Joint Damage In Psoriatic Arthritis Research Articles

Spatial dependence modeling of latent susceptibility and time to joint damage in psoriatic arthritis.

Important scientific insights into chronic diseases affecting several organ systems can be gained from modeling spatial dependence of sites experiencing damage progression. We describe models and methods for studying spatial dependence of joint damage in psoriatic arthritis (PsA). Since a large number of joints may remain unaffected even among individuals with a long disease history, spatial dependence is first modeled in latent joint-specific indicators of susceptibility. Among susceptible joints, a Gaussian copula is adopted for dependence modeling of times to damage. Likelihood and composite likelihoods are developed for settings, where individuals are under intermittent observation and progression times are subject to type K interval censoring. Two-stage estimation procedures help mitigate the computational burden arising when a large number of processes (i.e., joints) are under consideration. Simulation studies confirm that the proposed methods provide valid inference, and an application to the motivating data from the University of Toronto Psoriatic Arthritis Clinic yields important insights which can help physicians distinguish PsA from arthritic conditions with different dependencepatterns.

Defining Pre-Clinical Psoriatic Arthritis in an Integrated Dermato-Rheumatology Environment.

In excess of three quarters of patients with psoriatic arthritis (PsA) have preceding psoriasis (PsO), which offers a clinical biomarker for the recognition of early PsA. Numerous surveys have shown a remarkably high frequency of clinically occult musculoskeletal symptoms in psoriasis patients. Imaging studies, particularly ultrasound, show a high prevalence of subclinical enthesitis and other inflammatory changes in psoriasis subjects. Since a serum biomarker, such as the case of anti-citrullinated protein antibodies (ACPA) in rheumatoid arthritis, neither exists nor seems biologically plausible at this point, this article explores how integration of rheumatological and dermatological assessment can be facilitated for the early recognition of potential PsA. Given that scalp disease is a PsA predictor, but may be managed in the community, then a particular need to access this group is needed. An integrated approach between rheumatology and dermatology can involve joint clinics, parallel clinics with discussion of relevant cases or virtual contact between specialties. Early therapy evaluation and integrated strategies have considerable implications for minimizing suffering and joint damage in PsA.

Proceedings of the 2018 GRAPPA Collaborative Research Network Meeting.

The Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA)-Collaborative Research Network (CRN) intends to launch and secure funding for 3 pilot projects related to psoriatic disease, psoriatic arthritis (PsA), and cutaneous psoriasis (PsC). The first pilot project, a PsA Biomarkers for Joint Damage (BioDAM) pilot, will seek to determine the independent predictive ability of serum biomarkers for joint damage in PsA. The second pilot project will aim to identify predictors of the development of PsA among patients with PsC. The third pilot project will aim to identify biomarkers that predict treatment response in PsA and PsC. These pilot projects will prompt the development of clinical protocols to operate across participating centers, lead to the development of standard operating procedures for the collection and transport of biosamples across international borders, and begin to establish administrative and managerial structures for the CRN. The CRN hopes that the successful completion and research outputs of these 3 pilot projects will demonstrate the CRN's value to prospective collaborators and sponsors and thereby secure sustainable longterm funding.

Score tests based on a finite mixture model of Markov processes under intermittent observation.

A mixture model is described, which accommodates different Markov processes governing disease progression in a finite set of latent classes. We give special attention to the setting in which individuals are examined intermittently and transition times are consequently interval censored. A score test is developed to identify genetic markers associated with class membership. Simulation studies are conducted to validate the algorithm, assess the finite sample properties of the estimators, and assess the frequency properties of the score tests. A permutation test is recommended for settings when there is concern that the asymptotic approximation to the score test is poor. An application involving progression in joint damage in psoriatic arthritis (PsA) provides illustration and identifies human leukocyte antigen markers associated with unilateral and bilateral sacroiliac damage in individuals with PsA.

Altered Bone Remodeling in Psoriatic Disease: New Insights and Future Directions.

