Evaluation of Plasma Microbial Cell-Free DNA Sequencing to Predict Bloodstream Infection in Pediatric Patients With Relapsed or Refractory Cancer | Pediatric Cancer | JAMA Oncology | JAMA Network
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Figure 1.  Sensitivity of mcfDNA-seq for the Prediction or Diagnosis of BSI by Day Before the Onset of Infection
Sensitivity of mcfDNA-seq for the Prediction or Diagnosis of BSI by Day Before the Onset of Infection

Logical derivation was used to impute values for missing data. BSI indicates bloodstream infection; mcfDNA-seq, plasma microbial cell-free DNA sequencing. Error bars show 95% CIs. Overall specificity of mcfDNA-seq was 82% (95% CI, 66%-91%), and specificity for common BSI pathogens was 91% (95% CI, 76%-97%).

Figure 2.  Population Kinetics of Pathogen DNA by Day Before the Onset of BSI
Population Kinetics of Pathogen DNA by Day Before the Onset of BSI

Circles represent individual values, lines represent penalized B-spline smoothing curves for bloodstream infection (BSI) episodes, and bands represent 95% CIs. Orange dots indicate a gram-negative pathogen; dark blue dots, a gram-positive pathogen; brown dots, overlapping samples.

Table.  Characteristics of Study Participants
Characteristics of Study Participants
1.
Adler  A, Yaniv  I, Solter  E,  et al.  Catheter-associated bloodstream infections in pediatric hematology-oncology patients: factors associated with catheter removal and recurrence.   J Pediatr Hematol Oncol. 2006;28(1):23-28.PubMedGoogle Scholar
2.
Christensen  MS, Heyman  M, Möttönen  M, Zeller  B, Jonmundsson  G, Hasle  H; Nordic Society of Paediatric Haematology and Oncology (NOPHO).  Treatment-related death in childhood acute lymphoblastic leukaemia in the Nordic countries: 1992-2001.   Br J Haematol. 2005;131(1):50-58. doi:10.1111/j.1365-2141.2005.05736.xPubMedGoogle ScholarCrossref
3.
Inaba  H, Pei  D, Wolf  J,  et al.  Infection-related complications during treatment for childhood acute lymphoblastic leukemia.   Ann Oncol. 2017;28(2):386-392.PubMedGoogle ScholarCrossref
4.
Cheung  YT, Eskind  A, Inaba  H,  et al.  Association of bacteremic sepsis with long-term neurocognitive dysfunction in pediatric patients with acute lymphoblastic leukemia.   JAMA Pediatr. 2018;172(11):1092-1095. doi:10.1001/jamapediatrics.2018.2500PubMedGoogle ScholarCrossref
5.
Finch  ER, Janke  LJ, Smith  CA,  et al.  Bloodstream infections exacerbate incidence and severity of symptomatic glucocorticoid-induced osteonecrosis.   Pediatr Blood Cancer. 2019;66(6):e27669. doi:10.1002/pbc.27669PubMedGoogle Scholar
6.
Goldstein  B, Giroir  B, Randolph  A; International Consensus Conference on Pediatric Sepsis.  International pediatric sepsis consensus conference: definitions for sepsis and organ dysfunction in pediatrics.   Pediatr Crit Care Med. 2005;6(1):2-8. doi:10.1097/01.PCC.0000149131.72248.E6PubMedGoogle ScholarCrossref
7.
Flygare  S, Simmon  K, Miller  C,  et al.  Taxonomer: an interactive metagenomics analysis portal for universal pathogen detection and host mRNA expression profiling.   Genome Biol. 2016;17(1):111. doi:10.1186/s13059-016-0969-1PubMedGoogle ScholarCrossref
8.
Fung  M, Zompi  S, Seng  H,  et al.  Plasma cell-free DNA next-generation sequencing to diagnose and monitor infections in allogeneic hematopoietic stem cell transplant patients.   Open Forum Infect Dis. 2018;5(12):ofy301. doi:10.1093/ofid/ofy301PubMedGoogle Scholar
9.
Ivy  MI, Thoendel  MJ, Jeraldo  PR,  et al.  Direct detection and identification of prosthetic joint infection pathogens in synovial fluid by metagenomic shotgun sequencing.   J Clin Microbiol. 2018;56(9):e00402-18. doi:10.1128/JCM.00402-18PubMedGoogle Scholar
10.
Centers for Disease Control and Prevention. Bloodstream infection event (central line-associated bloodstream infection and non-central line associated bloodstream infection). http://www.cdc.gov/nhsn/PDFs/pscManual/4PSC_CLABScurrent.pdf. Accessed February 4, 2019.
11.
Blauwkamp  TA, Thair  S, Rosen  MJ,  et al.  Analytical and clinical validation of a microbial cell-free DNA sequencing test for infectious disease.   Nat Microbiol. 2019;4(4):663-674. doi:10.1038/s41564-018-0349-6PubMedGoogle ScholarCrossref
12.
Simon  R.  Optimal two-stage designs for phase II clinical trials.   Control Clin Trials. 1989;10(1):1-10. doi:10.1016/0197-2456(89)90015-9PubMedGoogle ScholarCrossref
13.
Gaur  AH, Bundy  DG, Werner  EJ,  et al; Children’s Hospital Association Childhood Cancer & Blood Disorders Network (CCBDN).  A prospective, holistic, multicenter approach to tracking and understanding bloodstream infections in pediatric hematology-oncology patients.   Infect Control Hosp Epidemiol. 2017;38(6):690-696. doi:10.1017/ice.2017.57PubMedGoogle ScholarCrossref
14.
Gafter-Gvili  A, Fraser  A, Paul  M,  et al.  Antibiotic prophylaxis for bacterial infections in afebrile neutropenic patients following chemotherapy.   Cochrane Database Syst Rev. 2012;1:CD004386. doi:10.1002/14651858.CD004386.pub3PubMedGoogle Scholar
15.
Wolf  J, Tang  L, Flynn  PM,  et al.  Levofloxacin prophylaxis during induction therapy for pediatric acute lymphoblastic leukemia.   Clin Infect Dis. 2017;65(11):1790-1798. doi:10.1093/cid/cix644PubMedGoogle ScholarCrossref
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    Brief Report
    December 19, 2019

