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Pooled estimate of diagnostic delay in psoriatic arthritis and spondyloarthritis. *Diagnostic delay calculated from summary data for age at onset and diagnosis. **Standard deviation imputed for meta-analysis.
Source publication
Background. Delay to diagnosis in axial spondyloarthritis (axSpA) is longer than many other rheumatic diseases. Prolonged delay is associate with poorer outcomes including functional impairment and quality of life. Our aims were to describe 1) global variation in delay to diagnosis, 2) factors associated with delay, and 3) delay compared with psori...
Contexts in source publication
Context 1
... et al [11] and Sørensen et al [12] reported delay in both axSpA and PsA. Bias scores were mostly 3 to 4 out of 6 stars (Supplementary Table S2 and Figure S2) indicating moderate bias. ...
Context 2
... univariate analysis, mechanical back pain remained significant in multivariable model [28,29]. The mean delay to PsA diagnosis was 2.6 years (95%CI 1.6 to 3.6, I 2 =99%) (Figure 2). ...
Similar publications
Objectives:
Rheumatoid arthritis (RA) and spondyloarthritis (SpA) are the most common inflammatory rheumatic diseases (IRD). The aim of this study was to elucidate differences in the outcome of SARS-CoV-2 infection in RA- and SpA-patients.
Methods:
Data from the German COVID-19 registry for IRD patients from 30th March to 16th November 2020 were...
Citations
... This is slightly higher than that reported in a recent meta-analysis by Zhao et al 15 which showed a mean diagnostic delay of 6.7 from a review of 64 different studies on patients with axSpA. 15 Our cohort, despite being relatively young (43.9 years), report symptoms of the disease for a long period of time (17.1 years of symptom duration). These results are unacceptable by most international standards and highlight the need to improve diagnostic tools (eg, specific biomarkers development and interpretation of imaging techniques) for the diagnosis of patients with axSpA. ...
Background
The International Map of Axial Spondyloarthritis (IMAS) is a global initiative aimed to assess the impact and burden of axial spondyloarthritis (axSpA) and identify the unmet needs from the patient’s perspective.
Method
IMAS is a collaboration between the Axial Spondyloarthritis International Federation (ASIF), the University of Seville, Novartis Pharma AG and steered by a scientific committee. IMAS collected information through an online cross-sectional survey (2017–2022) from unselected patients with axSpA from Europe, Asia, North America, Latin America and Africa who completed a comprehensive questionnaire containing over 120 items.
Results
5557 patients with axSpA participated in IMAS. Mean age was 43.9 ±12.8 years, 55.4% were female, 46.2% had a university education and 51.0% were employed. The mean diagnostic delay was 7.4 ±9.0 years (median: 4.0), and the mean symptom duration was 17.1 ±13.3 years. 75.0% of patients had active disease (Bath Ankylosing Spondylitis Disease Activity Index ≥4), and 59.4% reported poor mental health (12-item General Health Questionnaire ≥3). In the year before the survey, patients had visited primary care physicians 4.6 times and the rheumatologist 3.6 times. 78.6% had taken non-steroidal anti-inflammatory drug ever, 48.8% biological disease-modifying antirheumatic drugs and 43.6% conventional synthetic disease-modifying antirheumatic drugs. Patients’s greatest fear was disease progression (55.9%), while the greatest hope was to be able to relieve pain (54.2%).
Conclusions
IMAS shows the global profile of patients with axSpA, highlighting unmet needs, lengthy delays in diagnosis and high burden of disease in patients with axSpA worldwide. This global information will enable more detailed investigations to obtain evidence on the critical issues that matter to patients around the world to improve their care and quality of life.
... Diagnosing axial spondyloarthritis (axSpA) can be challenging, requiring first disease suspicion and referral to rheumatologists, and later an accurate evaluation of the patient's symptoms and signs, as well as laboratory and imaging tests [1], often resulting in a long period [2]. ...
