Evaluating the impact of a pharmacist-led venetoclax ramp-up clinic for chronic lymphocytic leukemia patients: A retrospective chart review
Bibliographic record
Abstract
IntroductionVenetoclax is a BCL-2 inhibitor, used for both treatment-naive, and relapsed/refractory chronic lymphocytic leukemia (CLL). To mitigate the risk of tumor lysis syndrome (TLS), a 5-week dose ramp-up strategy with frequent assessment is required. Pharmacists are medication experts and skilled in managing adverse effects. They are ideally positioned to manage patients during ramp-up and can reduce hematologist visits. We sought to describe the impact of a pharmacist-led venetoclax ramp-up clinic implemented at our institution.MethodsThe primary objective was to describe pharmacist interventions made during ramp-up to prevent TLS. Key secondary objectives included describing the rates of TLS and rates of venetoclax target dose achievement. The study was a retrospective electronic chart review including CLL patients with ≥1 visit to the pharmacist-led clinic between October 2020-January 2024. Data was collected using a standardized form and descriptive statistics were used for analysis.ResultsEighty-eight patients were included. The median age was 70 years old and 97% of patients were low or moderate risk for TLS. Common interventions made for TLS prevention were education, occurring during all 907 patient visits, and changes to TLS prophylaxis, occurring during 113 (12.5%) patient visits. Two (2.3%) patients experienced laboratory TLS and 0 experienced clinical TLS. Eighty-three (94.3%) patients achieved target dose at the end of the study period.ConclusionsThe results of the study support that a pharmacist-led venetoclax clinic is both safe and effective for patients with CLL. Up-titration, active TLS prophylaxis, education and adverse event management are key components to the clinic.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".