634. Investigational Microbiome Therapeutic SER-109 Reduces Recurrence of <i>Clostridioides difficile</i> Infection (CDI) Compared to Placebo, Regardless of Risk Factors for Recurrence
Bibliographic record
Abstract
Abstract Background Several demographic and clinical characteristics, including age, sex, medication use and presence of comorbid conditions are considered risk factors for recurrent CDI (rCDI). We examined the efficacy of an investigational purified oral microbiome therapeutic, SER-109, versus placebo in an exploratory analysis of subgroups of patients with risk factors for recurrence who enrolled in ECOSPOR III, a double-blind, placebo controlled trial. Forest Plot of Relative Risks for Recurrence at Week 8 for Selected Baseline Characteristics in the ITT population Methods Patients with ≥ 3 CDI episodes were treated with SER-109 or placebo (four capsules daily for three days) following standard treatment of CDI. The primary efficacy objective was to demonstrate superiority of SER-109 versus placebo in reducing rCDI up to 8 weeks after treatment. In this exploratory analysis, we analyzed the rate of CDI recurrence among SER-109 treated subjects compared to placebo in subgroups defined by rCDI baseline risk factors: proton-pump inhibitor use, number of CDI recurrences, prior FMT history, presence of comorbid conditions and exposure to non-CDI antibiotics after dosing. We also analyzed the rate of CDI recurrence among SER-109 treated subjects by age (≥ 65 and ≤ 65) and gender, which were pre-specified. Results Of 281 patients screened,182 were enrolled. Overall recurrence rates were lower in SER-109 treated patients compared to placebo (12.4% vs 39.8%, respectively); relative risk (RR), 0.32 [95% CI, 0.18-0.58; P&lt; 0.001 for RR&lt; 1.0:P&lt; 0.001 for RR&lt; 0.833]. Co-morbidities including diabetes, renal disease, malignancy, cardiac disease, COPD/asthma, colitis, or immunocompromised status were observed in most patients in the overall study population; 33.5%, 32.4% and 34.1% had 0, 1, or ≥ 2 comorbidities. SER-109 was consistently observed to show greater benefit than placebo in reducing CDI recurrence in all subgroups regardless of the presence or absence of the rCDI risk factor (Fig 1). Conclusion Regardless of risk factor status, SER-109 reduced recurrence of CDI compared to placebo. Most subjects in ECOSPOR III had co-morbidities consistent with the broad inclusion criteria in this Phase 3 trial. Despite a high proportion of patients with co-morbidities in ECOSPOR III, SER-109 significantly reduced the risk of recurrence compared to placebo. Disclosures Stuart H. Cohen, MD, Seres (Research Grant or Support) 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) Elaine E. Wang, MD, Seres Therapeutics (Employee) Elaine E. Wang, MD, Seres Therapeutics (Employee, Shareholder) Barbara McGovern, MD, Seres Therapeutics (Employee, Shareholder) Kelly Brady, MS, Seres Therapeutics (Employee, Shareholder) Lisa von Moltke, MD, Seres Therapeutics (Employee, Shareholder)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".