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medRxiv preprint doi: https://doi.org/10.1101/2023.01.12.22280967; this version posted January 14, 2023. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
It is made available under a CC-BY-ND 4.0 International license .
Diagnostic value of plasma microbial cell-free DNA sequencing in hematopoietic
stem cell transplant recipients: A systematic review and meta-analysis
Nicholas Degner, MD1, Nicole C. Vissichelli, MD2, David M. Berman, DO1, Matt Smollin,
PharmD1, and Megan K. Morales, MD2
1. Karius, Inc.
2. Virginia Commonwealth University Health System, Department of Medicine, Division of
Infectious Diseases
Corresponding author: Nicole C. Vissichelli, MD
Nicole.vissichelli@vcuhealth.org
PO BOX 980049, Richmond, VA 23298
Phone: 804-828-9711
Fax: 804-828-3097
Author contributions: Conceptualization of the paper by all listed authors; ND performed the
literature review and statistical analysis; ND, NV, MM and DB reviewed published cases for data
extraction; writing by ND, NV, MM; manuscript review and editing by all authors.
Declaration of Interest: ND, DB, and MS are employees of Karius, Inc. DB is a consultant for
Precision Health Lab. MM is a paid member of the Karius speaker bureau and a consultant for
Cidara Therapeutics. NV has no conflicts of interest to disclose.
Keywords: Karius, cell-free DNA sequencing, stem cell transplant, bone marrow transplant
Short title: plasma microbial cell-free DNA sequencing in HSCT recipients
NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.medRxiv preprint doi: https://doi.org/10.1101/2023.01.12.22280967; this version posted January 14, 2023. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
It is made available under a CC-BY-ND 4.0 International license .
Abstract:
Hematopoietic stem cell transplant (HSCT) recipients are at increased risk for a wide spectrum
of infections, including opportunistic infections with atypical presentations. Diagnosis can be
challenging and often requires extensive testing and invasive procedures. Sequencing of plasma
microbial cell-free DNA (mcfDNA) allows non-invasive untargeted detections of human
pathogens, making this modality appealing for this patient population.
The purpose of this study was to perform a meta-analysis to evaluate the diagnostic value of
sequencing of plasma mcfDNA for infections in HSCT recipients. We searched for relevant
articles in BASE, PubMed, and ClinicalTrials.gov from January 1996 to November 2022. Studies
were eligible for inclusion if they assessed the diagnostic performance of sequencing of plasma
mcfDNA and included HSCT recipients with sufficient data to assign plasma mcfDNA test results
as true positive, true negative, false positive, or false negative, which were used to calculate
diagnostic test accuracy.
A total of 6 studies and 69 patients were included. All included studies were published in 2019
or later and were conducted in the United States. Three studies were exclusively pediatric, two
exclusively adult, and one a mixture of both adult and pediatric patients. The pooled sensitivity
was 0.90 (95% CI 0.71-0.97) and the pooled specificity was 0.75 (0.49-0.90).
The high pooled diagnostic odds ratio suggests that sequencing of plasma mcfDNA may have a
unique diagnostic role in HSCT recipients. Its high sensitivity and capability to detect a broad
array of pathogens makes it a promising adjunct to traditional diagnostic testing.medRxiv preprint doi: https://doi.org/10.1101/2023.01.12.22280967; this version posted January 14, 2023. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
It is made available under a CC-BY-ND 4.0 International license .
Introduction
Hematopoietic stem cell transplant (HSCT) recipients experience periods of profound deficiency
in both innate and adaptive immunity putting them at risk for a wide spectrum of infections,
including organisms which are not normally pathogenic in immunocompetent hosts (1). The
epidemiology of infections after HSCT changes with time and immune system recovery and is
generally divided up into three periods; (1) Pre-engraftment: from transplantation to neutrophil
recovery (typically day 20 to day 30 post-transplant), in which bacterial infections and
candidiasis are most common, followed by (2) early post-engraftment (from engraftment to day
100) in which fungi become more common, and finally (3) late post-engraftment (after day 100)
in which a patient is at risk for encapsulated bacteria, herpes viruses, and fungi (1).