To assess differences in the diagnosis journey and access to care in a large sample of patients with axial spondyloarthritis (axSpA) from around the world, included in the International Map of Axial Spondyloarthritis (IMAS).
IMAS was a cross-sectional online survey (2017–2022) of 5557 unselected patients with axSpA from 27 countries. Across five worldwide geographic regions, the patient journey until diagnosis and healthcare utilization in the last 12 months prior to survey were evaluated. Univariable and multivariable linear regression was used to analyze factors associated with higher healthcare utilization.
Of 5557 participants in IMAS, the diagnosis took an average of 7.4 years, requiring more than two visits to HCPs (77.7% general practitioner and 51.3% rheumatologist), and more than two diagnostic tests [67.5% performed human leukocyte antigen B27 (HLA-B27), 64.2% x-ray, and 59.1% magnetic resonance imaging (MRI) scans]. North America and Europe were the regions with the highest number of healthcare professional (HCP) visits for diagnosis, while the lowest number of visits was in the Asian region. In the previous 12 months, 94.9% (n = 5272) used at least one healthcare resource, with an average of 29 uses per year. The regions with the highest healthcare utilization were Latin America, Europe, and North America. In the multiple linear regression, factors associated with higher number of healthcare utilization were younger age (b = – 0.311), female gender (b = 7.736), higher disease activity (b = 1.461), poorer mental health (b = 0.624), greater functional limitation (b = 0.300), greater spinal stiffness (b = 1.527), and longer diagnostic delay (b = 0.104).
The diagnosis of axSpA usually takes more than two visits to HCPs and at least 7 years. After diagnosis, axSpA is associated with frequent healthcare resource use. Younger age, female gender, higher disease activity, poorer mental health, greater functional limitation, greater spinal stiffness, and longer diagnostic delay are associated with higher healthcare utilization. Europe and North America use more HCP visits and diagnostic tests before and after diagnosis than the other regions.
... Behcet's patients of Turkish origin from the non-endemic Innsbruck sub-cohort present differently compared to those living in Turkey [26]. Polypharmacy defined by ≥ 5 drugs was observed by 33.7% of patients with RA in the Middle-European cohort, compared to 61.6% in the literature [29]; and 88.8% of all Middle-European RA patients were in remission or had low disease activity, with hypertension (38.8%) and osteoporosis (30.0%) as the most frequent comorbidities [27]. The potential need for genetic testing is immense, with 57.3% of patients having the potential to benefit from genetic testing according to their diagnosis and treatment and 53.3% of patients with actually performed genetic testing for diagnostic, prognostic, or pharmacogenetic purposes [21]. ...
Recent developments in digital health technologies are overwhelming, and their use in routine work is still difficult to anticipate. This narrative review summarizes the concept of consecutive cohorts in the literature, together with local research experiences in consecutive rheumatic outpatients. Digital health techniques have to reflect the clinicians' needs, support real-life care of patients, and allow for the specific assessment of quality parameters fulfilling the Donabedian aspect of qualified health care, using quality indicators to improve health care and research. Rapidly growing observational cohorts will perform best to provide follow-up data as the basis for further development of healthcare approaches for rheumatic patients. The challenges of a selection bias, patients with limited disease expression, and chances of early detection of patients with rare diseases are addressed. For research purposes, sequential analyses with growing cohort size, comparative cross-sectional studies with sequential hypothesis testing and other prognostic, diagnostic, and therapeutic aspects of patient management can be performed. With the support of new technologies, young clinicians can easily approach such clinical topics, and learn about clinical data analyses. The use of quality standards as proposed in international recommendations for diagnostic issues and classification criteria, management recommendations, monitoring, and training issues can be supported by digital technologies. In conclusion, collaborative projects allow detailed clinical analyses of large cohorts, but local initiatives can prepare these co-operations, provide first local logistics and research experiences, and teach clinicians how to perform clinical research. Digital health technologies will strongly support these local initiatives.
