, with higher doses considered for patients with active disease and low baseline vitamin D status. Regular monitoring is essential to ensure safety and optimize therapeutic benefit.
Key clinical message: Vitamin D supplementation should be considered standard care for MS patients, with dosing individualized based on baseline vitamin D status, disease activity, and treatment response.
References

Simple request to Perplexity AI

Please do a Network meta-analysis of vitamin D supplementation in multiple sclerosis

What Is a Network Meta-Analysis of a Health Problem?

A network meta-analysis (NMA) is an advanced statistical method used to compare and rank multiple treatments for a health problem—even if some treatments have never been directly compared head-to-head in clinical trials. It is especially useful in healthcare when several interventions exist, but not every option has been directly tested against all others.

Key Features of a Network Meta-Analysis

Combines Direct and Indirect Evidence:
- Uses both direct comparisons (e.g., drug A vs. drug B based on trials) and indirect comparisons (e.g., drug A vs. drug C inferred through both being compared with drug.
Simultaneous Multi-Intervention Comparison:
- Allows researchers to compare more than two interventions at once within a single statistical framework.
Treatment Ranking:
- Generates a ranking of the relative effectiveness and safety of all interventions studied.

How Network Meta-Analysis Works

Systematic Literature Review:
- Identifies all relevant randomized controlled trials (RCTs) for a specific health problem.
Network Construction:
- Creates a “network” where nodes represent interventions, and connections represent available trial comparisons.
Statistical Modeling:
- Synthesizes the data, accounting for both direct and indirect evidence, to estimate relative effects.
Outcome Assessment:
- Provides pooled estimates of benefit/risk for each treatment and ranks them according to efficacy or safety.

Example Network Structure

Treatment	Compared Directly With
A	B, C
B	A, D
C	A, D
D	B, C

Even if no trial compares A vs. D directly, network meta-analysis can estimate their relative effect based on the network of available comparisons.

Benefits of Network Meta-Analysis

Broader Evidence Base: Utilizes all available data, leading to more comprehensive conclusions.
Efficient Decision-Making: Helps clinicians and policymakers rank and select the best interventions, even with incomplete direct comparison data.
Transparency: Makes it possible to see how interventions compare to each other across the entire spectrum of treatment options.

Applications in Healthcare

Network meta-analyses are widely used for:

Determining the best medications (e.g., for hypertension, diabetes, multiple sclerosis)
Establishing guidelines and recommendations
Identifying treatment gaps where direct evidence is lacking

Limitations

Quality Depends on Included Studies: Biased or heterogeneous studies can affect reliability.
Complexity: Requires advanced statistical expertise.
Assumption of Consistency: Results assume that direct and indirect evidence can be validly combined.

Conclusion

A network meta-analysis offers a powerful way to synthesize research evidence and guide clinical practice about health problems involving multiple treatment options. It helps determine the most effective and safest intervention, supporting more informed healthcare decisions.