Clinical and diagnostic values of metagenomic next-generation sequencing for infection in hematology patients: a systematic review and meta-analysis

Hematology patients are prone to various infections due to neutropenia and immunosuppression [1]. Many infections in hematology patients are hospital-acquired and have a high rate of drug resistance, and conventional antimicrobial therapy is often ineffective [2, 3]. Infectious diseases have been one of the leading causes of death in hematology patients [4]. A prospective study in which hematology patients with febrile neutropenia received short-course (3 days) or long-course (≥9 days) antimicrobial therapy with meropenem showed that the treatment failure rates were 19% and 15% for the short and long treatment groups, respectively [5]. It is essential for the treatment of infection to identify the type of pathogen in a timely manner and adjust antibiotic therapy. However, traditional methods such as blood culture are limited by their low throughput, narrow coverage of pathogen spectrum and time consumption, which has led to the irrational use of antibiotics [6].

In recent years, metagenomic next-generation sequencing (mNGS) has rapidly emerged as a technology for the detection of pathogenic microorganisms. In comparison with other conventional diagnostic technologies, mNGS has many advantages. First, mNGS covers a wide range of pathogens, such as viruses, bacteria, fungi, and parasites, that can be detected simultaneously, as long as the sample contains detectable DNA or RNA [7]. mNGS is an unbiased sampling method that enables broad identification of known and unexpected pathogens or even the discovery of new organisms [8]. On the other hand, it takes a shorter time for mNGS to report pathogens of infection [7]. The turnaround time for mNGS from receipt of the sample to completion of data analysis varies depending on the sequencing technology, method and bioinformatics analysis method, ranging from 6 hours to 7 days (average 48 hours) [9]. mNGS has shown importance in the identification and subsequent treatment of pathogens in infectious diseases. Several studies have revealed the diagnostic advantages of mNGS over traditional pathogen detection methods [10, 11]. A meta-analysis illustrated that the diagnostic efficacy of mNGS varied depending on the sample, with a sensitivity and specificity of 90 and 86% for blood specimens, 75 and 96% for cerebrospinal fluid, and 84 and 67% for orthopedic samples, respectively [12].

Infection in hematology patients is more severe than that in most other departments because the pathogens are often opportunistic pathogens due to the use of cytotoxic chemotherapy or immunosuppressive therapy and the status of hematopoietic stem cell transplantation (HSCT). However, a systematic review and meta-analysis of the clinical value of mNGS for infection in hematology patients has not been performed. Thus, this meta-analysis focused on systematically assessing the clinical value of mNGS, including diagnostic value and impact on prognosis for infection in hematology patients.

Infection is one of the leading causes of death in hematology due to the need for large amounts of hormones, immunosuppressive drugs, broad-spectrum antibacterial drugs, chemotherapeutic drugs, etc. [37]. mNGS is widely used in hematology as an unbiased pathogen detection technique by detecting DNA or RNA [38]. The advantages of mNGS include faster, more comprehensive and more accurate data analysis, especially in the detection of specific pathogens [7, 39]. However, there are no meta-analyses assessing the practical clinical value of mNGS for infection in hematology patients. We included 22 studies to evaluate the positive detection rate, diagnostic value and clinical influence of mNGS for infection in hematology patients.