... The diagnosis of SpA, particularly AxSpA, is frequently delayed by several years. [2][3][4][5][6] Multiple factors may contribute to this delay, including insidious onset, intermittent disease course, lack of awareness among nonrheumatology health care providers, absence of specific diagnostic biomarkers, and confusion with other musculoskeletal disorders. 4,[7][8][9] A diagnostic delay of as little as six months from symptom onset is associated with structural damage and poor functional outcomes. ...
Objective
Extramusculoskeletal manifestations of spondyloarthritis (SpA) may precede the development of articular features. Patients seen in ophthalmology, dermatology, and gastroenterology clinics with uveitis, psoriasis, or inflammatory bowel disease (IBD) may have undiagnosed SpA. We set out to identify and evaluate screening tools for SpA in patients with psoriasis, uveitis, and IBD and determine factors that influence the performance of these instruments.
Methods
This scoping review followed Preferred Reporting Items for Systematic Reviews and Meta‐Analyses guidelines. PubMed, Embase, and Web of Science were searched from inception to January 2022.
Results
We identified 13 screening tools for psoriatic arthritis, 2 SpA screening tools for uveitis, and 3 SpA screening tools for IBD. All screening tools were patient‐oriented questionnaires except for the Dublin Uveitis Evaluation Tool, a physician‐applied algorithm. The questionnaires varied in length, scoring method, cutoff score, and spectrum of included SpA features. Average completion time was less than five minutes. Across the three patient populations, the sensitivities and specificities of these screening tools were comparable in the primary validation cohorts. Sensitivities and specificities were generally lower in secondary validation studies, with marked variability among cohorts.
Conclusion
Our results highlight the heterogeneity and limitations of existing SpA screening tools. Although these tools show promise for use within a specific target population, none are generalizable to all patients with extramusculoskeletal manifestations at risk of SpA. Future studies should explore the utility of a generic patient‐oriented SpA screening tool that can be applied to patients with psoriasis, uveitis, or IBD; is easy to use and comprehend; and captures all clinical domains of SpA.
... Ax-SPA is a gradual development of disease, the initial effects of sacroiliac 19:96 joints, late can spread to the spine, causing pain and dysfunction and quality of life [2,3]. SPA pathogenesis is relatively hidden, and early diagnosis and early treatment are needed to minimize the loss function of patients with long-term, the hair of late complications [4][5][6]. Sacroiliitis is the hallmark of Ax-SPA [7][8][9][10]. Therefore, early diagnosis and accurate evaluation of sacroiliac arthritis is particularly important. ...
Objective
To create an automated machine learning model using sacroiliac joint MRI imaging for early sacroiliac arthritis detection, aiming to enhance diagnostic accuracy.
Methods
We conducted a retrospective analysis involving 71 patients with early sacroiliac arthritis and 85 patients with normal sacroiliac joint MRI scans. Transverse T1WI and T2WI sequences were collected and subjected to radiomics analysis by two physicians. Patients were randomly divided into training and test groups at a 7:3 ratio. Initially, we extracted the region of interest on the sacroiliac joint surface using ITK-SNAP 3.6.0 software and extracted radiomic features. We retained features with an Intraclass Correlation Coefficient > 0.80, followed by filtering using max-relevance and min-redundancy (mRMR) and LASSO algorithms to establish an automatic identification model for sacroiliac joint surface injury. Receiver operating characteristic (ROC) curves were plotted, and the area under the ROC curve (AUC) was calculated. Model performance was assessed by accuracy, sensitivity, and specificity.
