An Individual Participant Data Meta-Analysis of 13 Randomized Trials to Evaluate the Impact of Prophylactic Use of Heparin in Oncological Patients
Notice bibliographique
Résumé
Abstract Background: Parenteral anticoagulants may improve outcomes in patients with cancer by reducing the risk of venous thromboembolism (VTE) and through a direct anti-tumour effect. Study-level meta-analysis indicates a reduction in VTE and provide moderate certainty that a small survival benefit exists; it is unclear if patients with specific cancers benefit more or less. Utilizing data from randomized controlled trials (RCT), this individual participant data meta-analysis examines the impact of heparin on survival, VTE and major bleeding in oncological patients randomized to low-molecular weight heparin (LMWH) or no LMWH. Methods: We performed a comprehensive systematic search for all RCTS (last search date March 2017) and contacted authors and sponsors to obtain individual participant data of patients with solid cancers and no other indication for prophylactic or therapeutic anticoagulation. We utilized the GRADE approach to evaluate the certainty of evidence and produce an evidence profile. All analyses followed the intention-to-treat principle. We calculated the impact on mortality through multivariable hierarchical models with patient-level variables as fixed effects and a categorical trial variable as a random effect. We adjusted the analysis for age, cancer type and metastasis status. To investigate whether intervention effects vary by predefined subgroups, including type of cancer, we tested interaction terms in the statistical model. Results: A total of 18 RCTs (n=10,041 participants) were eligible for inclusion and we obtained data from 82.4% of the participants (13 RCTs, n=8,278; n=4,139 for LMWH and n=4,139 for no LMWH). The meta-analysis revealed an adjusted relative risk of mortality within one year of 0.99 (95% CI: 0.95, 1.03) and a hazard ratio of 0.97 (95% CI: 0.82, 1.14) after one year. The relative risk for VTE was 0.58 (95% CI: 0.48, 0.71), 0.57 (95% CI: 0.44, 0.74) for symptomatic deep vein thrombosis and 0.58 (95%CI: 0.44, 0.77) for symptomatic pulmonary embolism, separately. For every 1,000 patients treated, approximately 16 fewer would experience symptomatic DVT and 16 fewer would experience any PE. The adjusted relative risk for major bleeding throughout trial duration was 1.24 (95% CI: 0.91, 1.69; P=0.17). Subgroup analysis, by cancer type, of VTE occurrence throughout trial duration identified lung cancer OR=0.52 (95% CI: 0.39, 0.68; P<0.001) and pancreatic cancer OR=0.55 (95% CI: 0.35, 0.88; P=0.01) patients as experiencing the greatest benefit from LMWH treatment. The certainty of the evidence for the outcomes was moderate to high. Conclusion: LMWH reduces risk of VTE without increasing risk of bleeding but does not improve survival across all patients. Funding: Canadian Institutes of Health Research knowledge synthesis grant, KRS 126594 Registration: International Prospective Register for Systematic Reviews (PROSPERO), CRD42013003526. Disclosures Schünemann: Canadian Institutes of Health Research: Research Funding. Crowther: Alexion: Speakers Bureau; Bayer: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Boehringer Ingelheim: Speakers Bureau; Leo Pharma: Research Funding; Pfizer: Honoraria; Portola: Consultancy; Shinogi: Consultancy. Macbeth: Pfizer: Other: Provision of Dalteparin for FRAGMATIC trial; Cancer Research UK: Research Funding. Griffiths: Pfizer: Consultancy, Other: Comment: I run an academic clinical trials unit, have received educational/investigator intiated research grants from companies that make these heparin agents. As consultant > 3 years ago, advised Pfizer on clinical trial designs unrelated to this study., Research Funding. Van Es: Pfizer: Employment, Other: Comment: Dr. van Es reports personal fees from Pfizer as a member of their advisory board. These fees are unrelated to this project.. Streiff: Roche: Research Funding; Portola: Research Funding; Janssen Scientific Affairs, LLC: Consultancy, Research Funding; CSL Behring: Consultancy, Research Funding. Ageno: BMS-Pfizer: Consultancy, Honoraria; Bayer AG: Consultancy, Honoraria, Research Funding; Boehringer Ingelheim: Consultancy, Honoraria; Daiichi Sankyo: Consultancy, Honoraria. Bozas: PharmaMar: Honoraria. McBane: Bristol Myers Squibb: Other: Research grant for cancer associated VTE. Maraveyas: Bayer: Other: Personal fees and conference attendance; Bristol-Myers Squibb: Other: Grants and personal fees; Leo Pharma: Other: Grants, personal fees and conference attendance; Pfizer: Other: Personal fees. Loprinzi: Bristol Myers: Other: Grant - unrelated to this project; Janssen: Other: Grant - unrelated to this project.
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 | 0,033 | 0,084 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,002 |
| Méta-épidémiologie (sens large) | 0,021 | 0,055 |
| Bibliométrie | 0,006 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 ».