Reanalysis of Urothelial Cancer Chemoimmunotherapy Trials With Differential Censoring
Notice bibliographique
Résumé
Importance: Three similar phase 3 randomized clinical trials have investigated PD-1/PD-L1 (programmed cell death 1 protein/programmed cell death 1 ligand 1) inhibitors in combination with platinum-based chemotherapy vs chemotherapy alone as first-line treatment for advanced urothelial carcinoma (IMvigor130, atezolizumab; KEYNOTE-361, pembrolizumab; and CheckMate901, nivolumab). Only CheckMate901 reported overall survival (OS) benefit for the combination. The reason for these inconsistent results is unclear. Objective: To explore whether differential censoring-that is, censoring imbalance between the study groups-is a possible explanation for these inconsistent findings. Design, Setting, and Participants: This comparative effectiveness study involved a censoring analysis of data from IMvigor130, KEYNOTE-361, and CheckMate901, which enrolled patients between 2016 and 2022. Participants included patients in these 3 trials. Exposure: Participation in 1 of the 3 trials. Main Outcomes and Measures: The primary outcomes were censoring rates adjusted for treatment effects. Censoring rates were calculated from the Kaplan-Meier (KM) curves. When excess censoring in the control group of open-label trials was found, the hypothesis was that better-performing patients might be dropping out to seek alternative treatments; a sensitivity analysis was conducted in which their survival was assumed to be similar to that of the longest surviving patients in the control group. Treatment effects of the censoring-adjusted KM curves were calculated using the 2-sided log-rank test. Results: The 3 trials involved a total of 2162 patients (1640 male [76%]; age range, 65-69 years) Analysis of progression-free survival (PFS) curves demonstrated no differential censoring in IMvigor130, but there was more than 30% excess censoring in the chemotherapy-only groups in KEYNOTE-361 and CheckMate901 trials. After sensitivity analysis, the PFS benefit was no longer significant in either study (KEYNOTE-361, adjusted hazard ratio [HR], 1.13 [95% CI, 0.95-1.35]; CheckMate901, adjusted HR, 1.17 [0.96-1.44]). Analysis of OS curves demonstrated no differential censoring in IMvigor130 or KEYNOTE-361, but there was more censoring in the chemotherapy-only group in CheckMate901. After sensitivity analysis, the OS benefit of adding nivolumab to chemotherapy was lost (before adjustment, HR, 0.77 [95% CI, 0.63-0.95]; P = .01; adjusted HR, 0.95 [95% CI, 0.77-1.17]; P = .64). Conclusions and Relevance: In this comparative effectiveness study, differential censoring explained the inconsistent results reported in the evaluated trials. The term perceived-inferiority censoring is suggested to describe a phenomenon wherein better-performing patients are aware of their treatment and drop out to pursue alternative therapeutic options; it is possible that this occurred in the open-label KEYNOTE-361 and CheckMate901 trials. Such censoring confounds randomization and interpretation of clinical trials, since a larger experimental group is compared with a selected group of controls with poorer prognosis.
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 | 0,176 | 0,347 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,017 |
| Bibliométrie | 0,006 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,001 |
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 ».