Results
We evaluated model performance, achieving an AUC of 0.943 for the SVM-T1WI training group, with accuracy, sensitivity, and specificity values of 0.878, 0.836, and 0.943, respectively. The SVM-T1WI test group exhibited an AUC of 0.875, with corresponding accuracy, sensitivity, and specificity values of 0.909, 0.929, and 0.875, respectively. For the SVM-T2WI training group, the AUC was 0.975, with accuracy, sensitivity, and specificity values of 0.933, 0.889, and 0.750. The SVM-T2WI test group produced an AUC of 0.902, with accuracy, sensitivity, and specificity values of 0.864, 0.889, and 0.800. In the SVM-bimodal training group, we achieved an AUC of 0.974, with accuracy, sensitivity, and specificity values of 0.921, 0.889, and 0.971, respectively. The SVM-bimodal test group exhibited an AUC of 0.964, with accuracy, sensitivity, and specificity values of 0.955, 1.000, and 0.875, respectively.
Conclusion
The radiomics-based detection model demonstrates excellent automatic identification performance for early sacroiliitis.
... Considering the possible limits of studies not included in the searchable PubMed and Embase fields, displaying DD in ax-SpA and AS only in the text and not in titles, we performed a forward snowballing of complementary papers with a manual search of cross-references in the citation track [34] for the selected studies and reviews, particularly in previous reports that performed a meta-analysis [14,35]. ...
... The data of initial eligible studies for systematic review ( Figure 1) are shown in Table 1, and information from the included studies was extracted into predefined tabulated summaries as follows: the first author, year of publication, geographic region (similar healthcare systems-Europe and Israel-and extra-European countries), classification criteria for AS and ax-SpA, sample size and sources, F/M ratio, World Bank (WB) economic class [14], mean age at onset (F vs. M), mean age at onset and at diagnosis (F vs. M), mean DD (F vs. M), as well as the significant differences between sexes. We considered Europe and Israel to have similar healthcare systems for the universal right for citizens to access tertiary centers. ...
... Successively, papers were assessed for risk of bias using an adapted version of the modified Newcastle-Ottawa Scale (m-NOS) for case-control studies (see Supplementary Table S1) based on their selection (score 0-4) (disease definition and representativeness), comparability (0-1) of F vs. M, and ascertainment of DD (records 0-1, same method between sexes 0-1, not response rate 0-1 = 0-3). The data of initial eligible studies for systematic review (Figure 1) are sho 1, and information from the included studies was extracted into predefine summaries as follows: the first author, year of publication, geographic reg healthcare systems-Europe and Israel-and extra-European countries), c criteria for AS and ax-SpA, sample size and sources, F/M ratio, World economic class [14], mean age at onset (F vs. M), mean age at onset and at diag Table 1. Summary of the main characteristics of the studies on DD difference between sexes, with data expressed as the mean (SD) or median (IQR, interquartile range) (*), included in the systematic review (n = 26) and in the meta-analysis (n = 18). ...
Diagnostic delay (DD) is associated with poor radiological and quality of life outcomes in axial spondyloarthritis (ax-SpA) and ankylosing spondylitis (AS). The female (F) population is often misdiagnosed, as classification criteria were previously studied mostly in males (M). We conducted a systematic review to investigate (i) the difference in DD between the sexes, the impact of HLA*B27 and clinical and social factors (work and education) on this gap, and (ii) the possible influence of the year of publication (before and after the 2009 ASAS classification criteria), geographical region (Europe and Israel vs. extra-European countries), sample sources (mono-center vs. multi-center studies), and world bank (WB) economic class on DD in both sexes. We searched, in PubMed and Embase, studies that reported the mean or median DD or the statistical difference in DD between sexes, adding a manual search. Starting from 399 publications, we selected 26 studies (17 from PubMed and Embase, 9 from manual search) that were successively evaluated with the modified Newcastle–Ottawa Scale (m-NOS). The mean DD of 16 high-quality (m-NOS > 4/8) studies, pooled with random-effects meta-analysis, produces results higher in F (1.48, 95% CI 0.83–2.14, p < 0.0001) but with significant results at the second analysis only in articles published before the 2009 ASAS classification criteria (0.95, 95% CI 0.05–1.85, p < 0.0001) and in extra-European countries (3.16, 95% CI 2.11–4.22, p < 0.05). With limited evidence, some studies suggest that DD in F might be positively influenced by HLA*B27 positivity, peripheral involvement, and social factors.
