GRAPPA Debate: Targeted Small Molecules Versus Biologics as First-Line Systemic Therapy After Conventional Therapy for Moderate-to-Severe Psoriasis
Bibliographic record
Abstract
In this debate at the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) 2023 annual meeting, arguments were made contrasting the first-line use of oral targeted small-molecule drugs vs biologic therapy for the treatment of moderate-to-severe psoriasis (PsO) after failure of conventional therapy. Arguments in favor of small-molecule drugs included good efficacy and safety, patient preference, cost savings, global health equity, and environmental stewardship. Arguments in favor of biologics included superior efficacy, excellent safety, availability of long-term data, pediatric regulatory approvals, and potential benefit for comorbidities. By the end of the debate, there was recognition of significant pros and cons of each approach. Both small-molecule drugs and biologic therapy are valuable options for PsO treatment, and their use can be tailored toward specific individuals or healthcare systems.
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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 | 0.061 | 0.108 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.034 | 0.058 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".