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ObjectivesTo compare the prevalence, clinical and radiographic characteristics of psoriatic spondyloarthritis (PsSpA) in psoriatic arthritis (PsA), with ankylosing spondylitis (AS).MethodsA prospective single-centre cross-sectional observational study recruited consecutive PsA and AS cases. Participants completed outcome measures, and underwent clinical examination, axial radiographic scoring and HLA-sequencing. Multivariable analyses are presented.ResultsThe 402 enrolled cases (201 PsA, 201 AS; fulfilling classification criteria for respective conditions) were reclassified based upon radiographic axial disease and psoriasis, as: 118 PsSpA, 127 peripheral-only PsA (pPsA), and 157 AS without psoriasis (AS) cases. A significant proportion of patients with radiographic axial disease had PsSpA (118/275; 42.91%), and often had symptomatically silent axial disease (30/118; 25.42%). Modified New York criteria for AS were fulfilled by 48/201 (23.88%) PsA cases, and Classification of Psoriatic Arthritis criteria by 49/201 (24.38%) AS cases. pPsA compared with PsSpA cases had a lower frequency of HLA-B*27 (OR 0.12; 95% CI 0.05 to 0.25). Disease activity, metrology and disability were comparable in PsSpA and AS. A significant proportion of PsSpA cases had spondylitis without sacroiliitis (39/118; 33.05%); they less frequently carried HLA-B*27 (OR 0.11; 95% CI 0.04 to 0.33). Sacroiliac joint complete ankylosis (adjusted OR, ORadj 2.96; 95% CI 1.42 to 6.15) and bridging syndesmophytes (ORadj 2.78; 95% CI 1.49 to 5.18) were more likely in AS than PsSpA. Radiographic axial disease was more severe in AS than PsSpA (Psoriatic Arthritis Spondylitis Radiology Index Score: adjusted incidence risk ratio 1.13; 95% CI 1.09 to 1.19).ConclusionsIn a combined cohort of patients with either PsA or AS from a single centre, 24% fulfilled classification criteria for both conditions. The pattern of axial disease was influenced significantly by the presence of skin psoriasis and HLA-B*27.

Psoriatic disease (PsD) is a heterogeneous condition that can affect peripheral and axial joints (arthritis), entheses, skin (psoriasis) and other structures. Over the past decade, considerable advances have been made both in our understanding of the pathogenesis of PsD and in the treatment of its diverse manifestations. However, several major areas of continued unmet need in the care of patients with PsD have been identified. One of these areas is the prediction of poor outcome, notably radiographic outcome in patients with psoriatic arthritis, so that stratified medicine approaches can be taken; another is predicting response to the numerous current and emerging therapies for PsD, so that precision medicine can be applied to rapidly improve clinical outcome and reduce the risk of toxicity. In order to address these needs, novel approaches, including imaging, tissue analysis and the application of proteogenomic technologies, are proposed as methodological solutions that will assist the dissection of the critical immune-metabolic pathways in this complex disease. Learning from advances made in other inflammatory diseases, it is time to address these unmet needs in a multi-centre partnership aimed at improving short-term and long-term outcomes for patients with PsD.In this Review, the authors discuss how new approaches, including imaging, tissue analysis and omics technologies, could be applied to identify patients with a poor prognosis and to predict response to treatment, thus enabling precision medicine and improving outcomes in psoriatic disease.

Aims: The ability to predict response to treatment remains a key unmet need in psoriatic disease. We conducted a systematic review of studies relating to biomarkers associated with response to treatment in either psoriasis vulgaris (PsV) or psoriatic arthritis (PsA). Methods: A search was conducted in PubMed, Embase and the Cochrane library from their inception to 2 September 2020, and conference proceedings from four major rheumatology conferences. Original research articles studying pre-treatment biomarker levels associated with subsequent response to pharmacologic treatment in either PsV or PsA were included. Results: A total of 765 articles were retrieved and after review, 44 articles (22 relating to PsV and 22 to PsA) met the systematic review’s eligibility criteria. One study examined the response to methotrexate, one the response to tofacitinib and all the other studies to biologic disease-modifying antirheumatic drugs (DMARDs). Whilst several studies examined the HLA-C*06 allele in PsV, the results were conflicting. Interleukin (IL)-12 serum levels and polymorphisms in the IL-12B gene show promise as biomarkers of treatment response in PsV. Most, but not all, studies found that higher baseline levels of C-reactive protein (CRP) were associated with a better clinical response to treatment in patients with PsA. Conclusion: Several studies have identified biomarkers associated with subsequent response to treatment in psoriatic disease. However, due to the different types of biomarkers, treatments and outcome measures used, firm conclusions cannot be drawn. Further validation is needed before any of these biomarkers translate to clinical practice.

