Donor, Patient age and Exposure to Antibiotics Are Associated With the Outcome of Faecal Microbiota Transplantation for Recurrent Clostridioides Difficile Infection

A Prospective Cohort Study

Simon M. D. Baunwall; Mette M. Hansen; Sara E. Andreasen; Marcel K. Eriksen; Nina Rågård; Jens Kelsen; Anne K. Grosen; Susan Mikkelsen; Christian Erikstrup; Jens F. Dahlerup; Christian L. Hvas

Disclosures

Aliment Pharmacol Ther. 2023;58(5):503-515. 

In This Article

Abstract and Introduction

Abstract

Background: Faecal microbiota transplantation (FMT) is effective for recurrent Clostridioides difficile infection (rCDI), but its effect varies inexplicably.

Aims: To optimise the effectiveness of FMT for rCDI and validate determinants for effect

Methods: We conducted a cohort study, including all patients treated with FMT for rCDI between October 2018 and June 2020. Statistical process control was used to evaluate the impact of prospective quality improvement on the effect of single FMT treatments per 10–11 patients. Targeting an 80% effect, optimisations included changes to processing procedures, preparation and clinical application of FMT. The primary outcome was the resolution of Clostridioides difficile-associated diarrhoea at week 8. If CDI recurred, FMT was repeated. All patients were followed for 8 weeks after their latest FMT.

Results: 183 patients with rCDI received 290 FMT treatments. A single FMT achieved resolution at week 8 in 127 (69%, 95% CI: 62%–76%), while repeated FMT cumulatively achieved resolution in 167/183 (91%, 95% CI: 86%–95%). The single FMT effect varied between 36% and 100% over time. In a mixed-effect model, patient age above 65 years, non-rCDI antibiotics at week 1 post-FMT, and donor were associated with effect. Neither increasing the dosages of faecal microbes nor standardising the processing improved outcomes.

Conclusion: FMT has a high cumulative effectiveness in patients with rCDI following multiple administrations, but the single FMT effect is variable and may be optimised using statistical process control. Optimising FMT by considering patient age, post-FMT antibiotics, donor and multiple administrations may improve the treatment outcomes.

ClinicalTrials.gov: (Study identifier: NCT03712722).

Introduction

Faecal microbiota transplantation (FMT) is an effective microbiota-based therapy for managing recurrent Clostridioides difficile infection (CDI), a common and serious health threat.[1,2] CDI often occurs after antibiotic treatment disrupts the intestinal microbiota and manifests as diarrhoea that may progress to pseudomembranous colitis, toxic megacolon or death. Comorbid patients over 65 years are particularly susceptible to CDI, which carries an excess in health care cost and mortality.[3] Despite appropriate standard antibiotic treatment, CDI often recur, and approximately 12% of all patients with CDI develop multiple, recurrent CDI.[4–7] For these patients, microbiota-restoration with FMT may be the only effective treatment for breaking the infectious cycle.

In Europe, fewer than 10% of the patients with an indication for FMT, three CDI episodes or more, receive FMT.[7] Practical barriers, safety concerns and unexplainable variations in effect limit its use and hinder adoption into clinical practice.[2] Encapsulated formulations have improved the practicality, but 12%–50% of patients treated with a single FMT still experience recurrence.[1]

Previous studies identified several factors associated with treatment response to FMT for recurrent CDI, some of which are potentially modifiable.[1,8–14] These factors broadly fall into three categories: (i) patient-related (such as patient age and comorbidity), (ii) FMT procedure-related (such as delivery method and dose) and (iii) CDI-related (such as disease severity).[8] These factors need validation to be clinically applicable, and no previous prospective studies have actively intervened on the potentially modifiable factors to optimise the clinical effect of FMT.

Statistical process control (SPC) is a quality improvement technique for monitoring data and making prospective improvements.[15,16] Unlike conventional statistics, SPC assesses data on an ongoing basis, enabling prospective data-driven decisions. SPC has successfully been used in healthcare settings to implement procedures, monitor the effect and optimise for better outcomes.[15,17]

In the present study, we aimed to optimise and monitor the effectiveness of FMT for recurrent CDI using SPC to validate and prospectively intervene on factors previously identified as associated with lower treatment responses.

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