Low CD49d expression in newly diagnosed chronic lymphocytic leukaemia may be associated with high‐risk features and reduced treatment‐free‐intervals
Bibliographic record
Abstract
This study was carried out to assess the prognostic power of low CD49d expression (≥10%) in newly diagnosed CLL patients using a previously described cohort. Eighty-five patients were included. Median age at diagnosis; 70 years (43-88); CD49d was expressed in 33/85 (38.8%); 23/33 (69.7%) at ≥30% referred to as 'HiCD49d' and 10/33 (30.3%) between 10 and 30% with a bimodal pattern on scatterplot analysis referred to as 'LoCD49d'. Eleven patients (12.9%) presented as Binet stage B, of whom 8 (72.7%) were CD49d+ (HiCD49d 7/8; LoCD49d 1/8). Seven of 81 patients (8.6%) were NOTCH1 mutated and all were CD49d+ (p ≤ .01). IgVH analysis was performed on 29 (87.8%) of the CD49d+ cases, of whom 21 (72.4%) were unmutated and 8 (27.6%) were mutated. CD38+/CD49d+ accounted for 11/20 (55%) (CD38+/HiCD49D: 9/11; CD38+/LoCD49D: 2/11). At 42 months, treatment had been initiated in 18/85 (21%) patients, of these 10/33 (30.3%) were CD49d+ versus 8/52 (15.4%) of the CD49d- group. The median treatment free interval for the CD49d+ group was 11 months (HiCD49d; 14.5 months, LoCD49d; 11 months) compared to 21.5 months for the CD49d- group. These findings suggest that the predictive value of CD49d expression is retained at expression levels down to 10%.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".