Precision prediction of intervertebral disc degeneration in ankylosing spondylitis using a nomogram model reveals the pivotal role of Th2-type immune dysregulation - Xiao-nan Wang; Xiao-nan Wang; Xiao-tian Ma; Jie Li; Run-tian Zhou; Yuan-zhang Jin; Xiao-feng Zhao; Dou-dou Jing; Bin Zhao; Bin Zhao (Frontiers in Immunology)
BackgroundAnkylosing 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.MethodsIn 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).ResultsMultivariable 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.ConclusionsThis 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.