Yet there is considerable overlap in the infectious risks and at any time patients may become
infected from bacteria, fungi, parasites, or viruses. Furthermore, without a properly functioning
immune system, patients often have atypical or minimal symptoms in response to infection.
Given this wide array of potential pathogens and atypical presentations, the differential
diagnosis for infection in HSCT recipients is broad and diagnostically challenging, often requiring
radiographic imaging to localize the source of fever, an extensive battery of tests, and invasive
procedures. While invasive procedures such as bronchoscopy or biopsy are often necessary to
diagnose deep seated infections, or those caused by fastidious organisms, there are many
patients in which such tests are non-diagnostic or are unable to be performed due to
procedural risk.(2) Non-invasive diagnostic tests such as cultures, antigens, plasma polymerase
chain reaction (PCR) and antibody testing are often used to assist in making the diagnosis of
many pathogens encountered in HSCT recipients. Fungal biomarkers such as 1,3-β-D-glucan and
galactomannan antigen can assist in the diagnosis of invasive fungal infections, however these
tests have limited specificity and sensitivity, which rapidly decreases with just 48 hours of
antifungal therapy.(3)
Sequencing of plasma microbial cell-free DNA (mcfDNA), in which fragments of genomic DNA
released from both human and microorganism cellular breakdown present in plasma are
sequenced and matched against a database for identification, has allowed breakthroughs in the
non-invasive diagnosis of cancer, fetal abnormalities, and allograft rejection. Given the
untargeted nature of sequencing, this modality is appealing for populations at risk for a wide
variety of infections and who manifest atypical presentations, leaving a wide differential, such
as HSCT recipients. Sequencing of plasma mcfDNA has been shown to have higher yield in
identifying clinically relevant pathogens in immunocompromised in comparison to
immunocompetent hosts (61% versus 35%) with a higher yield compared to traditional
methods from samples obtained invasively.(4) However, there have been limited studies that
exclusively focus on HSCT recipients. To better understand the performance of plasma mcfDNA
sequencing in diagnosing infections in HSCT recipients, we performed a systematic review and
meta-analysis of the existing literature.
MethodsmedRxiv preprint doi: https://doi.org/10.1101/2023.01.12.22280967; this version posted January 14, 2023. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
It is made available under a CC-BY-ND 4.0 International license .
Literature Search
We searched BASE, PubMed, and ClinicalTrials.gov from January 1996 to November 2022. We
used the following search terms: sequencing, microbial cell-free DNA, infection, pathogens,
infectious diseases, diagnostics, liquid biopsy, immunocompromised, cancer, hematology,
hematopoietic cell transplant. We also contacted the corresponding authors by e-mail
requesting unpublished or individual HSCT patient level data when not available in the
publication. Studies were excluded if no response was received. All analyses of this systemic
review were based on previous published studies, so no ethical approval or patient consent is
required.
Inclusion and Exclusion Criteria
Studies were eligible for inclusion if they: assessed the diagnostic performance of sequencing of
plasma mcfDNA in HSCT recipients and included individual level data that allowed abstraction
of HSCT cases with sufficient data to construct a two-by-two table of true positives (TP), false
negatives (FN), false positives (FP), and true negatives (TN). The search was limited to English
language publications. The exclusion criteria were: animals; case reports and case series;
duplicate articles; articles focused on only one particular set of micro-organisms (i.e., only
viruses or only fungi, etc.). Individual cases were excluded if the final diagnosis was an RNA
virus given that this would not be expected to be detected in sequencing plasma mcfDNA.
Data Extraction
Included studies had the following data extracted: author names, year published, mean age and
range in age of cohort, sample size, geographical region, medical history, study author
classification of diagnostic test results, results of standard of care microbiologic testing, and
results of plasma mcfDNA sequencing.
