Early detection to improve outcome in people with undiagnosed psoriatic arthritis: the PROMPT research programme including RCT

BackgroundDespite increasing awareness of the disease, rates of undiagnosed psoriatic arthritis (PsA) are high in patients with psoriasis (PsO). The validated Psoriasis Epidemiology Screening Tool (PEST) is a five‐item questionnaire developed to help identify PsA at an early stage.ObjectivesTo assess the risk of possible undiagnosed PsA among patients with PsO and characterize patients based on PEST scores.MethodsThis study included all patients enrolled in the Corrona PsO Registry with data on all five PEST questions. Demographics, clinical characteristics and patient‐reported outcomes were compared in Corrona PsO Registry patients with PEST scores ≥3 and <3 using t‐tests for continuous variables and chi‐squared tests for categorical variables; scores ≥3 may indicate PsA.ResultsOf 1516 patients with PsO, 904 did not have dermatologist‐reported PsA; 112 of these 904 patients (12.4%) scored ≥3 and were significantly older, female, less likely to be working, and had higher BMI than patients with scores <3. They also had significantly longer PsO duration, were more likely to have nail PsO and had worse health status, pain, fatigue, Dermatology Life Quality Index and activity impairment.ConclusionsImproved PsA screening is needed in patients with PsO because the validated PEST identified over one‐tenth of registry patients who were not noted to have PsA as having scores ≥3, who could have had undiagnosed PsA. Appropriate, earlier care is important because these patients were more likely to have nail PsO, worse health‐related quality of life and worse activity impairment.

BackgroundEarly detection of psoriatic arthritis (PsA) in patients with skin psoriasis (Pso) is critical to reduce the risk of joint damage, disability, and comorbidities. However PsA is mostly under-diagnosed in...

BackgroundPsoriatic arthritis (PsA), an immune-mediated chronic inflammatory skin and joint disease, affects approximately 0.27% of the adult population, and 20% of patients with psoriasis. Up to 10% of psoriasis patients are estimated for having undiagnosed PsA. Early diagnosis and treatment can prevent irreversible joint damage, disability and deformity. Questionnaires for screening to identify undiagnosed PsA patients require patient and physician involvement. ObjectiveTo evaluate a proprietary machine learning tool (PredictAI™) developed for identification of undiagnosed PsA patients 1–4 years prior to the first time that they were suspected of having PsA (reference event). MethodsThis retrospective study analyzed data of the adult population from Maccabi Healthcare Service between 2008 and 2020. We created 2 cohorts: The general adult population (“GP Cohort”) including patients with and without psoriasis and the Psoriasis cohort (“PsO Cohort”) including psoriasis patients only. Each cohort was divided into two non-overlapping train and test sets. The PredictAI™ model was trained and evaluated with 3 years of data predating the reference event by at least one year. Receiver operating characteristic (ROC) analysis was used to investigate the performance of the model, built using gradient boosted trees, at different specificity levels. ResultsOverall, 2096 patients met the criteria for PsA. Undiagnosed PsA patients in the PsO cohort were identified with a specificity of 90% one and four years before the reference event, with a sensitivity of 51% and 38%, and a PPV of 36.1% and 29.6%, respectively. In the GP cohort and with a specificity of 99% and for the same time windows, the model achieved a sensitivity of 43% and 32% and a PPV of 10.6% and 8.1%, respectively. ConclusionsThe presented machine learning tool may aid in the early identification of undiagnosed PsA patients, and thereby promote earlier intervention and improve patient outcomes.

