The successful application of metagenomic next-generation sequencing (mNGS; or clinical metagenomics) for the diagnosis of infectious diseases directly from a clinical specimen generated significant interest from a high-profile report nearly a decade ago [1]. Several case series have since emerged, generating further interest and building momentum for clinical use. Metagenomic NGS is promising in improving and streamlining the diagnosis of infectious diseases because of its untargeted nature, facilitating organism detection without a priori knowledge of the differential diagnosis. However, mNGS requires more advanced molecular and bioinformatics expertise and is more expensive than conventional microbiologic testing. Currently, mNGS test ordering is driven by local institutional practice, often ad hoc as a test of last resort, and with inconsistent oversight by laboratory medicine and infectious disease specialists [2]. The evidence base supporting clinical mNGS has been largely retrospective and limited by the lack of standardized definitions, variable mNGS timing in the care pathway, and need for stratification by specific patient population or clinical syndrome (Table 1) [3–15]. Reviewing this evidence, we note that several studies report that the positive clinical impact of plasma mNGS is strongest in immunocompromised hosts. However, positive impact varied widely across studies, and negative impact has also been reported. Furthermore, most studies highlight the unmet need for prospective studies and clinical correlation of plasma mNGS results, both of which we seek to address with the current study design.
Table 1.
Review of plasma mNGS studies assessing test performance and/or clinical impact
| Study reference | Number of sites (location) | Number of participants | Number of tests | % Peds | % IC | Study design | Indication for testing (%) | ID/Micro approval required | Primary outcome | Secondary outcomes | Pos rate (% poly) | Main findings |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Benamu et al., 2022 [4] | 1 (Stanford, USA) | 55 | 151 | 0 | 100% | Prospective observational | FN (100%) | NA, tested if fit study criteria | Diagnostic performance compared with composite reference (conventional Micro, radiology, and clinical adjudication by ID) | Diagnostic performance on subsequent testing | 85% (61%) | Sen 92%/Spe 70% |
| Time to diagnosis | Earlier time to diagnosis in 87% | |||||||||||
| Anticipated change in antimicrobial management | Potential early optimization of antimicrobials in 47% | |||||||||||
| Hill et al., 2020 [6] | 1 (Seattle, USA) | 114 | 114 | 0 | 100% | Retrospective observational | Suspected pulmonary IFI (100%) | NA, tested if fit study criteria | Diagnostic performance compared with conventional Micro and clinical adjudication for discrepant cases | 51% (5/75) | p/p pulmonary IFI: Sen 51%/Spe 100% p/p non-Aspergillus IFI: Sen 79% p/p Aspergillus IFI: Sen 31% mNGS complementary to GM |
|
| Rossoff et al., 2019 [7] | 1 (Chicago, USA) | 79 | 100 | 100% | 76% | Retrospective chart review | Suspected IFI (55%) | No, but 94% ordered by ID | Diagnostic performance compared with conventional Micro and clinical adjudication for discrepant cases | 70.0% (33%) | Sen 92%/Spe 64% (overall) | |
| Fever/sepsis (22%) Prolonged/recurrent fever (18%) Lymphadenopathy (4%) |
Sen 93%/Spe 59% (IC) 56 (80%) clinically relevant 14 identified by mNGS only |
|||||||||||
| Niles et al., 2020 [8] | 1 (Houston, USA) | 60 | 60 | 100% | 62% | Retrospective chart review | Lung lesion (27%) Unclear (20%) |
No | Diagnostic performance compared with conventional Micro | Time to diagnosis | 63% (42%) | PPA 61%/NPA 58% Conventional time to diagnosis 3.5 d earlier |
| FN (10%) Sepsis (10%) |
Change in therapy | When mNGS identified new organism, no change in therapy in 74% | ||||||||||