    Evaluation of Plasma Microbial Cell-Free DNA Sequencing to Predict Bloodstream Infection in Pediatric Patients With Relapsed or Refractory Cancer

    Author Affiliations
    • 1Department of Infectious Diseases, St Jude Children's Research Hospital, Memphis, Tennessee
    • 2Department of Oncology, St Jude Children's Research Hospital, Memphis, Tennessee
    • 3Karius Inc, Redwood City, California
    • 4Department of Pathology, St Jude Children's Research Hospital, Memphis, Tennessee
    • 5Department of Pediatrics, The University of Tennessee Health Science Center, Memphis
    • 6Department of Biostatistics, St Jude Children's Research Hospital, Memphis, Tennessee
    • 7Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
    • 8Department of Computational Biology, St Jude Children's Research Hospital, Memphis, Tennessee
    JAMA Oncol. 2020;6(4):552-556. doi:10.1001/jamaoncol.2019.4120
    Key Points

    Question  Might plasma microbial cell-free DNA sequencing (mcfDNA-seq) predict bloodstream infection (BSI) in immunocompromised patients days before the onset of attributable symptoms?

    Findings  This pilot cohort study included 47 pediatric patients with relapsed or refractory cancer. The causative pathogen was identified by mcfDNA-seq in the 3 days before onset of BSI in 12 of 16 episodes; of 33 negative control samples collected from the same patient population, mcfDNA-seq was negative in 27 and identified no common pathogens in 30.

