Thrombotic risk in patients with hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer treated with CDK 4/6 inhibitors: a meta-analysis
Bibliographic record
Abstract
Abstract Background Breast cancer is ranked as the most common cancer worldwide. The use of CDK4/6 inhibitors has improved the prognosis and has become a new strategy for hormone receptor -positive, human epidermal growth factor receptor-2-negative breast cancer; however, such drugs have been found to increase the risk of thrombosis in randomized controlled trials (RCTs), and this risk may be higher in the real-world setting. This study aimed to compare the thromboembolic risk of CDK4/6 inhibitors plus endocrine therapy (ET) and ET alone in RCTs and determine the incidence of thromboembolic events associated with the use of CDK4/6 inhibitors in RCTs and in the real world. Methods PubMed and EMBASE databases were searched up to December 31, 2022, for RCTs and cohort studies of CDK4/6 inhibitors in patients with breast cancer. The quality of the literature was assessed using the Cochrane Handbook and Newcastle–Ottawa Scale, and meta-analysis was performed using Review Manager 5.4 and R version 4.2.2. Results A total of 13 RCTs and 9 real-world studies were identified and included in this analysis. RCTs only reported venous thromboembolic events (VTEs); VTEs occurred in 192 patients (2.1%) in the CDK4/6 inhibitor group and 55 patients (0.7%) in the control group. Compared with ET alone, receiving CDK4/6 inhibitors plus ET increased the risk of VTEs in patients with breast cancer, with an odds ratio of 2.67 (95% confidence interval [CI]: 1.98, 3.59, p < 0.001). In real-world studies, the aggregate incidence rate of thromboembolic events was found to be 4.5% (95% CI: 2.2, 7.5). Conclusions CDK4/6 inhibitors combined with ET are associated with a significantly increased risk of VTEs in women with breast cancer compared with ET alone. The incidence of thromboembolic events was higher with CDK4/6 inhibitors in the real world than in RCTs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".