GEPARD-Patientenfragebogen

Härle, Peter; Hartung, Wolfgang; Lehmann, Petra; Ehrenstein, Boris; Schneider, Neil; Müller, Hermann L.; Müller‐Ladner, Ulf; Tarner, Ingo H.; Vogt, Thomas; Bongartz, Tim

doi:10.1007/s00393-009-0462-2

Cited by 23 publications

(6 citation statements)

References 9 publications

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“…The ability of German dermatologists to diagnose PsA on their own is improving with the use of the GErman Psoriasis ARthritis Diagnostic questionnaire (GEPARD) or Psoriasis Epidemiology Screening Tool (PEST), and these patients should be presented to a rheumatologist along with their clinical characteristics (e.g. arthritis, swollen joints, tendon pain) [ 32 ].…”

Section: Discussionmentioning

confidence: 99%

Psoriatic arthritis epidemiology, comorbid disease profiles and risk factors: results from a claims database analysis

Rech

Sticherling

Stoessel³

et al. 2020

Rheumatology Advances in Practice

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Abstract Objective Psoriasis (PsO) is a systemic inflammatory disease often accompanied by comorbid diseases, including metabolic syndrome, cardiovascular diseases and depression. Up to 41% of PsO patients develop psoriatic arthritis (PsA), making it one of the most relevant manifestations. A large health claims data set was analyzed to determine the rate of PsA development in PsO patients. Furthermore, comorbid disease profiles of PsO patients with or without PsA were compared, and potential risk factors for the development of PsA were identified. Methods This was a non-interventional, retrospective analysis of anonymized insurance health claims data using a subset of the Institute of Applied Health Research Berlin (InGef) database. The primary outcome was the prevalence and incidence of diagnosed PsA among PsO patients in Germany. Risk factors for the development of PsA in PsO patients were determined by conditional logistic regression analysis. Results The cumulative percentage of patients with existing PsO developing concomitant PsA (PsO–PsA) over 4 years was 3.44% with a mean time to diagnosis of PsA of 1.5 years. PsO patients diagnosed with acute rheumatism (odds ratio: 2.93, 95% CI=1.76–4.86; p= < 0.001) or “pain in unspecific joints” (odds ratio: 1.74, 95% CI=1.01–2.99; p=0.047) showed an increased risk to develop PsA later on. Interestingly, less than half of the patients with concomitant PsA consulted a rheumatologist. Conclusions Unspecific arthritic symptoms likely precede PsA diagnoses and can develop soon after PsO onset with accumulating risk over time. There is a high unmet need for early rheumatologic assessment of PsO patients.

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Section: Discussionmentioning

confidence: 99%

Psoriatic arthritis epidemiology, comorbid disease profiles and risk factors: results from a claims database analysis

Rech

Sticherling

Stoessel³

et al. 2020

Rheumatology Advances in Practice

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“…In the statistical evaluation of the study, we calculated a cut-off value of greater than or equal to 4 positive answered questions. This cut-off showed a sensitivity of 89% and a specificity of 73% to detect PsA in Ps patients (Härle, 2010).…”

Section: Psychosomatic Comorbidity Is Important To Considermentioning

confidence: 99%

Detecting Psoriasis Arthritis Early in the Disease Course – Why This is Important and How Dermatologists and Rheumatologists Can Successfully Cooperate?

