639. Time to Recurrence of <i>Clostridioides difficile</i> Infection (rCDI) is Rapid Following Completion of Standard of Care Antibiotics: Results from ECOSPOR-III, a Phase 3 Double-Blind, Placebo-Controlled Randomized Trial of SER-109, an Investigational Microbiome Therapeutic
Notice bibliographique
Résumé
Abstract Background The natural history of CDI recurrence after antibiotics may be helpful to understand the window of opportunity for microbiome repair. ECOSPOR III evaluated the efficacy of SER-109, an investigational microbiome therapeutic, compared to placebo with rates of rCDI as the primary endpoint. SER-109 was superior to placebo in reducing the rate of rCDI following standard-of-care antibiotics at 8 weeks (12.4% vs 39.8%, respectively; P < 0.001). Herein, we describe results from the secondary endpoint, time to recurrence, in this well-characterized study population. Methods A total of 182 C. difficile toxin+ adults with ≥ 3 CDI episodes and symptom resolution on CDI antibiotics were randomly assigned to SER-109 (4 capsules orally x 3 days) or placebo. Recurrence for this analysis was defined as ≥ 3 unformed stools/day for ≥ 48 hours, ± C. difficile stool toxin test, and an investigator decision to treat. Time to CDI recurrence was analyzed using observed data and Kaplan-Meier methods. Data were not imputed for subjects lost to follow-up or discontinued from study. Subjects who did not have a CDI recurrence were censored on the date of study completion, study discontinuation or death. Results Through 24 weeks, 11/89 (12.4%) SER-109 and 36/93 (38.7%) placebo subjects had rCDI (P < 0.001). Of all recurrence events in the study population, 16/47 (34.0%) were observed within 1 week; 30/47 (63.8%) within 2 weeks; and 34/47 (72.3%) within 4 weeks after randomization, highlighting the rapid onset of recurrence. On the other hand, 12/47 (25.5%) recurrences occurred between 4 and 12 weeks, highlighting late onset of recurrence in a subset of patients (Table). Significantly lower rates of recurrence in patients on SER-109 compared to placebo was maintained throughout the 24-week follow-up (Figure). Time of rCDI K-M Plot Conclusion SER-109, an investigational oral microbiome therapeutic, maintained significant efficacy in reducing rCDI vs placebo through 24 weeks. About two-thirds of all recurrences occurred within 14 days of antibiotic completion highlighting the need for rapid repair of the disrupted microbiome. However, the significant number of late recurrences in the placebo arm also highlights that rCDI trials limited to 4 weeks of follow-up after treatment completion may underestimate recurrences. Disclosures Thomas J. Louie, MD, Artugen (Advisor or Review Panel member)Crestone (Consultant, Grant/Research Support)Da Volterra (Advisor or Review Panel member)Finch Therapeutics (Grant/Research Support, Advisor or Review Panel member)MGB Biopharma (Grant/Research Support, Advisor or Review Panel member)Rebiotix (Consultant, Grant/Research Support)Seres Therapeutics (Consultant, Grant/Research Support)Summit PLC (Grant/Research Support)Vedanta (Grant/Research Support, Advisor or Review Panel member) Matthew Sims, MD, PhD, Astra Zeneca (Independent Contractor)Diasorin Molecular (Independent Contractor)Epigenomics Inc (Independent Contractor)Finch (Independent Contractor)Genentech (Independent Contractor)Janssen Pharmaceuticals NV (Independent Contractor)Kinevant Sciences gmBH (Independent Contractor)Leonard-Meron Biosciences (Independent Contractor)Merck and Co (Independent Contractor)OpGen (Independent Contractor)Prenosis (Independent Contractor)Regeneron Pharmaceuticals Inc (Independent Contractor)Seres Therapeutics Inc (Independent Contractor)Shire (Independent Contractor)Summit Therapeutics (Independent Contractor) Richard Nathan, DO, none (Other Financial or Material Support, I am PI on several clinical trials. If you need that information, I would be happy to supply it.) Princy N. Kumar, MD, AMGEN (Other Financial or Material Support, Honoraria)Eli Lilly (Grant/Research Support)Gilead (Grant/Research Support, Shareholder, Other Financial or Material Support, Honoraria)GSK (Grant/Research Support, Shareholder, Other Financial or Material Support, Honoraria)Merck & Co., Inc. (Grant/Research Support, Shareholder, Other Financial or Material Support, Honoraria) Elaine E. Wang, MD, Seres Therapeutics (Employee) Elaine E. Wang, MD, Seres Therapeutics (Employee, Shareholder) Robert Stevens, PharmD, Seres Therapeutics (Employee, Shareholder) Kelly Brady, MS, Seres Therapeutics (Employee, Shareholder) Barbara McGovern, MD, Seres Therapeutics (Employee, Shareholder) Lisa von Moltke, MD, Seres Therapeutics (Employee, Shareholder)
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| 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 | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».