FormalPara Key Points for Decision Makers

It is critical to find the best treatment for immunocompromised patients with pneumonia, but usual care diagnostic tests are often unable to identify the cause of the infection.

This study examined whether plasma microbial cell-free DNA (mcfDNA) sequencing would be a cost-effective approach to identifying the cause of the infection sooner and more accurately than usual care tests alone.

We found that adding mcfDNA to usual care diagnostic testing would lead to more patients receiving appropriate therapy earlier and improvement of patient outcomes, translating into a cost-effective alternative to usual care testing alone.

1 Introduction

Patients treated for hematological malignancies and those undergoing hematopoietic stem transplantation are at high risk for life-threatening immunocompromised host pneumonia (ICHP) caused by diverse and often rapidly progressive pathogens [1, 2]. Rapid identification of an infectious cause for ICHP enables clinicians to optimize antimicrobial therapy and health outcomes, but usual care (UC) diagnostic testing usually fails to identify an etiology [3,4,5]. Bronchoscopy is often used to obtain clinical specimens for diagnostic testing, though delays often decrease utility, and bronchoscopy-associated adverse events occur in about 10% of patients [6,7,8].

Current UC diagnostic testing in patients with cancer demonstrated a diagnostic yield range from 0% to 57.7% for blood cultures and from 0.2% to 67.2% for bronchoalveolar lavage fluid cultures, with the majority falling under 50% [9]. New diagnostic testing strategies are needed for ICHP to increase yield, decrease the time to etiology-specific antimicrobial therapy, decrease use of empiric antimicrobial therapies, and, when possible, avoid invasive diagnostic procedures like bronchoscopy. Plasma microbial cell-free DNA (mcfDNA) metagenomic sequencing is a promising new strategy for diagnosing infections in ICHP [1]. This approach is taxonomically agnostic and allows simultaneous detection and quantification of more than 1000 human pathogens, including bacteria, DNA viruses, fungi, and parasites [10].

The “Pneumonia in the Immunocompromised—Use of the Karius Test for Detection of Undiagnosed Pathogens” (PICKUP) study was recently published [11]. This was a prospective, multicenter, observational study conducted at ten US academic medical centers designed to evaluate the additive diagnostic value of plasma mcfDNA sequencing compared to all UC diagnostic testing for ICHP, including bronchoscopy. ICHP etiology was centrally adjudicated by a committee including experienced infectious diseases and pulmonary specialists.

In total, 173 of the 257 patients met the “per protocol” conditions of receiving complete baseline testing, a bronchoscopy, and a valid mcfDNA result. Infectious ICHP etiology was identified by UC testing in 52 patients (30.1%), plasma mcfDNA in 49 patients (28.3%), and the combination of both in 73 patients (42.2%). Plasma mcfDNA exclusively identified an etiology of ICHP in 21 of 173 patients (additive diagnostic value: 12.1%, 95% confidence interval [CI] 7.7–18.0, P < 0.001). In the per protocol subgroup with negative UC testing, plasma mcfDNA identified an infectious ICHP etiology in 21 of 121 patients (clinical additive diagnostic value: 17.4%, 95% CI 11.1– 25.3).

Based on the findings of the PICKUP study and supplemented by secondary sources, the objective of this study was to perform a cost-effectiveness analysis (CEA) of adding mcfDNA sequencing to UC diagnostic testing for hospitalized ICHP patients.

2 Methods

This model examines the cost-effectiveness of adding plasma mcfDNA testing to UC diagnostic tests to further increase the diagnostic yield, expedite the diagnostic process, minimize delays in targeted treatment initiation, and enhance the precision of treatment decisions. This CEA was designed and validated in alignment with good modelling practice guidelines and recommendations [12,13,14]. The modelling approach was informed by a structured review of the clinical and economic literature and refined through a collaborative process utilizing expert clinical perspectives.

Currently, patients with suspected ICHP are initially treated with broad-spectrum antimicrobials prior to identifying the infectious etiology. They undergo various non-invasive (NI) and invasive diagnostic tests, including bronchoscopy, to determine the pneumonia-causing pathogen. As test results become available, treatment strategies are dynamically adjusted to ensure that they are appropriate for the identified pathogens and their susceptibilities to antimicrobials. This personalized approach optimizes therapy, leading to quicker recovery, earlier discharge, and reduced mortality risk.

