Efficacy Outcomes in Patients Using Alefacept in the AWARE Study
Bibliographic record
Abstract
BACKGROUND: Alefacept has demonstrated efficacy in clinical trials of patients with chronic plaque psoriasis, either as monotherapy or combined with other treatment modalities such as phototherapy. OBJECTIVE: AWARE (Amevive Wisdom Acquired from Real-World Evidence) is a multicenter, observational, phase IV Canadian registry of psoriasis patients treated with alefacept. METHODS: Patients with chronic plaque psoriasis were treated with at least one course of alefacept, either alone or added on to their existing antipsoriatic treatment regimen. Each course of alefacept was followed by a period of at least 12 weeks off treatment. Efficacy outcomes included physicians' and patients' assessments of response at week 18, as well as change in percent body surface area (BSA) involvement with psoriasis. The time to retreatment was assessed in patients receiving a second course of alefacept during at least 60 weeks of prospective follow-up. RESULTS: The majority of patients received alefacept in combination with other antipsoriatic therapies. Physicians' and patients' assessments of response at 18 weeks showed that 42% and 41% of patients, respectively, had a "cleared to marked response" and a further 42% had a "moderate to some response." Among those patients whose psoriasis was moderately controlled or not controlled at baseline, 49 to 51% and 33 to 36%, respectively, improved to "cleared to marked response" at 18 weeks. A substantial shift in percent BSA involvement with psoriasis was observed at 18 weeks, with 55% of patients having a BSA involvement of < 10% at week 18 compared to only 20% having this level of BSA involvement at baseline. The mean time to retreatment among the 60% of patients who received a second course of alefacept was 19.3 weeks (range 2-47 weeks). CONCLUSION: A single course of alefacept therapy improved outcomes in this broad population of real-world chronic plaque psoriasis patients. STUDY LIMITATIONS: The limitations of this study include its nonrandomized, noncontrolled, noncomparative design, which allowed multiple different treatment approaches across all patients. The rating scales used in this study have not been previously validated, and ranges were assigned to baseline control and response data that are not specifically defined. Clinicians did not receive specific training in using these scales; therefore, interrater variability could not be assessed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".