The Global Kidney Patient Trials Network and the CAPTIVATE Platform Clinical Trial Design
Notice bibliographique
Résumé
Importance: Chronic kidney disease (CKD) is a global health priority affecting almost 1 billion people. New therapeutic options and clinical trial innovations such as adaptive platform trials provide an opportunity to efficiently test combination therapies. Objective: To describe the design and baseline results of the Global Kidney Patient Trials Network (GKPTN) and the design and structure of the global adaptive platform clinical trial Chronic Kidney Disease Adaptive Platform Trial Investigating Various Agents for Therapeutic Effect (CAPTIVATE) to find new therapeutic options and treatments for people with kidney disease. Design, Setting, and Participants: The GKPTN is a multicenter registry that started in May 2020 and is ongoing, while CAPTIVATE is a multicenter, multifactorial, phase 3, placebo-controlled adaptive platform randomized clinical trial that includes patients with CKD. The first participant was randomized in September 2024. The GKPTN recruits patients from kidney and endocrinology practices, and CAPTIVATE aims to recruit patients from GKPTN sites where possible. Both the GKPTN and CAPTIVATE recruit patients with nondialysis CKD. Intervention: CAPTIVATE will test several investigational agents or combinations of agents, beginning with a mineralocorticoid receptor antagonist. Main Outcomes and Measures: The GKPTN monitors clinical characteristics, treatment, and outcomes to identify eligible clinical trial participants and provide a contemporary global picture of patients with CKD. The primary outcome of CAPTIVATE is to identify investigational agents or combinations of agents to reduce the rate of chronic estimated glomerular filtration rate (eGFR) decline. The default maximum sample size per treatment arm in each domain, based on bayesian simulations, is 500 participants, providing approximately 90% power to detect a clinically meaningful improvement of 2.6 mL/min/1.73 m2 in eGFR at the end of the 104-week study period. Results: The GKPTN has enrolled 4334 patients across 119 sites in 8 countries (US, Australia, Argentina, China, Italy, Canada, Spain, and Japan). The mean (SD) participant age at enrollment was 64.5 (16.2) years, 2542 participants (58.7%) were female, and diabetic kidney disease was most frequently reported among patients for CKD etiology (1875 [43.3%]). Among the participants, the mean (SD) eGFR was 52.9 (29.3) mL/min/1.73 m2, and the median urinary albumin-to-creatinine ratio was 89 mg/g (coefficient of variation, 20-420 mg/g). In the GKPTN cohort, the mean eGFR decline was steeper among participants with a baseline eGFR of 60 mL/min/1.73 m2 or more (-2.29 [95% CI, -3.14 to -1.44]) compared with those with an eGFR of less than 60 mL/min/1.73 m2 (-1.16 [95% CI, -1.77 to -1.44]) and was progressively steeper in more severe albuminuria subgroups. Conclusions and Relevance: The GKPTN registry and the CAPTIVATE trial have the potential to expand and optimize therapeutic options for people with CKD using an adaptive platform clinical trial design. Trial Registration: ClinicalTrials.gov Identifiers: NCT04389827 and NCT06058585.
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 | 0,015 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| 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 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 ».