Cytogenetic correlation with efficacy on alemtuzumab (CAM) vs chlorambucil (CHLO) as front-line therapy for patients with progressive B-cell chronic lymphocytic leukemia (BCLL)
Bibliographic record
Abstract
6601 Background: CAM307, a phase III, open-label, randomized comparative trial, enrolled 297 Rai stage I-IV BCLL patients with previously untreated, progressive disease requiring treatment. Patients were randomized to treatment with CAM (n=149) vs. CHLO (n=148) using standard dosing regimens. Methods: Cytogenetic assessment was conducted prior to the start of protocol-specified therapy. Chromosomal aberrations were detected by fluorescence in situ hybridization (FISH) using specific probes. Molecular cytogenetic analyses by FISH included deletions (del) 6q21, 6q telomere, 11q22–23, 13q14–14.3 and 17p13; trisomy bands of 8q24 and 12p11.1-q11.1. Results: A total of 271 patients have been evaluated. Chromosomal aberrations were detected in 207 patients (76%) while 64 patients (24%) exhibited normal karyotype. Cytogenetic abnormalities were evaluated by response [overall response rate (ORR) and complete response (CR)] to each therapy based upon an independent response review. The comparisons of ORR and CR between treatment arms for each mutation type were calculated using the Exact method. Conclusions: Preliminarydata demonstrate a statistically significant superior response to CAM in patients with del 13q (ORR and CR) and del 11q (ORR) as well as a statistically significant superior CR to CAM in patients with normal cytogenetics. In addition, although the sample size is small, there is a trend towards a better ORR in patients with del 17p. Further exploration of CAM response rates relative to cytogenetic abnormality is warranted. [Table: see text] [Table: see text]
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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 | 0.000 |
| 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 | 0.001 | 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".