Evidence map›Paper›PMID 41568556›Full record

ArticleArthritis care & research2026

Use of a Molecular Signature Response Classifier to Inform Treatment Selection Improves Clinical Disease Activity Among Patients with Rheumatoid Arthritis Initiating a Biologic or Targeted Synthetic Disease-Modifying Antirheumatic Drug.

Fenglong Xie, Timothy Beukelman, Nicholas P McCormick, Jeffrey R Curtis

Abstract read
In one paragraph

Article in Arthritis care & research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

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5 · Who and what money

Authors and funding

4 authors.

Fenglong XieFoundation for Advancing Science, Technology, Education and Research, Birmingham, Alabama.
Timothy BeukelmanFoundation for Advancing Science, Technology, Education and Research, Birmingham, Alabama.
Nicholas P McCormickFoundation for Advancing Science, Technology, Education and Research, Birmingham, Alabama.
Jeffrey R CurtisFoundation for Advancing Science, Technology, Education and Research, Birmingham, Alabama.ORCID https://orcid.org/0000-0002-8907-8976

Funding

Scipher Medicine
6 · The paper itself

Abstract

objectiveWe assessed the effectiveness of PrismRA to improve clinical outcomes among patients with rheumatoid arthritis (RA) initiating treatment with a biologic or targeted synthetic disease-modifying antirheumatic drug (b/tsDMARD).

methodsPrismRA incorporated 19 gene expression features and four clinical features to assess a patient's likelihood of inadequate response to tumor necrosis factor inhibitor (TNFi). PrismRA was assessed in a prospective, interventional cohort study of patients initiating treatment with a b/tsDMARD. PrismRA results were provided to treating rheumatologists and incorporated into the selection of TNFi vs non-TNFi for study treatment. External comparator patients were identified in a rheumatology provider electronic health records system and matched to PrismRA patients using propensity scores. All patients had moderate-high disease activity at baseline. The primary study outcome was achievement of minimal important difference (MID) in clinical disease activity index (CDAI) at 24 weeks. Last observation carried forward was used to impute missing data.

resultsThere were 330 PrismRA cohort patients and 990 matched comparator patients. Key baseline patient characteristics were all well-balanced between cohorts. Study treatment selection was consistent with PrismRA results in 82% of PrismRA cohort patients. CDAI MID at 24 weeks was achieved by 63.0% of PrismRA patients and 42.4% of comparator patients (odds ratio 2.31, confidence interval 1.79-2.99).

conclusionPrismRA results informing selection of TNFi vs non-TNFi treatment was associated with better CDAI outcomes compared to matched external comparator patients. PrismRA testing helps fill the need for a precision medicine approach to more rapidly identify the most effective therapy for individual patients with RA.

Indexed as

Antirheumatic AgentsArthritis, RheumatoidBiological ProductsGene Expression ProfilingAdultAgedFemaleHumansMaleMiddle AgedProspective StudiesSeverity of Illness IndexTreatment Effect HeterogeneityTreatment OutcomeAntirheumatic AgentsBiological Products

Identifiers

PMID41568556
PMCPMC13511282

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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.