Jasmohan S Bajaj1, Chathur Acharya1, Masoumeh Sikaroodi2, Patrick M Gillevet2, Leroy R Thacker3. 1. Division of Gastroenterology, Hepatology and Nutrition, Virginia Commonwealth University and McGuire VA Medical Center, Richmond, Virginia. 2. Microbiome Analysis Center, George Mason University, Manassas, Virginia. 3. Department of Biostatistics, Virginia Commonwealth University Medical Center, Richmond, Virginia.
Abstract
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 is 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 modeled 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 LT, 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 standard of care. This cost-saving remained robust even after sensitivity analyses that varied the background admission rates.
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 is 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 modeled 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 LT, 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 standard of care. This cost-saving remained robust even after sensitivity analyses that varied the background admission rates.
Authors: Jasmohan S Bajaj; Andrew Fagan; Melanie B White; James B Wade; Phillip B Hylemon; Douglas M Heuman; Michael Fuchs; Binu V John; Chathur Acharya; Masoumeh Sikaroodi; Patrick M Gillevet Journal: Am J Gastroenterol Date: 2019-07 Impact factor: 10.864
Authors: Jasmohan S Bajaj; Ramazan Idilman; Leila Mabudian; Matthew Hood; Andrew Fagan; Dilara Turan; Melanie B White; Fatih Karakaya; Jessica Wang; Rengül Atalay; Phillip B Hylemon; Edith A Gavis; Robert Brown; Leroy R Thacker; Chathur Acharya; Douglas M Heuman; Masoumeh Sikaroodi; Patrick M Gillevet Journal: Hepatology Date: 2018-05-10 Impact factor: 17.425
Authors: Jasmohan S Bajaj; Hugo E Vargas; K Rajender Reddy; Jennifer C Lai; Jacqueline G O'Leary; Puneeta Tandon; Florence Wong; Robert Mitrani; Melanie B White; Megan Kelly; Andrew Fagan; Rohan Patil; Shaimaa Sait; Masoumeh Sikaroodi; Leroy R Thacker; Patrick M Gillevet Journal: Clin Gastroenterol Hepatol Date: 2018-07-20 Impact factor: 11.382
Authors: Nicolas Goossens; Amit G Singal; Lindsay Y King; Karin L Andersson; Bryan C Fuchs; Cecilia Besa; Bachir Taouli; Raymond T Chung; Yujin Hoshida Journal: Clin Transl Gastroenterol Date: 2017-06-22 Impact factor: 4.396