The HostDx sepsis test from Inflammatix, Burlingame, Calif, has been shown to be cost-effective versus standard-of-care interventions in patients suspected of acute respiratory tract infections in US emergency departments.1
A recently published health economic model illustrates the potential clinical and economic benefits of widespread adoption of the HostDx sepsis test by hospital-based clinicians.
Tim Sweeney, MD, PhD, Inflammatix.
“Despite best intentions, current practices for evaluating patients suspected of acute respiratory tract infections are insufficient. Many patients without bacterial infections are overtreated with unnecessary antibiotics and extended hospital stays, while some patients with infections are missed, leading to dire clinical outcomes,” says Tim Sweeney, MD, PhD, cofounder and chief executive officer of Inflammatix. “This study shows that Inflammatix’s HostDx sepsis test for the diagnosis of acute infections and sepsis could allow for improved patient outcomes and substantial health system savings.”
The publication assesses the application of a cost-impact model comparing the cost of standard care versus use of the HostDx sepsis test in two hypothetical arms with 1,000 patients presenting with symptoms of acute respiratory tract infections in the emergency department of an average US hospital.
Compared to standard of care, on average, the HostDx sepsis test arm showed a 0.80-day reduction in hospital length of stay (a 36.7% decrease), 1.49 reduction in days of antibiotic treatment (a 29.5% decrease), and a 1.67% decrease in 30-day mortality rate (a 13.64% decrease). Average cost savings were estimated at $1,974 per patient tested and nearly $2 million for the 1,000-patient cohort (before considering the price of the HostDx sepsis test, which has not yet been established).
For each scenario, standard care and HostDx sepsis, costs of treatment, hospitalizations, medications, and outpatient visits were considered. HostDx sepsis produces three scores for each patient: the likelihood of a bacterial infection, the likelihood of a viral infection, and a risk stratification score. The HostDx sepsis arm assumed application of the test’s performance as reported in previously published prospective clinical validation studies.2–4 These included area under the receiver operating curve of 0.85 for the detection of a bacterial infection, 0.90 for the detection of a viral infection, and 0.88 for predicting 30-day mortality (risk stratification).
“The ability to interrogate and understand how the immune system reacts to infection is more important than ever given the current covid-19 pandemic. Whether it’s covid-19, influenza, or bacterial infections, physicians need the ability to rapidly identify the presence, type, and severity of infection in a timely manner,” says Sweeney. “Tests with robust performance characteristics that are generalizable are key to improving outcomes and reducing healthcare costs.”
In the United States, sepsis leads to 270,000 deaths and $27 billion in Medicare costs annually. Inflammatix’s HostDx sepsis test uses proprietary machine-learning algorithms that incorporate the expression of multiple immune genes (host response) to identify the presence of bacterial or viral infections and to determine whether a patient has or is likely to develop sepsis.
Inflammatix’s simple-to-use, sample-to-answer HostDx system is designed to produce results at or near the point of care in 30 minutes or less. The company plans to advance its HostDx tests through commercial launch in Europe and submission to FDA in 2021.
For more information, visit Inflammatix.
References
1. Schneider JE, Romanowsky J, Schuetz P, et al. Cost-impact model of a novel multi-mRNA host response assay for diagnosis and risk assessment of acute respiratory tract infections and sepsis in the emergency department. JHEOR. 2020;7(1):24–34; doi: 10.36469/jheor.2020.12637.
2. Sweeney TE, Wong HR, Khatri P. Robust classification of bacterial and viral infections via integrated host gene expression diagnostics. Sci Transl Med. 2016;8(346):346ra91; doi: 10.1126/scitranslmed.aaf7165.
3. Mayhew MB, Buturovic L, Luethy R, et al. A generalizable 29- mRNA neural-network classifier for acute bacterial and viral infections. Nat Commun. 2020;11(1):1177; 10.1038/s41467-020-14975-w.
4. Sweeney TE, Perumal TM, Henao R, et al. A community approach to mortality prediction in sepsis via gene expression analysis. Nat Commun. 2018;9(1):694; doi: 10.1038/s41467-018-03078-2.