Background:One in three patients with psoriasis (Pso) will develop psoriatic arthritis (PsA) (1). When untreated, this can lead to disability and irreversible joint damage (2). Current screening methods are mostly based on questionnaires. These lack specificity and sensitivity (3,4). Thus, a significant portion of PsA patients remains undetected.Objectives:Our main objective is to ascertain the prevalence of PsA in a cohort of Pso patient, treated at a dermatology outpatient clinic. Secondary, we wish to make a referral tool for dermatologist to detect patients suspected of PsA.Methods:A sample of 300 patients, stratified for current skin therapy (topical, systemic non-biologic, biologic), will be screened by a rheumatology resident for PsA signs and symptoms. When PsA is suspected, patients are referred to a rheumatologist for confirmation. We gather information about demography, treatment (past and current) and comorbidity. On top of that, we gather data on disease specifics (age of onset, disease duration, severity). We store biomaterials and DNA. Eventually, all these data will be used to form a more specific prediction model which can be used at the dermatology department for more efficient referral.Results:We will present preliminary data of the first 100 patients. In this cohort, we found 14 patients with known PsA. 10 patients were suspected of (previously undiagnosed) PsA, and were referred to a rheumatology clinic. Three cases were confirmed, and 4 are still under analysis. This makes the prevalence of PsA in Pso 17-21%. Of these three new cases, one was treated with topical therapy only, one was treated with a biologic, and one received targeted therapy. In the patients with PsA, we found a higher amount of men. On top of that, we found a trend towards more intensive therapy. This may be due to indication bias, were the presence of arthritis may lead to a more aggressive treatment. Interestingly, 2 of the 3 previously undiagnosed PsA patients were treated with a biological for their skin symptoms.Conclusion:Preliminary data of the DAPPER study reveal that the prevalence of confirmed PsA in Pso patients is 17%. If all suspected PsA are confirmed, this rises to 21%. Even under systemic biologic treatment, arthritis can still be active.

BackgroundThe available data showed great discrepancies in the performance of screening tools in detecting psoriatic arthritis (PsA) in patients with psoriasis, and those including the diagnosed PsA in the validation...

ObjectivesThe objectives of this study were to: (1) assess the prevalence of psoriatic arthritis (PsA) among Psoriasis (Ps) patients attending dermatology clinics; (2) identify clinical predictors of the development of...

BackgroundPsoriasis (PsO) is a chronic, systemic, immune-mediated disease with multiorgan involvement. Psoriatic arthritis (PsA) is an inflammatory arthritis that is present in 6%-42% of patients with PsO. Approximately 15% of patients with PsO have undiagnosed PsA. Predicting patients with a risk of PsA is crucial for providing them with early examination and treatment that can prevent irreversible disease progression and function loss.ObjectiveThe aim of this study was to develop and validate a prediction model for PsA based on chronological large-scale and multidimensional electronic medical records using a machine learning algorithm.MethodsThis case-control study used Taiwan’s National Health Insurance Research Database from January 1, 1999, to December 31, 2013. The original data set was split into training and holdout data sets in an 80:20 ratio. A convolutional neural network was used to develop a prediction model. This model used 2.5-year diagnostic and medical records (inpatient and outpatient) with temporal-sequential information to predict the risk of PsA for a given patient within the next 6 months. The model was developed and cross-validated using the training data and was tested using the holdout data. An occlusion sensitivity analysis was performed to identify the important features of the model.ResultsThe prediction model included a total of 443 patients with PsA with earlier diagnosis of PsO and 1772 patients with PsO without PsA for the control group. The 6-month PsA risk prediction model that uses sequential diagnostic and drug prescription information as a temporal phenomic map yielded an area under the receiver operating characteristic curve of 0.70 (95% CI 0.559-0.833), a mean sensitivity of 0.80 (SD 0.11), a mean specificity of 0.60 (SD 0.04), and a mean negative predictive value of 0.93 (SD 0.04).ConclusionsThe findings of this study suggest that the risk prediction model can identify patients with PsO at a high risk of PsA. This model may help health care professionals to prioritize treatment for target high-risk populations and prevent irreversible disease progression and functional loss.

Twin and family studies suggest that the genetic contribution to psoriatic arthritis (PsA) is higher than psoriasis, leading to the expectation that there will be genetic loci that contribute to...

Many questionnaires are available for assessment of psoriatic arthritis (PsA), but there is little evidence comparing them. To test the proposed CONTEST questionnaire, which was developed to identify patients with psoriasis who have undiagnosed PsA, and compare it with the validated Psoriasis Epidemiology Screening Tool (PEST) questionnaire in a primary-care setting. A random sample of adult patients with psoriasis and no diagnosis of arthritis was identified from five general practice surgeries in Yorkshire, U.K. Consenting patients completed both questionnaires and were assessed by a dermatologist and rheumatologist. Diagnosis of PsA was made by the assessing rheumatologist. Receiver operator characteristic (ROC) curve analysis examined the sensitivity and specificity of potential cut points. In total 932 packs were sent to recruit 191 (20·5%) participants. Of these, 169 (88·5%) were confirmed to have current or previous psoriasis. Using physician diagnosis 17 (10·1%) were found to have previously undiagnosed PsA, while 90 (53·3%) had another musculoskeletal complaint and 62 (36·7%) had no musculoskeletal problems. Using ROC curve analysis, all of the questionnaires showed a significant ability to identify PsA. The area under the curve (AUC) for the CONTEST questionnaires was slightly higher than that of PEST (0·69 and 0·70 vs. 0·65), but there was no significant difference identified. Examining the sensitivities and specificities for the different cut points suggested that a PEST score ≥ 2 would perform better in this dataset, and the optimal scores for CONTEST and CONTEST plus joint manikin were 3 and 4, respectively. The accuracy of the questionnaires to identify PsA appeared similar, with a slightly higher AUC for the CONTEST questionnaires. The optimal cut points in this study appeared lower than in previous studies.

