Third and Fourth Vaccine Doses Broaden and Prolong Immunity to SARS-CoV-2 in Adult Patients with Immune-Mediated Inflammatory Diseases.

Previous studies have reported impaired humoral responses after SARS-CoV-2 mRNA vaccination in patients with immune-mediated inflammatory diseases (IMIDs), particularly those treated with anti-TNF biologics. We previously reported that IMID patients diagnosed with inflammatory bowel disease, psoriasis, psoriatic arthritis, ankylosing spondylitis, or rheumatoid arthritis exhibited greater waning of Ab and T cell responses than healthy control subjects after SARS-CoV-2 vaccine dose 2. Fewer data are available on the effects of third and fourth doses. This observational cohort study collected plasma and PBMCs from healthy control subjects and untreated or treated patients with IMIDs prevaccination and after one to four doses of SARS-CoV-2 mRNA vaccine (BNT162b2 or mRNA-1273). SARS-CoV-2-specific Ab levels, neutralization, and T cell cytokine release were measured against wild-type and Omicron BA.1 and BA.5 variants of concern. Third vaccine doses substantially restored and prolonged Ab and T cell responses in patients with IMIDs and broadened responses against variants of concern. Fourth-dose effects were subtle but also prolonged Ab responses. However, patients with IMIDs treated with anti-TNF, especially patients with inflammatory bowel disease, exhibited lower Ab responses even after the fourth dose. Although T cell IFN-γ responses were maximal after one dose, IL-2 and IL-4 production increased with successive doses, and early production of these cytokines was predictive of neutralization responses at 3-4 mo postvaccination. Our study demonstrates that third and fourth doses of the SARS-CoV-2 mRNA vaccines sustain and broaden immune responses to SARS-CoV-2, supporting the recommendation for three- and four-dose vaccination regimens in patients with IMIDs.

Classifying patients with psoriatic arthritis according to their disease activity status using serum metabolites and machine learning.

INTRODUCTION: Psoriatic arthritis (PsA) is a heterogeneous inflammatory arthritis, affecting approximately a quarter of patients with psoriasis. Accurate assessment of disease activity is difficult. There are currently no clinically validated biomarkers to stratify PsA patients based on their disease activity, which is important for improving clinical management. OBJECTIVES: To identify metabolites capable of classifying patients with PsA according to their disease activity. METHODS: An in-house solid-phase microextraction (SPME)-liquid chromatography-high resolution mass spectrometry (LC-HRMS) method for lipid analysis was used to analyze serum samples obtained from patients classified as having low (n = 134), moderate (n = 134) or high (n = 104) disease activity, based on psoriatic arthritis disease activity scores (PASDAS). Metabolite data were analyzed using eight machine learning methods to predict disease activity levels. Top performing methods were selected based on area under the curve (AUC) and significance. RESULTS: The best model for predicting high disease activity from low disease activity achieved AUC 0.818. The best model for predicting high disease activity from moderate disease activity achieved AUC 0.74. The best model for classifying low disease activity from moderate and high disease activity achieved AUC 0.765. Compounds confirmed by MS/MS validation included metabolites from diverse compound classes such as sphingolipids, phosphatidylcholines and carboxylic acids. CONCLUSION: Several lipids and other metabolites when combined in classifying models predict high disease activity from both low and moderate disease activity. Lipids of key interest included lysophosphatidylcholine and sphingomyelin. Quantitative MS assays based on selected reaction monitoring, are required to quantify the candidate biomarkers identified.

Residual Disease Activity in Canadian Patients With Psoriatic Arthritis Treated With Advanced Therapies: Results From a Multiregistry Analysis (UNISON-PsA).