2.1 Model Structure

A semi-Markov model structure was implemented in Microsoft Excel® (2023) to compare health outcomes and associated costs from the US payer perspective for the addition of mcfDNA to UC diagnostic testing, including NI and invasive testing. The model structure is presented in Fig. 1. A semi-Markov model relaxes the Markov assumption for sojourn time, allowing for dynamic transition probabilities between health states. The model describes the pathways as patients receive test results and treatment, which may or may not be appropriate given the test result. The primary endpoints of the model were discounted costs, life-years (LYs), equal value life-years (evLYs), quality-adjusted life-years (QALYs), and the incremental cost-effectiveness ratio (ICER) per QALY.

Fig. 1
figure 1

Structure of semi-Markov model. Arrows represent possible transitions between cycles; grey health states indicate the patient has been tested for ICHP but the test result has not yet been received. ICHP Immunocompromised host pneumonia

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The model structure (Fig. 1) was designed to encompass the key aspects of a patient's journey when suspected of ICHP, focusing on microbiological testing results and subsequent changes in antimicrobial treatment. It considers antimicrobial treatment adjustments before and after receiving test results, appropriateness of therapy in response to test results, and patient outcomes including hospitalization, discharge, or death.

Patients start in one of the first two initial health states described below, awaiting a test result, with an ICHP pathogen that may or may not be identifiable. It was assumed that UC and mcfDNA sequencing can detect all identifiable ICHP pathogens, based on the overlap between detectable pathogens by the mcfDNA test and known pneumonia pathogens [15, 53]. Due to different factors that impact test sensitivity, such as time from infection to specimen collection and time on antimicrobials, UC and mcfDNA tests may miss some pathogens that the other might detect. After test results are received, patients transition between model states to indicate whether they receive appropriate or inappropriate treatment (defined below). In any health state, patients can experience mortality or be discharged from the hospital, unless they have an identifiable probable ICHP pathogen, in which case, a test result is always received first (transitions not shown). A half-cycle correction is applied to costs and benefits to account for the movement of patients at any point during a cycle.

The Markov health states in the model are defined as follows:

  • ICHP with microbial etiology: Patients with clinical signs/symptoms of ICHP with a microbiological evaluation in progress (test result not yet received) that will eventually identify an infectious ICHP etiology. Patients in this state may not be discharged. The proportion of patients that start in this state is informed by the proportion of patients in the population with an infectious ICHP etiology. From this state, patients may transition into the “ICHP with microbial etiology—appropriate treatment” or “ICHP with microbial etiology—inappropriate treatment” model states when test results are received, or they may die.

  • ICHP with no microbial etiology: Patients with clinical signs/symptoms of ICHP with a microbiological evaluation in progress (test result not yet received) that will not identify an infectious ICHP etiology. This may be due to non-infectious causes or limitations in testing (e.g., prior antibiotic use, low pathogen levels, fastidious organisms). The proportion of patients that start in this state is informed by the proportion of patients in the population without an infectious ICHP etiology. From this state, patients may transition into the “ICHP with no microbial etiology—appropriate treatment” or “Non-ICHP infection with no microbial etiology—inappropriate treatment” model states when a test result is received, or independently of the test result, they may be discharged or die.

  • ICHP with microbial etiology—appropriate treatment: Patients with clinical signs/symptoms of ICHP with the microbiological evaluation completed (test result received) and an infectious ICHP etiology is identified. Treatment is optimized as necessary so that it is appropriate for the identified pathogen(s). From this state, patients may be discharged, or they may die.

  • ICHP with no microbial etiology—appropriate treatment: Patients with clinical signs/symptoms of ICHP with the microbiological evaluation completed (test result received) and no infectious ICHP etiology is identified. Treatment is administered based on the clinical data and the assumption of unknown pathogen. From this state, patients may be discharged, or they may die.

  • ICHP with microbial etiology—inappropriate treatment: Patients with clinical signs/symptoms of ICHP with the microbiological evaluation completed (test result received), and while an infectious ICHP etiology is present, it is missed by the evaluation. Treatment remains unchanged, and thus inappropriate. From this state, patients may be discharged, or they may die.

Note: No further information will become available to guide treatment, meaning that patients in this model state cannot transition into an appropriate treatment health state.

  • Non-ICHP infection with no microbial etiology—inappropriate treatment: Patients with clinical signs/symptoms of ICHP with the microbiological evaluation completed (test result received) and no infectious ICHP etiology is identified. Treatment remains unchanged, and thus inappropriate.