Although some data addressing the burden of illness associated with psoriasis and psoriatic arthritis (PsA) have been reported for American and European patient populations, similar data have been lacking for Canadians with these diseases. We sought to characterize the natural history of disease in a sample of Canadians with a history of moderate to severe psoriasis, with or without diagnosed PsA or other recognized comorbid conditions, and to identify factors that influenced their perception of psoriasis as a problem in their daily lives. A nationwide telephone survey, pSoriasis Knowledge IN Canada (SKIN), was conducted between April 30 and June 2, 2007, on 500 people who indicated that they had been diagnosed with psoriasis and that their skin lesions had at some time affected an area at least as large as three palms of their hand (3% of body surface area [BSA]). The mean age at diagnosis for psoriasis among SKIN survey respondents was 28 years, with 31% (155 of 500) indicating that they developed the disease prior to age 18 years. At the time of the survey, 54% (269 of 500) of respondents were experiencing lesions affecting a BSA equivalent to at least three palms (3%). In response to questions on the burden of illness, 35% (176 of 500) of respondents indicated that they considered psoriasis to be a substantial problem in their daily life. Both affected BSA at the time of the survey and self-reported extent of skin involvement at the height of the condition (BSAmax) correlated with the perception of psoriasis as a substantial problem. Other subpopulations in which psoriasis was commonly identified as a substantial problem included women and individuals with diagnosed PsA. Whereas 18% (88 of 500) of respondents were diagnosed with PsA, the number who reported joint pain or stiffness was substantially higher (51%; 256 of 500), suggesting that some respondents may have had incipient or undiagnosed PsA. This survey reveals that psoriasis, PsA, and their associated comorbidities impose a severe burden on the daily lives of Canadians with a history of moderate to severe psoriasis.

Several screening tools have been developed to facilitate early diagnosis of psoriatic arthritis (PsA); however, their performance varied greatly across different studies. In this study, we validated and compared the performance of four screening tools in detecting undiagnosed PsA Chinese patients with psoriasis, and determined the key questions and their weights. The four screening tools were the Early Arthritis for Psoriatic Patients (EARP) questionnaire, Psoriatic Arthritis Screening and Evaluation (PASE) questionnaire, Psoriasis and Arthritis Screening Questionnaire (PASQ), and Psoriasis Epidemiology Screening Tool (PEST). The receiver-operator curve (ROC) with area under curve (AUC) was used to determine sensitivity, specificity, and accuracy. Least absolute shrinkage and selection operator and logistic regression were utilized to retrieve key questions, and a nomogram was utilized to visualize their weights. Of 482 psoriasis patients from dermatology clinics, 77 were newly diagnosed with PsA. Another 68 patients with newly diagnosed PsA from rheumatology clinics were incorporated in the analysis. ROC analysis indicated that the optimal cut-off values for EARP, PASE, PASQ, and PEST were 3, 40, 7, and 3, with corresponding sensitivities of 91.4%, 88.6%, 86.2%, and 88.5%, and specificities of 88.6%, 75.2%, 80.2%, and 83.6%, respectively. The AUC of EARP (0.925) was higher than those of PASE (0.885), PASQ (0.905), and PEST (0.827). However, none of them were sufficiently sensitive to identify pure axial PsA (sensitivities of EARP, PASQ, and PASE were 25.0%, 36.8%, and 42.1%, respectively). Twelve key questions were retrieved from these four tools to establish a nomogram with a high discrimination (C-index=0.993) and a good calibration (mean absolute error=0.014). In conclusion, to screen undiagnosed PsA, EARP has slightly better balanced sensitivity and specificity, and higher accuracy. The retrieval of key questions and nomogram signify the necessity of attributing different scores to differently weighted questions when developing a new screening tool to make it function more efficiently.