| Lee et al., 2020 [9] | 1 (Boston, USA) | 54 | 59 | 100% | 56% | Retrospective chart review | Resp (31%) | Yes | Clinical impact of mNGS compared with conventional Micro | Diagnostic performance compared with conventional Micro | 49% (35%) | Clinical impact in 14% |
| FUO (19%) | Organism clinical relevance | IC status associated with significant clinical impact | ||||||||||
| Multisite (15%) | Effect of treatment on mNGS result | PPA 53%/NPA 79% | ||||||||||
| Cardiac (14%) | Interpretation of MPM of plasma | |||||||||||
| Hogan et al., 2021 [10] | 5 (Stanford, Los Angeles (2), New York, Salt Lake City, USA) | 82 | 98 | 52.40% | 65% | Retrospective chart review | FUO (23%) Resp (13%) Sepsis (10%) IE (9%) FN (7%) |
Initially no, then yes through study period | Clinical impact of mNGS compared with conventional Micro | Clinical impact of mNGS compared with conventional Micro for repeat testing | 61.0% (50%) | No impact 86.6% Pos impact 7.3% Neg impact 3.7% |
| Wilke et al., 2021 [11] | 1 (San Diego, USA) | 110 | 142 | 100% | 33% | Retrospective chart review | Clinical symptoms suggestive of infection (48%) | Yes | Diagnostic performance compared with conventional Micro | Clinical impact of mNGS compared with conventional Micro for repeat testing | 74% (56%) | PPA 90%/NPA 52% |
| Focal imaging finding (27%) | Clinical impact in 32% | |||||||||||
| Shishido et al., 2022 [12] | 1 (Baltimore, USA) | 80 | 80 | 0% | 56% | Retrospective chart review | Resp (31%) Sepsis (15%) IE (13%) FUO (10%) |
Yes | Clinical impact of mNGS compared with conventional Micro | 61% (51%) | No impact 55% Pos impact 43% Neg impact 3% Highest impact in SOTR, sepsis, and individuals on antimicrobial therapy for <7d |
|
| Niles et al., 2022 [13] | 1 (Houston, USA) | 169 | 169 | 100% | 76% | Retrospective chart review | Deep-seated infection (49%) Resp (30%) GI (11%) Lymphadenopathy (7%) |
No | Clinical impact of mNGS compared with conventional Micro | Clinical impact of mNGS compared with conventional Micro for repeat testing | 64% (47%) | No impact 82% Pos impact 12% Neg impact 5% Highest yield in IC (56 vs. 30%) |
| Vijayvargiya et al., 2022 [14] | 1 (Rochester, USA) | 20 | 60 | 0% | 100% | Prospective observational | FN (100%) | NA, tested if fit study criteria | Ginical impact of metagenome shotgun sequencing compared with conventional Micro | 15% “clinically relevant” (0%) | No concordance with BCx for bacterial targets supports noninfectious aetiology of FN | |
| Vissichelli et al., 2023 [15] | 1 (Richmond, USA) | 36 | 36 | 0% | 92% | Retrospective chart review | Pneumonia (72%) Fever(67%) |
NA | Ginical impact of mNGS compared with conventional Micro | 58% (NA) | Higher impact in immunocompromised hosts; driven by antimicrobial initiation and de-escalation | |
| Hepatosplenic lesions (5%) Invasive sinusitis (3%) | ||||||||||||
| Schulz et al., 2022 [5] | 1 (Graz, Austria) | 60 | 97 | 0% | 100% | Prospective observational | FN (100%) | NA, tested if fit study criteria | Diagnostic performance compared with blood cultures | 43% (36%) | PPA 85%/NPA 63% Sen bacteria 40% Sen fungi 19% |
|
| Grumaz et al., 2019 [3] | 1 (Heidelberg, Germany) | 48 | 239 | 0% | NA | Retrospective chart review | Sepsis (100%) Abdominal source (90%), lung source (8%), and genitourinary (2%) |
NA | Diagnostic performance compared with conventional Micro | Change in therapy would have been warranted | 72% at sepsis onset; 71% overall (56%) | 95% of the mNGS findings were plausible; 53% would have led to change in clinical intervention |
#, number; BCx, blood culture; FN, febrile neutropenia; FUO, fever of unknown origin; GI, gastrointestinal; GM, galactomannan; IC, immunocompromised; ID, infectious disease; IE, infective endocarditis; IFI, invasive fungal infection; Micro, microbiology; mNGS, metagenomic next-generation sequencing; MPM, molecules per microlitre; NA, not available; Neg, negative; NPA, negative percent agreement; Poly, polymicrobial; Pos, positivity; PPA, positive percent agreement; Resp, respiratory; Sen, sensitivity; SOTR, solid organ transplant recipient; Spe, specificity.