In our meta-analysis, mNGS showed a superior positive detection rate compared to CMT in both blood (71.64% vs. 24.82%, P < 0.001), BALF (89.86% vs. 20.78%, P < 0.001) and mixed specimens (82.02% vs. 28.12%, P < 0.001), demonstrating the advantages of mNGS for pathogen detection in a variety of specimens in hematology patients. Different specimens have different positivity rates and diagnostic value for infections. For example, pulmonary infections are one of the major causes of death in patients with hematologic malignancies, and reports have shown that approximately 30% of patients with malignancies have combined pulmonary infections [40], which can reach 70% in HSCT recipients [41]. For lower respiratory tract infections, there are many optional specimens such as transbronchial lung biopsy (TBLB), bronchoalveolar lavage fluid (BALF), and bronchial needle brushing (BB) specimens, blood and so on [42]. The Chinese expert consensus [43] published in 2023 states that mNGS is preferred for BALF in patients with lower respiratory tract infections. And blood specimens have a limited ability to detect pathogens in lower respiratory tract infections [44]. In our study, BALF has a much higher mNGS positivity rate than CMT (OR = 27.80, 95% CI (12.63, 61.19), P < 0.001), illustrating that BALF can be used as a preferred specimen for mNGS sent from patients with pulmonary infections. However, it’s worth mentioning that BALF specimens have their limitations and our findings may exaggerate their advantages. As a kind of open specimen, BALF is susceptible to contamination during the sampling process and can colonize nonpathogens [45]. Therefore, it is important to choose the appropriate specimen to send for testing, direct collection from the site of infection should be preferred. Whether detecting bacteria, fungi or viruses, the positive rate of mNGS was higher than that of CMT, illustrating the advantages of mNGS as a powerful complement to and extension of CMT, which helped clinicians choose targeted antibiotics. However, we cannot ignore the point that it is not uncommon for hematology patients to be tested for non-pathogenic viruses, including EBV, CMV, HSV or JCV, most of which were considered to be colonized or of no clear pathogenic significance [43]. Therefore, although the viral test positivity rate of mNGS is significantly higher than that of CMT (OR = 6.80, P < 0.001), its value for clinical guidance remains to be explored. All in all, considering that there is currently no unified international standard to interpreting the results of mNGS [11], the determination of mNGS reports should fully evaluate the pathogenicity, epidemiology, and bioinformatics information of the detected microorganisms, and at the same time make a comprehensive judgment based on the comprehensive combination of the clinical characteristics of the patients.

In our study, there was no difference in the rate of detection of mNGS in the neutropenia and non-neutropenia groups (79.55% vs. 77.98%, P = 0.70). This was inconsistent with our common viewpoint that mNGS was more advantageous in patients with neutropenia, but given that our meta-analysis only included four studies, there may be bias. The vast majority of the studies we included were premedicated with antibiotics, which have previously been reported to affect the positive of CMT. Compared to blood cultures, mNGS is less affected by widely empirical antibiotics [23, 46]. mNGS targets nucleic acid fragment sequences of pathogens that survive longer in plasma or other tissue fluids. Therefore, mNGS still has satisfactory positive rates despite the use of broad-spectrum antibiotics. All of the above findings support that mNGS remains relatively advantageous for patients with previous antibiotic exposure.

The pooled sensitivity and specificity of mNGS for infectious diseases in hematology patients were 87% (95% CI: 81–91%) and 59% (95% CI: 43–72%), respectively, indicating an excellent diagnostic performance of mNGS for infection in hematology patients. Our results are similar to the data of a retrospective study on the diagnostic performance of mNGS for infection in hematologic patients, in which the sensitivity of mNGS for pathogens was 82.6% and the specificity was 59.0% [47].

The included studies had substantial heterogeneity in sensitivity (I² = 89.72%, P < 0.001) and specificity (I² = 91.12%, P < 0.001) using a random-effects model. We further explored the sources of heterogeneity by subgroup analysis. For sensitivity, the reference standard and the presence or absence of combined neutropenia may contribute to the heterogeneity. Considering that CMT has a high negative rate, for example, the bacterial positive rate of blood cultures in patients with neutropenia is only 10–25% [48]. Therefore, the pooled sensitivity of the clinical diagnosis group was lower than that of the CMT group (85% vs. 91%, P = 0.01). It is worth noting that we categorized the patients into a neutropenia group and an incomplete neutropenia group based on whether all patients had neutropenia. Previous studies have reported a higher rate of positive microbiologic testing in patients with neutropenia. However, our study suggested that the sensitivity was worse in the neutropenia group (76% vs. 89%, P = 0.01). We explained that the clinical presentation of infections in patients with neutropenia is often atypical [20], and it is often difficult to determine the source of infection and select the most direct specimen for sending mNGS for testing, which can reduce the sensitivity of mNGS.

