Validity and reliability of the Turkish version of Psoriasis Epidemiology Screening Tool for the detection of psoriatic arthritis in patients with psoriasis
Bibliographic record
Abstract
Objectives: The Psoriasis Epidemiology Screening Tool (PEST) is a simple and useful questionnaire designed to screen arthritis in patients with psoriasis. This study aims to evaluate the validity and reliability of the PEST questionnaire in Turkish patients with psoriasis. Patients and methods: Between August 2019 and September 2019, a total of 158 adult patients with psoriasis (61 males, 68 females; mean age: 43.1±13.3 years; range, 29.8 to 56.4 years) who were not previously diagnosed with PsA were included. The testing procedure for translation and cultural adaptation was carried out according to the following steps: preparation, forward translation, reconciliation, back-translation/back-translation review, harmonization, finalization, and proofreading. Patients' demographic parameters, comorbidities, PEST, and Toronto Psoriatic Arthritis Screen (ToPAS 2) results were recorded. The patients were, then, assessed by a rheumatologist who was blinded to their PEST scores. The diagnosis of PsA was made according to the Classification criteria for Psoriatic Arthritis (CASPAR). The receiver operating characteristic (ROC) was assessed to obtain the sensitivity and specificity of the PEST questionnaire. Results: Of the patients, 42 had PsA, while 87 did not. Each parameter of PEST showed a low-high internal consistency ranging from 0.366 to 0.781. When the Question 3 was excluded, Cronbach alpha value increased to 0.866. The Cronbach alpha value of the whole scale was 0.829. The test-retest reliability of the Turkish version of PEST was determined as 0.86 for the total score (ICC=0.866 95% CI: 0.601-0.955; p<0.0001). There was a strong positive correlation between PEST and ToPAS 2 (r=0.763; p<0.001) and a moderate positive correlation between PEST and CASPAR (r=0.455; p<0.001). A cut-off value of ≥3 yielded a sensitivity of 93% and a specificity of 89% for the diagnosis of PsA with the highest Youden's index. The PEST scale was found to have a higher sensitivity, but lower specificity in the head-to-head comparison with ToPAS 2. Conclusion: The Turkish version of PEST is a reliable and valid tool for screening PsA in Turkish patients with psoriasis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".