Diagnosing infectious diseases can be a daunting task. This is especially true for the diagnosis of respiratory infections, where there are often many symptoms overlapping among many possible types of infections. Consider pneumonia: despite the availability of many testing options, the source of pulmonary infection is not detected in as many as 60 percent of patients.1
Recent advances in molecular testing are driving improvements in the diagnosis of respiratory infections. Among the advances is a novel, hypothesis-free approach known as clinical metagenomics that promises to dramatically increase the success rate for identifying causative agents of pulmonary infections. With the advent of more and more testing options, it can be difficult for clinical laboratory professionals to select the right assay among so many options, or to determine when send-out testing is warranted. A good understanding of the factors that need to be taken into consideration during the decision-making process, however, can help streamline that process. And knowledge of the power of the metagenomic approach can ultimately improve the testing workflow.
Key factors
Cost. Second only to accuracy in test selection, cost is at the forefront of each lab manager’s mind when prioritizing individual assays. Increasingly, panels of healthcare and laboratory professionals who review the clinical utility and cost of each test must approve test menus. Molecular diagnostics that offer the benefit of generating rapid results, for example, may be deemed appropriate for in-house testing, but even high-quality tests will not be adopted if costs cannot be kept in check.
Specimen type. Specimen type has significant influence over which test can be performed. Many FDA-cleared assays are approved for only a limited set of types, putting lab directors in the position of having to run expensive and time-consuming validation studies if they want the flexibility of using the FDA-approved test on other specimens. In those cases, it can be more cost-effective to send out alternative specimen types to a lab that has already completed the validation studies for laboratory-developed tests.
Patient risk factors. Test selection for an otherwise healthy patient is much more straightforward than for an elderly or immunocompromised patient. Travel history is also important to consider, because travel can introduce infections that might otherwise never be suspected. When there are complicating risk factors, labs typically run more extensive diagnostic tests because the source of a respiratory infection may not be one of the common causes. For these cases, performing a battery of tests—from cultures to molecular assays and even highly specialized diagnostics—is generally considered more appropriate.
Comprehensiveness. In some cases of pulmonary infections, molecular test panels supplant the conventional test-by-test series to cover the most likely sources of infection. Selection of these more comprehensive molecular tests can be guided as much by reimbursement policies as any other factor, since insurance companies do not universally cover the molecular tests.
Turnaround time. While turnaround time would seem to be a major driver of test selection, it is in reality often a secondary concern. For instance, bacterial cultures are still popular in most microbiology labs despite the fact that these tests can take days or weeks to produce results. Rapid molecular tests can deliver results much faster than many other types of tests, but unless a molecular test is run at high volume in the lab, there is typically a
pre-appointed testing schedule that may delay the use of molecular tests for several hours or as much as a couple of days. For tests run at low volume, even operating them on restricted schedules can often be financially inefficient; many labs, therefore, choose to send these tests out instead.
Clinical metagenomics
The adoption of next-generation sequencing for clinical assays has paved the way for a new approach in the field of diagnostics for infectious diseases. The new method, known as clinical metagenomics, does not restrict users to testing a set of likely causes of infection. This hypothesis-free approach is based on the concept of metagenomics, a research protocol for identifying individual members of a microbial community by sequencing the whole population and matching DNA results to microbial sequences in publicly available genome databases.
A recently launched clinical metagenomics test for pneumonia allows clinical lab teams to ask the question “What’s in my sample?” instead of “Is this specific organism in my sample?” With the approach of clinical metagenomics, it is possible to identify hundreds of common and rare pathogens—bacterial, fungal, or viral—in one assay with a single, straightforward analysis pipeline.2 For clinical labs trying to diagnose a pulmonary infection, a clinical metagenomics assay could serve as an effective complementary test for cases where conventional assays do not generate useful results.
The impact of antibiotic resistance
Today, uncertainty around sources of respiratory infections largely contributes to the overuse of antibiotics. Particularly for patients with health risk factors, medical providers may prefer to cover all possible etiologies with broad-spectrum antibiotics, sometimes in combination with antiviral and antifungal agents. While this approach is understandable given the circumstances, it is expensive, puts the patient at risk of side effects, and contributes to the emergence of antibiotic-resistant bacterial species.
By selecting the right combination of tests, including the hypothesis-free clinical metagenomics assay, labs can chip away at a large proportion of undiagnosed respiratory infections. Comprehensive and actionable diagnostic results will enable physicians to offer more targeted and effective treatment of patients for not only improved health outcomes but also shorter hospital stays and lower healthcare costs.
REFERENCES
- Graf EH, Simmons KE, Taradif KD, et al. Unbiased detection of respiratory viruses by use of RNA sequencing-based metagenomics: a systematic comparison to a commercial PCR panel. J Clin Microbiol. 2016;54(4):1000-1007.
- Graf EH, Xie H, Flygare S, et al. 2017 Detection of previously missed pathogens in immunocompromised children with suspected pulmonary infections by a validated next-generation sequencing test. Poster presentation at the American Thoracic Society Annual Meeting May 2017. http://www.idbydna.com/wp-content/uploads/2017/07/Detection-of-Previously-Missed-Pathogens_ATS-2017.pdf.
Hu Ding, MD, PhD, serves as the Chair and Medical Director of the Department of Pathology at Lakeview Hospital in Salt Lake City, Utah. Dr. Ding is also the CEO of DS GenoMed, a U.S. company with a genetic diagnostic testing business in China.
