Practical Guidelines for Managing Patients With Psoriasis on Biologics: An Update
Bibliographic record
Abstract
The paradigm for treating inflammatory diseases has shifted dramatically in the past 10 to 20 years with the discovery of targeted therapeutics or "biologic" agents. Patients with rheumatoid arthritis, inflammatory bowel disease, psoriatic arthritis, and psoriasis, among others, are reaping the benefits of decades of bench to bedside research, allowing them to live more productive lives with less side effects than traditional systemic therapies. Despite these advances, many physicians unfamiliar with biologics are left to care for the basic needs of these patients and may be unaware of the multisystem comorbidities associated with psoriasis and the screening, monitoring, and other special considerations required of biologics patients. This can be overwhelming to primary care physicians and inadvertently expose patients to undue risks. The aim of this review is to provide a practical approach for all health care providers caring for patients with psoriasis being treated with biologics to facilitate communication with their treating dermatologist and ultimately provide patients with more comprehensive care.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".