Evidence map›Paper›PMID 42377326›Full record

ArticleJournal of immunology research2026

Distinct Longitudinal Trajectories of SLEDAI-2K Scores Predict Prognosis in Systemic Lupus Erythematosus Based on Group-Based Trajectory Modeling.

Renren Ouyang, Ali Xiong, Xiaochun Shu, Ting Wang, Wei Wei, Rujia Chen, Feng Wang, Hongyan Hou, Shiji Wu

Abstract read
In one paragraph

Article in Journal of immunology research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

9 authors.

Renren OuyangDepartment of Laboratory Medicine, Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China, hust.edu.cn.ORCID https://orcid.org/0009-0002-2336-9022
Ali XiongDepartment of Laboratory Medicine, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, hust.edu.cn.ORCID https://orcid.org/0000-0003-3309-654X
Xiaochun ShuDepartment of Laboratory Medicine, Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China, hust.edu.cn.ORCID https://orcid.org/0009-0006-3722-4560
Ting WangDepartment of Laboratory Medicine, Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China, hust.edu.cn.ORCID https://orcid.org/0009-0006-2756-6014
Wei WeiDepartment of Laboratory Medicine, Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China, hust.edu.cn.ORCID https://orcid.org/0009-0000-5107-5094
Rujia ChenDepartment of Laboratory Medicine, Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China, hust.edu.cn.ORCID https://orcid.org/0009-0000-1111-9275
Feng WangDepartment of Laboratory Medicine, Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China, hust.edu.cn.ORCID https://orcid.org/0000-0001-6324-9135
Hongyan HouDepartment of Laboratory Medicine, Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China, hust.edu.cn.ORCID https://orcid.org/0000-0003-2337-0509
Shiji WuDepartment of Laboratory Medicine, Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China, hust.edu.cn.ORCID https://orcid.org/0009-0002-6666-8380

Funding

Health Commission of Hubei Province WJ2023M010
6 · The paper itself

Abstract

objectiveTo apply group-based trajectory modeling (GBTM) to longitudinal real world data from patients with systemic lupus erythematosus (SLE) to identify distinct disease activity trajectories and factors associated with 6 month clinical status.

methodsA total of 91 patients with SLE treated between 2017 and 2024 were included. SLE Disease Activity Index 2000 (SLEDAI-2K) scores were assessed at baseline, 3 months, and 6 months. GBTM was used to characterize longitudinal disease activity patterns. Heatmap clustering analysis was performed to compare clinical laboratory variables and SLEDAI-2K scores across trajectory groups and to further explore their association with 6 month clinical status.

resultsTwo distinct disease activity trajectories were identified. Class 1, comprising patients with higher initial SLEDAI-2K scores, was predominantly composed of nonremission cases (90.91%). Class 2, characterized by lower initial SLEDAI-2K scores, showed a more balanced distribution of nonremission (46.81%) and remission (53.19%) patients. At 6 months, the remission subgroup had significantly lower SLEDAI-2K scores and lower urinary biomarker levels, including 24 h urinary microalbumin (24 h-UMA), 24 h urinary micrototal protein (24 h-UMTP), UMA, and UMTP, than the nonremission subgroup.

conclusionsLongitudinal monitoring of SLEDAI-2K trajectories may help identify patients at risk for persistent high disease activity or nonremission at 6 months and those who may benefit from closer monitoring and treatment adjustment. These findings support a stratified management approach in SLE based on trajectory profiles.

Indexed as

Lupus Erythematosus, SystemicAdultBiomarkersDisease ProgressionFemaleHumansLongitudinal StudiesMaleMiddle AgedPrognosisRemission InductionSeverity of Illness IndexBiomarkersdisease activitygroup-based trajectory modelingsix month clinical statusSLEDAI-2Ksystemic lupus erythematosus

Identifiers

PMID42377326
PMCPMC13317468

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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.