Precision prediction of intervertebral disc degeneration in ankylosing spondylitis using a nomogram model reveals the pivotal role of Th2-type immune dysregulation

被引:0
作者
Wang, Xiao-nan [1 ,2 ]
Ma, Xiao-tian [1 ]
Li, Jie [2 ]
Zhou, Run-tian [1 ]
Jin, Yuan-zhang [1 ]
Zhao, Xiao-feng [1 ]
Jing, Dou-dou [1 ]
Zhao, Bin [1 ,2 ]
机构
[1] Shanxi Med Univ, Clin Med Coll 2, Dept Orthopaed, Taiyuan, Peoples R China
[2] Shanxi Med Univ, Acad Med Sci, Taiyuan, Peoples R China
关键词
precision medicine; ankylosing spondylitis; intervertebral disc degeneration; nomogram; Th2; cells; IL-4; chronic inflammation; immune imbalance; SOCIETY CLASSIFICATION CRITERIA; DIAGNOSTIC-CRITERIA;
D O I
10.3389/fimmu.2025.1556738
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
Background Ankylosing spondylitis (AS) is an immune-mediated chronic inflammatory disease. When AS is complicated by intervertebral disc degeneration (IVDD), disease complexity increases substantially, often resulting in poor long-term outcomes. Although previous studies have explored the mechanisms linking AS and IVDD, reliable tools for precise risk prediction and early intervention remain scarce.Methods In this retrospective study, we enrolled 144 patients with AS (60 with and 84 without IVDD). Their clinical features, immune status, and inflammatory cytokine levels were analyzed. A nomogram prediction model was constructed using multivariable logistic regression. Model performance was evaluated via receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).Results Multivariable analysis identified body mass index (BMI), peripheral blood Th2 cell percentage (Th2%), and serum IL-4 levels as independent risk factors for IVDD in patients with AS. All associations remained statistically significant after Benjamini-Hochberg correction (BMI: BH-adjusted P = 0.001; Th2%: BH-adjusted P = 0.019; IL-4: BH-adjusted P = 0.019). Incorporation of these factors into a nomogram yielded excellent discriminative performance (area under the curve, AUC = 0.83) and calibration, outperforming a simplified model based solely on BMI (AUC = 0.74). This improvement in predictive accuracy was statistically significant, as determined by DeLong's test (P = 0.018). DCA revealed that at a threshold probability of 60.8%, the nomogram effectively distinguished high-risk patients, underscoring its strong clinical applicability.Conclusions This study is the first to highlight the critical roles of Th2 cells and IL-4 in AS complicated by IVDD, and establishes a nomogram that accurately predicts the risk of IVDD in AS. Beyond offering a tool for early detection and personalized management, these findings open avenues for investigating overlapping pathogenic mechanisms and potential immunotherapeutic targets in AS-IVDD.
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