Psoriatic arthritis (PsA) is an inflammatory rheumatic disorder that occurs in patients with psoriasis and predominantly affects musculoskeletal structures, skin, and nails. The etiology of PsA is not well understood but evidence supports an interplay of genetic, immunologic, and environmental factors which promote pathological bone remodeling and joint damage in PsA. Localized and systemic bone loss due to increased activity of osteoclasts is well established in PsA based on animal models and translational studies. In contrast, the mechanisms responsible for pathological bone remodeling in PsA remain enigmatic although new candidate molecules and pathways have been identified. Recent reports have revealed novel findings related to bone erosion and pathologic bone formation in PsA. Many associated risk factors and contributing molecular mechanisms have also been identified. In this review, we discuss new developments in the field, point out unresolved questions regarding the pathogenetic origins of the wide array of bone phenotypes in PsA, and discuss new directions for investigation.

The association between sonographic enthesitis and radiographic damage in psoriatic arthritis

BackgroundTo examine the association between sonographic enthesitis and the severity of radiographic features of damage in the peripheral and axial joints in psoriatic arthritis (PsA).MethodsA cross-sectional analysis was conducted in patients with PsA. The MAdrid Sonography Enthesitis Index (MASEI) scoring system was used to quantify the extent of sonographic entheseal abnormalities. Radiographic damage in the peripheral joints and spine was assessed by the modified Steinbrocker score (mSS), Modified New York Criteria for sacroiliitis, and the modified Stoke Ankylosing Spondylitis Spine Score (mSASSS). The association between MASEI and the extent of radiographic damage was assessed using negative binomial and logistic regression. The results were expressed in terms of the regression coefficient estimates and their exponentiated values (eβ) or odds ratios (OR), and 95% confidence intervals (CI).ResultsTwo hundred and twenty three patients were analyzed; 58% were males, with mean ± SD age of 55.9 ± 12.9 years and PsA duration of 16.7 ± 12.4 years. Regression analyses yielded an association between higher MASEI scores (10 units increase) and peripheral joint damage including mSS (eβ = 1.42, 95% CI: 1.15, 1.72), joint ankylosis (OR = 1.93, 95% CI: 1.37, 2.72), arthritis mutilans (OR = 1.77, 95% CI: 1.23, 2.54), and periostitis (OR = 1.41, 95% CI: 1.08, 1.84). Similarly, an association was found between higher MASEI scores and axial damage as measured by mSASSS (eβ = 2.18, 95% CI: 1.16, 4.09) and sacroiliitis (OR = 1.33, 95% CI: 1.03, 1.72).ConclusionsThe severity of sonographic enthesitis is a potential marker of radiographic peripheral and axial joint damage in PsA.

Exploring the existence of a stayer population with mover-stayer counting process models: application to joint damage in psoriatic arthritis.

SummaryMany psoriatic arthritis patients do not progress to permanent joint damage in any of the 28 hand joints, even under prolonged follow‐up. This has led several researchers to fit models that estimate the proportion of stayers (those who do not have the propensity to experience the event of interest) and to characterize the rate of developing damaged joints in the movers (those who have the propensity to experience the event of interest). However, when fitted to the same data, the paper demonstrates that the choice of model for the movers can lead to widely varying conclusions on a stayer population, thus implying that, if interest lies in a stayer population, a single analysis should not generally be adopted. The aim of the paper is to provide greater understanding regarding estimation of a stayer population by comparing the inferences, performance and features of multiple fitted models to real and simulated data sets. The models for the movers are based on Poisson processes with patient level random effects and/or dynamic covariates, which are used to induce within‐patient correlation, and observation level random effects are used to account for time varying unobserved heterogeneity. The gamma, inverse Gaussian and compound Poisson distributions are considered for the random effects.

Trivariate mover-stayer counting process models for investigating joint damage in psoriatic arthritis.

In psoriatic arthritis, many patients do not develop permanent joint damage even after a prolonged follow‐up. This has led several authors to consider the possibility of a subpopulation of stayers (those who do not have the propensity to experience the event of interest), as opposed to assuming the entire population consist of movers (those who have the propensity to experience the event of interest). In addition, it is recognised that the damaged joints process may act very differently across different joint areas, particularly the hands, feet and large joints. From a clinical perspective, interest lies in identifying possible relationships between the damaged joints processes in these joint areas for the movers and estimating the proportion of stayers in these joint areas, if they exist. For this purpose, this paper proposes a novel trivariate mover‐stayer model consisting of mover‐stayer truncated negative binomial margins, and patient‐level dynamic covariates and random effects in the models for the movers and stayers, respectively. The model is then extended to have a two‐level mover‐stayer structure for its margins so that the nature of the stayer property can be investigated. A particularly attractive feature of the proposed models is that only an optimisation routine is required in their model fitting procedures. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Risk Factors and Predictors of Psoriatic Arthritis in Patients with Psoriasis