Diagnostic Result Classification
Extracted results were classified in the following way: (1) if the paper provided a diagnostic test
classification (true-positive, false-positive, true-negative, or false-negative) for each HSCT
recipient, that classification was used; (2) if the paper did not provide a test classification, we
used test concordance (whether both explained the clinical syndrome for method 1, or were
present and responsible pathogens in method 2); (3) if the publication did not provide a test
classification and there was test discordance, then clinical relevance or impact as provided by
the primary study authors was used according to the following schema:
Positive Negative
True SOC negative, KT positive and Both SOC testing and KT
authors deemed the KT negative
detection clinically relevant
False SOC testing negative, KT SOC testing positive, KT
positive but deemed clinically negativemedRxiv preprint doi: https://doi.org/10.1101/2023.01.12.22280967; this version posted January 14, 2023. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
It is made available under a CC-BY-ND 4.0 International license .
irrelevant
SOC = Standard of care
KT = Karius test
Justification for these cases in these tables is provided in the supplementary material. The
accuracy of the data was verified by each study author. If discrepancies arose, all authors who
are board-certified infectious diseases specialists participated in a discussion that led to a
consensus. Study quality and risk of bias was determined with QUADAS-2 (quality assessment
of diagnostic accuracy studies) (5).
Diagnostic Accuracy Measures, Synthesis of Results, and Meta-analysis
Given the absence of a reference gold standard for plasma mcfDNA, we calculated positive
percent agreement (PPA; agreement between mNGS test and infection diagnosis determined
by the methodology above) and negative percent agreement (NPA; agreement between
negative mNGS test and infection diagnosis determined by the methodology above) instead of
sensitivity and specificity. PPA is calculated the same as sensitivity (TP/(TP+FN)) and NPA is
calculated the same as specificity (TN/(TN+FP)).
Two methods were utilized to classify plasma mcfDNA results in which more than one organism
was reported, in accordance with the methodology previously used in Lee et al (6). In Method
1, which was considered the primary analysis, the test was considered as one test even if
multiple organisms were detected. If an organism considered a TP was detected the test result
was considered a true positive. In some instances, FP are identified as well, but by method 1,
the test would be classified as a TP based on identification of a clinically relevant organism even
if clinically irrelevant organism(s) were also identified. Therefore, this method does not fully
account for the detection of additional potentially clinically irrelevant organisms. To account for
this, method 2 was employed where each organism classification result is assessed
independently.
Statistical analysis was performed using the STATA software (version 17.0, Stata Corporation,
TX) with the metadta package and included diagnostic performance statistics, SROC plot, test of
heterogeneity between studies, and subgroup analyses further specified in supplemental
methodology (Supplemental Materials) (7). PRISMA guidelines were followed throughout the
study protocol.
RESULTS
Literature Search
The results of the literature search are summarized in Figure 1. A total of 440 records were
retrieved from initial search on electronic databases. In total, 48 records were removed as
duplicates by computer. After screening, 392 articles were excluded. This resulted in 15 full
texts examined for eligibility for inclusion, of which six were included and nine were excluded:medRxiv preprint doi: https://doi.org/10.1101/2023.01.12.22280967; this version posted January 14, 2023. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
It is made available under a CC-BY-ND 4.0 International license .
six did not contain individual level data and three focused on one group of organisms only
(Table 1).
Characteristics of Included Studies
The main characteristics of included studies are presented in Table 1. In total 6 studies were
analyzed, which included a total of 69 patients. All included studies were published in 2019 or
later and were conducted in the United States. Three studies were exclusively pediatric, two
exclusively adult, and one a mixture of both adult and pediatric patients.
Diagnostic Performance of Sequencing of Plasma mcfDNA
Study level diagnostic performance outcomes are presented in Table 2 and Figure 2. A total of
71 patients were evaluated. Two patients were excluded due to insufficient data available to
provide accurate classification and therefore a total of 69 patients were included. Using
Method 1, 6 patients required additional review by infectious diseases experts. In these
instances, 1 case was classified as a TP, 1 FN, and 4 TN. There were no discrepancies in the
application of Method 2. Summary statistics of the pooled diagnostic performance outcomes of
the meta-analysis are presented in Table 3. Using a random effects model, the pooled PPA was
0.90 (95% CI 0.71-0.97) and the pooled NPA was 0.75 (0.49-0.90). The pooled positive likelihood
ratio was 3.58 (1.49-8.56), pooled negative likelihood ratio was 0.14 (0.04-0.48), the pooled
diagnostic odds ratio was 26.57 (4.06-173.7), and the pooled false positive rate was 0.25 (0.10-
0.51). The SROC plot (Supplementary Figure 1), risk of bias assessment (Supplementary Table 1)
and further meta-analysis statistics (Supplementary Tables 2 and 3) can be found in the
supplemental material. Using test classification methodology 2 (in which individual organisms
detected are classified rather than the entire test) the PPA was 0.87 (0.76-0.94) and the NPA
was 0.21 (0.12-0.35) (Table 4).