    Meaning  In patients with imminent BSI, it appears that mcfDNA-seq can identify clinically relevant pathogens days before onset of attributable symptoms.

    Abstract

    Importance  Bloodstream infection (BSI) is a common, life-threatening complication of treatment for cancer. Predicting BSI before onset of clinical symptoms would enable preemptive therapy, but there is no reliable screening test.

    Objective  To estimate sensitivity and specificity of plasma microbial cell-free DNA sequencing (mcfDNA-seq) for predicting BSI in patients at high risk of life-threatening infection.

    Design, Setting, and Participants  A prospective pilot cohort study of mcfDNA-seq for predicting BSI in pediatric patients (<25 years of age) with relapsed or refractory cancers at St Jude Children’s Research Hospital, a specialist quaternary pediatric hematology-oncology referral center. Remnant clinical blood samples were collected during chemotherapy and hematopoietic cell transplantation. Samples collected during the 7 days before and at onset of BSI episodes, along with negative control samples from study participants, underwent blinded testing using a mcfDNA-seq test in a Clinical Laboratory Improvement Amendments/College of American Pathologists–approved laboratory.

    Main Outcomes and Measures  The primary outcomes were sensitivity of mcfDNA-seq for detecting a BSI pathogen during the 3 days before BSI onset and specificity of mcfDNA-seq in the absence of fever or infection in the preceding or subsequent 7 days.

    Results  Between August 9, 2017, and June 4, 2018, 47 participants (27 [57%] male; median age [IQR], 10 [5-14] years) were enrolled; 19 BSI episodes occurred in 12 participants, and predictive samples were available for 16 episodes, including 15 bacterial BSI episodes. In the 3 days before the onset of infection, predictive sensitivity of mcfDNA-seq was 75% for all BSIs (12 of 16; 95% CI, 51%-90%) and 80% (12 of 15; 95% CI, 55%-93%) for bacterial BSIs. The specificity of mcfDNA-seq, evaluated on 33 negative control samples from enrolled participants, was 82% (27 of 33; 95% CI, 66%-91%) for any bacterial or fungal organism and 91% (30 of 33; 95% CI, 76%-97%) for any common BSI pathogen, and the concentration of pathogen DNA was lower in control than predictive samples.

    Conclusions and Relevance  A clinically relevant pathogen can be identified by mcfDNA-seq days before the onset of BSI in a majority of episodes, potentially enabling preemptive treatment. Clinical application appears feasible pending further study.

    Trial Registration  ClinicalTrials.gov identifier: NCT03226158

    Introduction

    Serious infections, especially bloodstream infections (BSIs), are among the most important complications affecting patients receiving treatment for cancer. An incident of BSI-related sepsis can cause death,1-3 multiorgan failure, and neurocognitive damage.4-6 Although a predictive test that enables preemptive, pathogen-directed therapy could reduce BSI-related morbidity and mortality, no validated test is available. Novel metagenomic microbiologic diagnostics, including plasma microbial cell-free DNA sequencing (mcfDNA-seq), show promise as diagnostic tests,7-9 but none has yet been systematically evaluated for BSI prediction.8 This prospective pilot study tested the novel hypothesis that mcfDNA-seq can identify a causative pathogen in the days before BSI develops.

    Methods
    Study Design and Ethics

    This study was approved by the St Jude Children’s Research Hospital Institutional Review Board and followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.

    Participants

    Participants were pediatric patients receiving treatment for relapsed or refractory cancer at St Jude Children’s Research Hospital. Informed consent and assent for participation were obtained. Participation continued until death, loss to follow-up, transfer of care, resolution of gastrointestinal graft-vs-host disease, 30 days after hematopoietic cell transplantation, or participant request.

