Alemtuzumab in clinical practice: A British Columbia experience
Bibliographic record
Abstract
Limited information is available on alemtuzumab in the nonclinical trial setting. We evaluated its efficacy and safety in 42 consecutive unselected patients who received alemtuzumab monotherapy in British Columbia between October 2002 and August 2006. Information on patient demographics, baseline clinical characteristics, dose and schedule, clinical response, survival, and toxicities associated with alemtuzumab was collected retrospectively. Thirty-nine of 42 patients had chronic lymphocytic leukemia, two had mycosis fungoides, and one had T-cell post-transplant lymphoproliferative disorder. In contrast to previous reports, 42% were treated by community practitioners and 83% received alemtuzumab subcutaneously. The median time from diagnosis to alemtuzumab was 58 months. One of 42 patients (2%) achieved a complete response, 20 (48%) achieved a partial response, and 13 (31%) had stable disease. The post-alemtuzumab median overall survival was 15.1 months. Response to alemtuzumab correlated with an increased progression-free survival (11 vs. 3.6 months, p = 0.001) compared to that seen in non-responders. Significant adverse events included grade 3/4 neutropenia (76%), thrombocytopenia (45%), infections (60%) and death (12%). With careful monitoring, alemtuzumab can be safely administered in a wide variety of clinical settings, including community practice, and is associated with a high level of activity in situations with few available alternative treatment options.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".