In view of the growth of clinical risk prediction models using genetic data, there is an increasing need for studies that use appropriate methods to select the optimum number of features from a large number of genetic variants with a high degree of redundancy between features due to linkage disequilibrium (LD). Filter feature selection methods based on information theoretic criteria, are well suited to this challenge and will identify a subset of the original variables that should result in more accurate prediction. However, data collected from cohort studies are often high-dimensional genetic data with potential confounders presenting challenges to feature selection and risk prediction machine learning models. Patients with psoriasis are at high risk of developing a chronic arthritis known as psoriatic arthritis (PsA). The prevalence of PsA in this patient group can be up to 30% and the identification of high risk patients represents an important clinical research which would allow early intervention and a reduction of disability. This also provides us with an ideal scenario for the development of clinical risk prediction models and an opportunity to explore the application of information theoretic criteria methods. In this study, we developed the feature selection and psoriatic arthritis (PsA) risk prediction models that were applied to a cross-sectional genetic dataset of 1462 PsA cases and 1132 cutaneous-only psoriasis (PsC) cases using 2-digit HLA alleles imputed using the SNP2HLA algorithm. We also developed stratification method to mitigate the impact of potential confounder features and illustrate that confounding features impact the feature selection. The mitigated dataset was used in training of seven supervised algorithms. 80% of data was randomly used for training of seven supervised machine learning methods using stratified nested cross validation and 20% was selected randomly as a holdout set for internal validation. The risk prediction models were then further validated in UK Biobank dataset containing data on 1187 participants and a set of features overlapping with the training dataset.Performance of these methods has been evaluated using the area under the curve (AUC), accuracy, precision, recall, F1 score and decision curve analysis(net benefit). The best model is selected based on three criteria: the ‘lowest number of feature subset’ with the ‘maximal average AUC over the nested cross validation’ and good generalisability to the UK Biobank dataset. In the original dataset, with over 100 different bootstraps and seven feature selection (FS) methods, HLA_C_*06 was selected as the most informative genetic variant. When the dataset is mitigated the single most important genetic features based on rank was identified as HLA_B_*27 by the seven different feature selection methods, consistent with previous analyses of this data using regression based methods. However, the predictive accuracy of these single features in post mitigation was found to be moderate (AUC= 0.54 (internal cross validation), AUC=0.53 (internal hold out set), AUC=0.55(external data set)). Sequentially adding additional HLA features based on rank improved the performance of the Random Forest classification model where 20 2-digit features selected by Interaction Capping (ICAP) demonstrated (AUC= 0.61 (internal cross validation), AUC=0.57 (internal hold out set), AUC=0.58 (external dataset)). The stratification method for mitigation of confounding features and filter information theoretic feature selection can be applied to a high dimensional dataset with the potential confounders.