    Clinical Data and Definitions

    The Centers for Disease Control and Prevention’s National Healthcare Safety Network definitions were used for BSI, with onset defined at the time of collection of the first positive blood culture.10 Institutional practice is to collect blood cultures in all episodes of fever or suspected infection. The a priori predictive period comprised the 3 days before BSI onset (eFigure 1 in Supplement 1). Negative control samples were obtained from participants on a day for which no fever or infection was documented within the prior or subsequent 7 days. Participants could contribute multiple BSI and negative control episodes.

    Laboratory Procedures

    Leftover blood was available from most samples collected for clinical hematology studies and was stored at 4° C until processed to plasma and frozen. Plasma mcfDNA-seq was performed in a Clinical Laboratory Improvement Amendments/College of American Pathologists–accredited laboratory (Karius Inc, Redwood City, California) as previously described.11 Briefly, cell-free DNA was extracted, DNA libraries were prepared, and sequencing was performed. Nonhuman sequencing reads were aligned to a curated pathogen database, and the concentration of pathogen-specific DNA fragments for each organism was reported in molecules per microliter (MPM). Available samples collected up to 7 days before each BSI episode were tested alongside 2 negative control samples per episode. The laboratory was blinded until results were finalized.

    Power and Statistical Considerations

    The Simon 2-stage design was used, with minimal acceptable sensitivity of 30% and favorable sensitivity of 50%.12 This pilot reports the preplanned first stage analysis.

    Predictive sensitivity was estimated for the 3-day predictive period and for each of the 7 days before BSI onset. Diagnostic sensitivity was estimated from samples collected on day of BSI onset. Predictive sensitivity was defined as the proportion of episodes for which mcfDNA-seq identified the same organism subsequently identified in blood culture. Logical derivation was used to impute missing values for sensitivity (eFigure 2 in Supplement 1). Overall sensitivity was estimated for different models of testing frequency.

    Specificity was defined as the proportion of negative control samples for which no bacterial or fungal organisms were identified by mcfDNA-seq. Specificity for common BSI pathogens, genera comprising 1% or more of central line–associated BSI in the Children’s Hospital Association Childhood Cancer & Blood Disorders Network BSI database,13 was an additional ad hoc measure (eTable 1 in Supplement 1). A third-degree penalized B-spline curve was used to analyze temporal trends in pathogen-specific DNA concentration. Data analysis was performed using SAS, version 9.4 (SAS Institute Inc).

    Results
    Population and BSI Episodes

    Between August 9, 2017, and June 4, 2018, 47 participants were enrolled (Table). Nineteen BSI episodes occurred in 12 participants (3.3 per 1000 patient-days; 95% CI, 2-5.2 per 1000 patient days) (eTable 2 in Supplement 1). Eight episodes (42%) were associated with signs of sepsis, including hypotension (n = 3), requirement for urgent intervention (n = 5), or intensive care unit admission (n = 2). A predictive period sample was available in 16 episodes. Broad-spectrum antibacterial therapy was administered during the prior week in 17 of 19 (89%) episodes, so a comparative subgroup analysis of the effect of pretreatment was not feasible.

    Sensitivity of mcfDNA-seq

    The BSI pathogen was identified by mcfDNA-seq during the predictive period in 12 of 16 BSI episodes (predictive sensitivity, 75%; 95% CI, 51%-90%) and in 12 of 15 bacterial BSI episodes (predictive sensitivity, 80%; 95% CI, 55%-93%). Diagnostic sensitivity was 83% (15 of 18; 95% CI, 61%-94%); diagnostic sensitivity for bacterial BSI was 88% (15 of 17; 95% CI, 66%-97%). Blood cultures were collected during the week before BSI in 10 episodes (eTable 4 in Supplement 1).

    Daily predictive sensitivity of mcfDNA-seq for BSI is shown in Figure 1 and eFigure 4 in Supplement 1. Pathogen-specific DNA concentrations typically increased in the days approaching BSI onset (Figure 2 and eTable 3 and eFigure 3 in Supplement 1). Assuming same-day results, projected median predictive sensitivity for bacterial BSI was 71% for twice-weekly testing (eTable 5 and eFigures 5 and 6 in Supplement 1).