Given the restricted availability of mNGS, high cost, labour-intensive nature, complexity of interpretation, and heterogeneous indications for testing, there has not yet been a coordinated approach in microbiology to pursue a large-scale, multisite, prospective, randomized-controlled trial (RCT) to assess the impact of plasma cell-free DNA mNGS on patient outcomes. Indeed, plasma mNGS testing has been largely performed by a single private laboratory in the United States (Karius, Redwood City, USA) [16] and by a separate company in Europe (Noscendo, Reutlingen, Germany) [4]. Two studies so far have focused on plasma mNGS in febrile neutropenia, but with observational designs and without real-world clinical impact assessment [5,6]. As mNGS applications expand across clinical syndromes and patient populations, the need to generate robust evidence to assess the true value of plasma mNGS testing as part of the initial diagnostic workup for individuals with suspected infection becomes imperative [17].
We propose a RCT design to assess the clinical and diagnostic impact of plasma mNGS testing on patients with haematological malignancy and febrile neutropenia. We believe that this question and study design to be the highest yield to inform the clinical impact of this technology and suggest it as a starting point and framework for future studies in this field. This research effort would be well supported by the creation of a multicentre consortium group for clinical mNGS testing that can lead efforts on research standardization, study design, and implementation, as inspired by similar efforts in oncology [18] and suggested recently for infectious diseases [19].
Proposed RCT study design
Hypothesis: in immunocompromised individuals with haematological malignancies and febrile neutropenia, plasma mNGS performed near the onset of febrile neutropenia may lead to improved clinical outcomes and allow greater diagnostic yield compared with standard-of-care microbiology methods for the diagnosis of infections.
Setting: multicentre tertiary care hospitals where plasma mNGS is not routinely performed as part of microbiology testing.
Patient population: adults with haematological malignancies who have both neutropenia and fever. Patients will be excluded if they have received antibiotics for >24 hours (excluding prophylactic antibiotics) (Table 2). Furthermore, patients for whom plasma mNGS testing is ordered by the treating team in the control group outside of the study protocol will be excluded from primary analysis.
Table 2.
Patient enrolment criteria
| Inclusion criteria | Adult patient (≥18 y) Underlying diagnosis of haematological malignancy (acute leukaemia, chronic myeloid neoplasm, B, T, and/or NK cell lymphoma, histiocytic neoplasm, and multiple myeloma) Neutropenia (absolute neutrophil count <500 cells/μL) Fever documented single oral temperature ≥101 °F (38.3 °C), or a temperature of ≥100.4 °F (38 °C) for at least an hour |
| Exclusion criteria | Prior targeted antibiotic therapy for >24 h (excluding prophylactic antibiotics)a Adequate blood sample not available Failure to obtain informed consent Patient is not expected to survive >24 h beyond the time of potential study enrolment visit |
Culture recovery can be compromised as the length of antibiotic treatment increases.
Intervention: plasma mNGS was ordered within 24 hours of hospital admission or onset of fever for patients who are already hospitalized. Plasma mNGS results will be reported in the patient chart with a target turnaround time of ≤48 hours.
Control: standard microbiology testing harmonized across study sites including cultures, nucleic acid amplification tests, host-response tests, serology, and broad-range bacterial (16S) or fungal (18S/28S/ITS) sequencing performed on plasma, body fluids, and/or tissue.
Treatment approach: all participants will undergo management and receive treatment as directed by their treating medical team. Participants in the intervention group may have their treatment modified in response to results of plasma mNGS testing.
Primary outcome: all-cause 30-day mortality.
Secondary outcomes: diagnostic yield of clinically relevant organisms compared with a composite reference standard, time-to-optimal antimicrobial therapy, hospital length-of-stay, febrile neutropenia–attributable 30-day mortality, time from specimen collection to result, and cost-effectiveness analysis based on modelling [20]. When feasible, confirmatory testing will be performed on all samples with positive results from either conventional or mNGS testing to help adjudicate analytical accuracy for samples with discrepant results. Plasma mNGS results will be compared with all available clinical and confirmatory test results (analytical comparison) and to a reference diagnosis established by consensus by a panel of three independent physicians in medical microbiology and/or infectious diseases (clinical adjudication). Clinical outcomes and cost of care based on billing codes per episode will be compared between the intervention and control groups to establish cost-effectiveness.
Future research: participants enrolled in the study will undergo collection of an additional tube of whole blood for either immediate plasma mNGS (intervention group) or standard of care with storage of plasma (control group). Stored plasma from both groups will be a valuable resource for future research studies to further investigate the diagnostic yield compared with conventional results.
