Incidence of Clinically Diagnosed Psoriatic Arthritis in Sweden
Bibliographic record
Abstract
OBJECTIVE: Prior incidence estimates of psoriatic arthritis (PsA) vary considerably. We aimed to assess the annual incidence of clinically diagnosed PsA among adults in Sweden in 2014-2016, overall and stratified by age/sex/education/geography, and to investigate potential time trends in incidence in 2006-2018. Use of disease-modifying antirheumatic drugs (DMARDs) during the 2 years after diagnosis was also examined. METHODS: Patients (aged ≥ 18 years) with incident clinically diagnosed PsA in Sweden were identified from the National Patient Register (NPR) and/or the Swedish Rheumatology Quality Register (SRQ). Population statistics, stratification variables, and DMARD information were retrieved from other nationwide registers. Incidence was estimated according to a base case (BC) definition (ie, ≥ 1 main International Classification of Diseases, 10th revision, diagnosis of PsA [L40.5/M07.0-M07.3] from rheumatology/internal medicine in NPR, or a PsA diagnosis in SRQ during the relevant year, and no prior such diagnoses) and 4 different sensitivity analysis case definitions. RESULTS: The mean annual incidence of clinically diagnosed PsA among adults in Sweden in 2014-2016 was estimated at 21.77 per 100,000 person-years (PYs) at risk, according to the BC definition; 17.41 per 100,000 PYs at risk after accounting for diagnostic misclassification; and 15.78 to 28.83 per 100,000 PYs at risk across all sensitivity analyses. Incidence was slightly higher in female individuals, was lower in those with higher education (aged > 12 years), and peaked during the ages of 50 to 59 years. No apparent increasing or decreasing time trend was observed in 2006-2018. Within 2 years of diagnosis, 71.03% of patients had received DMARD therapy (22.37% biologic or targeted synthetic DMARDs). CONCLUSION: From 2014 to 2016, the annual incidence of clinically diagnosed PsA in the adult Swedish population was approximately 20 per 100,000 PYs at risk. Two years after diagnosis, almost three-quarters of patients had received DMARD therapy.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".