Predictive Value of Active Sacroiliitis in MRI for Flare Among Chinese Patients with Axial Spondyloarthritis in Remission

Qing Zheng, Wen Liu, Yu Huang, Zhenyu Gao, Yuanhui Wu, Xiaohong Wang, Meimei Cai, Yan He, Shiju Chen, Bin Wang, Lingyu Liu, Shuqiang Chen, Hongjie Huang, Ling Zheng, Rihui Kang, Xiaohong Zeng, Jing Chen, Huaning Chen, Junmin Chen, Zhibin Li, Guixiu Shi, Qing Zheng, Wen Liu, Yu Huang, Zhenyu Gao, Yuanhui Wu, Xiaohong Wang, Meimei Cai, Yan He, Shiju Chen, Bin Wang, Lingyu Liu, Shuqiang Chen, Hongjie Huang, Ling Zheng, Rihui Kang, Xiaohong Zeng, Jing Chen, Huaning Chen, Junmin Chen, Zhibin Li, Guixiu Shi

Abstract

Introduction: In recent axSpAx patients with remission lasting at least 3 months and later followed-up monthly for a median of 8 months, we compared the predictive value of baseline MRI of sacroiliac joints and constructed a nomogram model for predicting flare.

Methods: This study included 251 patients with axial spondyloarthritis, according to the ASAS axSpA classification criteria, who achieved Low Disease Activity (ASDAS) and underwent MRI examination. A total of 144 patients from the First Affiliated Hospital of Xiamen University were used as the nomogram training set; 107 from the First Affiliated Hospital of Fujian Medical University were for external validation.

Results: The median time of relapse was 8.705 months (95% CI 8.215-9.195) and 7.781 months (95% CI 7.075-8.486) for MRI-positive patients and 9.8 months (95% CI 9.273-10.474) for MRI negative patients, respectively. Both active sacroiliitis on MRI (HR 1.792, 95% CI 1.230-2.611) and anti-TNF-α treatments (HR 0.507, 95% CI 0.349-0.736) were significantly associated with disease flares. Gender, disease duration, HLA-B27, MRI, and anti-TNF-α treatment were selected as predictors of the nomogram. The areas under the ROC curve (AUROCs) of the 1-year remission probability in the training and validation groups were 0.71 and 0.729, respectively. Nomogram prediction models present better AUROCs, C-indices, and decision curve analysis cure than the clinical experience model.

Conclusions: Active sacroiliitis in MRI requires weighting in order to estimate remission and disease flares, when axSpA patients achieve low disease activity. The simple nomogram might be able to discriminate and calibrate in clinical practice.

Trial registration: ClinicalTrials, NCT03425812, Registered 8 February 2018, https://clinicaltrials.gov.

Keywords: Joint; Magnetic resonance imaging; Predictive value of tests; Sacroiliac spondylitis.

Figures

Fig. 1
Fig. 1
Flowchart of participants selection
Fig. 2
Fig. 2
Nomogram model for predicting flare in axSpA patients achieving low disease activity
Fig. 3
Fig. 3
Calibration curves of the nomogram for the training set (a) and validation set (b). The areas under the AUROC curve of the 1-year remission probability in the training (c) and validation (d) groups, respectively
Fig. 4
Fig. 4
The C-indices of the clinical experience model in the training (a) and validation groups (b), respectively. AUROCs of the clinical experience model for predicting 1-year remission probability in the training (c) and validation groups (d)

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