Real-world incidence of venetoclax toxicities in British Columbia
Bibliographic record
Abstract
INTRODUCTION: Venetoclax is used to treat relapsed/refractory chronic lymphocytic leukemia (r/r CLL). Tumour lysis syndrome (TLS) is a serious toxicity associated with venetoclax, and real-world studies suggest that the incidence may be higher than in clinical trials. The purpose of this study is to describe the incidence of venetoclax toxicities in British Columbia (BC). METHODS: Retrospective review of electronic medical charts for patient characteristics and clinical outcomes of patients treated with venetoclax for r/r CLL in BC. Patients were classified according to their risk for developing TLS. The incidence of TLS was categorized based on laboratory metrics or clinical diagnosis. Other non-TLS toxicities were also collected. RESULTS: Of 33 patients identified, 40%, 33%, and 27% were at low, intermediate, and high risk for TLS, respectively. Laboratory TLS occurred in 1/33 patients (3%), and no clinical TLS was reported. Grade 3 or 4 toxicities occurred in 19/33 patients (58%). Of these, neutropenia was the most common, occurring in 16 patients (84%) followed by thrombocytopenia, which occurred in 8 patients (42%). CONCLUSIONS: The incidence of TLS in patients treated with venetoclax for r/r CLL in BC was lower than in other real-world studies. Findings may warrant further investigation to determine if the higher incidence of TLS in real-world reports may be mitigated through modifying TLS risk categorization and associated prophylactic measures. Neutropenia was the most common grade 3 or 4 venetoclax toxicity reported, and the incidence in BC is comparable to other centres.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".