Impact of concurrent antiplatelet/NSAID use on the safety and efficacy of thromboprophylaxis with apixaban in patients with cancer: A post-hoc analysis of the AVERT trial
Notice bibliographique
Résumé
Abstract Background: The risk of venous thromboembolism (VTE) is significantly increased in patients with cancer compared to the general population. The AVERT trial demonstrated that thromboprophylaxis with apixaban significantly reduced the risk of VTE in intermediate-to-high-risk patients with cancer initiating chemotherapy but may be associated with a higher rate of major bleeding. There is a paucity of data on the risks of bleeding associated with the concurrent use of prophylactic doses of an anticoagulant and anti-platelet agents or nonsteroidal anti-inflammatory drugs (NSAID), particularly in patients with active cancer. Thus, we aim to evaluate the impact of concurrent antiplatelet/NSAID use on the safety and efficacy of apixaban thromboprophylaxis in patients with cancer. Methods: This is a post-hoc analysis of the AVERT trial, which was a randomized, placebo-controlled, double-blind clinical trial comparing apixaban (2.5 mg twice daily) to placebo for thromboprophylaxis in intermediate-to-high risk (Khorana score ≥2) ambulatory patients with cancer who were initiating chemotherapy. For the current analysis, the primary outcome was clinically relevant bleeding defined as a combination of major and clinically relevant non-major bleeding (CRNMB) as per the International Society on Thrombosis and Haemostasis. Secondary outcomes included major VTE, major bleeding, CRNMB and death. Hazard ratios (HR) for the different outcomes in patients with and without concurrent antiplatelet or NSAID use were calculated using a Cox-proportional hazards model, controlling for age and sex. Additional subgroup analyses were performed to calculate HRs separately among patients using antiplatelet agents and those using NSAIDs. Results: Out of the 574 patients randomized in the AVERT trial, a total of 557 patients were included in this study and stratified according to the presence or absence of concurrent antiplatelet/NSAID use throughout the study period. Of all patients, 182 had concurrent antiplatelet/NSAID use (apixaban n=98, placebo n=84) while 375 did not (apixaban n=186, placebo n=189). In the apixaban group, those using concurrent antiplatelets or NSAIDs had a significantly higher risk of clinically relevant bleeding (HR 1.78, 95% CI 1.13 to 2.78) and CRNMB (HR 1.98, 95% CI 1.19 to 3.30), without a significant reduction in VTE (HR 0.60, 95% CI 0.26 to 1.39), compared to those with no concurrent use. The risk of major bleeding did not differ between those two groups (HR 1.02, 95% CI 0.25 to 4.10). Among the subgroup of patients taking antiplatelet agents (n=61), the risks of clinically relevant bleeding (HR 2.0, 95% 1.27 to 3.15) and CRNMB (HR 2.59, 95% CI 1.57 to 4.28) were significantly higher compared to those with no concurrent antiplatelet use, with no increased risk of major bleeding (HR 0.73, 95% CI 0.16 to 3.4). Among the subgroup of patients taking NSAIDs (n=42), there were no significant differences in the risks of clinically relevant bleeding (HR 1.31, 95% CI 0.56 to 3.04), CRNMB (HR 0.86, 95% CI 0.65 to 1.14) or major bleeding (HR 3.59, 95% CI 0.52 to 24.75). In the placebo group, concurrent antiplatelet/NSAID use was not associated with a higher risk of clinically relevant bleeding (HR 1.38, 95% CI 0.78 to 2.46) or decreased risk of VTE (HR 1.03, 95% CI 0.61 to 1.73) but was associated with a higher risk of CRNMB (HR 1.91, 95% CI 1.0 to 3.64). In both groups, antiplatelet/NSAID use did not affect mortality outcomes. Conclusions: The use of antiplatelet agents or NSAIDs in cancer patients receiving apixaban thromboprophylaxis is associated with a significantly increased risk of clinically relevant bleeding and CRNMB, with no reduction in VTE risk. These findings highlight the need to re-evaluate the indication for antiplatelet agent and NSAID use, and to conduct an individualized bleeding risk assessment prior to the initiation of thromboprophylaxis in cancer patients.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,010 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,000 |
| Méta-épidémiologie (sens large) | 0,005 | 0,013 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».