The heterogeneity of specificity was high (I² = 91.12%, P < 0.001). First, subgroup analysis showed that research type contributes to the heterogeneity of specificity. Prospective studies can choose the proper proportion of uninfected and infected populations in their inclusion, while retrospective studies included mostly infected patients and only a minority of noninfected patients. Second, some of the studies chose CMT as the reference standard, which has a high false negative rate, leading to a low specificity [20, 21, 23‐25, 49]. This was also evidenced by our subgroup analysis of the reference standard (70% vs. 32%, P = 0.01). Third, determining a positive threshold for mNGS in clinical applications, but there is currently no unified international standard [8]. In our included studies, there was subjectivity in the interpretation of mNGS results, and the positive reports of mNGS were mostly interpreted according to the subjective judgment of clinicians, which to some extent led to increased bias in the calculation of diagnostic metrics for mNGS.

To assess the clinical value of mNGS for patients with hematologic infections, we evaluated the pooled antibiotic adjustment rate and the pooled effectiveness rate. The antibiotic adjustment rate based on mNGS was as high as 49.6, and 80.9% of patients benefited after antibiotic adjustment. Considering that mNGS is still relatively expensive now, the rate of antibiotic adjustment based on mNGS did not seem to be very cost-effective in the studies we included (only 49.6%). We consider that hematology patients are more likely to be treated by clinicians with a wide range of broad-spectrum antibiotics at the onset of the infection, and the microorganisms detected by mNGS can often be covered by prior anti-microbial regimens. But results of mNGS still provides guidance for clinical treatment, like confirmation of the correctness of the empirical use of antibiotics. And in clinical practice, mNGS is usually a supplemental test after a failed CMT or poor treatment with the antimicrobial regimen it guides, so most patients included are those with difficult-to-obtain pathology or poor treatment, which can make it more difficult to change antibiotic regimes. More prospective studies are needed in the future to explore the optimal timing for sending mNGS.

In the real world, the application of mNGS is still a complementary diagnostic examination after the failure of traditional tests to identify the pathogen. Therefore, more prospective studies should be conducted in the future to explore the sensitivity and specificity of mNGS in the diagnosis of infection in hematology patients. On the other hand, considering that the difficulty of detecting pathogens is different for different types of infection, future studies should also explore the diagnostic value of mNGS in different types of infection, such as bloodstream infection, pulmonary infection, urinary tract infection and other infections.

Currently, mNGS is emerging as a technology that plays an important role in the detection of pathogens in infectious diseases. Our present study demonstrated the value and potential of mNGS in clinical practice in hematology patients with a high detection positive rate. Our subgroup analysis illustrated that neutropenia affects the sensitivity of mNGS. Our analysis revealed the clinical utility of mNGS for infection in hematology patients. At present, mNGS has several disadvantages, such as not being widely available in clinical practice because of its high cost and because the criteria for positivity and interpretation of mNGS are not uniform. In the future, mNGS will be an excellent tool for diagnosing infectionsin hematology patients and helping with treatment.

This study has several limitations. First, most of the studies we included were retrospective studies rather than prospective clinical controlled trials (RCTs), which can introduce bias. Second, some of the studies had relatively small sample sizes and were not convincing enough to detect the diagnostic efficacy of mNGS. Third, there are several other sources of heterogeneity in our pooled sensitivity and specificity. Because of the differences in genome length and sequencing platforms used for different types of microorganisms, it is impossible to establish a uniform positive standard for all microorganisms [50‐52], so we did not perform subgroup analysis for positive criteria of mNGS. However, different positive criteria may affect the diagnostic efficacy of mNGS. In the future, updated guidelines on mNGS positive criteria for clinical practice and how to interpret mNGS results are needed.