... A recent systematic review and meta-analysis found that the mean duration of diagnostic delay was 6.7 years for axSpA worldwide. 2 Studies in large axSpA cohorts in Germany and the United Kingdom reported a mean delay ranging from 5.7 to 8.5 years, respectively. 3,4 Prior research noted that longer delay to diagnosis is associated with increased functional impairment, greater radiographic progression, higher health care costs, and higher rates of unemployment. ...
... 18 The duration of delay observed in our study (mean 6.8 years, median 3.8 years) is consistent with the mean and median delay reported in two recent meta-analyses of axSpA diagnostic delay. 2,19 Our findings were also consistent with two investigations of diagnostic delay in the United States that noted a mean delay of 6.0 to 7.6 years, 20,21 and shorter than the delay described in the Prevalence of Axial SpA cohort, which reported a mean of 14 years of symptoms at diagnosis. 22 We reported a median age of symptom onset of 29.5 years in our cohort, slightly older than reported in the ASAS Peripheral Involvement in Spondyloarthritis study (median 26 years) 23 and in US patients with axSpA who responded to the International Map of Axial Spondyloarthritis survey (mean 26.4 years). ...
... 24 Our study found that older age at symptom onset was associated with shorter delay, which parallels several prior studies that noted similar findings with younger age at symptom onset being associated with longer delay. 2,3 The exact cause of this association is unclear but may occur if younger patients are more frequently misdiagnosed with mechanical causes of back pain. 3 In contrast, peripheral arthritis findings may trigger a prompt referral to rheumatology-our finding associating peripheral arthritis with shorter delay is consistent with prior research that demonstrated associations between longer delay and a lack of extramusculoskeletal and peripheral musculoskeletal disease manifestations. ...
Objective
Patients with axial spondyloarthritis (axSpA) often experience significant delay between symptom onset and diagnosis for reasons that are incompletely understood. We investigated associations between demographic, medical, and socioeconomic factors and axSpA diagnostic delay.
Methods
We identified patients meeting modified New York criteria for ankylosing spondylitis (AS) or 2009 Assessment of Spondyloarthritis International Society criteria for axSpA in the Mass General Brigham health care system between December 1990 and October 2021. We determined the duration of diagnostic delay, defined as the duration of back pain symptoms reported at diagnosis, as well as disease manifestations and specialty care prior to diagnosis from the electronic health record. We obtained each patient's Social Vulnerability Index (SVI) by mapping their address to the US Centers for Disease Control SVI Atlas. We examined associations among disease manifestations, SVI, and diagnostic delay using ordinal logistic regression.
Results
Among 554 patients with axSpA who had a median diagnostic delay of 3.8 years (interquartile range 1.1–10), peripheral arthritis (odds ratio [OR] 0.65, 95% confidence interval [CI] 0.45–0.93) and older age at symptom onset (OR 0.83, 95% CI 0.78–0.88 per five years) were associated with shorter delay. AS at diagnosis (OR 1.85, 95% CI 1.30–2.63), a history of uveitis prior to diagnosis (OR 2.77, 95% CI 1.73–4.52), and higher social vulnerability (defined as national SVI 80th to 99th percentiles; OR 1.99, 95% CI 1.06–3.84) were associated with longer diagnostic delay.
Conclusion
Older age at back pain onset and peripheral arthritis were associated with shorter delay, whereas uveitis was associated with longer diagnostic delay. Patients with higher socioeconomic vulnerability had longer diagnostic delay independent of clinical factors.