The investigation of psoriatic arthritis on psoriasis patients and the optimization of the screening methods should be seen as a priority in the clinical practice due to the potential consequences involved in joint damage in psoriatic arthritis. It is already known the potential sequelae involved in joint damage in psoriatic arthritis and that they can be avoided by the identification of the disease’s predictors. Furthermore, the large range of psoriasis diagnosis and diagnosis of early stage of psoriatic arthritis should be reduced. In this review, we discuss recent literature with highlights about some predictive markers of early arthritis in patients with psoriasis.

Composite likelihood for joint analysis of multiple multistate processes via copulas

A copula-based model is described which enables joint analysis of multiple progressive multistate processes. Unlike intensity-based or frailty-based approaches to joint modeling, the copula formulation proposed herein ensures that a wide range of marginal multistate processes can be specified and the joint model will retain these marginal features. The copula formulation also facilitates a variety of approaches to estimation and inference including composite likelihood and two-stage estimation procedures. We consider processes with Markov margins in detail, which are often suitable when chronic diseases are progressive in nature. We give special attention to the setting in which individuals are examined intermittently and transition times are consequently interval-censored. Simulation studies give empirical insight into the different methods of analysis and an application involving progression in joint damage in psoriatic arthritis provides further illustration.

SAT0309 Serum 14-3-3 ETA: An independent biomarker associated with joint damage in psoriatic arthritis

BackgroundThe 14-3-3 protein family consists of seven highly conserved isoforms described as intracellular chaperones based on their ability to bind to a multitude of functionally diverse proteins. One isoform, 14-3-3η,...

Statistical Issues in Modeling Chronic Disease in Cohort Studies

Observational cohort studies of individuals with chronic disease provide information on rates of disease progression, the effect of fixed and time-varying risk factors, and the extent of heterogeneity in the course of disease. Analysis of this information is often facilitated by the use of multistate models with intensity functions governing transition between disease states. We discuss modeling and analysis issues for such models when individuals are observed intermittently. Frameworks for dealing with heterogeneity and measurement error are discussed including random effect models, finite mixture models, and hidden Markov models. Cohorts are often defined by convenience and ways of addressing outcome-dependent sampling or observation of individuals are also discussed. Data on progression of joint damage in psoriatic arthritis and retinopathy in diabetes are analysed to illustrate these issues and related methodology.

Likelihood estimation for longitudinal zero-inflated power series regression models

In this paper, a zero-inflated power series regression model for longitudinal count data with excess zeros is presented. We demonstrate how to calculate the likelihood for such data when it is assumed that the increment in the cumulative total follows a discrete distribution with a location parameter that depends on a linear function of explanatory variables. Simulation studies indicate that this method can provide improvements in obtaining standard errors of the estimates. We also calculate the dispersion index for this model. The influence of a small perturbation of the dispersion index of the zero-inflated model on likelihood displacement is also studied. The zero-inflated negative binomial regression model is illustrated on data regarding joint damage in psoriatic arthritis.

Biomarkers and prognostic stratification in psoriatic arthritis

In rheumatic diseases, biomarkers may serve as surrogate endpoints for diagnosis, prognosis, disease activity, therapeutic response and disease outcome. In recent years a great effort has been made to identify useful tools to establish early diagnosis, prognosis and therapeutic response especially in rheumatoid arthritis (RA). In psoriatic arthritis (PsA) serological biomarkers have been frequently borrowed from RA, but this approach have sometimes lead to inappropriate choices of biomarkers and incorrect conclusions. Furthermore, the heterogeneous spectrum of articular manifestation of PsA and the variable course of the disease can make diagnosis and prognosis difficult. Recently, the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) identified two key areas for biomarkers development in psoriasis and PsA: the diagnosis of the articular disease in patients with psoriasis and the evaluation of joint damage in PsA. In this review we revised the currently available and the new potential markers for PsA, such as serum, genetic, cellular and histological biomarkers, clinical and imaging data, with particular attention on the prognostic aspect in order to identify progressive disease suitable for a more aggressive treatment.

