# Latent class analysis identifies distinct pain phenotypes in newly diagnosed systemic juvenile idiopathic arthritis

**Authors:** Hui Zhang, Xiaoqiong Wei, Wei Liu, Hongyao Leng, Qiao Shen, Xin Wan, Ximing Xu, Xianlan Zheng

PMC · DOI: 10.1186/s13075-025-03534-7 · 2025-03-31

## TL;DR

This study identifies three distinct pain patterns in children newly diagnosed with systemic juvenile idiopathic arthritis, which could help improve personalized treatment strategies.

## Contribution

The study introduces a novel classification of pain phenotypes in sJIA patients using latent class analysis and identifies age and IL-10 levels as influencing factors.

## Key findings

- Three distinct pain phenotypes were identified in sJIA patients using latent class analysis.
- Age and serum IL-10 levels were found to significantly influence these pain phenotypes.
- Different pain phenotypes were associated with variations in hospital stay duration and discharge pain status.

## Abstract

Patients with systemic juvenile idiopathic arthritis (sJIA) exhibit highly heterogeneous pain manifestations, which significantly impact their quality of life and disease prognosis. An understanding of the pain phenotypes for this disorder and their influencing factors is crucial for individualized pain management.

To explore the pain phenotypes of newly diagnosed sJIA patients via latent class analysis (LCA), analyse the influencing factors of these phenotypes, and evaluate the impacts of different pain phenotypes on short-term inpatient outcomes.

A retrospective cohort study was conducted by collecting the electronic health records of 165 patients who were first diagnosed with sJIA at the Children’s Hospital of Chongqing Medical University from January 2018 to July 2024. Patient pain characteristics, laboratory indicators, and inpatient outcome data were extracted. LCA was used to identify pain phenotypes, and multivariate logistic regression was used to analyse the influencing factors. The Lanza–Tan–Bray method and the data combination analysis technique were applied to evaluate the relationships between pain phenotypes and clinical outcomes.

LCA categorized the pain phenotypes of sJIA patients into three distinct classes, including (1) Class 1: inflammation-related moderate to severe pain with functional impairment (53.9% of patients); (2) Class 2: mild intermittent pain with extra-articular symptoms (19.4% of patients); and (3) Class 3: no joint pain with mild functional impairment (26.7% of patients). The analysis revealed that age (P = 0.023) and serum IL-10 levels (P = 0.047) were significant factors influencing pain phenotypes. Significant differences were observed among different pain phenotypes in terms of hospital stay duration, intrahospital department transfer rates, and pain status at discharge.

Pain in sJIA patients can be classified into three distinct phenotypes, which are influenced by factors such as age and IL-10 levels. The identification of these pain phenotypes has important clinical significance for developing individualized pain management strategies.

The online version contains supplementary material available at 10.1186/s13075-025-03534-7.

## Linked entities

- **Proteins:** IL10 (interleukin 10)
- **Diseases:** systemic juvenile idiopathic arthritis (MONDO:0019434), sJIA (MONDO:0019434)
- **Species:** Homo sapiens (taxon 9606)

## Full-text entities

- **Genes:** IL10 (interleukin 10) [NCBI Gene 3586] {aka CSIF, GVHDS, IL-10, IL10A, TGIF}
- **Diseases:** functional impairment (MESH:D003072), juvenile idiopathic arthritis (MESH:D001171), joint pain (MESH:D018771), inflammation (MESH:D007249), Pain (MESH:D010146)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

1 figure with captions in the complete paper: https://tomesphere.com/paper/PMC11956179/full.md

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Source: https://tomesphere.com/paper/PMC11956179