OBJECTIVE: Although patient outcomes in psoriatic arthritis (PsA) have improved with the advent of advanced therapies, there remains a high unmet need to treat residual disease activity. The objective of the current study was to quantify residual disease activity and burden of disease in Canadian patients with PsA. METHODS: This was a multiregion, observational, retrospective analysis of patient data extracted from the Rhumadata and the International Psoriasis and Arthritis Research Team (IPART) registries, analyzing deidentified data from patients who had initiated advanced therapy for the treatment of PsA between January 2010 and December 2019. The primary endpoint was the proportion of patients failing to achieve minimal disease activity (MDA) within 6 months; secondary endpoints included clinical and patient-reported burden of disease. Descriptive statistics included summaries by region, treatment class, and number of prior advanced therapies. RESULTS: One thousand five hundred ninety-six patients were included. The proportions of patients who failed to achieve MDA within 6 months of an advanced therapy were 64.8% in Ontario, 68.3% in Western Canada, 74.8% in Quebec, and 75% in the Atlantic/East region. Failure to achieve MDA was higher among patients receiving an IL-17i compared with a TNFi in all regions except the Atlantic/East. Between 73.2% and 78.6% of patients reported pain at 6 months, and continuing functional impairment varied from 24% in the West to 83.3% in the Atlantic/East. CONCLUSION: There is substantial burden and unmet need for improved therapies for Canadians with PsA. There is a wide regional variation in outcomes that requires further assessment.

When Should I Get My Next COVID-19 Vaccine? Data From the Surveillance of Responses to COVID-19 Vaccines in Systemic Immune-Mediated Inflammatory Diseases (SUCCEED) Study.

OBJECTIVE: To determine how serologic responses to coronavirus disease 2019 (COVID-19) vaccination and infection in immune-mediated inflammatory disease (IMID) are affected by time since last vaccination and other factors. METHODS: Post-COVID-19 vaccination, data, and dried blood spots or sera were collected from adults with rheumatoid arthritis, inflammatory bowel disease, systemic lupus erythematosus, ankylosing spondylitis and spondylarthritis, and psoriasis and psoriatic arthritis. The first sample was collected at enrollment, then at 2 to 4 weeks and 3, 6, and 12 months after the latest vaccine dose. Multivariate generalized estimating equation regressions (including medications, demographics, and vaccination history) evaluated serologic response, based on log-transformed anti-receptor-binding domain (RBD) IgG titers; we also measured antinucleocapsid (anti-N) IgG. RESULTS: Positive associations for log-transformed anti-RBD titers were seen with female sex, number of doses, and self-reported COVID-19 infections in 2021 to 2023. Negative associations were seen with prednisone, anti-tumor necrosis factor agents, and rituximab. Over the 2021-2023 period, most (94%) of anti-N positivity was associated with a self-reported infection in the 3 months prior to testing. From March 2021 to February 2022, anti-N positivity was present in 5% to 15% of samples and was highest in the post-Omicron era, with antinucleocapsid positivity trending to 30% to 35% or higher as of March 2023. Anti-N positivity in IMID remained lower than Canada's general population seroprevalence (> 50% in 2022 and > 75% in 2023). Time since last vaccination was negatively associated with log-transformed anti-RBD titers, particularly after 210 days. CONCLUSION: Ours is the first pan-Canadian IMID assessment of how vaccine history and other factors affect serologic COVID-19 vaccine responses. These findings may help individuals personalize vaccination decisions, including consideration of additional vaccination when > 6 months has elapsed since last COVID-19 vaccination/infection.

Total Hip Arthroplasty Versus Education and Exercise: A Propensity-Matched Analysis of 266 Patients Who Have Hip Osteoarthritis.

