Cost‐effectiveness of integrating gut microbiota analysis into hospitalisation prediction in cirrhosis. Issue 2 (24th February 2020)

• Record Type: Journal Article
• Authors: Bajaj, Jasmohan S.; Acharya, Chathur; Sikaroodi, Masoumeh; Gillevet, Patrick M.; Thacker, Leroy R.
• Is Part Of: GastroHep. Volume 2:Issue 2(2020)
• Page Start: 79
• Page End: 86
• Publication Date: 2020-02-24
• Subjects: Gastroenterology -- Periodicals; Hepatology -- Periodicals; 616.33
• DOI: 10.1002/ygh2.390
• Languages: English
• ISSNs: 2689-3711

Abstract

Summary: Background: Admissions in cirrhosis are expensive and often unpredictable based on purely clinical variables. Admissions could be related to complications associated with gut microbial changes, which can improve prognostication. However, the cost‐effectiveness remains unclear. Aims: Determine cost‐effectiveness of adding gut microbiota analysis to clinical parameters in prediction and subsequent reduction of admissions in cirrhosis. Methods: Using a Markov model of 1000 cirrhosis patients over 90 days, we modelled microbiota testing using 16srRNA ($250/sample), low‐depth ($350/sample) and high‐depth ($650/sample) metagenomics added to standard‐of‐care (SOC) for prevention of admissions using standard outcome costs and rates of development. We generated quality of life years (QALY) and Incremental cost‐effectiveness ratios (ICER) for the base scenarios and performed sensitivity analyses by varying costs for outcomes (transplant, death, admission) and admission rates (40%, range 25%‐60%). Results: Using fixed costs of outcomes and outcome rates, microbiota analysis was cost‐saving ($47K‐$97K) at $250 and $350/sample if admissions were reduced by 5% over SOC and >10% with $650/sample. When costs of liver transplant, death and admissions were varied, these cost‐savings remained robust provided there was >2.1% reduction (range 1.3%‐3.2%) for $250/sample, >2.9% (range 1.8%‐4.4%) for $350/sample and >5.4% (range 3.3%‐8.2%) for $650/sample. These cost‐savings remained robust even when the assumed admission rate was varied for all sample cost values. Conclusions: Gut microbiota analysis is cost‐effective for predicting and potentially preventing 90‐day admissions in cirrhosis over current SOC. This cost‐saving remained robust even after sensitivity analyses that varied the background admission rates.