Background: Involvement of the axial skeleton (sacroiliac joints and spine) is a relatively frequent manifestation associated with psoriatic skin disease, mostly along with involvement of peripheral musculoskeletal structures (peripheral arthritis, enthesitis, dactylitis), which are referred to as psoriatic arthritis (PsA). Data suggest that up to 30% of patients with psoriasis have PsA. Depending on the definition used, the prevalence of axial involvement varies from 25% to 70% of patients with PsA. However, there are currently no widely accepted criteria for axial involvement in PsA.Objective: The overarching aim of the Axial Involvement in Psoriatic Arthritis (AXIS) study is to systematically evaluate clinical and imaging manifestations indicative of axial involvement in patients with PsA and to develop classification criteria and a unified nomenclature for axial involvement in PsA that would allow defining a homogeneous subgroup of patients for research. Design: Prospective, multicenter, multinational, cross-sectional study. Methods and analyses: In this multicenter, multinational, cross-sectional study, eligible patients [adult patients diagnosed with PsA and fulfilling Classification Criteria for Psoriatic Arthritis (CASPAR) with musculoskeletal symptom duration of ⩽10 years not treated with biological or targeted synthetic disease-modifying anti-rheumatic drugs] will be recruited prospectively. They will undergo study-related clinical and imaging examinations. Imaging will include radiography and magnetic resonance imaging examinations of sacroiliac joints and spine. Local investigators will evaluate for the presence of axial involvement based on clinical and imaging information which will represent the primary outcome of the study. In addition, imaging will undergo evaluation by central review. Finally, the central clinical committee will determine the presence of axial involvement based on all available information. Ethics: The study will be performed according to the ethical principles of the Declaration of Helsinki and International Council for Harmonisation Good Clinical Practice guidelines. The study protocol will be approved by the individual Independent Ethics Committee / Institutional Review Board of participating centers. Written informed consent will be obtained from all included patients.Registration: ClinicalTrials.gov ID: NCT04434885.

Objectives: To: (a) determine the extent of ultrasound (US)-detected peripheral enthesitis in a cohort of patients with psoriatic arthritis (PsA); (b) compare this with three clinical examination (CE) enthesitis indices; and (c) determine the effect of concurrent fibromyalgia on the evaluation of enthesitis. Methods: A prospective single-centre cross-sectional study of consecutive outpatients with established PsA undergoing clinical examination for enthesitis and US examination for inflammatory and structural lesions of enthesitis. Multivariable analyses tested for association between US scores, CE enthesitis indices and influence of concurrent fibromyalgia. Results: A total of 106 patients were assessed. Of these, 91/106 (85.8%) had CE enthesitis and 105/106 (99.1%) had ⩾1 US feature of enthesitis. There was a moderate correlation between US entheseal inflammation and both the Leeds Enthesitis Index (LEI) (Spearman rank, r = 0.36) and Spondyloarthritis Research Consortium of Canada Enthesitis Index (SPARCC) (r = 0.44). US entheseal damage did not correlate with CE enthesitis indices. Twenty-eight (26.4%) patients were classified as having concurrent fibromyalgia, in whom multivariable regression analyses demonstrated no correlation between US scores and CE enthesitis indices. PsA patients without fibromyalgia demonstrated a statistically significant association between both LEI (r = 0.48, p < 0.0001) and SPARCC (r = 0.62, p < 0.0001) and US entheseal inflammation. Conclusion: There is a moderate association between US entheseal inflammation, but not damage, and CE enthesitis indices in patients with PsA. The presence of concurrent fibromyalgia is linked with higher CE enthesitis scores, without an increase in US inflammation, suggesting that CE enthesitis indices should be used/interpreted with caution in these patients. Imaging, including US, should be the preferred modality to detect enthesitis in PsA patients with concurrent fibromyalgia.

Multidisciplinary (MD) care is essential in the management of patients with spondyloarthritis (SpA) and is one of the main pillars of disease management and patient care. However, evidence supporting the effectiveness and benefits of this strategy in SpA is scarce. In this review we discuss the three types of MD care models: (i) combined clinics (MD units), including ‘face to face’, ‘parallel’ and ‘circuit approach’ clinics; (ii) MD team meetings; (iii) group consultations. The most frequently used model in SpA studies has been the ‘parallel’ combined clinic and usually encompasses a rheumatologist and another specialist, most commonly a dermatologist or a gastroenterologist, that work in tandem according to predefined referral criteria and treatment algorithms. MD working seems to improve the care of patients with SpA by a better identification and diagnosis of the disease, an earlier and more comprehensive treatment approach, and better outcomes for patients in terms of disease activity, physical function, quality of life and patient satisfaction. Nevertheless, challenges remain. Data on effectiveness and feasibility are scarce and are mostly derived from studies with design issues and often without a unidisciplinary care comparator arm. Although patient centricity is one of the core values of patient care and MD setting in SpA, the patient often does not play an active role in most of the MD settings studied or in common clinical practice. Further efforts should be made so that MD care reflects patients’ expectations and needs. Overcoming these limits will help to implement successfully SpA MD care in daily clinical practice and subsequently to achieve a higher quality of care for our patients.