BACKGROUND: Total hip arthroplasty (THA) for osteoarthritis (OA) is a major health system cost. Education and exercise (Edu + Ex) programs may reduce the number of THAs needed, but supporting data are limited. This study aimed to estimate the treatment effect of THA versus Edu + Ex on pain, function, and quality of life outcomes 3 and 12 months after treatment initiation for hip OA. METHODS: Patients who had hip OA who underwent THA or an Edu + Ex program were included in this propensity-matched study. In 778 patients (Edu + Ex, n = 303; THA, n = 475), propensity scores were based on pretreatment characteristics, and patients were matched on a 1:1 ratio. Between-group treatment effects (pain, function, and quality of life) were estimated as the mean difference (MD) in change from pretreatment to 3-month and 12-month follow-up using linear mixed models. RESULTS: The matched sample consisted of 266 patients (Edu + Ex, n = 133; THA, n = 133) who were balanced on all pretreatment characteristics except opioid use. At 12-month follow-up, THA resulted in significantly greater improvements in pain (MD 35.4; 95% confidence interval [CI] 31.4 to 39.4), function (MD 30.5; 95% CI 26.3 to 34.7), and quality of life (MD 33.6; 95% CI 28.8 to 38.4). Between 17% and 30% of patients receiving Edu + Ex experienced a surgical threshold for clinically meaningful improvement in outcomes, compared to 84% and 90% of THA patients. CONCLUSIONS: A THA provides greater improvements in pain, function, and quality of life. A notable proportion of Edu + Ex patients had clinically meaningful improvements, suggesting Edu + Ex may result in THA deferral in some patients, but confirmatory trials are needed.

Histone deacetylase inhibitors as a potential new treatment for psoriatic disease and other inflammatory conditions.

Collectively known as psoriatic disease, psoriasis and psoriatic arthritis (PsA) are immune-mediated inflammatory diseases in which patients present with cutaneous and musculoskeletal inflammation. Affecting roughly 2-3% of the world's total population, there remains unmet therapeutic needs in both psoriasis and PsA despite the availability of current immunomodulatory treatments. As a result, patients with psoriatic disease often experience reduced quality of life. Recently, a class of small molecules, commonly investigated as anti-cancer agents, called histone deacetylase (HDAC) inhibitors, have been proposed as a new promising anti-inflammatory treatment for immune- and inflammatory-related diseases. In inflammatory diseases, current evidence is derived from studies on diseases like rheumatoid arthritis (RA) and systematic lupus erythematosus (SLE), and while there are some reports studying psoriasis, data on PsA patients are not yet available. In this review, we provide a brief overview of psoriatic disease, psoriasis, and PsA, as well as HDACs, and discuss the rationale behind the potential use of HDAC inhibitors in the management of persistent inflammation to suggest its possible use in psoriatic disease.

Fingerprint Systems: Sensors, Image Acquisition, Interoperability and Challenges.

The fingerprint is a widely adopted biometric trait in forensic and civil applications. Fingerprint biometric systems have been investigated using contact prints and latent and contactless images which range from low to high resolution. While the imaging techniques are advancing with sensor variations, the input fingerprint images also vary. A general fingerprint recognition pipeline consists of a sensor module to acquire images, followed by feature representation, matching and decision modules. In the sensor module, the image quality of the biometric traits significantly affects the biometric system's accuracy and performance. Imaging modality, such as contact and contactless, plays a key role in poor image quality, and therefore, paying attention to imaging modality is important to obtain better performance. Further, underlying physical principles and the working of the sensor can lead to their own forms of distortions during acquisition. There are certain challenges in each module of the fingerprint recognition pipeline, particularly sensors, image acquisition and feature representation. Present reviews in fingerprint systems only analyze the imaging techniques in fingerprint sensing that have existed for a decade. However, the latest emerging trends and recent advances in fingerprint sensing, image acquisition and their challenges have been left behind. Since the present reviews are either obsolete or restricted to a particular subset of the fingerprint systems, this work comprehensively analyzes the state of the art in the field of contact-based, contactless 2D and 3D fingerprint systems and their challenges in the aspects of sensors, image acquisition and interoperability. It outlines the open issues and challenges encountered in fingerprint systems, such as fingerprint performance, environmental factors, acceptability and interoperability, and alternate directions are proposed for a better fingerprint system.

Classification of HEp-2 Staining Pattern Images Using Adapted Multilayer Perceptron Neural Network-Based Intra-Class Variation of Cell Shape.