DISCUSSION
Despite use of broad antimicrobial chemoprophylaxis, HSCT recipients remain at high risk of
infection due not only to neutropenia in the pre-engraftment period and ongoing
immunosuppression prior to full reconstitution, but also due to loss of protective barriers in the
setting of oropharyngeal or intestinal mucositis, use of central lines and foley catheters, as well
as dysbiosis, and prolonged hospitalization with progressive risk of hospital-acquired
infections.(8,9) Early and appropriate empiric therapy is essential to minimize the morbidity
and mortality of infection. Accuracy and rapid TAT are crucial to establish a diagnosis and
allow for targeted therapy.
In this meta-analysis, we found plasma mcfDNA sequencing to be a promising non-invasive
diagnostic test in HSCT recipients through an examination of diagnostic performance as
reported in the literature. Plasma mcfDNA sequencing had an overall high PPA of 93% and 89%
when the overall test was considered (Method 1) and each individual organism (Method 2) wasmedRxiv preprint doi: https://doi.org/10.1101/2023.01.12.22280967; this version posted January 14, 2023. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
It is made available under a CC-BY-ND 4.0 International license .
considered, respectively. This is similar to reported rates across variable populations reported
in the literature, suggesting its potential benefit in HSCT recipients.(10)
There are several reasons why the PPA of plasma mcfDNA sequencing may be higher in the
HSCT population. After HSCT, there are various factors that increase infection risk including
disrupted mucosal barriers of the mouth and intestine, mucositis, presence of catheters,
neutropenia, immunodeficiency and dysbiosis.(11,12) Disrupted mucosal barriers coupled with
intensive immunosuppression confer a high risk of translocation and is associated with
significant morbidity and mortality.(8,13) They are also at higher risk for opportunistic
infections, the range of which cannot always be covered by prophylactic regimens. In addition,
treating physicians may be more likely to use advanced diagnostic testing such as plasma
mcfDNA sequencing earlier during the diagnostic work up if the pre-test probability is high for
opportunistic pathogens as these infections are more difficult to detect by traditional
microbiologic methods and often require invasive procedures. With a high diagnostic odds ratio
and high PPA, this test may not only be beneficial in providing a clinical diagnosis but also allow
for some patients to avoid such invasive procedures.
In addition to our main findings, we also compared two methodologies of interpreting plasma
mcfDNA sequencing reports which have been previously reported in the literature:
interpretation of individual pathogens (Method 2) versus interpretation of the report in its
entirety (Method 1).(6) We found that the NPA decreased with Method 2 from 74% to 20%
when all organisms detected were considered individually instead of the overall test. As
outlined above, this is a population which may be prone to mucositis and “leaky gut,” with
subsequent detection of multiple colonizing microorganisms. Of the 69 patients included, 5
patients had 5 or more microorganisms detected. When multiple microorganisms are
detected, they do not represent false positives in that they are truly present, though not all may
be clinically significant.
Additionally, plasma mcfDNA sequencing has been able to identify a pathogen prior to its
traditional clinical presentation in HSCT recipients.(14,15) As with all infectious diseases
diagnostics, the clinical context must be considered when interpreting each microorganism.
