Cappelli Laura C, Perin Jamie, Zeger Scott, Jones Michelle, Bingham Clifton O, Shah Ami A
Johns Hopkins University School of Medicine, Division of Rheumatology, USA.
Johns Hopkins Bloomberg School of Public Health, Department of Biostatistics, USA.
Semin Arthritis Rheum. 2025 Jun 19;74:152773. doi: 10.1016/j.semarthrit.2025.152773.
Immune checkpoint inhibitors (ICI) for cancer treatment can cause inflammatory arthritis (IA). Since ICI-IA has a unique pathogenesis, applying categories of traditional IA may be of limited use.
Participants were ≥18 years old, treated with anti-PD-1, anti-PD-L1, and/or anti-CTLA-4 agents, and had ICI-IA diagnosed by a rheumatologist. We clustered patients using latent class analysis (LCA) applied with phenotypic data from the baseline rheumatology visit. The Bayesian Information Criteria (BIC) was used to select the number of phenotypes. We compared demographics, cancer type and treatments, and IA clinical features and treatments between the estimated phenotypes. Finally, we explored differences in cytokine levels and the presence of shared epitope between the groups.
Twenty variables were used to estimate latent classes. Two distinct phenotypes were indicated by the BIC; 77 patients were estimated to be the first phenotype and 49 in the second phenotype. The statistically significant features that distinguished the phenotypes included higher levels of all components of the CDAI, more stiffness, and more small and upper extremity joint involvement for phenotype 2. Patients in phenotype 2 were marginally more likely to require steroids during their course. There were no significant differences in cancer type, stage or ICI treatment between the phenotype groups. Baseline levels of VEGF-A were higher in phenotype 2.
Two separate phenotypes of ICI-IA were identified using LCA, the second having a more severe polyarthritis at baseline and involving the upper extremities. These subgroups provide an opportunity to identify corresponding biomarkers to predict disease outcomes.
用于癌症治疗的免疫检查点抑制剂（ICI）可引发炎性关节炎（IA）。由于ICI-IA具有独特的发病机制，应用传统IA的分类方法可能作用有限。
参与者年龄≥18岁，接受过抗PD-1、抗PD-L1和/或抗CTLA-4药物治疗，且由风湿病学家诊断为ICI-IA。我们使用潜在类别分析（LCA）对患者进行聚类，该分析应用了基线风湿病就诊时的表型数据。采用贝叶斯信息准则（BIC）来选择表型数量。我们比较了估计出的各表型之间的人口统计学特征、癌症类型及治疗情况、IA临床特征及治疗情况。最后，我们探究了各组之间细胞因子水平及共享表位存在情况的差异。
使用20个变量来估计潜在类别。BIC表明存在两种不同的表型；估计77例患者为第一种表型，49例为第二种表型。区分这些表型的具有统计学意义的特征包括，对于第二种表型，CDAI所有成分水平更高、僵硬程度更高，以及小关节和上肢关节受累更多。第二种表型的患者在病程中更有可能需要使用类固醇。表型组之间在癌症类型、分期或ICI治疗方面无显著差异。第二种表型中VEGF-A的基线水平更高。
使用LCA识别出了ICI-IA的两种不同表型，第二种表型在基线时具有更严重的多关节炎且累及上肢。这些亚组为识别相应的生物标志物以预测疾病转归提供了机会。
