2722. Risk of Infectious Adverse Events of Venetoclax Therapy in the Treatment of Hematologic Malignancies: A Systematic Review and Bayesian Meta-Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
Abstract Background Venetoclax is a small molecule inhibitor of BCL-2 used in the treatment of acute myelogenous leukemia and chronic lymphocytic leukemia. Recent post-marketing studies on venetoclax suggested that it may predispose to opportunistic infections (OIs). We sought to systematically review the randomized controlled trial (RCT) evidence on venetoclax to assess whether it predisposes patients to infectious adverse events (IAEs) and neutropenia. Methods We systematically reviewed the RCTs comparing venetoclax therapy to active (i.e., a regimen with additional anti-cancer agents) or placebo controls in patients with hematologic malignancies, irrespective of treatment line. Data on IAEs and neutropenia were pooled by Bayesian meta-analysis and we computed the probability of any increased risk in infectious or neutropenic complications (Risk Ratio [RR] >1). Subgroup analyses were conducted based on treatment line, use of an inactive comparator, malignancy type, and prophylaxis strategy. Additionally, we pooled the incidence rates of fatal OIs between venetoclax and comparator arms and compared them by univariate meta-regression. Results Seven RCTs were included comprising 2067 patients. In venetoclax versus comparator regimens there was a 81.1% probability of any increase in IAEs (RR=1.14, 95% Confidence Interval [95%CI]=0.76-1.66). The probabilities of venetoclax increasing the risk of grade 3-5 and fatal IAEs were 86.6% (RR=1.16, 95%CI=0.86-1.55) and 81.1% (RR=1.40, 95%CI=0.66-2.94), respectively. There was a 97.2% likelihood that venetoclax increased the risk of grade 3-5 neutropenia (RR=1.44, 95%CI=1.01-2.10). Venetoclax treatment did not increase the incidence of fatal OIs (P=0.55). Conclusion Our results suggest that venetoclax likely increases the risk of high-grade neutropenia and IAEs overall, but not fatal OIs. However, our analyses did not identify any specific IAEs that would benefit from routine anti-infective prophylaxis or pre-emptive testing. Disclosures Michael Sebag, MD, PhD, Amgen: Advisor/Consultant|BMS: Advisor/Consultant|Focus Therapeutics: Advisor/Consultant|Gilead: Advisor/Consultant|Janssen: Advisor/Consultant|Novartis: Advisor/Consultant|Pfizer: Advisor/Consultant|Sanofi: Advisor/Consultant Matthew Cheng, MD, Amplyx Pharmaceuticals: Grant/Research Support|AstraZeneca: Advisor/Consultant|AstraZeneca: Honoraria|Cidara Therapeutics: Grant/Research Support|GEn1E lifesciences: Advisor/Consultant|GEn1E lifesciences: Stocks/Bonds|Kanvas Biosciences, Inc.: Board Member|Kanvas Biosciences, Inc.: Pending patents|Kanvas Biosciences, Inc.: Ownership Interest|Merck: Honoraria|nomic bio: Advisor/Consultant|nomic bio: Stocks/Bonds|Pfizer: Honoraria|Scynexis Inc.: Grant/Research Support|Takeda: Advisor/Consultant|Takeda: Honoraria
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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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.064 | 0.017 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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; both teacher heads agree on what is shown here.
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".