    Note: This model state is only relevant for patients in the UC comparator. No further information will become available to guide treatment, meaning that patients cannot transition into an appropriate treatment health state.

  • Discharged: Patients who have been discharged from the hospital.

  • Dead: Patients who have died—all patients in the model are at risk of mortality.

2.2 Target Population

The populations considered in the analysis were based on the PICKUP study: immunocompromised hospitalized adult patients undergoing diagnostic bronchoscopy to establish the microbiological etiology of clinically suspected infectious ICHP [11]. The recently published guidelines for ICHP defined the main patient populations at risk by underlying disease states: cancer and hematopoietic cell transplant recipients, patients with HIV, chronic immunosuppression, solid organ transplant, and inborn errors of immunity [1]. The group with one of the highest risks of ICHP is represented in the PICKUP study population: patients receiving treatment for an active hematological malignancy, recently undergoing hematopoietic cell transplantation, or receiving immunosuppressive therapy for active graft versus host disease [1, 9, 16]. The per protocol population (N = 173) was previously defined [11]. The second population (N = 223) encompasses the per protocol population and represents all patients with an adjudicated plasma mcfDNA test, including patients with plasma mcfDNA collected close to but outside 24 h from study enrollment. The median age of the per protocol population in the PICKUP study was 61 years, and 65.3% of patients were male.

2.3 Treatment Comparators

The following comparators were considered in this analysis:

  • All UC utilized a range of NI tests alongside invasive testing (including early bronchoscopy). All tests were administered (assumed to be at the same time) to patients, and then test results were received over time as they became available.

  • All UC & mcfDNA consisted of the All UC comparator described above with the plasma mcfDNA administered at the time of other testing.

  • NI UC & mcfDNA & conditional UC Bronch consisted of the plasma mcfDNA and NI tests administered at the outset, followed by further invasive tests and later bronchoscopy 5 days after the initial tests for patients who are negative in the initial tests. Note that prevalence and delay data from the PICKUP study were not collected specifically for this comparator. Therefore, data from the trial and other sources were combined to assess the potential cost-effectiveness of this comparator.

The turnaround time of test results and the ability to detect infectious ICHP etiology directly impact patient outcomes in the model. Before a test result is received a proportion of patients in the population will experience adverse outcomes (e.g., longer hospital stays, higher mortality risk) to reflect the presence of infectious ICHP etiology. After receiving the test results, similar adverse outcomes occur if the test misses the infectious ICHP etiology, leading to inappropriate treatment.

2.4 Time Horizon and Cycle Length

A lifetime time horizon (maximum age is 100 years old) initiated at the time of testing was implemented in the base-case analysis. A time horizon of 1 year was evaluated as part of scenario analyses. In order to parameterize the model using diagnostic delay data that is reported hourly (see Fig. 3), a cycle length of 1 h was used for the first 3 months of the analysis. Beyond the time span of the diagnostic delay data, in order to increase the speed and efficiency of the model, the time cycle was 3 months for the remainder of the first year, and 1 year from the second year onwards.

2.5 Discount Rates

Discount rates of 3% per year for benefits and costs were applied in the base case as per the Institute for Clinical and Economic Review reference case [17]. Additional scenario analyses evaluated outcomes for benefits and costs without discounting and with discounting at 5% per year.

2.6 Disease Prevalence

The overall proportion of patients with relevant infectious ICHP etiology was informed by the test results in the PICKUP study and based on the All UC and All UC & mcfDNA comparators as shown in Fig. 2. In the All UC arm, an etiology of pneumonia was identified by All UC testing in 52 of 173 patients (30.1%). At time zero, the proportion of patients with ICHP microbial etiology in the model was 42.2% (73/173). Among these 73 patients, an etiology of pneumonia was identified by All UC alone in 25, All UC & mcfDNA in 27, and mcfDNA alone in 21. It was assumed that the comparators with mcfDNA eventually diagnosed all infectious ICHP pathogens, subject to delays to diagnosis or mortality.

Fig. 2
figure 2

Infectious ICHP positive etiology identified in 173 patients. ICHP immunocompromised host pneumonia, mcfDNA microbial cell-free DNA, UC usual care

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2.7 Appropriateness of Treatment

It would never be the case that patients would knowingly be given inappropriate treatment. However, by comparing the testing results for UC and plasma mcfDNA, conclusions can be drawn as to the proportion of patients that may receive inappropriate treatment.