    Specificity of mcfDNA-seq

    Thirty-three negative control samples obtained from study participants underwent mcfDNA-seq testing. (eTable 6 in Supplement 1); 27 of 33 had no bacterial or fungal organism identified (specificity, 82%; 95% CI, 66%-91%) and 30 of 33 had no common BSI pathogen identified (specificity, 91%; 95% CI, 76%-97%). The concentration of bacterial DNA in negative control samples was typically lower than in predictive samples, with a maximum of 609 MPM for any bacteria and a maximum of 112 MPM for common BSI pathogens compared with higher than 609 MPM in 11 of 16 predictive episodes (69%; 95% CI, 44%-86%) and higher than 112 MPM in 12 of 16 episodes (75%; 95% CI, 51%-90%).

    Additional bacteria, including common pathogens, were identified by mcfDNA-seq in many samples collected before BSI episodes (eTable 7 in Supplement 1). We attempted to assess the clinical significance of these, but all identified bacteria were potentially susceptible to empirical antimicrobial therapy, so treatment failure associated with untreated organisms was not evaluable. Fungal DNA was also identified by mcfDNA-seq in 2 participants with and 1 participant without evidence of invasive fungal infection.

    Discussion

    This prospective pilot study shows that mcfDNA-seq has the potential to predict most episodes of BSI before onset in high-risk pediatric cancer patients. The estimated predictive sensitivity of 75% (95% CI, 51%-90%) exceeds the predefined favorable value of 50%, which was chosen because it represents the approximate efficacy of antibacterial prophylaxis.14,15 In addition to BSI organisms, viruses and invasive fungi that infect immunocompromised patients were also detected. Further studies are needed to determine whether mcfDNA-seq can reliably predict infection with nonbacterial pathogens in this patient population.

    Limitations

    This study does have important limitations. A specificity of 82% would make mcfDNA-seq screening impractical because of the high false-positive rate; specificity might be improved by excluding uncommon BSI pathogens, applying quantitative break points, or performing short interval repeat testing.7,8 Return of mcfDNA-seq results in a time frame that allows implementation of screening may not yet be feasible in most centers. Technological and practical advances will be required to reduce turnaround time considerably and might also improve sensitivity to predict BSI even earlier. Application of mcfDNA-seq screening to febrile neutropenia and clinically documented and other microbiologically documented infections was not evaluated in this study and will be important for future studies. Once these challenges are overcome, implementation of predictive mcfDNA-seq has the potential to significantly reduce treatment-related morbidity and mortality of pediatric cancer patients and could potentially be applied to other immunocompromised patient populations.

    Conclusions

    We provide to our knowledge the first evidence that mcfDNA-seq can predict infections in approximately 75% of relapsed pediatric cancer patients with impending BSI with a specificity of more than 80%. Strategic implementation and continued technological advancements may enable the use of mcfDNA-seq to guide preemptive therapy and reduce infection-related morbidity and mortality in high-risk immunocompromised patients.

    Back to top
    Article Information

    Accepted for Publication: July 28, 2019.

    Published Online: December 19, 2019. doi:10.1001/jamaoncol.2019.4120

    Correction: This article was corrected on February 27, 2020, to change to CC-BY-NC-ND open access status.

    Open Access: This is an open access article distributed under the terms of the CC-BY-NC-ND License. © 2019 Goggin KP et al. JAMA Oncology.

    Corresponding Authors: Joshua Wolf, MBBS, PhD, FRACP, Department of Infectious Diseases, St Jude Children's Research Hospital, 262 Danny Thomas Pl, Mailstop 320, Memphis, TN 38105 (joshua.wolf@stjude.org) and Charles Gawad, MD, PhD, Department of Oncology, St Jude Children's Research Hospital, 262 Danny Thomas Pl, Mailstop 1260, Memphis, TN 38105 (charles.gawad@stjude.org).