There exists a growing interest from the clinical practice research communities in the development of methods to automate HEp-2 stained cells classification procedure from histopathological images. Challenges faced by these methods include variations in cell densities and cell patterns, overfitting of features, large-scale data volume and stained cells. In this paper, a multi-class multilayer perceptron technique is adapted by adding a new hidden layer to calculate the variation in the mean, scale, kurtosis and skewness of higher order spectra features of the cell shape information. The adapted technique is then jointly trained and the probability of classification calculated using a Softmax activation function. This method is proposed to address overfitting, stained and large-scale data volume problems, and classify HEp-2 staining cells into six classes. An extensive experimental analysis is studied to verify the results of the proposed method. The technique has been trained and tested on the dataset from ICPR-2014 and ICPR-2016 competitions using the Task-1. The experimental results have shown that the proposed model achieved higher accuracy of 90.3% (with data augmentation) than of 87.5% (with no data augmentation). In addition, the proposed framework is compared with existing methods, as well as, the results of methods using in ICPR2014 and ICPR2016 competitions.The results demonstrate that our proposed method effectively outperforms recent methods.

Identifying Serum Metabolomic Markers Associated with Skin Disease Activity in Patients with Psoriatic Arthritis.

Psoriatic arthritis (PsA) is a chronic, systemic, immune-mediated inflammatory disease causing cutaneous and musculoskeletal inflammation that affects 25% of patients with psoriasis. Current methods for evaluating PsA disease activity are not accurate enough for precision medicine. A metabolomics-based approach can elucidate psoriatic disease pathogenesis, providing potential objective biomarkers. With the hypothesis that serum metabolites are associated with skin disease activity, we aimed to identify serum metabolites associated with skin activity in PsA patients. We obtained serum samples from patients with PsA (n = 150) who were classified into mild, moderate and high disease activity groups based on the Psoriasis Area Severity Index. We used solid-phase microextraction (SPME) for sample preparation, followed by data acquisition via an untargeted liquid chromatography-mass spectrometry (LC-MS) approach. Disease activity levels were predicted using identified metabolites and machine learning algorithms. Some metabolites tentatively identified include eicosanoids with anti- or pro-inflammatory properties, like 12-Hydroxyeicosatetraenoic acid, which was previously implicated in joint disease activity in PsA. Other metabolites of interest were associated with dysregulation of fatty acid metabolism and belonged to classes such as bile acids, oxidized phospholipids, and long-chain fatty acids. We have identified potential metabolites associated with skin disease activity in PsA patients.

Isolated axial disease in psoriatic arthritis and ankylosing spondylitis with psoriasis.

OBJECTIVES: To compare isolated axial psoriatic arthritis (PsA), axial PsA with peripheral involvement and isolated axial ankylosing spondylitis (AS) with psoriasis. To evaluate predictors for developing peripheral disease from isolated axial PsA over time. METHODS: Two PsA and AS cohorts identified patients with PsA with axial disease and isolated axial patients with AS with psoriasis. Logistic regression compared isolated axial PsA to axial PsA with peripheral involvement and isolated axial AS with psoriasis. Cox proportional hazards model evaluated predictors for developing peripheral disease from isolated axial PsA. RESULTS: Of 1576 patients with PsA, 2.03% had isolated axial disease and 29.38% had axial and peripheral disease. human leucocyte antigen HLA-B*27 positivity (OR 25.00, 95% CI 3.03 to 206.11) and lower Health Assessment Questionnaire scores (OR 0.004, 95% CI 0.00 to 0.28) were associated with isolated axial disease. HLA-B*27 also predicted peripheral disease development over time (HR 7.54, 95% CI 1.79 to 31.77). Of 1688 patients with AS, 4.86% had isolated axial disease with psoriasis. Isolated axial patients with PsA were older at diagnosis (OR 1.06, 95% CI 1.01 to 1.13), more likely to have nail lesions (OR 12.37, 95% CI 2.22 to 69.07) and less likely to have inflammatory back pain (OR 0.12, 95% CI 0.02 to 0.61) compared with patients with isolated axial AS with psoriasis. CONCLUSIONS: Isolated axial PsA and AS with psoriasis are uncommon. HLA-B*27 positivity is associated with isolated axial PsA and may identify those who develop peripheral disease over time. Isolated axial PsA is associated with better functional status. Isolated axial PsA appears clinically distinct from isolated axial AS with psoriasis.

Defining imaging sub-phenotypes of psoriatic arthritis: integrative analysis of imaging data and gene expression in a PsA patient cohort.

