BONE SARCOMA IS NOT ASSOCIATED WITH INCREASED VENOUS THROMBOEMBOLISM RISK COMPARED TO SOFT-TISSUE SARCOMA: A META-ANALYTIC REVIEW
Notice bibliographique
Résumé
There has been recent increased interest in rates of VTE in orthopaedic oncology. Some studies and commentary have suggested that bone sarcoma has higher rates of VTE than soft tissue sarcoma. Proposed aetiologies have included use of chemotherapy or comparatively larger resections or reconstructions for bone sarcoma. However, evidence to support the base assumption of increased risk is not clearly borne out in the literature, with some studies showing differing conclusions. This meta-analysis aims to summarize existing evidence for VTE incidence in bone and soft tissue sarcoma. A systemic search was performed according to PRISMA protocol using PubMed and EMBASE. Studies describing VTE incidence in sarcoma patients undergoing operative intervention were identified and reviewed. Meta-analysis of effect sizes was done using the Mantel-Haenszel method with a random effects model in RStudio (Version 2023.06.0+421). We also performed a network meta-analysis of prophylaxis strategies and their effect on VTE rates. Thirty-five studies were included in this meta-analysis, including 74635 bone and 5937 soft tissue sarcoma patients respectively and 2283 VTE cases. The analysis found a VTE rate of 0.0448 [0.0317; 0.0629 95% CI] for sarcoma overall. For bone sarcoma the rate was 0.0429 [0.0288; 0.0636 95% CI], and 0.0343 [0.0146; 0.0785 95% CI] for soft tissue sarcoma (Fig 1: Forest Plot of VTE Rates). These rates did not differ significantly, with a p-value of 0.5656. There was significant heterogeneity in the studies (tau2 = 1.24, I2 = 94.5%), and a GOSH analysis was performed to identify outliers. However, the overall effect size was not changed with removal of outliers. Network meta-analysis of prophylaxis strategies included 2286 observations for 8 treatment types and 43 treatment arm pairs. Treatment strategies were compared against rates of VTE with no prophylaxis. No treatments were identified as superior to no prophylaxis (Fig 2: Forest Plot of Prophylactic Treatments). Heparins were found to have an odds ratio of 2.3526 for VTE, as compared to no prophylaxis (p=0.06). This is mostly likely due to selection bias. Heterogeneity within this arm of the study was low (tau2 = 0.3799; I2 = 38.1%.), however risk of bias is elevated mainly due to the designs of the included studies and relatively few comparisons. Published data does not show evidence of increased risk of VTE in patients with bone sarcoma compared with soft tissue sarcoma, based on meta-analysis of 35 studies including 85425 patients. This rate is lower than that quoted in the literature for other cancers and more in line with rates of matched controls; despite typically large surgical resections and reconstructions along with radiation or chemotherapy. Despite this, a network meta-analysis of prophylaxis treatments in the literature does not identify any strategies decrease odds of VTE compared to no prophylaxis. However, this should be interpreted with caution due to the few studies included with elevated risk of bias. Further work is needed to improve the evidence for or against prophylaxis for VTE in patients with sarcoma. For any figures or tables, please contact the authors directly.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,001 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 tête enseignante, 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 ».