Dramatic Repair of Joint Damage in Psoriatic Arthritis

Repair on radiographs of hands and feet is not a new phenomenon. Carefully comparing consecutive sets of radiographs of patients with rheumatoid arthritis (RA) in clinical remission occasionally revealed disappearing erosions over time in the prebiological era1, but repair, or “healing” as it was called in those days, was not systematically evaluated until recently. Nevertheless, there were true believers of healing that rightfully claimed, as do Eder and colleagues in this issue of The Journal in patients with psoriatic arthritis (PsA)2: “We believe what we see.” The methodological interest in repair was fuelled by the advent of phase 3 trials with tumor necrosis factor (TNF) inhibitors. These trials showed for the first time in history not only a near-complete arrest in radiographic progression, but also negative progression scores in a significant proportion of the patients treated with TNF inhibitors. In order to understand these negative scores, it is important to briefly outline how progression scores are generated in clinical trials. Usually, 2 independent readers are presented with consecutive sets of radiographs of hands and feet in order to comparatively score these radiographs on a per-joint basis for erosions and joint space narrowing. Importantly, these readers are not aware of the true time order of the radiographs, so that … Address correspondence to Dr. van der Heijde; E-mail: d.vanderheijde{at}kpnplanet.nl

Standardizing the monitoring of outcome measures: imaging in psoriatic arthritis

The wide spectrum of manifestations of musculoskeletal inflammation in psoriatic arthritis makes standardized assessment of joint damage in psoriatic arthritis a challenge. Assessment of erosions and joint space narrowing on plain radiographs of the hands and feet has remained the benchmark for assessing damage in psoriatic arthritis. The methods used to assess damage have been mostly borrowed from those used in rheumatoid arthritis. Axial joint involvement has not been systematically addressed. Methods to assess spinal disease have been borrowed from those used in ankylosing spondylitis. Both ultrasound and MRI have demonstrated promise in the assessment of psoriatic arthritis. The Outcome Measures in Rheumatology Clinical Trials (OMERACT) group is involved in the development of valid, reliable and feasible methods for assessment of joint involvement in psoriatic arthritis.

Inflammation in an individual joint predicts damage to that joint in psoriatic arthritis

ObjectiveThe authors have previously reported on the relationship between activity and subsequent damage at the patient level for patients with psoriatic arthritis (PsA). The aim of this study was to...

Update on Biomarkers in Psoriatic Arthritis

Biomarkers in psoriatic arthritis (PsA) may serve as surrogate end points for disease outcome and can provide insights into disease susceptibility and natural history. Biomarkers could relate to diagnosis, pathogenesis, prognosis, therapeutic response, and comorbidities. The "felt need" is, however, in the development of biomarkers for the presence of PsA in patients with psoriasis, as well as that for joint damage. During the past few years, many studies related to PsA biomarkers have been conducted. These studies are reviewed here. C-reactive protein, matrix metalloproteinase-3, and circulating osteoclast precursors show promise. An international goal-directed study to determine biomarkers for joint damage in PsA is now under way through a collaborative effort of GRAPPA (the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis) and OMERACT (Outcome Measures for Rheumatology Clinical Trials).

Golimumab May Reverse Joint Damage in Psoriatic Arthritis

Golimumab May Reverse Joint Damage in Psoriatic Arthritis

Analysis of Interval-Censored Data from Clustered Multistate Processes: Application to Joint Damage in Psoriatic Arthritis

Summary A conditionally Markov multiplicative intensity model is described for the analysis of clustered progressive multistate processes under intermittent observation. The model is motivated by a long-term prospective study of patients with psoriatic arthritis with the aim of characterizing progression of joint damage via an irreversible four-state model. The model accommodates heterogeneity in transition rates between different individuals and correlation in transition rates within patients. To do this we introduce subject-specific multivariate random effects in which each component acts multiplicatively on a specific transition intensity. Through the association between the components of the random effect, correlations in transition intensities are accommodated. A Monte Carlo EM algorithm is developed for estimation, which features closed form expressions for estimators at each M-step.