OBJECTIVES: To define imaging sub-phenotypes in patients with PsA; determine their association with whole blood gene expression and identify biological pathways characterizing the sub-phenotypes. METHODS: Fifty-five patients with PsA ready to initiate treatment for active disease were prospectively recruited. We performed musculoskeletal ultrasound assessment of the extent of inflammation in the following domains: synovitis, peritenonitis, tenosynovitis and enthesitis. Peripheral whole blood was profiled with RNAseq, and gene expression data were obtained. First, unsupervised cluster analysis was performed to define imaging sub-phenotypes that reflected the predominant tissue involved. Subsequently, principal component analysis was used to determine the association between imaging-defined sub-phenotypes and peripheral blood gene expression profile. Pathway enrichment analysis was performed to identify underlying mechanisms that characterize individual sub-phenotypes. RESULTS: Cluster analysis revealed three imaging sub-phenotypes: (i) synovitis predominant [n = 31 (56%)]; (ii) enthesitis predominant [n = 13 (24%)]; (iii) peritenonitis predominant [n = 11 (20%)]. The peritenonitis-predominant sub-phenotype had the most severe clinical joint involvement, whereas the enthesitis-predominant sub-phenotype had the highest tender entheseal count. Unsupervised clustering of gene expression data identified three sub-phenotypes that partially overlapped with the imaging sub-phenotypes suggesting biological and clinical relevance of these sub-phenotypes. We therefore characterized enriched differential pathways, which included: immune system (innate system, B cells and neutrophil degranulation), complement system, platelet activation and coagulation function. CONCLUSIONS: We identified three sub-phenotypes based on the predominant tissue involved in patients with active PsA. Distinct biological pathways may underlie these imaging sub-phenotypes seen in PsA, suggesting their biological and clinical importance.

pathDIP 4: an extended pathway annotations and enrichment analysis resource for human, model organisms and domesticated species.

PathDIP was introduced to increase proteome coverage of literature-curated human pathway databases. PathDIP 4 now integrates 24 major databases. To further reduce the number of proteins with no curated pathway annotation, pathDIP integrates pathways with physical protein-protein interactions (PPIs) to predict significant physical associations between proteins and curated pathways. For human, it provides pathway annotations for 5366 pathway orphans. Integrated pathway annotation now includes six model organisms and ten domesticated animals. A total of 6401 core and ortholog pathways have been curated from the literature or by annotating orthologs of human proteins in the literature-curated pathways. Extended pathways are the result of combining these pathways with protein-pathway associations that are predicted using organism-specific PPIs. Extended pathways expand proteome coverage from 81 088 to 120 621 proteins, making pathDIP 4 the largest publicly available pathway database for these organisms and providing a necessary platform for comprehensive pathway-enrichment analysis. PathDIP 4 users can customize their search and analysis by selecting organism, identifier and subset of pathways. Enrichment results and detailed annotations for input list can be obtained in different formats and views. To support automated bioinformatics workflows, Java, R and Python APIs are available for batch pathway annotation and enrichment analysis. PathDIP 4 is publicly available at http://ophid.utoronto.ca/pathDIP.

Assessment of the Toronto Psoriatic Arthritis Screen 2 as a Screening Tool for Psoriasis.

BACKGROUND: Psoriasis is a chronic inflammatory disease affecting multiple organ systems and resulting in reduced quality of life for many patients. A screening tool would be useful, particularly in underserviced or research settings with limited access to dermatologists. The Toronto Psoriatic Arthritis Screen, version 2 (ToPAS 2) is a validated screening tool for psoriatic arthritis containing questions specific for psoriasis. OBJECTIVES: To evaluate the performance of skin-specific questions from ToPAS 2 for the diagnosis of psoriasis. METHODS: Participants aged >18 were recruited from Dermatology and Family Medicine clinics and completed the ToPAS 2 questionnaire prior to being examined by a dermatologist for psoriasis. Two scoring indexes were derived from the ToPAS 2 skin-related questions using backward selection regression models. Statistical analysis was performed using receiver operating characteristic (ROC) curves to measure their performances. RESULTS: Two hundred and fifty eight participants were recruited. 32 (12%) were diagnosed with psoriasis by dermatologist assessment. Index 1 includes all 5 skin-related questions from ToPAS 2, while Index 2 includes three of the five questions. Both indexes demonstrate high specificity (82% to 92%), sensitivity (69% to 84%), and excellent negative predictive value (NPV) (>95%) for a diagnosis of psoriasis. The overall discriminatory power of these models is 0.823 (Index 1) and 0.875 (Index 2). CONCLUSIONS: Skin-related questions from ToPAS 2 have discriminatory value in detecting psoriasis, specifically questions relating to a family history, a prior physician diagnosis of psoriasis or a rash consistent with images of plaque psoriasis. This study is a valuable step in developing a screening tool for psoriasis.

