A longer and/or better life for the oldest old with glioblastoma
Notice bibliographique
Résumé
Despite standard-of-care treatment with surgery, radiation, and chemotherapy, the prognosis of glioblastoma (GBM) remains dismal, with a median overall survival (OS) of only 9 months for older patients. Managing GBM in the elderly is challenging due to complex medical issues such as higher rates of age-related comorbidities, frailty, and polypharmacy, rendering them vulnerable to treatment-related toxicities. They may also have pre-existing neurocognitive dysfunction, which may affect their disease understanding and ability to fully participate in decision-making. Despite the increasing incidence of GBM in the elderly, there is a paucity of high-quality randomized data on the effectiveness and toxicities of treatment in those aged 80 years and above regarded as the “oldest old.” Stadler and colleagues conducted a retrospective analysis of GBM patients aged 80 years old and above treated between 2005 and 2018 in 6 institutions across 2 European countries and described current practices and predictors for survival.1 One-third of their 107 patients had best supportive care alone, mostly due to poor performance status and patient refusal of postsurgical therapy. Most (45/100, 45%) had surgical biopsy only. Patients received either radiation (RT) alone (36%), temozolomide (TMZ) alone (14%), or RT with concomitant TMZ (12%), with 2 patients receiving maintenance TMZ. The RT dose ranged from 34 to 60 Gy, with most receiving 40 Gy. Bevacizumab was also used as first-line treatment in 1 patient on a clinical trial. The median progression-free survival was 3.3 months, and the median OS was 4.2 months. Those treated with TMZ had clinically significant toxicities. Patients treated with chemoradiation had longer OS. On univariate analysis, Karnofsky Performance Status (KPS) was the most powerful predictor of survival, while pre-existing conditions did not affect prognosis. On multivariate analysis, a high KPS of more than 90 and treatment with TMZ in those with MGMT promoter methylation were associated with favorable outcomes. The study also revealed high hospital utilization in these patients, with a median cumulative time spent hospitalized from diagnosis until death of 30 days (range 4–168 days). Supportive care was highlighted as central to management. They also presented details on important aspects of care for the elderly, such as psycho-oncological support and place of end-of-life care. This study provided real-world data on the current state of GBM management in patients 80 years and older, who are typically excluded from trials due to explicit age cutoffs and comorbid conditions. The results are similar to other retrospective series showing that careful patient selection in the oldest old with GBM can lead to superior outcomes.2–5 Based on these data, there is some suggestion that multimodality treatment may provide better outcomes, especially for patients with methylated MGMT and good clinical status. However, hospitalization during treatment and added toxicity are still a concern.2,3 Although randomized “elderly” trials to address the optimal treatment of patients who cannot tolerate the standard 6-week course of RT and chemotherapy did not specifically enroll patients 80 years old and above, results show the feasibility of more aggressive approaches in the elderly. Maximal safe surgery and radiotherapy, including hypofractionated RT schedules such as 40 Gy in 15 fractions or 20 Gy in 5 fractions, lead to better outcomes than best supportive care alone.6–8 Conventional RT was even found to lead to worse outcomes than hypofractionated schedules in a larger randomized clinical trial.9 Adding TMZ to hypofractionated RT improved median OS, especially in those with MGMT-methylated tumors.10 Those treated with TMZ alone, including relatively fit older patients, had a median OS of 18.4 months.10 Randomized data, likewise, suggest the benefits of a more aggressive approach to treatment in the elderly with good performance status. This study has several limitations. It is subject to selection bias given its retrospective nature. As the cohort only included those with tissue-confirmed glioblastoma, it was not possible to estimate and compare outcomes to those with presumed GBM on imaging who may already be too frail for surgery. This information is important in guiding discussion around the goals of care and the risk benefit of surgery. A proportion of these patients were treated after the pivotal EORTC/NCIC-CTG pivotal trial which excluded patients 70 years and older, and well before randomized data on elderly glioblastoma became available. As a result, the cohort reported here was undertreated by today’s standards. This study may reflect regional variation, which is expected as practices vary depending on geographical and sociocultural factors. Nonetheless, this study highlights the time toxicity of cancer treatment by providing data on hospital utilization, which is not typically evaluated in clinical trials but is relevant in patients with limited time. The optimal management strategy for GBM in this age group remains unclear, and there is a need for more high-quality studies. The overarching issue is clearly not just a matter of underrepresentation in the current data, as wider enrollment criteria for elderly clinical trials may not address all of the relevant issues. Rather, clinical trials should be specifically designed for older people wherein the true physiological costs and benefits of treatment are evaluated with comprehensive geriatric assessment incorporated as a standard and considering the competing risk of death from other causes. Clinically meaningful endpoints such as patient-reported outcomes and functional status are very important in this patient population. Therefore, while additional research is necessary for this demographic, a more personalized, patient-centered approach that considers individual circumstances and preferences with a comprehensive geriatric assessment to inform treatment decisions may be the most effective way forward. Finally, despite recognizing that age alone should not be the sole deciding factor in treatment considerations, societal biases may exist against treating older patients, and how these biases can impact medical decision-making should be explored. Examining perspectives on managing GBM in the oldest old may be valuable. Moreover, broader influences such as cost-effectiveness of treatment and resource allocation also temper how this population is managed and should be explored. All these must be considered to improve therapeutic choices and optimize the management of the oldest old patients with GBM without negatively affecting their quality of life. None declared.
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 | 0,003 | 0,026 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,005 | 0,003 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,008 | 0,012 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,021 | 0,014 |
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 ».