Evidence map›Paper›PMID 42416060›Full record

Trial reportFrontiers in immunology2026

Early divergence of treatment response trajectories to adalimumab or its biosimilar in active ankylosing spondylitis: consensus clustering analysis of a randomized controlled trial.

Zhiqiang Zhong, Hongjuan Lu, Ting Li, Lingying Ye, Ling Zhou, Xiaobing Wang, Xin Wu, Huji Xu

Abstract readRandomized Controlled TrialClinical Trial, Phase III
In one paragraph

Trial report in Frontiers in immunology, 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

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.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors.

Zhiqiang ZhongDepartment of Rheumatology and Immunology, Shanghai Changzheng Hospital, Naval Medical University, Shanghai, China.
Hongjuan LuDepartment of Rheumatology and Immunology, Shanghai Changzheng Hospital, Naval Medical University, Shanghai, China.
Ting LiDepartment of Rheumatology and Immunology, Shanghai Changzheng Hospital, Naval Medical University, Shanghai, China.
Lingying YeDepartment of Rheumatology and Immunology, Shanghai Changzheng Hospital, Naval Medical University, Shanghai, China.
Ling ZhouDepartment of Rheumatology and Immunology, Shanghai Changzheng Hospital, Naval Medical University, Shanghai, China.
Xiaobing WangDepartment of Rheumatology and Immunology, Shanghai Changzheng Hospital, Naval Medical University, Shanghai, China.
Xin WuDepartment of Rheumatology and Immunology, Shanghai Changzheng Hospital, Naval Medical University, Shanghai, China.
Huji XuDepartment of Rheumatology and Immunology, Shanghai Changzheng Hospital, Naval Medical University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Patients with active ankylosing spondylitis (AS) exhibit substantial heterogeneity in their clinical responses to tumor necrosis factor alpha inhibitors (TNFi). Consensus clustering, an unsupervised cluster discovery method, may identify AS subgroups with more homogeneous treatment response patterns to adalimumab (ADA), a widely prescribed TNFi. Methods: We performed longitudinal consensus clustering based on 8 repeated measurements of 10 core response variables in 438 patients with active AS enrolled in a 24-week phase III randomized controlled trial of ADA or its biosimilar, IBI303. Baseline characteristics and important endpoints-including the Assessment of SpondyloArthritis International Society (ASAS)-based and Ankylosing Spondylitis Disease Activity Score Inactive Disease (ASDAS)-based response criteria-were compared between the identified clusters. Predictive models of cluster membership reconstructed from data beyond week 2 were developed and internally validated to facilitate early, prospective identification of the clusters based on baseline and week-2 data. Results: Two longitudinal clusters were characterized: a favorable-response cluster (C1, n = 246, 56.2%) and a less favorable-response cluster (C2, n = 192, 43.8%). Compared with C1, C2 was characterized by older age, longer disease duration, and more frequent prior TNFi exposure, despite comparable baseline C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR). For the majority of clinical endpoints except CRP and BASMI, significant divergence emerged as early as week 2 and was sustained through week 24. For instance, C1 achieved significantly higher rates of ASDAS-Inactive Disease (ASDAS-ID) than C2 at week 2 (0.21 [95% CI 0.16, 0.26] vs. 0.01 [95% CI 0.00, 0.02]; Risk Difference [RD]: -0.21 [95% CI -0.26, -0.15], p < 0.001) and week 24 (0.63 [95% CI 0.57, 0.69] vs. 0.14 [95% CI 0.09, 0.18]; RD: -0.49 [95% CI -0.57, -0.42], p < 0.001). A multivariable model incorporating one baseline and eight week-2 variables had an optimism-corrected C-statistic of 0.880 [95% CI 0.859, 0.915] to correctly identify C2. Conclusions: These observed response trajectories exhibited distinct baseline characteristics and early response divergence at week 2. While these findings provide a hypothesis-generating framework for early patient stratification, their utility for prospective clinical patient triage requires further independent validation.

Indexed as

AdalimumabAntirheumatic AgentsBiosimilar PharmaceuticalsSpondylitis, AnkylosingAdultCluster AnalysisClustering AlgorithmsFemaleHumansMaleMiddle AgedTreatment Effect HeterogeneityTreatment OutcomeAdalimumabAntirheumatic AgentsBiosimilar Pharmaceuticalsadalimumabankylosing spondylitisbiosimilarclusterheterogeneitytumor necrosis factor inhibitors

Identifiers

PMID42416060
PMCPMC13337383

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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.