    Author Contributions: Drs Wolf and Gawad had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Wolf and Gawad contributed equally to the study.

    Concept and design: Goggin, Hong, Wolf, Gawad.

    Acquisition, analysis, or interpretation of data: All authors.

    Drafting of the manuscript: Goggin, Gonzalez-Pena, Inaba, Hong, Natarajan, Kuenzinger, Sun, Wolf, Gawad.

    Critical revision of the manuscript for important intellectual content: Goggin, Allison, Hong, Ahmed, Hollemon, Mahmud, Youssef, Brenner, Maron, Choi, Rubnitz, Tang, Wolf, Gawad.

    Statistical analysis: Sun, Tang, Wolf.

    Obtained funding: Wolf, Gawad.

    Administrative, technical, or material support: Gonzalez-Pena, Inaba, Allison, Hong, Hollemon, Natarajan, Brenner, Choi, Rubnitz, Wolf, Gawad.

    Supervision: Wolf, Gawad.

    Conflict of Interest Disclosures: Dr Ahmed reports being an employee of Karius Inc. Dr Brenner reports receiving nonfinancial support from Karius Inc and grants from the National Cancer Institute. Dr Gawad reports receiving nonfinancial support from Karius Inc; support from a Career Award for Medical Scientists from the Burroughs Wellcome Fund, a Scholar Award from the Hyundai Foundation for Pediatric Cancer Research, and a Special Fellow award from the Leukemia & Lymphoma Society; and developmental funds from the St Jude Children’s Research Hospital Cancer Center. Ms Hollemon reports being an employee of Karius Inc. Dr Hong reports receiving personal fees as an employee of Karius Inc. Dr Inaba reports receiving nonfinancial support from Karius Inc. Dr Wolf reports receiving nonfinancial support from Karius Inc and research support from Merck, Astellas, Cempra, and CareFusion. No other disclosures were reported.

    Funding/Support: This study was supported by the American Lebanese Syrian Associated Charities and Karius Inc.

    Role of the Funder/Sponsor: The American Lebanese Syrian Associated Charities had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Karius Inc had no role in the design or conduct of the study. Representatives of Karius Inc were involved in sample processing; management, analysis and interpretation of the data; preparation, review and approval of the manuscript; and decision to submit the manuscript for publication.

    Additional Contributions: We thank Keith Laycock, PhD, for editorial support, Jose Ferrolino, MD, for database support, and Kristen Branum, BS, for advice about study design and conduct, as well as Aditya Gaur, MD, and the Children’s Hospital Association Childhood Cancer & Blood Disorders Network for directly providing a list of organisms from blood cultures from their bloodstream infections database to help develop a list of common bloodstream infections pathogens in children with cancer. Dr Laycock, Dr Ferrolino, and Ms Branum were compensated by St Jude for their contributions.