IntroductionPsoriatic arthritis (PsA) affects 10–30% of individuals with psoriasis. Early detection of PsA is crucial to prevent potential irreversible joint damage. The Psoriasis Epidemiology Screening Tool (PEST) has proven to be an effective tool in daily clinical practice, but limited data is available on the analysis of positive responses. Our study aimed to determine the combination of positive responses to individual questions and characterize patients with positive PEST results based on specific anatomical sites of psoriasis, duration of the disease, and epidemiological parameters that could potentially predict PEST positivity.MethodsThe PEST questionnaire was randomly administered to patients with psoriasis without psoriatic arthritis attending the outpatient unit for psoriasis treatment. A total of 351 patients completed the PEST questionnaire over a 24-month period. Patients undergoing various types of therapy were included. Each patient completed the PEST questionnaire once, and epidemiological data (such as age, weight, height, body mass index, smoking status, age of disease onset, disease duration, and family history of psoriasis) were collected, as well as types of therapy.ResultsWe included 242 men and 109 women with an average age of 49.4 years and duration of psoriasis of 23.3 years. A positive PEST questionnaire result was found in 28.5% of patients; 13.1% had a score of 3, 8.0% a score of 4 and 7.4% a score of 5. Nail psoriasis, higher age, and therapy with biological/targeted therapy were associated with PEST positivity. The most frequently observed positive response was nail involvement.ConclusionThe PEST questionnaire is a well-established screening tool for identifying patients at risk of having undiagnosed psoriatic arthritis in daily dermatological practice. Patients with nail involvement, higher age, or treated with modern systemic therapy should be closely monitored, as these factors indicate a higher risk of a positive PEST result and consequently higher risk of having psoriatic arthritis.

Background Psoriatic arthritis (PsA) is a long-term immune mediated condition. That can develop in individuals with psoriasis, often before any obvious symptoms appear. These asymptomatic individuals, classified as having occult PsA, may already have joint involvement detectable only through imaging, making early diagnosis difficult. Timely identification is essential to avoid permanent structural damage. This study investigates the possible use of hematological inflammatory markers in identifying hidden or undiagnosed PsA. Methods A case–control study involved 60 patients with psoriasis. were divided into two groups: 30 with imaging-confirmed occult psoriatic arthritis (PsA) and 30 with psoriasis only, all without clinical arthritis. Hematological inflammatory biomarkers including neutrophil-to-lymphocyte ratio (NLR), derived NLR (dNLR), monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI), and platelet-to-monocyte ratio (PMR) were assessed from venous blood samples. Musculoskeletal ultrasonography was performed to detect subclinical joint involvement. Results Patients with occult PsA showed significantly elevated levels of white blood cells, neutrophils, and monocytes. In addition, inflammatory markers such as the NLR, dNLR, MLR, SII, SIRI, and AISI were also notably increased, while PMR was decreased (all p &lt; 0.001). NLR and dNLR demonstrated perfect diagnostic accuracy (AUC = 1.000). WBC &gt; 6.7, MLR &gt; 0.17, and PMR ≤ 503 were independently associated with occult PsA. Conclusion Hematological markers, especially NLR, dNLR, and MLR, may serve as effective, low-cost tools for early identification of occult PsA in psoriasis patients, enabling earlier intervention and improved outcomes.

Psoriatic Arthritis (PsA) is considered part of the spondyloarthritis group, which is present in up to 42% of individuals with psoriasis and up to 15% of patients with psoriasis may have undiagnosed PsA. Psoriatic arthritis Mutilans is a rare but very aggressive type of advanced joint disease in patients with psoriasis. This report describes the case of a 67 years old patient with family history of psoriasis and undiagnosed psoriatic arthritis with nail lesions for more than 16 years, arthritis for 15 years and severe disease during the last 3 years with disability and bedridden. She had serious joint complications of the disease, as well as severe malnutrition. A missdiagnosis of rheumatoid arthritis was given during 15 years, HLAB27 was positive and radiography of hands and feet showed classic findings of psoriatic arthritis mutilans. We present this case to show the severity of the disease with rapid progression and multiple additional joint complications.

384 Differences in musculoskeletal impact on health among patients with psoriasis based on disease type, disease severity and undiagnosed psoriatic arthritis (PsA)