This patient population was selected due to the ongoing major unmet diagnostic need for identification of the aetiology of febrile neutropenia and associated high risk of poor clinical outcomes [21]. Additionally, several targeted cancer drugs and biotherapies are associated with increased risk of infections particularly when used in combination therapy regimens [22]. Hence, this patient population would greatly benefit from robust, rapid, and minimally invasive diagnostics to inform optimal clinical antimicrobial therapy and avert the need for more invasive sampling, including bronchoalveolar lavage and/or biopsy.
A key consideration in this RCT of a novel diagnostic assay is whether it is ethically justifiable to withhold testing from the participants in the control group given that testing is available without trial enrolment. Some participants may presume that more testing is intrinsically better because the information may lead to more accurate diagnosis. However, there may be risks to receiving additional test results, such as false-positive detections, leading to unnecessary treatment and follow-up procedures. The true clinical impact of plasma mNGS is unknown, and it is this state of equipoise that justifies the need for this study.
A RCT is the most desirable study design to investigate this research question as the randomization provides optimal control of potential confounders between the two groups. In this study design, we strived to establish a balance between meaningful primary and secondary outcomes, and pragmatic considerations of enrolment logistics and cost, to propose a realistic research plan. To inform our selection of the primary outcome of 30-day mortality, we considered different clinical outcomes and required sample sizes to achieve 80% power (Table 3). The numbers required varied markedly from 23 (diagnostic yield difference of 40% in favour of mNGS) to 13 495 individuals per group (mortality difference of 1%) and varied within each proposed outcome based on the difference estimate, all of which would influence the budget required to pursue the study. Investigators may consider focusing on alternate primary clinical outcomes when designing smaller studies. We also considered alternative study designs including assessment of plasma mNGS diagnostic yield relative to conventional testing alone paired with hypothetical clinical utility assessment and prospective studies based on comparison with a historical control group. Although more feasible and rapid to perform, these study designs lack the quality of evidence that is required to properly guide the use of plasma mNGS testing. Importantly, hypothetical utility may overestimate benefit given the complexity and scope of factors that influence a physician acting on a plasma mNGS test result. Finally, the potential for mNGS to reduce health care expenditures will be investigated as previously described [20].
Table 3.
Estimated required sample size by group for different scenarios
| Outcome category | Analysis type | Outcome | Proportion/estimate in the control group | Proportion/estimate range in the intervention group | Estimated range for delta (absolute values) | Estimated required sample size range per groupa |
|---|---|---|---|---|---|---|
| Diagnostic Clinical | Difference in proportions | Diagnostic yield | 30% | 50–70% | 20–40% | 23–93 |
| 30-d all-cause mortality | 10% | 7–9% | 1–3% | 1355–13 495 | ||
| Invasive diagnostic procedure required | 10% | 2–8% | 2–8% | 137–3213 | ||
| Unnecessary antimicrobial utilization | 10% | 15–25% | 5–15% | 100–686 | ||
| Time-to-event | Time-to-optimal antimicrobial management | 2.5 d | 1–2 d | 0.5–1.5 d | 24–360 | |
| Hospital length-of-stay | 16d | 11–15 d | 1–5 d | 178–6378 |
Sample size calculation based on two-sided t-test, alpha of 0.05, and power of 0.8.
Future directions
The proposed study focuses on a limited research question that we considered high yield, but that could not address the full range of remaining questions. The field of clinical metagenomics is burgeoning, and we propose several additional and complementary research questions that will require dedicated study (Table 4). Investigations of the utility of plasma mNGS testing in other patient populations and for other indications, or mNGS testing on other sample types, may use a similar study design to that proposed here. Although not available commercially at present, the utility of plasma mNGS testing that includes RNA should also be investigated as RNA viruses are otherwise missed by current approaches. Given the complexity and reach of these questions, a clinical metagenomics consortium is needed to establish a collaborative academic research infrastructure, lead multisite studies, and streamline efforts and resources towards the highest quality research to guide practice. Stakeholders across the spectrum—patients, providers, laboratories, and industry—will all benefit from a better understanding and optimized use of mNGS testing.
Table 4.