Appropriate treatment is defined here as patients that have received a test result and then receive treatment that is appropriate for an identified ICHP or non-ICHP microbial etiology. It is assumed in the base case that All UC & mcfDNA can detect all infectious ICHP pathogens.

Inappropriate treatment is defined as patients that receive a test result, but due to the shortcomings of testing, do not receive appropriate treatment for an ICHP or non-ICHP microbial etiology. A total of 21 out of 173 patients that would otherwise have been missed with UC testing were found to be positive for infectious ICHP etiology by plasma mcfDNA (Fig. 2). It is assumed in this study that a proportion of patients in the All UC arm may receive inappropriate treatment, leading to adverse outcomes. The proportion is informed by data (see Section 2.9).

The presence of relevant non-ICHP pathogens can also lead to some patients receiving inappropriate therapy. These pathogens are detected for all patients that receive plasma mcfDNA testing in addition to All UC (and therefore appropriately treated), but not for all patients in the All UC group. This proportion of patients at risk of inappropriate treatment was estimated based on the subgroup of patients in the PICKUP study for whom mcfDNA would have changed the choice of antimicrobial therapy (22/223, 9.9%) (manuscript under review).

Note that once patients receive a test result and have their treatment possibly modified as a result, no transitions between inappropriate or appropriate treatment states are possible.

2.8 Transition Probabilities

Patient transitions between model states per cycle were informed by data on the length of time spent in each state and the probability of patients experiencing an event.

2.8.1 Delays to Diagnosis

Transitions between model states as test results are received (see flows from grey to white states in Fig. 1) were informed by data from the PICKUP study (manuscript under review), shown in Fig. 3. These data illustrate the proportion of patients identified with positive infectious ICHP etiology by test type over time. It was assumed that the time to either a positive or negative diagnosis was the same.

Fig. 3
figure 3

Delays to diagnosis of infectious ICHP relevant etiology. All UC invasive and non-invasive usual care only, All UC & mcfDNA invasive and non-invasive usual care + mcfDNA, ICHP immunocompromised host pneumonia, I UC invasive usual care only, mcfDNA plasma microbial cell-free DNA, NI UC non-invasive usual care only

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2.8.2 Probability of Diagnosis

The probabilities of diagnosis for each comparator over time were calculated by scaling each curve based on the maximum prevalence of an identifiable infectious ICHP pathogen. For example, the All UC & mcfDNA comparator is scaled to 100% as it is assumed that this test detects all relevant infectious ICHP pathogens. Based on the PICKUP study, the All UC comparator is scaled to 52/73 (i.e., number of patients with pathogen identified by All UC alone divided by number of patients with pathogen identified by All UC & mcfDNA). From the resultant curves, hourly transition probabilities for diagnosis were calculated using Eq. (1), where t is time (hours) and α is the value on the scaled diagnosis curve at time = t. Thus, the probability of diagnosis at 5 h is based on the difference in delay curve values at hours 4 and 5. As can be seen from the delay curves in Fig. 3, the curves are sometimes flat and the corresponding probability of diagnosis is zero.

$${P}_{t}=1-\left(\frac{1-{\alpha }_{t}}{1-{\alpha }_{t-1}}\right)$$
(1)

As noted above, as data for the NI UC & mcfDNA & conditional UC Bronch scenario were not collected, assumptions about time to diagnosis must be made. The model assumed this delay curve followed the NI UC curve until the mcfDNA test delivered results, and then the curve increased based on the mcfDNA test. The curve then followed the invasive UC curve until the remaining infectious ICHP pathogen had been diagnosed. The scaled values, including the estimated NI UC & mcfDNA & conditional Bronch curve, are shown in Fig. 4. This has been scaled to the prevalence estimates in Fig. 2 combined with the delay curves in Fig. 3.

