Comparison of Long-term Survival Benefits in Trials of Immune Checkpoint Inhibitor vs Non–Immune Checkpoint Inhibitor Anticancer Agents Using ASCO Value Framework and ESMO Magnitude of Clinical Benefit Scale
Notice bibliographique
Résumé
Importance: Recently, anticancer agents have generated excitement owing to their capacity to preserve long-term durable survival in some patients who are represented by a tail of the survival curve. However, because traditional measures of clinical benefit may not accurately capture durable survival, amendments to various valuation frameworks have been proposed to capture this benefit. Objectives: To determine how frequently immune checkpoint inhibitor (ICI) anticancer agents vs non-ICI anticancer agents displayed trends of long-term durable survival, as defined by the American Society of Clinical Oncology Value Framework version 2 (ASCO-VF v2) and European Society of Medical Oncology Magnitude of Clinical Benefit Scale version 1.1 (ESMO-MCBS v1.1), as well as to further analyze the degree of agreement between ASCO and ESMO frameworks. Design, Setting, and Participants: In this cohort study, anticancer agents from phase 2 or 3 randomized clinical trials (RCTs) cited for clinical efficacy evidence in drug approval by the US Food and Drug Administration between January 2011 and March 2018 were identified. Data required for the ASCO-VF v2 tail-of-the-curve bonus and the ESMO-MCBS v1.1 immunotherapy-triggered long-term plateau adjustments were extracted from relevant RCTs. Frequency and difference in proportions were calculated to determine how often survival benefits were awarded to anticancer agents overall and to ICI and non-ICI anticancer agents individually. Main Outcomes and Measures: American Society of Clinical Oncology Value Framework v2 tail-of-the-curve bonuses and ESMO-MCBS v1.1 immunotherapy-triggered long-term plateau adjustments. Results: In total, 247 RCTs were identified, and 100 RCTs involving 57 164 patients were included, with 14 examining ICI agents (1 ipilimumab, 5 pembrolizumab, 5 nivolumab, 2 atezolizumab, and 1 durvalumab) and 86 examining non-ICI agents (74 targeted therapy, 8 chemotherapy, 3 hormone therapy, and 1 radiopharmaceutical). Randomized clinical trials were awarded ASCO-VF v2 tail-of-the-curve bonuses more often than ESMO-MCBS v1.1 immunotherapy-triggered long-term plateau adjustments (ASCO-VF v2, 45.0% [8 of 14 ICI RCTs and 37 of 86 non-ICI RCTs] vs ESMO-MCBS v1.1, 2.6% [1 of 12 ICI RCTs and 1 of 66 non-ICI RCTs). Randomized clinical trials for ICIs were not more likely to receive an ASCO-VF v2 bonus or ESMO-MCBS v1.1 adjustment than non-ICI RCTs (ASCO-VF: risk difference, 0.14; 95% CI, -0.14 to 0.42; P = .32; ESMO-MCBS: risk difference, 0.07; 95% CI, -0.09 to 0.23; P = .40). Poor agreement was found between the framework algorithms in identifying long-term survival benefits from RCTs (κ = 0.01; 95% CI, -0.23 to 0.22; P = .50). Conclusions and Relevance: The ASCO-VF v2 and ESMO-MCBS v1.1 may require additional refinement to accurately capture the benefit of durable long-term survival, or ICI agents may not preserve long-term survival as conventionally thought.
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 | 0,010 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,005 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 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 ».