This concept of carefully interpreting each organism identified within the clinical context was
reinforced by the low NPA when results are considered in total (Method 2). The ordering
physician must ask not only “what organisms are present,” but instead, “what organism is
responsible for causing X syndrome,” be it neutropenic fever, sepsis, pneumonia, or another
infection. There are two main scenarios in which the detection of organisms without clinical
significance seems to occur: through (1) the detection of DNA of organisms that are part of
normal flora (either gastrointestinal, oral, skin, or respiratory flora) without a compatible
clinical illness; or (2) the presence of DNA from viruses without a compatible clinical illness that
may represent reactivation or shedding in the setting of acute illness. The organism
concentration, quantified in molecules per microliter of plasma (MPM), may help determine
clinical significance, with higher concentrations often implying higher likelihood of true
infection, although MPM is not comparable between organisms and may be affected by the
location of infection and preceding use of antimicrobials.(15,16) In addition, some opportunisticmedRxiv preprint doi: https://doi.org/10.1101/2023.01.12.22280967; this version posted January 14, 2023. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
It is made available under a CC-BY-ND 4.0 International license .
organisms should be considered pathogenic if identified regardless of the MPM value, including
invasive fungi such as Mucorales, Nocardia, Legionella, Bartonella, Mycobacteria and
Toxoplasma spp.
The negative likelihood ratio of 0.1 suggests that there may also be a role for negative plasma
mcfDNA sequencing results in HSCT recipients, although the confidence interval is large due to
the low number of true negatives or controls included in the studies. Given the broad range of
infectious disease mimickers after HSCT such as engraftment syndrome, diffuse alveolar
hemorrhage, graft versus host disease, etc., a negative test may be helpful for both
antimicrobial stewardship (de-escalation or avoidance of empiric escalation) and when
considering non-infectious etiologies, especially when biopsies and other invasive procedures
may be contraindicated due to thrombocytopenia or critical illness. However, further research
will be needed to determine the negative predictive value of plasma mcfDNA sequencing
particularly in patients already on empiric therapy which may alter diagnostic performance.
As a systematic review, this study is limited by the quality of the studies that are included. We
were able to include 69 pediatric and adult HSCT recipients from multiple institutions with
varied clinical presentations. However, the ability to determine the diagnostic accuracy of this
test was limited by the available information. Four Infectious Diseases experts independently
evaluated each reported case to determine how results should be classified. However, often
additional information regarding patient outcomes, preceding/future treatment, and additional
studies were not available that would have assisted in these classifications. In addition, because
different presentations were included, the diagnostic testing that was completed was not
consistent, and often gold standard diagnostic procedures such as bronchoscopies or biopsies
were not completed to compare results. This reflects real world practice in which these are not
uniformly obtained. In addition, there was not sufficient data to determine the clinical impact
of the test results in the data obtained and how it impacted clinical decision making. Further
studies need to be done to assess this.
In summary, infection remains a chief contributor to morbidity and mortality in HSCT recipients.
Overall, plasma mcfDNA sequencing is a promising test for the diagnosis of infections in HSCT
recipients and may have a potential role for negative results ruling out infection.medRxiv preprint doi: https://doi.org/10.1101/2023.01.12.22280967; this version posted January 14, 2023. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
It is made available under a CC-BY-ND 4.0 International license .
