# Fecal microbiota composition is a better predictor of recurrent Clostridioides difficile infection than clinical factors in a prospective, multicentre cohort study

## TL;DR

This study finds that gut microbiota composition is a better predictor of recurrent Clostridioides difficile infection than clinical factors, suggesting potential for improved treatment strategies.

## Contribution

The study demonstrates that gut microbiota composition outperforms clinical factors in predicting recurrent Clostridioides difficile infection.

## Key findings

- Microbiota composition variables were better predictors of reCDI than clinical factors.
- Bacteroidetes abundance and diversity after CDI treatment were robust predictors of reCDI.
- Proteobacteria diversity increase relative to baseline was a strong predictor of reCDI.

## Abstract

Clostridioides difficile infection (CDI) is the most common cause of antibiotic-associated diarrhoea. Fidaxomicin and fecal microbiota transplantation (FMT) are effective, but expensive therapies to treat recurrent CDI (reCDI). Our objective was to develop a prediction model for reCDI based on the gut microbiota composition and clinical characteristics, to identify patients who could benefit from early treatment with fidaxomicin or FMT.

Multicentre, prospective, observational study in adult patients diagnosed with a primary episode of CDI. Fecal samples and clinical data were collected prior to, and after 5 days of CDI treatment. Follow-up duration was 8 weeks. Microbiota composition was analysed by IS-pro, a bacterial profiling technique based on phylum- and species-specific differences in the 16–23 S interspace regions of ribosomal DNA. Bayesian additive regression trees (BART) and adaptive group-regularized logistic ridge regression (AGRR) were used to construct prediction models for reCDI.

209 patients were included, of which 25% developed reCDI. Variables related to microbiota composition provided better prediction of reCDI and were preferentially selected over clinical factors in joint prediction models. Bacteroidetes abundance and diversity after start of CDI treatment, and the increase in Proteobacteria diversity relative to baseline, were the most robust predictors of reCDI. The sensitivity and specificity of a BART model including these factors were 95% and 78%, but these dropped to 67% and 62% in out-of-sample prediction.

Early microbiota response to CDI treatment is a better predictor of reCDI than clinical prognostic factors, but not yet sufficient enough to predict reCDI in daily practice.

The online version contains supplementary material available at 10.1186/s12879-024-09506-7.