... In the United Kingdom, diagnostic delay remains a challenge in axial spondyloarthritis (axSpA). A comprehensive literature review demonstrated a mean average of 8.7 years of delay between symptom onset and formal diagnosis [1,2]. Numerous studies have demonstrated that early diagnosis and treatment of axSpA are associated with better outcomes [1][2][3]. ...
... A comprehensive literature review demonstrated a mean average of 8.7 years of delay between symptom onset and formal diagnosis [1,2]. Numerous studies have demonstrated that early diagnosis and treatment of axSpA are associated with better outcomes [1][2][3]. Early identification and referral of patients with a high suspicion of axSpA to rheumatology is important as this is often the rate-limiting step in timely diagnosis and treatment [1][2][3]. Spondyloarthritis (SpA) is a group of overlapping diseases characterised by inflammation in the spine (spondylitis) and joints (arthritis) with symptoms of inflammatory back pain (IBP) [3]. ...
... Numerous studies have demonstrated that early diagnosis and treatment of axSpA are associated with better outcomes [1][2][3]. Early identification and referral of patients with a high suspicion of axSpA to rheumatology is important as this is often the rate-limiting step in timely diagnosis and treatment [1][2][3]. Spondyloarthritis (SpA) is a group of overlapping diseases characterised by inflammation in the spine (spondylitis) and joints (arthritis) with symptoms of inflammatory back pain (IBP) [3]. Types of SpA include non-radiographic axSpA, ankylosis spondylitis (AS), psoriatic arthritis (PsA), reactive arthritis and undifferentiated SpA [3]. ...
Background
In the United Kingdom, diagnostic delay remains a challenge in axial spondyloarthritis (axSpA). Psoriasis is a frequently identified extra-musculoskeletal manifestation associated with axSpA. In this study, we aimed to determine the prevalence of inflammatory back pain (IBP) in psoriasis patients at a specialized psoriasis dermatology clinic in a London NHS Trust. Our primary goal was to identify psoriasis patients with IBP who were not referred to a rheumatologist, potentially leading to axSpA diagnostic delays. Additionally, we aimed to investigate factors contributing to these delays and strategies to address them.
Methodology
A patient survey consisting of 22 questions was used to assess the prevalence of IBP among 66 psoriasis patients attending a weekly specialized psoriasis dermatology clinic within a London NHS Trust between May and July 2023. The survey comprised patient demographic information along with inquiries about the existence of back pain exceeding three months. The Berlin Criteria was utilized to identify IBP among patients who reported experiencing back pain for over three months. Additionally, the survey sought information on prior diagnosis of axSpA and whether participants had consulted healthcare professionals regarding their back pain.
Results
Of the 66 patients invited, 51 (77%) completed the survey. The average age of the patients was 50 years (range = 19-74 years), with 58.8% being female. The mean duration of psoriasis was 15.7 years (range = 2-44 years). Overall, 45% (23/51) reported back pain lasting over three months. Among the patients who reported back pain for more than three months, 13 met the Berlin Criteria for IBP (25% of the total surveyed), and only four of these patients had a diagnosis of axSpA. Notably, seven patients (14% of the total surveyed) potentially had undiagnosed axSpA. General practitioners (GPs) were commonly consulted for back pain, yet only 39% of those with prolonged back pain had seen a rheumatologist. Despite experiencing prolonged back pain, 17% of patients had not sought healthcare advice for their symptoms.
Conclusions
This study highlights that IBP is a common yet underdiagnosed comorbidity in psoriasis patients. Dermatologists, GPs, and other allied healthcare professionals play a crucial role in detecting early axSpA. However, limited awareness of IBP hinders its identification in psoriasis patients and subsequent referral to rheumatologists. This highlights the need for improving awareness and education regarding axSpA among dermatologists and allied healthcare professionals as well as the public and patients to ensure timely diagnosis. The development of simple and easy-to-administer screening questionnaires to aid non-rheumatologists in identifying patients with IBP together with simplified referral pathways would increase onward referrals of appropriate patients to rheumatologists.
