Joint association between pan-immune inflammation value and physical pain with self-perception of patients in rheumatoid arthritis: a retrospective cohort study employing traditional statistics and interpretable machine learning.

Background: Patients with rheumatoid arthritis (RA) frequently experience increased physical pain and impaired self-perception. However, the combined impact of the pan-immune-inflammation value (PIV) and the visual analogue scale (VAS), representing subjective pain on SPP has not been thoroughly investigated. Methods: This retrospective cohort study included baseline clinical data of patients with RA admitted to the First Affiliated Hospital of Anhui University of Chinese Medicine. The study outcome was defined as SPP scores, while the exposure variables were the initial PIV and VAS values. The associations were evaluated using Spearman's correlation, restricted cubic splines, and multivariate logistic regression. Interaction effects were evaluated by incorporating product terms, and potential mechanisms were explored through mediation analysis. Additionally, Extreme gradient boosting (XGBoost) models were developed for SPP outcomes, followed by the Shapley Additive exPlanations (SHAP) method to explain predicted values. Results: The analysis included 1,426 patients with RA. Patients with concurrent high levels of PIV and VAS exhibited significantly elevated inflammatory markers and the poorest SPP scores (all P < 0.001). Higher levels of PIV and VAS were independently associated with increased risks of deterioration across multiple SPP domains, with significant multiplicative and additive interactions observed. Compared with the low PIV and low VAS group, the high PIV and high VAS group demonstrated the greatest risk of decline in physical functioning, bodily pain, vitality, role-emotional, mental health, the Chinese Patient-Reported Activity Index for RA (CPRI-RA), Syndrome Score of Dampness-Heat, and Syndrome Score of Dampness Stagnancy due to Spleen Deficiency. Mediation analysis revealed VAS partially mediated the association between PIV and several SPP outcomes. The XGBoost models integrating PIV and VAS achieved superior predictive performance for social functioning and CPRI-RA (AUC = 0.755 and 0.748, respectively). SHAP analysis identified VAS and PIV as the most important predictive features. Conclusion: PIV and VAS are independent and synergistic risk factors for impaired SPP in RA patients. Combined assessment of PIV and VAS improves the prediction of SPP deterioration and may serve as a valuable strategy for optimizing clinical management.