Additional research questions to investigate the utility of plasma mNGS testing
| Clinical research questions |
| How does test performance and impact vary by patient population? |
| What are the high- and low-yield clinical syndromes? |
| What are high- and low-yield organisms or organism categories (bacterial, fungal, viral, etc.)? |
| What is the ideal timing to pursue testing? |
| How is mNGS best used in conjunction with conventional microbiologic testing? |
| What is the utility of longitudinal testing? |
| Can mNGS be implemented as an appropriate tool for antimicrobial escalation and de-escalation? |
| Is there utility for quantitative mNGS to monitor response to therapy? |
| Testing research questions |
| What is optimal sample volume? |
| Does addition of cell-free RNA detection increase diagnostic yield and/or improve clinical outcomes? |
| Does a broad-range amplicon-based approach perform better than untargeted mNGS? |
| What is the comparative performance of different plasma mNGS assays? |
| What is the impact of optimized bioinformatics pipelines? |
| Should the mNGS analysis pipeline be tailored to syndrome of interest? |
| How do laboratory-developed plasma mNGS methods perform compared with commercial methods? |
mNGS, metagenomic next-generation sequencing.
Conflict of interest
Catherine A. Hogan reports consulting from Inflammatix. David C. Gaston reports receiving research reagents from Illumina Inc. and IDbyDNA Inc. and consulting from bioMerieux Inc. Patricia J. Simner reports grant from T2 Diagnostics and Affinity Biosensors; grant/consulting from OpGen Inc., BD Diagnostics, and Qiagen Sciences Inc.; consulting from Shionogi Inc., bioMerieux Inc., Entasis, and Merck & Co.; payment/honoraria from GenMark Dx, OpGen Inc, and BD Diagnostics; and having stock of GeneCapture. N. Esther Babady reports grant/consulting from Cantata-Bio; grant from Copan Diagnostics; and consulting from Roche, Bio-Rad, and Agena Biosciences. The remaining authors declare that they have no conflicts of interest.
Funding
This work was supported in part by the National Institute of Health/National Cancer Institute Cancer Center Support (grant number: P30 CA008748) to N.E.B.
References
- [1].Wilson MR, Naccache SN, Samayoa E, Biagtan M, Bashir H, Yu G, et al. Actionable diagnosis of neuroleptospirosis by next-generation sequencing. N Engl J Med 2014;370:2408–17. 10.1056/NEJMoa1401268. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [2].Simner PJ, Miller S, Carroll KC. Understanding the promises and hurdles of metagenomic next-generation sequencing as a diagnostic tool for infectious diseases. Clin Infect Dis 2018;66:778–88. 10.1093/cid/cix881. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [3].Grumaz S, Grumaz C, Vainshtein Y, Stevens P, Glanz K, Decker SO, et al. Enhanced performance of next-generation sequencing diagnostics compared with standard of care microbiological diagnostics in patients suffering from septic shock. Crit Care Med 2019;47:e394–402. 10.1097/CCM.0000000000003658. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [4].Benamu E, Gajurel K, Anderson JN, Lieb T, Gomez CA, Seng H, et al. Plasma microbial cell-free DNA next-generation sequencing in the diagnosis and management of febrile neutropenia. Clin Infect Dis 2022;74:1659–68. 10.1093/cid/ciab324. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [5].Schulz E, Grumaz S, Hatzl S, Gornicec M, Valentin T, Huber-Krassnitzer B, et al. Pathogen detection by metagenomic next-generation sequencing during neutropenic fever in patients with hematological malignancies. Open Forum Infect Dis 2022;9:ofac393. 10.1093/ofid/ofac393. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [6].Hill JA, Dalai SC, Hong DK, Ahmed AA, Ho C, Hollemon D, et al. Liquid biopsy for invasive mold infections in hematopoietic cell transplant recipients with pneumonia through next-generation sequencing of microbial cell-free DNA in plasma. Clin Infect Dis 2021;73:e3876–83. 10.1093/cid/ciaa1639. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [7].Rossoff J, Chaudhury S, Soneji M, Patel SJ, Kwon S, Armstrong A, et al. Noninvasive diagnosis of infection using plasma next-generation sequencing: a single-center experience. Open Forum Infect Dis 2019;6. 10.1093/ofid/ofz327. [DOI] [Google Scholar]
