Frontline treatment with the combination obinutuzumab ± chlorambucil for chronic lymphocytic leukemia outside clinical trials: Results of a multinational, multicenter study by ERIC and the Israeli CLL study group
Bibliographic record
Abstract
In recent years, considerable progress has been made in frontline therapy for elderly/physically unfit patients with CLL. The combination of obinutuzumab and chlorambucil (O-Clb) has been shown to prolong progression free survival (PFS, median PFS-31.5 months) and overall survival (OS) compared to chlorambucil alone. More recently, obinutuzumab given in combination with either ibrutinib or venetoclax improved PFS but not OS when compared to O-Clb. In this retrospective multinational, multicenter co-operative study, we evaluated the efficacy and safety of frontline treatment with O ± Clb in unfit patients with CLL, in a "real-world" setting. Patients with documented del (17p13.1)/TP53 mutation were excluded. A total of 437 patients (median age, 75.9 years; median CIRS score, 8; median creatinine clearance, 61.1 mL/min) were included. The clinical overall response rate was 80.3% (clinical complete and partial responses in 38.7% and 41.6% of patients, respectively). Median observation time was 14.1 months and estimated median PFS was 27.6 months (95% CI, 24.2-31.0). In a multivariate analysis, high-risk disease [del (11q22.3) and/or IGHV-unmutated], lymph nodes of diameter > 5 cm, obinutuzumab monotherapy and reduced cumulative dose of obinutuzumab, were all independently associated with shorter PFS. The median OS has not yet been reached and estimated 2-year OS is 88%. In conclusion, in a "real-world" setting, frontline treatment with O-Clb achieves PFS comparable to that reported in clinical trials. Inferior outcomes were noted in patients with del (11q22.3) and/or unmutated IGHV and those treated with obinutuzumab-monotherapy. Thus, O-Clb can be still considered as legitimate frontline therapy for unfit CLL patients with low-risk disease.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".