Fecal Microbiota Therapy for Clostridium difficile Infection: A Health Technology Assessment.
Bibliographic record
Abstract
BACKGROUND: Fecal microbiota therapy is increasingly being used to treat patients with Clostridium difficile infection. This health technology assessment primarily evaluated the effectiveness and cost-effectiveness of fecal microbiota therapy compared with the usual treatment (antibiotic therapy). METHODS: We performed a literature search using Ovid MEDLINE, Embase, Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, CRD Health Technology Assessment Database, Cochrane Central Register of Controlled Trials, and NHS Economic Evaluation Database. For the economic review, we applied economic filters to these search results. We also searched the websites of agencies for other health technology assessments. We conducted a meta-analysis to analyze effectiveness. The quality of the body of evidence for each outcome was examined according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria. Using a step-wise, structural methodology, we determined the overall quality to be high, moderate, low, or very low. We used a survey to examine physicians' perception of patients' lived experience, and a modified grounded theory method to analyze information from the survey. RESULTS: For the review of clinical effectiveness, 16 of 1,173 citations met the inclusion criteria. A meta-analysis of two randomized controlled trials found that fecal microbiota therapy significantly improved diarrhea associated with recurrent C. difficile infection versus treatment with vancomycin (relative risk 3.24, 95% confidence interval [CI] 1.85-5.68) (GRADE: moderate). While fecal microbiota therapy is not associated with a significant decrease in mortality compared with antibiotic therapy (relative risk 0.69, 95% CI 0.14-3.39) (GRADE: low), it is associated with a significant increase in adverse events (e.g., short-term diarrhea, relative risk 30.76, 95% CI 4.46-212.44; abdominal cramping, relative risk 14.81, 95% CI 2.07-105.97) (GRADE: low). For the value-for-money component, two of 151 economic evaluations met the inclusion criteria. One reported that fecal microbiota therapy was dominant (more effective and less expensive) compared with vancomycin; the other reported an incremental cost-effectiveness ratio of $17,016 USD per quality-adjusted life-year for fecal microbiota therapy compared with vancomycin. This ratio for the second study indicated that there would be additional cost associated with each recurrent C. difficile infection resolved. In Ontario, if fecal microbiota therapy were adopted to treat recurrent C. difficile infection, considering it from the perspective of the Ministry of Health and Long-Term Care as the payer, an estimated $1.5 million would be saved after the first year of adoption and $2.9 million after 3 years. The contradiction between the second economic evaluation and the savings we estimated may be a result of the lower cost of fecal microbiota therapy and hospitalization in Ontario compared with the cost of therapy used in the US model. Physicians reported that C. difficile infection significantly reduced patients' quality of life. Physicians saw fecal microbiota therapy as improving patients' quality of life because patients could resume daily activities. Physicians reported that their patients were happy with the procedures required to receive fecal microbiota therapy. CONCLUSIONS: In patients with recurrent C. difficile infection, fecal microbiota therapy improves outcomes that are important to patients and provides good value for money.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.085 | 0.217 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.021 |
| Bibliometrics | 0.045 | 0.023 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".