Comparison of treatment-related adverse events (TRAE) of different CDK4/6 inhibitors (CDK4/6i) in metastatic breast cancer (MBC): A network meta-analysis.
Bibliographic record
Abstract
e13052 Background: CDK4/6i in combination with endocrine therapy (ET) are a standard of care in hormone receptor positive, HER2 negative MBC. Palbociclib, ribociclib and abemaciclib have all been approved and while efficacy appears similar, differences in safety and tolerability are apparent. Here we quantify TRAEs comparing the 3 CDK4/6i in a network meta-analysis. Methods: We searched PubMed and ASCO and ESMO proceedings to identify randomized trials (RCT) of CDK4/6i. Data on common and serious TRAE were extracted for each approved CDK4/6i. The odd ratio (OR) for each TRAE and the hazard ratio (HR) for progression-free survival (PFS) were calculated relative to ET alone. A network meta-analysis was then performed for each ET backbone (aromatase inhibitor (AI) or fulvestrant) to compare ribociclib and abemaciclib to palbociclib. Results: 7 RCT were included in the analysis and comprised 2715 patients receiving CDK4/6i (palbociclib: 789 patients; ribociclib: 1153 patients; abemaciclib: 773 patients). In 4 RCT (1440 patients) ET backbone was an AI and in 3 RCT (1275 patients) it was fulvestrant. Compared to palbociclib, ribociclib and abemaciclib showed lower grade 3-4 hematological toxicity, but higher GI toxicity (see table). Treatment discontinuation was higher with abemaciclib than other CDK4/6i. Efficacy of the 3 CDK4/6i was similar. Compared to palbociclib, for AI backbone, the HR for PFS for ribociclib was 1.00 and for abemaciclib 1.04. For fulvestrant backbone, the HR were 0.88 and 0.93 respectively. Conclusions: The three approved CDK4/6i show comparable efficacy, but differences in safety and tolerability. Abemaciclib has worse tolerability with significantly higher treatment discontinuation likely due to gastro-intestinal toxicity. [Table: see text]
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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 | 0.019 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.044 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".