- [8].Niles DT, Wijetunge DSS, Palazzi DL, Singh IR, Revell PA. Plasma metagenomic next-generation sequencing assay for identifying pathogens: a retrospective review of test utilization in a large children’s hospital. J Clin Microbiol 2020;58. 10.1128/JCM.00794-20. [DOI] [Google Scholar]
- [9].Lee RA, Al Dhaheri F, Pollock NR, Sharma TS. Assessment of the clinical utility of plasma metagenomic next-generation sequencing in a pediatric hospital population. J Clin Microbiol 2020;58. 10.1128/JCM.00419-20. [DOI] [Google Scholar]
- [10].Hogan CA, Yang S, Garner OB, Green DA, Gomez CA, Dien Bard J, et al. Clinical impact of metagenomic next-generation sequencing of plasma cell-free DNA for the diagnosis of infectious diseases: a multicenter retrospective cohort study. Clin Infect Dis 2021;72:239–45. 10.1093/cid/ciaa035. [DOI] [PubMed] [Google Scholar]
- [11].Wilke J, Ramchandar N, Cannavino C, Pong A, Tremoulet A, Padua LT, et al. Clinical application of cell-free next-generation sequencing for infectious diseases at a tertiary children’s hospital. BMC Infect Dis 2021;21:552. 10.1186/s12879-021-06292-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [12].Shishido AA, Noe M, Saharia K, Luethy P. Clinical impact of a metagenomic microbial plasma cell-free DNA next-generation sequencing assay on treatment decisions: a single-center retrospective study. BMC Infect Dis 2022;22:372. 10.1186/s12879-022-07357-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [13].Niles DT, Revell PA, Ruderfer D, Marquez L, McNeil JC, Palazzi DL. Clinical impact of plasma metagenomic next-generation sequencing in a large pediatric cohort. Pediatr Infect Dis J 2022;41:166–71. 10.1097/INF.0000000000003395. [DOI] [PubMed] [Google Scholar]
- [14].Vijayvargiya P, Feri A, Mairey M, Rouillon C, Jeraldo PR, Esquer Garrigos Z, et al. Metagenomic shotgun sequencing of blood to identify bacteria and viruses in leukemic febrile neutropenia. PLoS One 2022;17:e0269405. 10.1371/journal.pone.0269405. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [15].Vissichelli NC, Morales MK, Kolipakkam B, Bryson A, Sabo RT, Toor AA. Cell-free next-generation sequencing impacts diagnosis and antimicrobial therapy in immunocompromised hosts: a retrospective study. Transpl Infect Dis 2023;25:e13954. 10.1111/tid.13954. [DOI] [PubMed] [Google Scholar]
- [16].Blauwkamp TA, Thair S, Rosen MJ, Blair L, Lindner MS, Vilfan ID, et al. Analytical and clinical validation of a microbial cell-free DNA sequencing test for infectious disease. Nat Microbiol 2019;4:663–74. 10.1038/s41564-018-0349-6. [DOI] [PubMed] [Google Scholar]
- [17].Hariton E, Locascio JJ. Randomised controlled trials - the gold standard for effectiveness research: study design: randomised controlled trials. BJOG 2018;125:1716. 10.1111/1471-0528.15199. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [18].European Organisation for Research and Treatment of Cancer, Strategic overview. https://www.eortc.org/strategic-overview/.
- [19].Gaston DC. Clinical metagenomics for infectious diseases: progress toward operational value. J Clin Microbiol 2023;61:e0126722. 10.1128/jcm.01267-22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [20].Fulton BD, Proudman DG, Sample HA, Gelfand JM, Chiu CY, DeRisi JL, et al. Exploratory analysis of the potential for advanced diagnostic testing to reduce healthcare expenditures of patients hospitalized with meningitis or encephalitis. PLoS One 2020;15:e0226895. 10.1371/journal.pone.0226895. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [21].Logan C, Koura D, Taplitz R. Updates in infection risk and management in acute leukemia. Hematol Am Soc Hematol Educ Program 2020;1:135–9. 10.1182/hematology.2020000098. [DOI] [Google Scholar]
- [22].Maschmeyer G, Bullinger L, Garcia-Vidal C, Herbrecht R, Maertens J, Menna P, et al. Infectious complications of targeted drugs and biotherapies in acute leukemia. Clinical practice guidelines by the European conference on infections in leukemia (ECIL), a joint venture of the European group for blood and marrow transplantation (EBMT), the European organization for research and treatment of cancer (EORTC), the international immunocompromised host society (ICHS) and the European leukemia net (ELN). Leukemia 2022;36:1215–26. 10.1038/s41375-022-01556-7. [DOI] [PMC free article] [PubMed] [Google Scholar]