Treatment patterns and outcomes of patients with high-grade glioma during the COVID-19 pandemic.
Notice bibliographique
Résumé
e14009 Background: During the first year of the COVID-19 pandemic there was global disruption in the provision of healthcare, causing significant pressure on hospital resources. High-grade gliomas (HGG) are rapidly progressive tumors, so patients with delays in diagnosis or treatment due to COVID-19-related disruptions might have poor outcomes. Therefore, we retrospectively evaluated the impact of the COVID-19 pandemic on treatment patterns and outcomes of patients with HGG in British Columbia (BC). Methods: A case cohort with a pathologic diagnosis of HGG (grade 4 astrocytoma and glioblastoma) treated at BC Cancer centers with radiotherapy between March 1, 2020 – March 1, 2021 (“COVID era”), and a control cohort treated between March 1, 2018 – March 1, 2019 (“pre-COVID era”) were identified. Patient demographics, tumor characteristics, treatment details, and dates of radiographic progression and death were included in the chart review. Analyses were performed with one-way ANOVA and Chi-squared tests for comparisons between eras. The Kaplan-Meier method was used to assess progression-free survival (PFS) and overall survival (OS) and differences in outcome between eras were investigated using the log-rank test. Results: 164 patients were identified: 85 in the pre-COVID era and 79 in the COVID era. There was no statistically significant baseline difference in age, sex, comorbidities, ECOG, tumor diameter, IDH mutation status, or MGMT methylation status between eras. There was also no statistically significant difference between time from symptom onset to first imaging, time from first imaging to surgery, time from surgery to oncologic consultation between eras, and time from surgery to radiotherapy. Significantly more patients were managed with biopsy relative to partial or gross total resection during the COVID era 22% (17/79) than the pre-COVID era 13% (11/85) (p = 0.04). However, radiation treatment (RT) did not differ between eras, with similar rates of conventionally fractionated RT in the pre-COVID era (87%, 74/85) and the COVID era (82%, 65/79) (p = 0.23). Use of concurrent and/or adjuvant temozolomide also was not significantly different between eras (p = 0.27 and p = 0.19, respectively). Median PFS was 7.0 months in both eras (CI95 = 5.5 – 8.5 months for pre-COVID era, CI95 = 5.8 – 8.2 months for COVID era, p = 0.3), and median OS was 13 months in the pre-COVID era (CI95 = 10.3 – 15.7 months) and 16 months in the COVID era (CI95 = 11.5 – 20.5 months), though this difference was not significant (p = 0.09). Conclusions: To our knowledge, this is the first study to assess outcomes of patients treated for HGG during the COVID-19 pandemic. We found that, despite less use of surgery in the COVID era, the outcomes of patients with HGG were not affected.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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) | 0,001 | 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 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 ».