Figure 1. Flow diagram for systematic review.medRxiv preprint doi: https://doi.org/10.1101/2023.01.12.22280967; this version posted January 14, 2023. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
Author Year Published Title Study Type Median age (age range) in yeaSetting Study Sample Size HSCT Sample Size Included/Excluded Rationale for Exclusion
Cell-free DNA next-generation sequencing successfully detects infectious pathogens in pediatric Focus on single pathogen
Armstrong, et al. 2021 oncology and hematopoietic stem cell transplant patients at risk for invasive fungal disease Prospective 11 (1.2-24.2) Ann & Robert H. Lurie Children's Hospital of Chicago, Ch 40 9 Excluded type (fungi only)
Study excluded 2/3 HCT
Plasma microbial cell-free DNA next-generation sequencing in the diagnosis and management of recipients and no patient-
Benamu, et al. 2022 febrile neutropenia Prospective 60 (20-82) Stanford University Hospital, Stanford, CA 55 3 Excluded level data available
Next-generation sequencing of microbial cell-free DNA for rapid noninvasive diagnosis of infectious
Camargo, et al. 2019 diseases in immunocompromised hosts Prospective 56 (20-65) Sylvester Comprehensive Cancer Center, Orlando, FL 10 6 Included n/a
Evaluation of Plasma Microbial Cell-Free DNA Sequencing to Predict Bloodstream Infection in Pediatric St. Jude Children's Research Hospital, Memphis, Patient level data not
Goggin, et al. 2020 Patients With Relapsed or Refractory Cancer Prospective 10 (5-14) Tennessee 47 17 Excluded available
Immunocompromised
patients included recent
chemotherapy but did not
University of California San Francisco, San Francisco, differentiate HCT, or
Gu, et al. 2021 Rapid pathogen detection by metagenomic next-generation sequencing of infected body fluids Prospective 53 (1-89) CA 82 -- Excluded provide patient-level data
Liquid Biopsy for Invasive Mold Infections in Hematopoietic Cell Transplant Recipients With Patient level data not
It is made available under a CC-BY-ND 4.0 International license .
Hill, et al. 2021 Pneumonia Through Next-Generation Sequencing of Microbial Cell-Free DNA in Plasma Retrospective 51 (16-74) Fred Hutchinson Cancer Research Center, Seattle, WA 117 117 Excluded available
Children's Hospital of Los Angeles, Los Angeles, CA;
Columbia University Medical Center, New York, NY;
Stanford Health Care, Stanford, CA; University of
Clinical Impact of Metagenomic Next-Generation Sequencing of Plasma Cell-Free DNA for the California, Los Angeles; Los Angeles, CA; University of
Hogan, et al. 2020 Diagnosis of Infectious Diseases: A Multicenter Retrospective Cohort Study Retrospective 25 (0.1-76) Utah, Salt Lake City, UT 82 8 Included n/a
Liquid biopsy for infectious diseases: sequencing of cell-free plasma to detect pathogen DNA in Focus on single pathogen
Hong, et al. 2018 patients with invasive fungal disease Prospective 50 (20-73) Stanford University Hospital, Stanford, CA 9 2 Excluded type (fungi only)
Next-Generation Sequencing to Detect Pathogens in Pediatric Febrile Neutropenia: A Single-Center Patient level data not
Horiba, et al. 2021 Retrospective Study of 112 Cases Retrospective 7 (not given) Nagoya University Hospital, Tsurumaicho, Japan 112 13 Excluded available
Assessment of the Clinical Utility of Plasma Metagenomic Next-Generation Sequencing in a Pediatric
Lee, et al. 2020 Hospital Population Retrospective 9 (not given) Children's Hospital, Boston, MA 54 9 Included n/a
Plasma Metagenomic Next-Generation Sequencing Assay for Identifying Pathogens: a Retrospective
Niles, et al. 2020 Review of Test Utilization in a Large Children's Hospital Retrospective 9 (not given) Children's Hospital, Houston, TX 60 13 Included n/a
Patient level data not
available in 25/29
Niles, et al. 2022 Clinical Impact of Plasma Metagenomic Next-generation Sequencing in a Large Pediatric Cohort Retrospective 10.2 (not given) Children's Hospital, Houston, TX 169 29 Excluded patients
Noninvasive Diagnosis of Infection Using Plasma Next-Generation Sequencing: A Single-Center
Rossoff, et al. 2019 Experience Retrospective 11 (0.5-24) Lurie's Childrens Hospital, Chicago, IL 79 13 Included n/a
Children's Hospital, Zhejiang University School of
Clinical assessment of the utility of metagenomic next-generation sequencing in pediatric patients of Medicine, National Clinical Research Center for Child Patient level data not
Shen, et al. 2020 hematology department Prospective Not given (reported 72.9% undHealth 70 Not reported Excluded available
Impact of Next-Generation Sequencing Cell-free Pathogen DNA Test on Antimicrobial Management in
Yu, et al. 2021 Adults with Hematological Malignancies and Transplant Recipients with Suspected Infections Retrospective 56 (18-75) AdventHealth Cancer Institute, Orlando, FL 31 21 Included n/a
Table 1. Studies examined for eligibility for inclusion.medRxiv preprint doi: https://doi.org/10.1101/2023.01.12.22280967; this version posted January 14, 2023. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
It is made available under a CC-BY-ND 4.0 International license .
