Axial spondyloarthritis (axSpA) is a chronic autoimmune and autoinflammatory disease characterized by low back pain and morning back stiffness with the prevalence of 0.24% in Europe and 0.17% in Asia (1, 2). The severity of axial disease and poor long-term outcome are strongly correlated with hip involvement, which commonly accounts for 18% to 25% in axSpA patients (3). Generally, inflammation with bone marrow edema (BME), synovitis, bone erosions and osteophytes can affect hip joints, which would lead to ankylosis progression and functional impairment (3, 4).

The 2016 update of the Assessment of SpondyloArthritis international Society and the European League Against Rheumatism (ASAS-EULAR) firstly recommends non-pharmacological management and drug treatment for axSpA. Regarding drug treatment, nonsteroidal anti-inflammatory drugs (NSAIDs) and biological disease-modifying antirheumatic drugs (bDMARDs) are recommended for axSpA, whereas conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) may be considered for axSpA patients with peripheral joints involvement (5, 6). However, not all axSpA patients with hip involvement are suitable for the recommendation because adverse events, including infections, gastrointestinal disorders and injection site reactions, might occur in some patients receiving drug treatment (2, 6). In particular, drug resistance in patients with systemic autoimmune disorders is still a challenge in treatment (7). Discontinuation or switching from drug therapy might lead to significantly worse clinical outcomes, including poor disease control and increased disease flares (8). Hence, predicting response to treatment and switching treatment plans before drug treatment help patients avoid adverse events and drug resistance.

Currently, hip involvement can be defined by different imaging techniques in axSpA patients, such as X-ray/computed tomography (CT) and magnetic resonance image (MRI) (4). Conventional radiography/CT can find structure damage and plays an essential role in the diagnosis and classification of axSpA, but it could not be used to detect early disease and predict treatment response (4). Comparatively, MRI could detect active inflammatory changes in early-stage axSpA, such as BME, synovitis, joint effusion and enthesitis (9). The Hip Inflammation MRI Scoring System (HIMRISS) is a feasible and reliable tool for evaluating BME and hip effusion (10). Some semi-quantitative MRI parameters of hip involvement proposed by radiologists have been used to evaluate disease progression and predict treatment response in axSpA (11, 12). Nonetheless, single MRI indicator could not predict treatment response in the individual axSpA patient with hip involvement. Berlin MRI spine score combined with symptom duration and C-reactive protein (CRP) could be used to predict response to drug treatment in axSpA (11, 12). However, an effective method for predicting therapy response for the hip involvement in axSpA to support physicians in clinical practice is still lacking.

We hypothesize that MRI indicators combined with clinical indicators might be associated with response to treatment for hip involvement in axSpA. Our study aimed to determine the potential predictive factors based on MRI and clinical indicators for treatment response in axSpA patients with hip involvement and build a robust model to predict whether the patient would benefit from pharmacological treatment in 1 year.

In this prospective study, we developed and validated a model to predict curative effect before drug treatment in axSpA patients with hip involvement in 1 year. The model consisting of MRI (BME and hip effusion) and clinical indicators (disease duration, ESR and CRP) demonstrated optimal performance in predicting treatment response.

Our study firstly demonstrated that hip effusion (r = 0.288, P < 0.05) was the MR indicator with the highest number of correlations with responses to drug treatment in axSpA patients with hip involvement. No research has previously been conducted on the association between hip effusion and treatment response for axSpA. Gaffney et al.’s study validated that joint effusion could be used to predict pain response in patients with knee osteoarthritis (OA) treated with intra-articular steroid injections (IASI) at 1 and 6 weeks, respectively (17). Similarly, another study on knee OA stated that joint effusion was associated with the increased benefit of IASI treatment (18). Some researchers found that joint effusion-synovitis could not offer sufficient insight into clinical responses of patients with hip OA who were treated after 8 weeks and of RA patients treated after 2 years (19, 20). Although these studies involved various diseases and different joints, and the patients were treated with different drugs, the joint effusion was still an essential predictor of treatment response. The explicit association between hip effusion and the improvement in axSpA patients with hip involvement after drug treatment needs to be confirmed by others studies.

BME in acetabulum could be a predictor of good treatment response within 1 year. Additionally, BME in femoral head helped improve the performance of the predictive model, which indicated that it was a potential factor for response prediction. Similarly, Rudwaleit et al.’s finding indicated that BME evaluated by Berlin MRI spine score in axial joints contributed to the prediction of treatment response in axSpA patients (11, 12). A small sample size study concentrated on short-term predictive outcome of BME for radiographic progression from 6 to 12 months in rheumatoid arthritis (RA) (21). Hetland et al. identified BME as a predictor of progression at long-term follow-up in RA (20, 22). The predictive value of BME was not reported in the same rheumatic disease or in the follow-up interval in these studies, making direct comparisons with our study results difficult. Nevertheless, BME could still provide sufficient predictive value for patients before drug treatment. Notably, widespread active inflammation in the joint was manifested as BME on MRI in axSpA, OA and RA (23, 24); it was considered as an additional predictive value for treatment response in our study. Local inflammation in the involved joint (BME) could be visualized and assessed on MRI, whereas the inflammatory markers (CRP and ESR) could reflect the global inflammation disease, thereby implying that these predictors were complementary components. A previous study supported our results that a combination of BME and CRP demonstrated more powerful predictive capacity than a single parameter (12).

