Evidence map›Paper›PMID 36909600›Full record

ArticleResearch square2023

Patterns in the sequential treatment of rheumatoid arthritis patients starting a b/tsDMARD: 10-year experience from a US-based registry.

Anton Matsson, Daniel H Solomon, Margaux M Crabtree, Ryan W Harrison, Heather J Litman, Fredrik D Johansson

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Article in Research square, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Anton MatssonChalmers University of Technology.ORCID 0000-0003-0729-8754
Daniel H Solomon
Margaux M Crabtree
Ryan W Harrison
Heather J Litman
Fredrik D Johansson

Funding

VERITY: Value and Evidence in Rheumatology using bioInformaTics, and advanced analYticsP30AR072577 · NIAMS · BRIGHAM AND WOMEN'S HOSPITAL · PI Daniel Hal Solomon · 2017 to 2026
$9.8M
NIAMS NIH HHS P30 AR072577
6 · The paper itself

Abstract

Objectives: Developing and evaluating new treatment guidelines for rheumatoid arthritis (RA) based on observational data requires a quantitative understanding of patterns in current treatment practice with biologic and targeted synthetic disease-modifying anti-rheumatic drugs (b/tsDMARDs). Methods: We used data from the CorEvitas RA registry to study patients starting their first b/tsDMARD therapy-defined as the first line of therapy-between 2012 and the end of 2021. We identified treatment patterns as unique sequences of therapy changes following and including the first-line therapy. Therapy cycling was defined as switching back to a treatment from a previously used therapeutic class. Results: 6,015 b/tsDMARD-naive patients (77% female) were included in the analysis. Their median age was 58 years, and their median disease duration was 3 years. In 2012-2014, 80% of the patients started a tumor necrosis factor inhibitor (TNFi) as their first b/tsDMARD. However, the use of TNFi decreased in favour of Janus kinase inhibitors (JAKi) since 2015. While the number of treatment patterns was large, therapy cycling was relatively common. For example, 601 patterns were observed among 1133 patients who changed therapy at least four times, of whom 85.3% experienced therapy cycling. Furthermore, the duration of each of the first three lines of therapy decreased over the past decade. Conclusion: First-line therapy was almost always TNFi, but diversity in treatment choice was high after that. This practice variation allows for proposing and evaluating new guidelines for sequential treatment of RA. It also presents statistical challenges to compare subjects with different treatment sequences.

Indexed as

b/tsDMARDsrheumatoid arthritistreatment patterns

Identifiers

PMID36909600
PMCPMC10002849

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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.