The Incidence and Risk Factors for Psoriatic Arthritis in Patients With Psoriasis: A Prospective Cohort Study
Bibliographic record
Abstract
OBJECTIVE: To estimate the incidence of psoriatic arthritis (PsA) in patients with psoriasis, and to identify risk factors for its development. METHODS: The study was designed as a prospective cohort study involving psoriasis patients who did not have a diagnosis of arthritis at the time of study enrollment. Information was collected about lifestyle habits, comorbidities, psoriasis activity, and medications. Patients who developed inflammatory arthritis or spondylitis were classified as having PsA if they fulfilled the criteria of the Classification of Psoriatic Arthritis Study group. The annual incidence of PsA was estimated using an event per person-years analysis. Cox proportional hazards models, involving fixed and time-dependent explanatory variables, were fitted to obtain estimates of the relative risk (RR) of the onset of PsA, determined in multivariate models stratified by sex and controlled for age at onset of psoriasis. RESULTS: The data obtained from the 464 patients who were followed up for 8 years were analyzed. A total of 51 patients developed PsA during the 8 years since enrollment. The annual incidence rate of PsA was 2.7 cases (95% confidence interval 2.1-3.6) per 100 psoriasis patients. The following baseline variables were associated with the development of PsA in multivariate analysis: severe psoriasis (RR 5.4, P = 0.006), low level of education (university/college versus high school incomplete RR 0.22, P = 0.005; high school graduate versus high school incomplete RR 0.30, P = 0.049), and use of retinoid medications (RR 3.4, P = 0.02). In multivariate models with time-dependent variables, psoriatic nail pitting (RR 2.5, P = 0.002) and uveitis (RR 31.5, P = 0.0002) were associated with the development of PsA. CONCLUSION: The incidence of PsA in patients with psoriasis is higher than previously reported. A severe psoriasis phenotype, presence of nail pitting, low level of education, and uveitis are predictive of the development of PsA in patients with psoriasis.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".