Targeted metabolomic profiling and prediction of cardiovascular events: a prospective study of patients with psoriatic arthritis and psoriasis.

OBJECTIVE: In patients with psoriatic disease (PsD), we sought serum metabolites associated with cardiovascular (CV) events and investigated whether they could improve CV risk prediction beyond traditional risk factors and the Framingham Risk Score (FRS). METHODS: Nuclear magnetic resonance metabolomics identified biomarkers for incident CV events in patients with PsD. The association of each metabolite with incident CV events was analysed using Cox proportional hazards regression models first adjusted for age and sex, and subsequently for traditional CV risk factors. Variable selection was performed using penalisation with boosting after adjusting for age and sex, and the FRS. RESULTS: Among 977 patients with PsD, 70 patients had incident CV events. In Cox regression models adjusted for CV risk factors, alanine, tyrosine, degree of unsaturation of fatty acids and high-density lipoprotein particles were associated with decreased CV risk. Glycoprotein acetyls, apolipoprotein B and cholesterol remnants were associated with increased CV risk. The age-adjusted and sex-adjusted expanded model with 13 metabolites significantly improved prediction of CV events beyond the model with age and sex alone, with an area under the receiver operator characteristic curve (AUC) of 79.9 versus 72.6, respectively (p=0.02). Compared with the FRS alone (AUC=73.9), the FRS-adjusted expanded model with 11 metabolites (AUC=75.0, p=0.72) did not improve CV risk discrimination. CONCLUSIONS: We identify novel metabolites associated with the development of CV events in patients with PsD. Further study of their underlying causal role may clarify important pathways leading to CV events in this population.

Serum metabolic fingerprinting of psoriasis and psoriatic arthritis patients using solid-phase microextraction-liquid chromatography-high-resolution mass spectrometry.

INTRODUCTION: Psoriatic arthritis (PsA), an inflammatory arthritis that develops in individuals with psoriasis, is associated with reduced quality of life. Identifying biomarkers associated with development of PsA as well as with PsA disease activity may help management of psoriatic disease. OBJECTIVES: To use metabolomic fingerprinting to determine potential candidate markers of disease conversion (psoriasis to PsA) and/or PsA activity. METHODS: A novel sample preparation protocol based on solid-phase microextraction (SPME) was used to prepare serum samples obtained from: (1) individuals with psoriasis, some of whom develop psoriatic arthritis (n = 20); (2) individuals with varying PsA activity (mild, moderate, severe; n = 10 each) and (3) healthy controls (n = 10). Metabolomic fingerprinting of the obtained extracts was performed using reversed-phase liquid chromatography coupled to high resolution mass spectrometry. RESULTS: Psoriasis patients who developed PsA had similar metabolomic profiles to patients with mild PsA and were also indistinguishable from patients with psoriasis who did not develop PsA. Elevated levels of selected long-chain fatty acids (e.g., 3-hydroxytetradecanedioic acid) that are associated with dysregulation of fatty acid metabolism, were observed in patients with severe PsA. In addition, 1,11-undecanedicarboxylic acid-an unusual fatty acid associated with peroxisomal disorders-was also identified as a classifier in PsA patients vs. healthy individuals. Furthermore, a number of different eicosanoids with either pro- or anti-inflammatory properties were detected solely in serum samples of patients with moderate and severe PsA. CONCLUSION: A global metabolomics approach was employed to analyze the serum metabolome of patients with psoriasis, PsA, and healthy controls in order to examine potential differences in the biochemical profiles at a metabolite level. A closer examination of circulating metabolites may potentially provide markers of PsA activity.

