Outcomes of Drug-Eluting Stents in comparison to Bare Metal Stents in Cancer Patients with Percutaneous Coronary Intervention: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background. Studies have demonstrated poor prognosis in cancer patients who undergo percutaneous coronary intervention (PCI) for coronary artery disease (CAD). Cancer patients receiving PCI are at increased risk of in-stent thrombosis, bleeding, hospital readmissions, and cardiovascular and noncardiovascular mortality when compared to patients without cancer. It is unclear if the poor outcomes in cancer patients are related to the stent type utilized for PCI. This meta-analysis attempts to identify differences in efficacy and safety outcomes when comparing drug-eluting stents (DESs) with bare metal stents (BMSs) in cancer patients. Methods. This meta-analysis is reported according to the Preferred Reporting Items for Systematic Review and Meta-Analyses guidelines. Medline, Scopus, and Cochrane Central Register of Controlled Trials were systematically searched to identify relevant studies. Risk of bias was assessed using the Modified Newcastle-Ottawa scale and Cochrane risk of bias tool. The primary outcomes of interest were in-stent thrombosis, bleeding, and mortality. Results. Four studies comprising of 54,414 patients met the inclusion criteria. There was no difference in in-stent thrombosis (odds ratio (OR): 0.79; 95% confidence interval (CI): 0.58–1.07), bleeding events (OR: 1.38; 95% CI: 0.77–2.49), or in-hospital mortality (OR: 1.92; 95% CI: 0.83–4.43) when comparing cancer patients who underwent PCI with DES vs BMS. Conclusions. This meta-analysis demonstrates no difference in mortality, bleeding, or in-stent thrombosis between revascularization with BMS vs DES in patients with cancer and CAD. Cancer patients included in this meta-analysis experienced higher rates of mortality, bleeding, and in-stent thrombosis after PCI compared to all-comers described in the literature.
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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 | 0.012 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.044 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".