Fig. 4
figure 4

Delay to diagnosis curves scaled to infectious ICHP prevalence estimates. All UC invasive and non-invasive usual care only, All UC & mcfDNA invasive and non-invasive usual care + mcfDNA, ICHP immunocompromised host pneumonia, I UC invasive usual care only, mcfDNA plasma microbial cell-free DNA, NI UC non-invasive usual care only, NI UC & mcfDNA—conditional UC Bronch non-invasive usual care + mcfDNA + conditional usual care bronchoscopy

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2.8.3 Probability of Hospital Discharge and In-hospital Mortality

The probabilities of discharge from hospital and mortality in hospital (46/173) were calculated from data collected during the PICKUP study [10], which observed an average length of hospital stay of 22.2 days. These probabilities are defined in Eq. (2), where P is the probability of an event per unit time, l is the length of time spent in the state (e.g., time spent in hospital), and t is the time period of interest, depending on the length of the time cycle.

$$P=1-exp \left(-\frac{1}{l}\right) t$$
(2)

The final transition probabilities used in the model for discharge and mortality are summarized in Table 1.

Table 1 Discharge- and mortality-related transition probabilities
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2.9 Changes in Antimicrobial Therapy

The potential changes in ICHP antimicrobial therapy following the mcfDNA test results are shown in Table 2. In the PICKUP study, the adjudication committee determined that knowledge of mcfDNA results in real time would have led to changes in antimicrobial therapy in 11 of 21 patients (52%) with a microbial etiology exclusively identified by plasma mcfDNA sequencing. Were these changes in therapy not undertaken, it was judged that these 11 patients receiving treatment directed by All UC testing would have received inappropriate treatment leading to adverse health outcomes.

Table 2 Appropriateness of treatment
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2.10 Adverse Events Due to Bronchoscopy

Bronchoscopy is associated with the risk of multiple complications. The frequencies of adverse events associated with bronchoscopy were sourced from the per protocol population in the PICKUP study and are presented in Table 3.

Table 3 Frequencies of bronchoscopy-associated adverse events
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2.11 Risk of Mortality

Mortality probabilities used in the model are summarized in Table 1. The probability of dying in hospital was sourced from the PICKUP study (26.5%, 46/173 patients), while the odds ratio (OR) for the reduction in mortality among patients with infectious ICHP treated with appropriate antimicrobials versus not (OR 0.35, 95% CI 0.24–0.51) was estimated in a recent systematic review by Bassetti and colleagues [18]. Post-discharge from hospital, the mortality rate is assumed to follow the age-specific values for the general population [19].

2.12 Health-Related Quality of Life

Life expectancy was adjusted for quality of life using health state utilities. QALYs were derived by multiplying remaining years of life by the utility value for each health state and an age specific utility value [20]. Several alternative secondary sources were considered in the estimation of the utility values (Table 4). In the case of disability weights, these values were multiplied by the health states for hematopoietic cell transplantation (a proxy for the broader patient population considered here) depending on the presence or absence of infectious ICHP. Disutility values for infectious ICHP modified the health state for hematopoietic cell transplantation by adding the values together (disutility is negative, leading to a lower value). The impact of using alternative sources was examined in scenario analyses.

Table 4 Health-related quality of life utility values
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.

Table 5 Disutilities of bronchoscopy-associated adverse events
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,

2.13 Cost Inputs

The base-case model included multiple costs: test administration, treatment, treatment administration, health care resource utilization, readmission, adverse events, productivity loss, and mortality. Productivity loss costs were excluded in the base-case scenario [17]. All costs were inflated to 2023 USD when necessary [29]. In the absence of available information, a multiplier of 2.24 was used to estimate commercial costs [30]. For the All UC and All UC & mcfDNA comparators, test administration and associated testing costs (including bronchoscopy and adverse event costs) are incurred in the model as a one-time cost at time zero. For the mcfDNA and NI UC comparator, bronchoscopy cost is applied when negative results of the NI tests are received (informed by the delay curves, Fig. 4). Health care resource costs, including treatment and bed days, are allocated over time to all patients in the in-hospital model states. Readmission costs, reported as an average over 12 months, are applied as a one-time cost to all patients in the discharged state.

A comprehensive description of all cost inputs and their sources are provided in the electronic supplementary material (“Supplementary Information”), with a summary of the key cost parameters shown in Table 6.

Table 6 Summary of key costs
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2.14 Sensitivity Analyses

Probabilistic sensitivity analyses (PSA) were conducted to account for simultaneous uncertainty in the input point estimate values. To conduct the PSA, probability distributions were assigned to inputs based on realistic levels of parameter uncertainty, estimated from sourced standard error values where available. In cases where the parameter uncertainty was not described, the standard error was assumed to be 10% of the point estimate. Beta distributions were used for proportions, percentages, and utilities; log-normal distributions were used for numbers that ranged from zero to infinity, including costs; and the normal distribution was used for patient weight (shown in the main text and electronic supplementary material). A total of 2000 Monte Carlo iterations of the model were run, with input values for each iteration simultaneously randomly drawn from associated distributions.