Table 2. Study Level Outcomes. TP: true positive; FN: false negative; FP: false positive; TN: true negative; N: sample size; PPA:
positive percent agreement; NPA: negative percent agreement; Weight PPA: weight of individual study PPA in meta-analysis; Weight NPA:
weight of individual study NPA in meta-analysis.Method1 was used to classify test results as TP, FN, FP, and TN. If any of the organisms
detected were considered to be clinically relevant based on the data available, it was considered a TP. This included if the diagnosis was
confirmed by traditional methods, the patient improved with treatment targeting the organism detected, and/or if the clinical syndrome fit
with the organism detected without an alternative diagnosis, even if it was not confirmed by traditional testing. If the organism that was
suspected to cause the clinical syndrome of the patient was not detected on plasma mcfDNA sequencing based on treatment response, other
data collected by traditional methods, the test was considered a FN. The test was considered a FP if it only detected organisms that were not
considered to be clinically relevant (detected by other traditional methods, not treated, and/or not compatible with the clinical syndrome). The
test was considered a TN if no organisms were detected on plasma mcfDNA sequencing and an infectious etiology was not detected by
additional methods, and an alternative non-infectious diagnosis was identified and considered the primary diagnosis. The NPA and PPA reflect
the agreement for Method 1 when considering all of the cases included in the studies specified. PPA = TP/(TP + FN), PPA and NPA = TN/(FP +
TN).medRxiv preprint doi: https://doi.org/10.1101/2023.01.12.22280967; this version posted January 14, 2023. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
It is made available under a CC-BY-ND 4.0 International license .
Figure 2. Forest plot of Positive Percent Agreement and Negative Percent Agreement. Study
labeled by first author with study sample size in parenthesis. X-axis reflects lower and upper 97.5% confidence interval of outcome amongst all
included studies.medRxiv preprint doi: https://doi.org/10.1101/2023.01.12.22280967; this version posted January 14, 2023. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
It is made available under a CC-BY-ND 4.0 International license .
Table 3. Pooled outcomes of meta-analysis of diagnostic test performance of plasma
microbial cell-free DNA sequencing in diagnosing infections in hematopoietic stem cell
transplant recipients.
Table 4. Pooled outcomes of meta-analysis of diagnostic test performance of plasma
microbial cell-free DNA sequencing in diagnosing infections in hematopoietic stem cell
transplant recipients based on individual organisms detected and not on test interpreted as a
whole.medRxiv preprint doi: https://doi.org/10.1101/2023.01.12.22280967; this version posted January 14, 2023. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
It is made available under a CC-BY-ND 4.0 International license .
SUPPLEMENTARY DATA
Supplementary Figure 1. SROC Plot.
Patient Selection: Patient Selection: Index Test: Risk of Index Test: Reference Standard: Reference Standard: Flow and Timing:
Reference Risk of Bias Applicability Bias Applicability Risk of Bias Applicability Risk of Bias
Camargo Low Low High Low High Low Low
Rossoff High Low High Low High Low High
Hogan High Low High Low High Low High
Lee High Low High Low High Low High
Niles High Low High Low High Low High
Yu High Low High Low High Low HighmedRxiv preprint doi: https://doi.org/10.1101/2023.01.12.22280967; this version posted January 14, 2023. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
It is made available under a CC-BY-ND 4.0 International license .
Supplementary Table 1. Risk of bias within individual studies.
Parameter Estimate
Random Effects Correlation 1
theta 0.013
lambda 3.09
beta -0.68
sigma theta 0
sigma alpha 0.604
Supplementary Table 3. Additional meta-analysis random effects statistics.medRxiv preprint doi: https://doi.org/10.1101/2023.01.12.22280967; this version posted January 14, 2023. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
It is made available under a CC-BY-ND 4.0 International license .
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