Fat deposition and bone erosion showed poor predictive value for treatment response in 1 year. However, Koo et al. demonstrated that fat deposition in the sacroiliac joint indicated a chronic stage of SpA, and the quantitative biomarker fat fraction was related to a worse outcome (25). No research has concentrated on the association between bone erosion and treatment response in SpA patients. However, similar to our results, research on RA patients indicated that bone erosion on MRI at baseline was not an independent predictor for radiographic progression in patients with early RA after 2 years (20). The follow-up time was relatively short in our study; thus, we were aware that long-term outcomes and life status after pharmacological treatment might be different from short-term results in SpA patients with hip involvement. More studies on long-term results are necessary, although they might be challenging. As thinner slices (2 or 3 mm) demonstrated high diagnostic accuracy and specificity for assessment of bone erosion on T1WI (26), 3 mm T1WI was applied to obtain a reliable and accurate assessment of bone erosion and to help identify the predictive value for treatment response in our study.

Higher ESR level and shorter disease duration predicted better treatment response. Despite that CRP showed no significance for prediction, it was reasonably added into the predictive model because of its advantage in response prediction (27), and the model performance was practically improved. These results were consistent with those of Lubrano et al., in which high ESR and CRP levels and low disease duration at baseline were confirmed to be significantly associated with improvement of BASFI (16), one of the four domains in the ASAS20 response criteria (13). Therefore, ESR and CRP levels could predict a better response to drug treatment in axSpA (28). Deodhar et al. confirmed our result that short disease duration was an important predictor for pharmacological response (29). ESR and CRP were important inflammatory markers but were limited because of their lack of sensitivity or specificity. Moreover, they might be affected by either non-infectious conditions or inflammation (30). Nonetheless, a combination of ESR and CRP with MRI indicators could improve the accuracy of the predictive model, which was currently used to help predict drug treatment response and guide patients’ treatment in clinical practice (27).

To our knowledge, this is the first time that MRI indicators were specifically considered in the construction of a predictive model for treatment response in axSpA patients with hip involvement. More evidence suggested that axSpA progression detected on MRI was related to treatment response (31). Inflammatory MRI findings on hip joint were an objective measurement whose association with inflammation on histopathology had been validated; they could serve as a reliable indicator (27). Some axSpA patients might benefit from MR examination before drug treatment; it could help prevent adverse events including infections and gastrointestinal disorder (2, 6), drug resistance (7), increased disease flares due to discontinuation of or switch from drug therapy (8) and the risk of undergoing total hip arthroplasty, i.e. heterotopic ossification and revision surgery (5, 32). We developed a predictive model consisting of six selected MRI and clinical indicators and showed that the model could successfully identify which patient can potentially benefit from a drug treatment with AUC values of 0.811 and 0.753 in training and validation cohorts, respectively. Thus, the constructed model could help rheumatologists discriminate responders and non-responders before treatment to increase the safety and effectiveness of drug therapy.

Several limitations should be acknowledged in our study. First, the sample size was relatively small in this single-centre study, which might lead to selection bias and influence the accuracy of our predictive model. Second, we used a scoring system similar to the HIMRISS and evaluated the hip joint on the axial plane instead of the coronal plane on MRI. Therefore, the reliability of our evaluation for hip joint and its correlation with the previous scoring system should be further tested. Third, many MRI indicators except for hip effusion were not quantitatively assessed, and assessment would be restricted by subjectivity and variability. Finally, the short-term effect (≤ 1 year) of treatment response was investigated in the study. As axSpA is a chronic condition, and continuous medication is regularly taken by patients (5), long-term outcomes of drug therapy need to be explored.

In conclusion, short disease duration, high ESR levels, hip effusion and BME in acetabulum predicted better treatment response within 1 year. The combination of MRI indicators, including hip effusion, BME in acetabulum and femoral head, and clinical indicators consisting of disease duration, ESR and CRP provided sufficient insights into response prediction. Prediction results would serve as promising guides in clinical decision-making for axSpA patients with hip involvement.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving human participants were reviewed and approved by the institutional review board of the Third Affiliated Hospital of Southern Medical University (IRB number 201501003). Written informed consent from the participants’ legal guardian/next of kin was not required to participate in this study in accordance with the national legislation and the institutional requirements.

ZX: Conceptualization, methodology, validation, investigation, data curation, software, and writing – original draft. ZL: Methodology, software, validation, formal analysis, and writing – review and editing. HC: Validation. QY: Visualization. CG: Data curation and investigation. KZ Data curation. XL: Investigation. QX: Data curation. SH: Data curation. QZ: Resource. YZ: Conceptualization, methodology, visualization, validation, writing – review and editing. All authors contributed to the article and approved the submitted version.

This study is supported by the National Natural Science Foundation of China (Grant No. 81871510).

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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