2.15 Scenario Analyses

Additional scenarios were explored to evaluate the effect on results when the model incorporated different time horizons, discounting assumptions, included costs, utility values, the effectiveness of the mcfDNA test in terms of appropriateness of treatment and reductions in mortality, and the price of the mcfDNA test.

3 Results

3.1 Base-Case Analysis

The base-case deterministic results comparing All UC & mcfDNA to All UC alone and to NI UC & mcfDNA & conditional UC Bronch are presented in Table 7.

Table 7 Summary of benefits (deterministic results over a lifetime horizon)
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Over a lifetime horizon, All UC & mcfDNA provided 13.39 LYs, 10.11 QALYs and 10.20 evLYs per patient, with a total cost of $165,247. The All UC comparator resulted in 12.47 LYs, 9.42 QALYs and 9.42 evLYs with a cost of $153,642. The NI UC & mcfDNA & conditional UC Bronch resulted in 13.19 LYs, 9.96 QALYs and 10.02 evLYs per patient, with a total cost of $162,655, Overall, both applications of the mcfDNA found the test to be more costly and more effective than All UC.

Detailed stratified lifetime costs for each comparator are included in the electronic supplementary material. The All UC & mcfDNA comparator incurred greater costs associated with testing, treatment, health care resource utilization (HCRU), and readmission, but produced small savings associated with mortality costs. In most cases, these additional costs were associated with the survival of patients either within hospital or after discharge.

3.2 Sensitivity Analyses

3.2.1 Probabilistic Sensitivity Analysis

A cost-effectiveness plane is displayed in Fig. 5, with the estimated costs and QALYs gained for each intervention over 2000 Monte–Carlo iterations (where 2000 iterations was found to be the optimum number based on congruence analysis). Deterministic results for each intervention are also shown, for comparative purposes.

Fig. 5
figure 5

Probabilistic sensitivity analysis: cost-effectiveness plane over 2000 model iterations. All UC only invasive and non-invasive usual care only, All UC & mcfDNA invasive and non-invasive usual care + mcfDNA, mcfDNA plasma microbial cell-free DNA, NI UC & mcfDNA &conditional UC Bronch non-invasive usual care + mcfDNA + conditional usual care bronchoscopy, QALY quality-adjusted life-year

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The cost-effective acceptability curve with variations in the willingness-to-pay (WTP) threshold for the QALY is displayed in Fig. 6. At a threshold of $50,000 per QALY and above, the All UC & mcfDNA scenario is 100% likely to be cost-effective compared to the other comparators. The NI UC & mcfDNA scenario is never the most cost-effective scenario irrespective of the WTP for the QALY. This is because when the WTP is low, the extra health effect provided by either of the mcfDNA scenarios is not worth paying for, but then, as the WTP increases, the scenario with the highest health benefit is preferred, which is All UC & mcfDNA.

Fig. 6
figure 6

Cost-effectiveness acceptability curve. All UC only invasive and non-invasive usual care only, All UC & mcfDNA invasive and non-invasive usual care + mcfDNA, mcfDNA plasma microbial cell-free DNA, NI UC & mcfDNA &conditional UC Bronch non-invasive usual care + mcfDNA + conditional usual care bronchoscopy

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The base-case probabilistic results comparing All UC & mcfDNA to All UC alone and to NI UC & mcfDNA & conditional UC Bronch are summarized in Table 8. These results are very much aligned with the deterministic results described in Table 7.

Table 8 Summary of benefits: probabilistic results over a lifetime horizon
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3.2.2 Scenario Analyses

Scenario analyses found that the All UC & mcfDNA always improved patient outcomes but was not cost saving, even when the price of mcfDNA was set to $0. Reducing the time horizon from lifetime to 1 year and increasing the OR describing the reduction in mortality due to appropriate treatment were the only scenario options that kept All UC & mcfDNA from being the most cost-effective testing option. The results of the scenario analysis are included as Supplementary Information.

4 Discussion

Based on the evidence available at the time of this analysis, the results from this CEA indicate that mcfDNA is a cost-effective approach to identify ICHP pathogens in immunocompromised patients, when added to All UC testing. Across a range of scenarios, mcfDNA was beneficial to patients but was not found to be cost-saving.