Since the second version of the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) treatment recommendations were published in 2015, therapeutic options for psoriatic arthritis (PsA) have advanced considerably. This work reviews the literature since the previous recommendations (data published 2013–2020, including conference presentations between 2017 and 2020) and reports high-quality, evidence-based, domain-focused recommendations for medication selection in PsA developed by GRAPPA clinicians and patient research partners. The overarching principles for the management of adults with PsA were updated by consensus. Principles considering biosimilars and tapering of therapy were added, and the research agenda was revised. Literature searches covered treatments for the key domains of PsA: peripheral arthritis, axial disease, enthesitis, dactylitis, and skin and nail psoriasis; additional searches were performed for PsA-related conditions (uveitis and inflammatory bowel disease) and comorbidities. Individual subcommittees used a GRADE-informed approach, taking into account the quality of evidence for therapies, to generate recommendations for each of these domains, which were incorporated into an overall schema. Choice of therapy for an individual should ideally address all disease domains active in that patient, supporting shared decision-making. As safety issues often affect potential therapeutic choices, additional consideration was given to relevant comorbidities. These GRAPPA treatment recommendations provide up-to-date, evidence-based guidance on PsA management for clinicians and people with PsA.This Evidence-Based Guideline presents the latest treatment recommendations for medication selection in psoriatic arthritis (PsA), covering the six clinical domains of PsA, related conditions and associated comorbidities, and reflecting important advances in the field since the previous update.

Background A recent systematic review identified four candidate serum-soluble bone-turnover biomarkers (dickkopf-1, Dkk-1; macrophage-colony stimulating factor, M-CSF; matrix metalloproteinase-3, MMP-3; osteoprotegerin, OPG) showing possible association with psoriatic arthritis (PsA). We aimed to: (i) confirm and determine if these four biomarkers are associated with PsA; (ii) differentiate psoriasis cases with and without arthritis; and (iii) differentiate PsA cases with and without axial arthritis. Methods A prospective cross-sectional comparative two-centre study recruited 200 patients with psoriasis without arthritis (PsC), 127 with PsA without axial arthritis (pPsA), 117 with PsA with axial arthritis (psoriatic spondyloarthritis, PsSpA), 157 with ankylosing spondylitis (AS) without psoriasis, and 50 matched healthy controls (HC). Serum biomarker concentrations were measured using ELISA. Multivariable regression and receiver operating characteristic analyses were performed. Results MMP-3 concentrations were significantly higher and M-CSF significantly lower in each arthritis disease group compared with HC ( p  ≤ 0.02). MMP-3 concentrations were significantly higher (adjusted odds ratio, OR adj 1.02 per ng/ml increase in concentration; p  = 0.0004) and M-CSF significantly lower (OR adj 0.44 per ng/ml increase; p  = 0.01) in PsA (pPsA and PsSpA combined) compared with PsC. Dkk-1 concentrations were significantly higher (OR adj 1.22 per ng/mL increase; p  = 0.01), and OPG concentrations significantly lower (OR adj 0.20 per ng/mL increase; p  = 0.02) in patients with axial arthritis (PsSpA and AS combined) than in those without (pPsA). Furthermore, Dkk-1 concentrations were significantly higher along a spectrum of increasing axial arthritis; Dkk-1 concentrations were higher in AS compared with PsSpA (OR adj 1.18 per ng/mL increase; p  = 0.02). Receiver operating characteristic analysis showed MMP-3 to be the best single biomarker for differentiating PsA from PsC (AUC 0.70 for a cut-off of 14.51 ng/mL; sensitivity 0.76, specificity 0.60). Conclusions MMP-3 and M-CSF are biomarkers for the presence of arthritis in psoriatic disease, and could therefore be used to screen for PsA in psoriasis cohorts. Dkk-1 and OPG are biomarkers of axial arthritis; they could therefore be used to screen for the presence of axial disease in PsA cases, and help differentiate PsSpA from AS. High concentrations of Dkk-1 in AS and PsSpA compared with HC, support previous reports that Dkk-1 is dysfunctional in the spondyloarthritides.