... With respect to diagnostic characteristics, the oldest age at symptom onset occurred in Latin America (30 years of age), while in the other regions it was around 26 years. A meta-analysis showed that the age at symptom onset ranged from 20 and 35 years [19], which is in line with the IMAS Regional differences in axial spondyloarthritis phenotype 5 cohort. Therefore, non-rheumatology medical specialists should consider the presence of back pain in young adults as a possible indicator of axSpA. ...
... The overall mean diagnostic delay for IMAS patients was about 7.4 years, the highest being in South Africa and the lowest in Asia. This is slightly longer than assessed by a metaanalysis of 64 studies that reported a mean diagnostic delay of 6.7 years and the systematic review of 69 studies by Hay reporting a median delay of between 2 and 6 years [19,20]. The diagnostic delay of patients with axSpA is unacceptable and may affect the progression of the disease and consequently the burden on the patients. ...
Objectives
To explore differences in axial spondyloarthritis (axSpA) clinical phenotype around the world in a large sample of patients included in the International Map of Axial Spondyloarthritis (IMAS).
Method
IMAS was a cross-sectional online survey (2017–2022) of 5557 unselected axSpA patients from 27 countries. We analysed across five geographic regions the age at symptom onset, diagnostic delay, gender, HLA-B27, family history, extra-musculoskeletal manifestations, presence of comorbidities, disease activity (BASDAI), level of spinal stiffness and treatments.
Results
Of 5557 IMAS participants, 3493 were from Europe, 770 from North America, 600 from Asia, 548 from Latin America and 146 from South Africa. Age at symptom onset ranged between 25 and 30 years and was higher in Latin America. Diagnostic delay was longest in South Africa and lowest in Asia. The lowest HLA-B27 positivity was observed in Latin America and the highest in Asia. Extra-musculoskeletal manifestations were the lowest in Europe. Mean disease activity (BASDAI) was 5.4, with highest values in South Africa and lowest in Asia. Most of the patients had used NSAIDs for their condition and less than half had ever taken conventional synthetic DMARDS; both were more frequent in Latin America and South Africa. Almost half of the patients had ever taken biologic DMARDs, more frequent use being in the Americas.
Conclusion
There is great heterogeneity of axSpA clinical phenotype presentation around the world. AxSpA manifests differently in different regions, so further understanding of these differences of phenotypes is needed to achieve early diagnosis and initiation of optimal disease treatment in axSpA in the different regions.
... The approach to treatment can involve a combination of medications, physical therapy, and lifestyle modifications. For individuals with more severe or persistent symptoms, the biologic and targeted disease-modifying anti-rheumatic drugs (DMARDs) are able to prevent the loss of functional capacity, if administered before to the structural lesions (4,5,8,9). ...
Early diagnosis in rheumatoid arthritis (RA) and axial spondyloarthritis (axSpA) is essential to initiate timely interventions, such as medication and lifestyle changes, preventing irreversible joint damage, reducing symptoms, and improving long-term outcomes for patients. Since magnetic resonance imaging (MRI) of the wrist and hand, in case of RA and MRI of the sacroiliac joints (SIJ) in case of axSpA can identify inflammation before it is clinically discernible, this modality may be crucial for early diagnosis. Artificial intelligence (AI) techniques, together with machine learning (ML) and deep learning (DL) have quickly evolved in the medical field, having an important role in improving diagnosis, prognosis, in evaluating the effectiveness of treatment and monitoring the activity of rheumatic diseases through MRI. The improvements of AI techniques in the last years regarding imaging interpretation have demonstrated that a computer-based analysis can equal and even exceed the human eye. The studies in the field of AI have investigated how specific algorithms could distinguish between tissues, diagnose rheumatic pathology and grade different signs of early inflammation, all of them being crucial for tracking disease activity. The aim of this paper is to highlight the implementation of AI models in MRI with focus on diagnosis of RA and axSpA through a literature review.