Sensitivity analyses were consistent with the base-case findings. The PSA results showed that at a cost-effectiveness threshold of $100,000, and acknowledging the assumptions associated with the analysis, All UC & mcfDNA was 100% likely to be cost-effective compared to All UC and NI UC & mcfDNA & conditional UC Bronch. Additional scenario analysis that examined the impact of changing various key parameters and model assumptions confirmed the robustness of the base-case results; reducing the time horizon from lifetime to 1 year and increasing the OR describing the impact of appropriate treatment on mortality were the only scenarios that prevented All UC & mcfDNA from being the most cost-effective option.

The addition of a test to identify infectious ICHP pathogens that can reduce in-hospital mortality will almost inevitably incur greater costs, as patients consume greater inpatient resources, and may be re-admitted at a later time. While costs associated with mortality are reduced, these savings do not produce cost savings overall.

This study was subject to a number of tests of validation to ensure its appropriateness. Validation of the conceptual model and input data were undertaken by a panel of experts from the PICKUP study with wide subject knowledge. The computerized model and its operation were validated through the implementation of the Cytel quality control process in which a modeler independent of the project subjects the model to a number of tests from multiple dimensions to ensure its validity (e.g., set all costs to zero, set utilities to zero), etc. However, there are currently no published economic evaluations that have focused on testing for ICHP patients, and thus, cross validity testing of the model results from this study is problematic. Furthermore, a recent systematic literature review of diagnostic gaps among immunocompromised patients with suspected infections highlighted how poorly served these patients are by UC diagnostic testing and the lack of strong evidence supporting current diagnostic practices [9]. Studies investigating HCRU outcomes in pediatric [31,32,33,34,35,36,37,38] and adult patients [39,40,41,42,43,44,45,46,47,48,49,50,51] with hematological cancer rarely assessed the cost impact of different diagnostic approaches, with no studies to our knowledge reporting on QALY or cost per QALY for metagenomic sequencing testing in cancer patients.

To provide additional context for the results described here, a cost-effectiveness study for treatment of ventilated hospital-acquired bacterial pneumonia and ventilator-associated bacterial pneumonia in a similar patient population with a high mortality rate and heavy health care resource needs found that the use of combined antimicrobial therapy (ceftolozane and tazobactam) for appropriate, specific, known pneumonia etiologies was cost-effective ($12,126 per QALY), being more costly and providing more QALYs when compared to meropenem, thereby demonstrating the value of appropriate treatment for this type of patient group [52]. The specific bacteria (e.g., Pseudomonas aeruginosa) most commonly associated with these types of pneumonia are the ones readily identified by plasma mcfDNA testing [15, 53], and selection of appropriate antimicrobial treatment was an important component of our analyses.

4.1 Limitations

This analysis has a number of limitations which are acknowledged here. The study used to inform the efficacy of All UC & mcfDNA at detecting infectious ICHP etiology consisted of 173 patients, and while the uncertainty associated with this small sample size is reflected in the results of the sensitivity analysis, this limitation is acknowledged.

The delay to diagnosis curves were based on data from the diagnosis of patients with positively identified pathogens; these have been extrapolated to assume that the rates of delay are the same for the diagnosis of both positive and negative patients.

There were no data to describe the delays to positive diagnosis for the mcfDNA and late bronchoscopy scenario; instead, the delay curves for NI UC, mcfDNA, and invasive UC were combined to infer the rate of diagnosis over time.

It was assumed that patients who survived the index hospital admission and were discharged had the same rates of readmission. However, it is possible that patients who receive a quicker diagnosis and more prompt appropriate treatment may have better long-term outcomes; this would make All UC & mcfDNA even more cost-effective than estimated here.

Finally, the PICKUP study did not examine the relationship between the selection of appropriate versus inappropriate therapy and hospital mortality in this patient population; instead, these estimates were based on a pooled analysis from a systematic review of 19 studies [18].

5 Conclusions

This analysis suggests that plasma mcfDNA is a cost-effective testing option to identify the causative pathogen in hospitalized immunocompromised patients with infectious ICHP, either as an addition to NI and invasive testing, including bronchoscopy, or as a triage alongside NI testing so that patients can be directed to appropriate treatment earlier, without having to wait for the results of an early bronchoscopy.