Proceedings of the 2020 GRAPPA Collaborative Research Network (CRN) Meeting.

At the 2020 Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA)-Collaborative Research Network (CRN) annual meeting, the GRAPPA-CRN group presented a pilot investigator-initiated study protocol to test electronic case report forms (eCRFs) and proposed Standardized Operating Procedures (SOPs) to evaluate biomarkers of psoriatic arthritis (PsA) associated with axial disease. The progress on 3 studies was also presented: BioDAM PsA (Biomarkers as Predictors of structural DAMage in PsA; to validate soluble biomarkers as predictors of structural damage in PsA), PreventPsA (examining the development of PsA and risk factors among patients with psoriasis and no arthritis), and PredictORPsA (Predicting Treatment respOnse in patients with eaRly PsA; in collaboration with Pfizer using samples from the Oral Psoriatic Arthritis TriaL [OPAL], to identify biomarkers of treatment response). GRAPPA-CRN funding partnerships and applications are also underway with both the Innovative Medicines Initiative (IMI) in Europe and Accelerating Medicines Partnerships (AMP) 2.0 in the USA, and the progress of these applications and associated objectives were presented.

Challenges in the clinical diagnosis of psoriatic arthritis.

Psoriatic arthritis (PsA) is a chronic heterogeneous inflammatory musculoskeletal disease. The non-specific and often subtle manifestations make early diagnosis and subsequent treatment challenging. In the absence of diagnostic criteria and biomarkers, the diagnosis is often delayed leading to poor long-term outcomes. In addition, the differential diagnosis of a patient presenting with arthritis in the setting of skin psoriasis is wide due to symptom overlap with many other diseases. Peripheral arthritis, dactylitis, enthesitis and axial arthritis are the 4 domains of musculoskeletal involvement in PsA and careful examination of each domain by a rheumatologist is the first step for a correct diagnosis. Other extra-musculoskeletal features such as the presence of uveitis, inflammatory bowel disease, nail psoriasis and elevated acute phase reactants aid in the diagnosis of PsA. Screening patients with skin psoriasis using validated questionnaires might help in early diagnosis especially when coupled with imaging.

The relationship between patient acceptable symptom state and disease activity in patients with psoriatic arthritis.

OBJECTIVES: The Psoriatic Arthritis Disease Activity Score (PASDAS) and Disease Activity Index for Psoriatic Arthritis (DAPSA) are composite PsA disease activity measures. We sought to identify the PASDAS and DAPSA cut-off points consistent with patient acceptable symptom state (PASS), the threshold of symptoms beyond which patients consider themselves well, and examine PASS across published PASDAS and DAPSA thresholds for low, moderate and high disease activity. METHODS: We used a standard protocol including physician assessment and patient-reported outcomes to prospectively record measures required to calculate PASDAS and DAPSA. We identified PASS thresholds for the PASDAS and DAPSA using receiver operating characteristics curve analyses. We assessed the frequency of reporting acceptable symptom state across disease activity thresholds for PASDAS and DAPSA scores. RESULTS: A total of 229 patients (58.5% male, mean age 55.5 years, mean disease duration 17.1 years) were recruited. The PASS threshold for the PASDAS was 3.79 [area under the curve (AUC) 0.86, sensitivity 0.75, specificity 0.82] and for the DAPSA was 11.10 (AUC 0.91, sensitivity 0.89, specificity 0.82). With the PASDAS, 90% of patients defined as having low disease activity considered their symptom state acceptable, compared with 55% and 17% among those with moderate and high disease activity, respectively. With the DAPSA, 98% of patients in disease remission considered their symptom state acceptable compared with 85, 22 and 18% among those with low, moderate and high disease activity, respectively. CONCLUSION: We have defined PASS thresholds for PASDAS and DAPSA. The PASDAS target for low disease activity and DAPSA targets of low disease activity or remission align well with PASS.

