Efficacy and Safety Outcomes in Patients with Cancer-Associated Thromboembolism Treated with Tinzaparin According to the Tumor Site: Meta-Analysis of Prospective Studies Involving 1413 Individual Patients' Data
Notice bibliographique
Résumé
Introduction DOAC (direct oral anticoagulant) and LMWH (Low Molecular Weight Heparin) are recommended by international guidelines as first line therapy in patients with CAT (Cancer Associated Thrombosis), but the risk of venous thromboembolic recurrence (rVTE) and the risk of major bleeding (MB) remains high. Several scores have attempted to predict these risks with disappointing results, probably because of heterogeneous treatments and small sample sizes representing various tumor sites. We conduct a meta-analysis on individual patient level data to report the rate of rVTE and MB by 6 months according to site of cancer from prospective studies involving CAT patients on tinzaparin. Methods The meta-analysis is based on individual patient data from prospective studies that included patients with CAT treated with tinzaparin who were followed for 6 months (PROSPERO registration CRD42019119907). Eligible studies must include controlled data and a central decision for study outcomes. Main outcomes were cumulative incidence of rVTE and MB at 6 months. Time-to-event outcomes were estimated using competing risk regression (Fine and Gray's method with death as competing risk). Cumulative incidences were presented with corresponding 95% confidence interval (95% CI). Time-to-event outcomes were estimated using competing risk regression (Fine and Gray's method with death as competing risk). Cumulative incidences were presented with corresponding 95% confidence interval (95% CI). Results Three prospective cohort studies (AXA - NCT02898051, 308 patients; PREDICARE - NCT03099031, 409 patients (1); TICAT - NCT01164046, 247 patients (2) and the Tinzaparin arm of the CATCH study (NCT01130025, 449 patients (3)) were included. A total of 1413 patients (median age 65.0 [IQR 56.0-73.5], 51.9% female) were included in the meta-analysis. Cancers were mostly solid tumors (91.7%); primary sites were gastrointestinal (27.0%), lung (18.0%), breast (11.8%), genitourinary (14.4%); ECOG performance status was ≥ 2 for 30.2%. At 6 months, 74 patients experienced a rVTE, for a cumulative incidence of 5.4% [95% CI: 4.3%; 6.7%], while 47 patients had a MB, for a cumulative incidence of 3.4% [95% CI: 2.6%; 4.6%]. Clinical outcomes according to the type of cancer are summarized in the Table. rVTE cumulative incidence varied from 0.6 to 8.5% and rVTE occurred more frequently in patients with genitourinary, lung and gynecological cancers, while MB cumulative incidence ranged from 2.1% to 4.2% across different cancer sites (Table). Overall mortality ranged from less than 18% (breast and hematological cancers) to 45.2% (lung cancer) within 6 months of the index VTE. Conclusion In CAT patients receiving tinzaparin for up to 6 months, rVTE and MB vary according to tumor site. The CAT entity is not sufficient to describe a situation at risk of recurrence or bleeding for patient management. References 1.Jara-Palomares L et al. Tinzaparin in cancer associated thrombosis beyond 6months: TiCAT study. Thromb Res. 2017; 157:90-96. 2. Girard P, et al. Failure of the Ottawa Score to Predict the Risk of Recurrent Venous Thromboembolism in Cancer Patients: The Prospective PREDICARE Cohort Study. Thromb Haemost. 2022; 122:151-157. 3. Lee AYY et al. CATCH Investigators. Tinzaparin vs Warfarin for Treatment of Acute Venous Thromboembolism in Patients With Active Cancer: A Randomized Clinical Trial. JAMA. 2015; 314(7):677-686.
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 | 0,018 | 0,027 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,014 | 0,059 |
| Bibliométrie | 0,005 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».