Development and internal validation of a model to predict long-term survival of ANCA associated vasculitis

Zhe Chen; Xinping Tian; Jingge Qu; Jing Chen; Yunjiao Yang; Jing Li

doi:10.2478/rir-2023-0005

Development and internal validation of a model to predict long-term survival of ANCA associated vasculitis

Rheumatol Immunol Res. 2023 Apr 18;4(1):30-39. doi: 10.2478/rir-2023-0005. eCollection 2023 Mar.

Authors

Zhe Chen^{1

2}, Xinping Tian¹, Jingge Qu^{1

3}, Jing Chen^{1

4}, Yunjiao Yang¹, Jing Li¹

Affiliations

¹ Department of Rheumatology and Clinical Immunology, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Ministry of Science & Technology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital (PUMCH), Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing 100730, China.
² Department of Rheumatology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, China.
³ Department of Respiratory and Critical Care Medicine, Peking University Third Hospital, Research Center for Chronic Airway Diseases, Peking University Health Science Center, Beijing 100191, China.
⁴ Department of Rheumatology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, Shandong Province, China.

Abstract

Objectives: Risk stratification and prognosis prediction are critical for appropriate management of anti-neutrophil cytoplasmic antibody (ANCA) associated vasculitis (AAV). Herein, we aim to develop and internally validate a prediction model specifically for long-term survival of patients with AAV.

Methods: We thoroughly reviewed the medical charts of patients with AAV admitted to Peking Union Medical College Hospital from January 1999 to July 2019. The Least Absolute Shrinkage and Selection Operator method and the COX proportional hazard regression was used to develop the prediction model. The Harrell's concordance index (C-index), calibration curves and Brier scores were calculated to evaluate the model performance. The model was internally validated by bootstrap resampling methods.

Results: A total of 653 patients were included in the study, including 303 patients with microscopic polyangiitis, 245 patients with granulomatosis with polyangiitis and 105 patients with eosinophilic granulomatosis with polyangiitis, respectively. During a median follow-up of 33 months (interquartile range 15-60 months), 120 deaths occurred. Age at admission, chest and cardiovascular involvement, serum creatinine grade, hemoglobin levels at baseline and AAV sub-types were selected as predictive parameters in the final model. The optimism-corrected C-index and integrated Brier score of our prediction model were 0.728 and 0.109. The calibration plots showed fine agreement between observed and predicted probability of all-cause death. The decision curve analysis (DCA) showed that in a wide range of threshold probabilities, our prediction model had higher net benefits compared with the revised five factor score (rFFSand) and the birmingham vasculitis activity score (BVAS) system.

Conclusion: Our model performs well in predicting outcomes of AAV patients. Patients with moderate-to-high probability of death should be followed closely and personalized monitoring plan should be scheduled.

Keywords: anti-neutrophil cytoplasmic antibody associated vasculitis; internal validation; long-term; mortality; prediction model.