Is axial psoriatic arthritis distinct from ankylosing spondylitis with and without concomitant psoriasis?

OBJECTIVE: The aim of this study was to compare patients with ankylosing spondylitis with psoriasis (ASP) and without psoriasis (AS), to axial PsA (axPsA) patients. METHODS: Two adult cohorts were recruited from the AS clinic: ASP and AS. These two cohorts were compared with two adult cohorts recruited from the PsA clinic: axPsA (radiographic sacroiliitis: ⩾bilateral grade 2 or unilateral grade 3 or 4); and Peripheral PsA. All patients were followed prospectively according to the same protocol. The demographic, clinical and radiographic variables were compared. Adjusted means were used to account for varying intervals between visits. A logistic regression was performed and adjusted for follow-up duration. RESULTS: There were 477 axPsA patients, 826 peripheral PsA, 675 AS and 91 ASP patients included. AS patients were younger (P < 0.001), more male and HLA-B*27 positive (76%, 72% vs 64%, P ⩽ 0.001, 82%, 75%, vs 19%, P = 0.001). They had more back pain at presentation (90%, 92% vs 19%, P = 0.001), worse axial disease activity scores (bath ankylosing spondylitis disease activity index: 4.1, 3.9 vs 3.5 P = 0.017), worse back metrology (bath ankylosing spondylitis metrology index: 2.9, 2.2 vs 1.8, P < 0.001), worse physician global assessments (2.4, 2.2 vs 2.1, P < 0.001), were treated more with biologics (29%, 21% vs 7%, P = 0.001) and had a higher grade of sacroiliitis (90%, 84% vs 51%, P < 0.001). Similar differences were detected in the comparison of ASP to axPsA and in a regression model. CONCLUSION: AS patients, with or without psoriasis, seem to be different demographically, genetically, clinically and radiographically from axPsA patients. axPsA seems to be a distinct entity.

Ixekizumab treatment of biologic-naïve patients with active psoriatic arthritis: 3-year results from a phase III clinical trial (SPIRIT-P1).

OBJECTIVE: The aim was to assess the safety and efficacy of up to 156 weeks of ixekizumab (an IL-17A antagonist) treatment in PsA patients. METHODS: In a phase III study, patients naïve to biologic treatment were randomized to placebo, adalimumab 40 mg every 2 weeks (ADA; active reference) or ixekizumab 80 mg every 2 weeks (IXEQ2W) or every 4 weeks (IXEQ4W) after an initial dose of 160 mg. At week 24 (week 16 for inadequate responders), ADA (after 8-week washout) and placebo patients were re-randomized to IXEQ2W or IXEQ4W. Outcomes were evaluated using a modified non-responder imputation [linear extrapolation for radiographic progression (modified total Sharp score = 0)] during extended treatment until week 156. RESULTS: Of 417 patients, 381 entered the extension, and 243 of 381 (63.8%) completed the 156-week study. Incidence rates of treatment-emergent and serious adverse events, respectively, were 38.0 and 5.2 with IXEQ2W (n = 189) and 38.1 and 8.0 with IXEQ4W (n = 197). One death occurred (IXEQ4W). With IXEQ2W and IXEQ4W, respectively, the response rates persisted to week 156 as measured by the ACR response ≥20% (62.5 and 69.8%), ≥50% (56.1 and 51.8%) and ≥70% (43.8 and 33.4%), psoriasis area and severity index (PASI) 75 (69.1 and 63.5%), PASI 90 (64.5 and 51.2%) and PASI 100 (60.5 and 43.6%). Inhibition of radiographic progression also persisted to week 156 in 61% of IXEQ2W and 71% of IXEQ4W patients. CONCLUSION: In this 156-week study of ixekizumab, the safety profile remained consistent with previous reports, and improvements in signs and symptoms of PsA were observed, including persistent low rates of radiographic progression. TRIAL REGISTRATION: ClinicalTrials.gov, http://clinicaltrials.gov, NCT01695239, EudraCT 2011-002326-49.