P14.76 Bevacizumab (BEV) alone or in combination with chemotherapy in recurrent Glioblastoma Multiforme (GBM): A real world experience
Notice bibliographique
Résumé
Abstract BACKGROUND Patients with glioblastoma multiforme (GBM) have a median survival of about 14 months. In recurrent GBM no active intervention has shown improvement in survival. Clinical trials has shown that bevacizumab (BEV) alone or in combination with chemotherapy is associated with better progression free survival (PFS). The current study aims to assess efficacy of BEV in real-world setting. MATERIAL AND METHODS Population-based retrospective cohort study patients with recurrent GBM diagnosed in the province of Saskatchewan during 2008–2018 and received BEV alone or in combination with chemotherapy were evaluated. Survival was compared with historic control. RESULTS 43 eligible patients with GBM treated with BEV with or without chemotherapy. 25 patients were treated with Bev alone and 18 patients treated with chemotherapy+ BEV. Median age of the patients were noted to be 53 years. 28 male, and 15 female. 80% of patients treated with single agent BEV had a performance status of either 2 or 3 compared to 33% of patient treated with BEV+ chemotherapy. Median PFS was 4.6 months with 95% CI 2.9–6.9. Median Overall survival (OS) from the time of diagnosis was 17.5 month. Median OS from the time of start of BEV was 5.4 months with 95% CI 3.4–6.8. Partial response (PR) was noted in 3 patients (7%) with stable disease (SD) in 6 patients (14%). 33 (77%) had progressive disease (PD). We were unable to confirm response status in one patient (2%). No statistically significant difference in response rate for patients treated with BEV and BEV+ Chemotherapy. From the start of Bev to the best response, 11 patients (30.56%) noted decrease in the dose of steroids, 14 patients (38.89%) dose remained unchanged. 7 patients (19.44%) required increase in the dose of steroids. 4 patients (11.11%) were not on steroids. For 7 patients we did not have the information on use of steroids. PFS was better for patients treated with chemotherapy + BEV with median PFS of 6.9 months, 95% CI 3.2- 22.3 verses BEV alone with median PFS 3.53 months 95% CI 1.4–5.3, P-value 0.0449. The Cox regression model for PFS to test comparing Bev with chemotherapy vs. Bev alone with the co-variables of sex, age, and ECOG performance status (PS). The model showed that patient with higher ECOG PS were noted to have inferior PFS with a Hazard ratio of 1.92 95% CI 1.09–3.37. P value of 0.2. Patient treated with BEV+ chemo had better PFS with a HR of 6.44 95% CI 1.86–22.28. P value of 0.003. CONCLUSION Retrospective real world study confirms that, patients with recurrent GBM, treatment with BEV is associated with similar PFS as reported in literature. Our study showed similar overall survival from the diagnosis compared to historic control. However the Median OS from Start of BEV was noted to be inferior to what is reported in EORTC EH1.3. Better ECOG performance status is associated with better PFS. Higher number of patients with ECOG 2 and 3 received BEV alone.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».