Integrating Biologic Agents into Management of Moderate-to-Severe Psoriasis: A Consensus of the Canadian Psoriasis Expert Panel
Bibliographic record
Abstract
BACKGROUND: Approximately 2% of people worldwide have psoriasis, with as many as 1 million people with psoriasis in Canada alone.1,2 The severity of psoriasis ranges from mild to severe. It can lead to substantial morbidity and psychological stress and have a profound negative impact on patient quality of life.3,4 Although available therapies reduce therapies reduce the extent and severity of the disease and improve quality of life,3 reports have indicated a patient preference for more aggressive therapy and a dissatisfaction with the effectiveness of current treatment options.5 OBJECTIVE: A Canadian Expert Panel, comprising Canadian dermatologists, convened in Toronto on 27 February 2004 to reach a consensus on unmet needs of patients treated with current therapies and how to include the pending biologic agents in and improve the current treatment algorithm for moderate-to-severe psoriasis. Current treatment recommendations suggest a stepwise strategy starting with topical agents followed by phototherapy and then systemic agents.3,6,7 The Panel evaluated the appropriate positioning of the biologic agents, once approved by Health Canada, for the treatment of moderate-to-severe psoriasis. METHODS: The Panel reviewed available evidence and quality of these data on current therapies and from randomized, controlled clinical trials.8-14 Subsequently, consensus was achieved by small-group workshops followed by plenary discussion. RESULTS: The Panel determined that biologic agents are an important addition to therapies currently available for moderate-to-severe psoriasis and proposed an alternative treatment algorithm to the current step wise paradigm. CONCLUSION: The Panel recommended a new treatment algorithm for moderate-to-severe psoriasis whereby all appropriate treatment options, including biologic agents, are considered together and patients' specific characteristics and needs are taken into account when selecting the most appropriate treatment option.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".