Evidence map›Paper›PMID 34783826›Full record

ArticleJAMA network open2021

Comparison of Dimethyl Fumarate vs Fingolimod and Rituximab vs Natalizumab for Treatment of Multiple Sclerosis.

Jue Hou, Nicole Kim, Tianrun Cai, Kumar Dahal, Howard Weiner, Tanuja Chitnis, Tianxi Cai, Zongqi Xia

Open access · goldAbstract readComparative Study
In one paragraph

Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
3.8field-weighted citation impact, top 6% of its field
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

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.

  1. Rituximab for people with multiple sclerosis.The Cochrane database of systematic reviews · 2025
    Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Clustering Sequence Data with Mixture Markov Chains with Covariates Using Multiple Simplex Constrained Optimization Routine (MSiCOR).Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America · 2024
    Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Therapeutic Advances in Multiple Sclerosis.Frontiers in neurology · 2022
    Review
  17. Comparative effectiveness of natalizumabTherapeutic advances in neurological disorders · 2022
    Article
  18. 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

8 authors at 3 institutions in 1 country.

Jue HouDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Nicole KimDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Tianrun CaiDivision of Rheumatology, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts.
Kumar DahalDivision of Rheumatology, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts.
Howard WeinerDepartment of Neurology, Brigham and Women's Hospital, Boston, Massachusetts.
Tanuja ChitnisDepartment of Neurology, Brigham and Women's Hospital, Boston, Massachusetts.
Tianxi CaiDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Zongqi XiaDepartment of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania.
Harvard University · USBrigham and Women's Hospital · USUniversity of Pittsburgh · US

Funding

Leveraging electronic health records to optimize treatment selection and response in multiple sclerosisR01NS098023 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Zongqi Xia · 2016 to 2026
$4.6M
NINDS NIH HHS R01 NS098023
6 · The paper itself

Abstract

Importance: As disease-modifying treatment options for multiple sclerosis increase, comparisons of the options based on real-world evidence may guide clinical decision-making. Objective: To compare the relapse outcomes between 2 pairs of disease-modifying treatments: dimethyl fumarate vs fingolimod and natalizumab vs rituximab. Design, Setting, and Participants: This comparative effectiveness study integrated data from a clinic-based multiple sclerosis research registry and its linked electronic health records (EHR) system between January 1, 2006, and December 31, 2016, and built treatment groups for each pairwise disease-modifying treatment comparison according to both registry records and electronic prescriptions. Parallel analyses were conducted from October 11, 2019, to July 7, 2021. Main Outcomes and Measures: The main outcomes were the 1-year and 2-year relapse rates as well as the time to relapse. To compare relapse outcomes, the study adjusted for covariates from 2 sources (registry and EHR) and corrected for confounding biases among the covariates by the doubly robust estimation. Results: The study included 4 treatment groups: dimethyl fumarate (n = 260; 198 women [76.2%]; 227 non-Hispanic White individuals [87.3%]; mean [SD] age at diagnosis, 41.7 [10.4] years), fingolimod (n = 267; 190 women [71.2%]; 222 non-Hispanic White individuals [83.1%]; mean [SD] age at diagnosis, 37.9 [9.9] years), natalizumab (n = 204; 160 women [78.4%]; 172 non-Hispanic White individuals [84.3%]; mean [SD] age at diagnosis, 37.2 [10.6] years), and rituximab (n = 115; 83 women [72.2%]; 99 non-Hispanic White individuals [86.1%]; mean [SD] age at diagnosis, 44.1 [11.1] years). No significant differences were found in the relapse outcomes between dimethyl fumarate and fingolimod after correcting for confounding biases and multiple testing (difference in 1-year relapse rate, 0.028 [95% CI, -0.031 to 0.084]; difference in 2-year relapse rate, 0.071 [95% CI, 0.008-0.128]; relative risk of 2-year non-relapse, 0.957 [95% CI, 0.884-1.035] with dimethyl fumarate as reference). When compared with rituximab, natalizumab was associated with a higher relapse rate for all 3 outcomes after bias correction and multiple testing (difference in 1-year relapse rate, 0.080 [95% CI, 0.013-0.137]; difference in 2-year relapse rate, 0.132 [95% CI, 0.043-0.189]; relative risk of 2-year non-relapse, 0.903 [95% CI, 0.822-0.944]). Confounders were identified from EHR data not recorded in the registry data through data-driven feature selection. Conclusions and Relevance: This study reports real-world evidence of equivalent relapse outcomes between dimethyl fumarate and fingolimod and relapse reduction in favor of rituximab relative to natalizumab. This approach illustrates the value of incorporating EHR data as high-dimensional covariates in real-world treatment comparison.

Indexed as

AdultDimethyl FumarateFemaleFingolimod HydrochlorideHumansImmunosuppressive AgentsMaleMiddle AgedMultiple SclerosisMultiple Sclerosis, Relapsing-RemittingNatalizumabRituximabDimethyl FumarateFingolimod HydrochlorideImmunosuppressive AgentsNatalizumabRituximab

Identifiers

PMID34783826
PMCPMC8596196
OpenAlexW3213676036

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.