Härle¹

2012

Psoriasis

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“…• PEST: Se = 56%; Sp = 85%; PV+ = 50; PV-= 88 • PEST (cut-off �2): Se = 89%; Sp = 63%; PV+ = 39; PV-= 96López-Estebaranz_2015[70] • PASE (cut-off �44): Se = 51%; Sp = 78%(73)(74)(75)(76)(77)(78)(79)(80)(81)(82)(83); AUC = 0.707Maejima_2016[71] • J-EARP: AUC = 0.99; Se = 97.2%; Sp = 97.2%Martire_2019[72] •GEPARDa (cut-off �6): Se = 88.6%; Sp = 89.7%; LR+ = 8.6; LR-= 0.12; AUC = 0.955 (0.91-0.99) Mazzotti_2019 [73] • PEST-bp: Se = 84.6%; Sp = 63.3%; PV+ = 37.9; PV-= 93.9; AUC = 0.81 (0.73-0.88) Mease_2014 [74] • PASQ: Se = 67%; Sp = 64%; PV+ = 43; PV-= 83 • PEST: Se = 84%; Sp = 75%; PV+ = 60; PV-= 91 • ToPAS: Se = 77%; Sp = 72%; PV+ = 54; PV-= 88 Mishra_2017 [75] • EARP: Se = 91%; Sp = 88%; AUC = 0.95 • PASE (cut-of �44): Se = 80%; Sp = 95%; AUC = 0.93 • PEST: Se = 53%; Sp = 95%; AUC = 0.92 • ToPAS: Se = 44%; Sp = 97%; AUC = 0.93 Oyur_2014 [51] • PASE (cut-off �44): Se = 62%; Sp = 76% Piaserico_2016 [76] • iPASE (cut-off �48): Se = 73.2%; Sp = 76.1%; AUC = 0.821 35 Salaffi_2018 [77] • SiPAS: Se = 79%; Sp = 87%; LR+ = 6.Tinazzi_2012 [16] • PCA: exclusion of 4 items (EARP of 10 items) α Cronbach = 0.83 • AUC PASE (cut-off �44) vs EARP: 0.895 vs 0.906 • EARP: Se = 85.2%; Sp = 91.6% • PASE (cut-off �44): Se = 90.7%; Sp = 67.2% 37 Tom_2015 [78] • ToPAS 2_cap (cut-off �8): Se = 87.2%; Sp = 82.7%; AUC = 0.910 38 Urbancek_2016 [79] • ToPAS vs PASE • Se: 72.6% vs 58.9% • Sp: 81.3% vs 80.5% 39 Vidal_2016 [80] • Tenosynovitis • PASE: Se = 66.7%; Sp = 63.4%; PV-= 93.3%; AUC = 0.65 • EARP: Se = 100%; Sp = 48.8%; PV-= 100%; LR+ = 1.81; AUC = 0.74 • Synovitis • PASE: PV+ = 12.3%; PV-= 93.5%; AUC = close to 0.50 • EARP: Se = 66.7%; Sp = 60.8%; PV-= 94.1%; LR+ = 1.65; AUC = 0.66 • Enthesitis • PASE: Se = 100%; Sp = 19.5%; PV+ = 8.3%; PV-= 100%; AUC = 0.66 • EARP: PV+ = 8.3%; PV-= 100%; AUC = 0.60 • PsA • PASE: Se = 100%; Sp = 66%; PV+ = 9%; PV-= 100%; AUC = 0.83 • EARP: not relevant for the PsA diagnosis 40 Walsh_2013 [81] • PEST: Se = 85%; Sp = 45% • ToPAS: Se = 75%; Sp = 55% • PASE: Se = 68%; Sp = 50% • PASE (�44): Se = 78%; Sp = 40% 41 You_2015 [52] • Korean PASE (cut-off �37): Se = 77.8%; Sp = 82.3%; PV+ = 37.8; PV-= 96.4; AUC = 0.82 (0.72-0.92) Abbreviations: CI = confidence interval; Se = sensitivity; Sp = specificity; PPV = Positive Predictive Value; NPV = Negative Predictive Value; AUC = area under the curve; FA: factor analysis; KR = Kunder-Richardson; ePASQ = electronic Psoriasis and Arthritis Screening Questionnaire; SiPAS = Simple Psoriatic Arthritis Screening; CEPPA = Center of Excellence for Psoriasis and Psoriatic Arthritis; GEPARD = GErman Psoriasis ARthritis Diagnostic questionnaire https://doi.org/10.1371/journal.pone.0248571.t002…”

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confidence: 99%

Psoriatic arthritis screening: A systematic literature review and experts’ recommendations

et al. 2021

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Objective To analyze the performance of psoriatic arthritis (PsA) screening tools, examine their implementation in daily practice, and reach a consensus about the best screening tool for implementation in daily practice in different medical settings. Methods A systematic literature review (SLR), structured telephone interviews to hospitals, and a multidisciplinary nominal group meeting were all conducted. The SLR employed sensitive search strategies using Medline, Embase, and the Cochrane Library up to January 2020. Two reviewers independently selected articles that reported data on PsA screening tools and that included sufficient data to at least calculate the sensitivity and specificity of those tools (e.g., questionnaires, algorithms, specific questions, and biomarkers). The hospital interviews collected data regarding the process of suspected PsA diagnosis and referral to rheumatology, the implementation of PsA screening tools, and barriers and facilitators to implementation of those tools. In the nominal group meeting, a multidisciplinary team of experts discussed all these data and subsequently recommended a screening tool for implementation. Results The SLR included 41 moderate-quality studies that analyzed 14 PsA screening tools, most of which were questionnaire-based tools. All of these studies reported a moderate-good performance but presented different characteristics regarding the time to completion or the number and type of items or questions. The implementation of screening tools was low (30.5%). The experts ultimately recommended regular use of a PsA screening tool, preferably the PURE-4 questionnaire. Conclusions The implementation of PsA screening tools like the PURE-4 questionnaire in daily practice likely improves the prognosis of PsA patients.

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GEPARD-Patientenfragebogen

Abstract: It is possible to detect PsA patients in a dermatologic outpatient setting with the GEPARD questionnaire.

Cited by 23 publications

References 9 publications

Psoriatic arthritis epidemiology, comorbid disease profiles and risk factors: results from a claims database analysis

Psoriatic arthritis epidemiology, comorbid disease profiles and risk factors: results from a claims database analysis

Detecting Psoriasis Arthritis Early in the Disease Course – Why This is Important and How Dermatologists and Rheumatologists Can Successfully Cooperate?

Psoriatic arthritis screening: A systematic literature review and experts’ recommendations

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