Updates from the American Society of Hematology 2019 Annual Meeting: Practice-Changing Studies in Treatment-Naïve Chronic Lymphocytic Leukemia
Bibliographic record
Abstract
The 2019 annual meeting of the American Society of Hematology took place 7-10 December in Orlando, Florida. At the meeting, results from key studies in treatment-naïve chronic lymphocytic leukemia (cll) were presented. Of those studies, phase iii oral presentations focused on the efficacy and safety of therapy with inhibitors of Bruton tyrosine kinase (btk) and Bcl-2. One presentation reported updated results of the Eastern Cooperative Oncology Group 1912 trial comparing the efficacy and safety of ibrutinib-rituximab with that of fludarabine-cyclophosphamide-rituximab in patients less than 70 years of age with cll. A second presentation reported interim results of the elevate tn trial, which is investigating the efficacy and safety of acalabrutinib-obinutuzumab or acalabrutinib monotherapy compared with chlorambucil-obinutuzumab. A third presentation reported on the single-agent zanubrutinib arm of the sequoia trial in patients with del(17p). The final presentation constituted a data update from the cll14 trial, which is evaluating fixed-duration venetoclax-obinutuzumab compared with chlorambucil-obinutuzumab, including the association of minimal residual disease status with progression-free survival. Our meeting report describes the foregoing studies and presents interviews with investigators and commentaries by Canadian hematologists about potential effects on Canadian practice.
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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 | 0.092 | 0.149 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.018 | 0.019 |
| Insufficient payload (model declined to judge) | 0.014 | 0.008 |
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".