Efficacy and Safety of Primary Thromboprophylaxis for the Prevention of Venous Thromboembolism in Patients with Cancer and Central Venous Catheter: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Abstract Background Venous thromboembolism (VTE) is a leading cause of mortality in patients with cancer and is associated with significant morbidity and healthcare expenditure. The risk of VTE is also increased following the insertion of a central venous catheter (CVC) for chemotherapy deliverance and supportive care. The risks and benefits of primary thromboprophylaxis in patients with cancer and newly inserted CVC are unclear. Objective We sought to assess the rates of VTE and major bleeding complications to determine the safety and efficacy of primary thromboprophylaxis in adult patients with cancer and a CVC. Methods A systematic search of MEDLINE, EMBASE, and all EBM was conducted. Randomized controlled trials (RCTs) of adult patients with cancer and a CVC receiving primary thromboprophylaxis or observation/placebo were included. The primary efficacy and safety outcomes were total VTE and major bleeding episodes, respectively. Results A total of 9 RCTs (3155 patients) were included in the analysis. The total rates of VTE were significantly lower in patients receiving primary thromboprophylaxis compared to those not receiving primary prevention (7.6% vs. 13%; Odds Ratio (OR) 0.51, 95% CI 0.32 to 0.82, p < 0.01, I² = 52%) (Figure 1). The rate of major bleeding complication was not increased in patients receiving thromboprophylaxis (0.9% vs. 0.7%; OR 1.12, 95% CI 0.29 to 4.40, p = 0.87, I² = 32%) (Figure 2). Conclusions Primary thromboprophylaxis significantly reduced the risk of VTE without increasing the risk of major bleeding complications in patients with cancer and CVC. Future studies are needed to confirm these findings. Figure 1 Figure 1. Disclosures Wang: Servier: Membership on an entity's Board of Directors or advisory committees; Leo Pharma: Research Funding. Ikesaka: LEO Pharma: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees. Wells: Bristol-Myers Squibb: Honoraria; Pfizer: Honoraria; Bayer: Honoraria; BMS/Pfizer: Research Funding; Servier: Honoraria. Carrier: Servier: Honoraria; Boehringer Ingelheim: Honoraria; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Aspen: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Honoraria; Bayer: Honoraria, Membership on an entity's Board of Directors or advisory committees; LEO Pharma: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi Aventis: Honoraria, Membership on an entity's Board of Directors or advisory committees.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.029 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".