    References
    1.
    Adler  A, Yaniv  I, Solter  E,  et al.  Catheter-associated bloodstream infections in pediatric hematology-oncology patients: factors associated with catheter removal and recurrence.   J Pediatr Hematol Oncol. 2006;28(1):23-28.PubMedGoogle Scholar
    2.
    Christensen  MS, Heyman  M, Möttönen  M, Zeller  B, Jonmundsson  G, Hasle  H; Nordic Society of Paediatric Haematology and Oncology (NOPHO).  Treatment-related death in childhood acute lymphoblastic leukaemia in the Nordic countries: 1992-2001.   Br J Haematol. 2005;131(1):50-58. doi:10.1111/j.1365-2141.2005.05736.xPubMedGoogle ScholarCrossref
    3.
    Inaba  H, Pei  D, Wolf  J,  et al.  Infection-related complications during treatment for childhood acute lymphoblastic leukemia.   Ann Oncol. 2017;28(2):386-392.PubMedGoogle ScholarCrossref
    4.
    Cheung  YT, Eskind  A, Inaba  H,  et al.  Association of bacteremic sepsis with long-term neurocognitive dysfunction in pediatric patients with acute lymphoblastic leukemia.   JAMA Pediatr. 2018;172(11):1092-1095. doi:10.1001/jamapediatrics.2018.2500PubMedGoogle ScholarCrossref
    5.
    Finch  ER, Janke  LJ, Smith  CA,  et al.  Bloodstream infections exacerbate incidence and severity of symptomatic glucocorticoid-induced osteonecrosis.   Pediatr Blood Cancer. 2019;66(6):e27669. doi:10.1002/pbc.27669PubMedGoogle Scholar
    6.
    Goldstein  B, Giroir  B, Randolph  A; International Consensus Conference on Pediatric Sepsis.  International pediatric sepsis consensus conference: definitions for sepsis and organ dysfunction in pediatrics.   Pediatr Crit Care Med. 2005;6(1):2-8. doi:10.1097/01.PCC.0000149131.72248.E6PubMedGoogle ScholarCrossref
    7.
    Flygare  S, Simmon  K, Miller  C,  et al.  Taxonomer: an interactive metagenomics analysis portal for universal pathogen detection and host mRNA expression profiling.   Genome Biol. 2016;17(1):111. doi:10.1186/s13059-016-0969-1PubMedGoogle ScholarCrossref
    8.
    Fung  M, Zompi  S, Seng  H,  et al.  Plasma cell-free DNA next-generation sequencing to diagnose and monitor infections in allogeneic hematopoietic stem cell transplant patients.   Open Forum Infect Dis. 2018;5(12):ofy301. doi:10.1093/ofid/ofy301PubMedGoogle Scholar
    9.
    Ivy  MI, Thoendel  MJ, Jeraldo  PR,  et al.  Direct detection and identification of prosthetic joint infection pathogens in synovial fluid by metagenomic shotgun sequencing.   J Clin Microbiol. 2018;56(9):e00402-18. doi:10.1128/JCM.00402-18PubMedGoogle Scholar
    10.
    Centers for Disease Control and Prevention. Bloodstream infection event (central line-associated bloodstream infection and non-central line associated bloodstream infection). http://www.cdc.gov/nhsn/PDFs/pscManual/4PSC_CLABScurrent.pdf. Accessed February 4, 2019.
    11.
    Blauwkamp  TA, Thair  S, Rosen  MJ,  et al.  Analytical and clinical validation of a microbial cell-free DNA sequencing test for infectious disease.   Nat Microbiol. 2019;4(4):663-674. doi:10.1038/s41564-018-0349-6PubMedGoogle ScholarCrossref
    12.
    Simon  R.  Optimal two-stage designs for phase II clinical trials.   Control Clin Trials. 1989;10(1):1-10. doi:10.1016/0197-2456(89)90015-9PubMedGoogle ScholarCrossref
    13.
    Gaur  AH, Bundy  DG, Werner  EJ,  et al; Children’s Hospital Association Childhood Cancer & Blood Disorders Network (CCBDN).  A prospective, holistic, multicenter approach to tracking and understanding bloodstream infections in pediatric hematology-oncology patients.   Infect Control Hosp Epidemiol. 2017;38(6):690-696. doi:10.1017/ice.2017.57PubMedGoogle ScholarCrossref
    14.
    Gafter-Gvili  A, Fraser  A, Paul  M,  et al.  Antibiotic prophylaxis for bacterial infections in afebrile neutropenic patients following chemotherapy.   Cochrane Database Syst Rev. 2012;1:CD004386. doi:10.1002/14651858.CD004386.pub3PubMedGoogle Scholar
    15.
    Wolf  J, Tang  L, Flynn  PM,  et al.  Levofloxacin prophylaxis during induction therapy for pediatric acute lymphoblastic leukemia.   Clin Infect Dis. 2017;65(11):1790-1798. doi:10.1093/cid/cix644PubMedGoogle ScholarCrossref
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