Management of Psoriatic Arthritis in Patients With Comorbidities: An Updated Literature Review Informing the 2021 GRAPPA Treatment Recommendations
Bibliographic record
Abstract
OBJECTIVE: The 2021 Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) treatment recommendations provide an evidence-based guide for selecting therapy based on the individual's disease features. Beyond the disease features and associated conditions (eg, uveitis and inflammatory bowel disease), comorbidities play an important role in selecting therapy for an individual patient. METHODS: We performed a systematic literature review. We examined the available evidence to inform treatment selection based on the presence or absence of comorbidities in psoriatic arthritis (PsA). RESULTS: Common comorbidities in PsA that may affect treatment selection include presence of baseline cardiovascular disease (CVD) or high risk for CVD, obesity and metabolic syndrome, liver disease, mood disorders, including depression in particular, chronic infections, malignancies, osteoporosis, and fibromyalgia and/or central sensitization. CONCLUSION: Comorbidities may influence both the effectiveness of a given therapy but also the potential for adverse events. It is important to assess for the presence of comorbidities prior to therapy selection.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".