The value of second-generation gene sequencing in lung cancer immunotherapy with concurrent infections

The value of second-generation gene sequencing in lung cancer immunotherapy with concurrent infections | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The value of second-generation gene sequencing in lung cancer immunotherapy with concurrent infections Yaqin Zhang, Qiangqiang Zhang, Yan Hu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6906725/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Oct, 2025 Read the published version in BMC Cancer → Version 1 posted 11 You are reading this latest preprint version Abstract Objective To observe the clinical characteristics of patients with lung cancer infection combined with immunotherapy, compare whether there is a difference in the detection of pathogens between the two groups of patients, and explore the diagnostic value of metagenomic next-generation sequencing (mNGS) for patients with lung cancer infection combined with immunotherapy. Methods Sixty-three patients with lung cancer co-infections were included in the First People's Hospital of Jingzhou City from December 2022 to April 2025, and were divided into 24 cases in the immunotherapy group and 39 cases in the non-immunotherapy group according to whether they were treated with immunotherapy or not, and underwent electron bronchoscopy and mNGS testing. We collected the detection of pathogens and various clinical information from the enrolled patients, explored the association between the infection characteristics and clinical characteristics of the patients in the two groups, and compared the detection of pathogens in the two groups. Results The CRP, PCT, IL-6, hospitalization days and hospitalization cost of patients in the immunotherapy group were higher than those in the non-immunotherapy group, and the differences were statistically significant (P < 0.05). In the immunotherapy group, 14 cases of bacteria, 14 cases of fungi, 9 cases of viruses and 18 cases of mixed infections were detected. In the non-immunotherapy group, 28 cases of bacteria, 25 cases of fungi, 14 cases of viruses and 28 cases of mixed infections were detected. The detection rate of fungal mixed infections was higher in the immunotherapy group (20.83%) than in the non-immunotherapy group (2.56%) (X 2 =5.755, P=0.016), with the infection rate of Aspergillus terreus in the immunotherapy group significantly higher than that in the non-immunotherapy group (X 2 =5.119, P=0.024). The differences in the detection rates of bacteria, virus and the rest of mixed infections were not statistically significant when compared with non-immunotherapy (P>0.05). Conclusion The incidence of mixed fungal infections increased after immunotherapy in lung cancer patients, in which the detection rate of Mycobacterium hyopneumoniae was significantly higher in the immunotherapy group than in the non-immunotherapy group. Bacterial infections were dominated by Mycobacterium tuberculosis complex, fungal infections were dominated by Aspergillus fumigatus and Pneumocystis japonicus, and viral infections were dominated by EBV. mNGS demonstrated good applicability in the population undergoing immunotherapy for lung cancer and had a greater impact on treatment. Lung cancer Immunotherapy Pulmonary infection Metagenomic second-generation sequencing pathogen detection Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Lung cancer is one of the common malignant tumors, and its incidence and mortality rates rank among the top malignant tumors worldwide [1] . According to the China Cancer Center, the number of new lung cancer cases in 2015 was 787,000, and the number of deaths was 630,000, and according to the JMIR Health and Detection data, it is predicted that China will attract a large number of new lung cancer patients in 2035 [2,3] .Currently, chemotherapy, radiotherapy, targeted therapy and immunotherapy are the main treatment options for lung cancer patients. In recent years, the emergence of immunotherapy has significantly prolonged the survival and improved the prognosis of patients.Clinical studies such as KEYNOTE-189 and IMpower-150 have found that the objective remission rate of patients treated with immunotherapy in combination with other medications is significantly higher than that of the chemotherapy group alone (P < 0.01) [4, 5] . However, at the same time, immunotherapy can lead to over-activation of the immune system, triggering the occurrence of immune-related adverse events, especially serious infections [6] . Metagenomic next-generation sequencing (mNGS) is a novel test with the advantages of high throughput, short time-consumption, and unbiased identification of common as well as rare pathogenic microorganisms, which can provide reference for early and precise anti-infective treatment, improve the prognosis of patients, and effectively shorten the number of hospital days and hospitalization costs [7] . In this study, we observed the clinical characteristics of patients after lung cancer immunotherapy combined with infection, explored the connection between infection characteristics and clinical characteristics of the two groups of patients, and compared the detection of pathogens in the two groups of patients. 1. Data and Methods 1.1 General From December 2022 to April 2025, the First People's Hospital of Jingzhou City diagnosed and treated 63 patients with lung cancer co-infection, which were divided into 24 cases in the immunotherapy group and 39 cases in the non-immunotherapy group according to whether they underwent immunotherapy or not, among which there were 19 males and 5 females in the immunotherapy group with the ages of 38-77 years old, and 27 males and 12 females in the non-immunotherapy group with the ages of 43-82 years old. age. Inclusion criteria: a. Age ≥18 years old; b. Clear pathological diagnosis of lung cancer by biopsy pathology (fiberoptic bronchoscopy, percutaneous lung puncture or tumor resection surgery, etc.) before treatment; c. All patients were required to meet the diagnostic criteria of community-acquired pneumonia/hospital-acquired pneumonia in China [8] ; d. All patients and/or authorizers had signed the relevant informed consent forms, including the bronchoscopy consent form; e. All patients in each group have completed the relevant pathogenicity testing and mNGS delivery as required; f. Pathogens have not been clarified by traditional laboratory testing methods; g. Empirical anti-infective treatment for ≥3 days (including the time of anti-infective treatment has been in an outside hospital) without remission; h. Patients' clinical medical records, tests and other data are complete. Exclusion criteria: a. Pregnant women or age <18 years old; b. Radiation pneumonia, immunopneumonia, etc. have been diagnosed before the use of immunotherapy or combined with serious lung infections; c. Patients who did not sign the relevant informed consent and did not improve the relevant pathogenicity testing; d. Those who have incomplete clinical medical records, tests and other data. This study was approved by the Medical Ethics Committee of the First People's Hospital of Jingzhou City. 1.2 Method 1.2.1 Observation indicators Basic information, basic diseases, clinical symptoms, blood routine, blood biochemistry, thrombosis index, procalcitonin, C-reactive protein (CRP), interleukin-6 (IL-6), sputum culture, mNGS, G test ((1,3)-β-Dlucan test), and GM test (Galactomannan test), etc., were collected from the included cases. Sputum culture, mNGS, G test ((1)-β-D-Glucan test), and GM test (Galactomannan test) were performed. 1.2.2 mNGS detection method and sputum culture The enrolled patients were operated in strict accordance with the standards of electronic bronchoscopy and alveolar lavage, and the alveolar lavage specimens of the patients were collected and immediately sent to the same third-party testing organization for genome sequencing and biological information analysis, and at the same time, sent to the laboratory of our hospital for microbial culture, G test and GM test. Sputum smear and sputum culture were retained according to the traditional sputum culture method, and the experimental results were observed and recorded. 1.2.3 mNGS detection Collect 0.5ml of alveolar lavage specimen from patients, extract DNA, construct DNA library, and then sequencing. Finally, low quality and short reads were removed, and the human host sequences were identified and excluded from the human reference genome by comparison with the microbial large database for data analysis. 1.2.4 Determination of pathogen detection results mNGS positive determination criteria [9] : analyze the quality of the report, determine the credibility of the results and grade them, according to the clinical characteristics and laboratory examination results, combined with the microbial species detected by mNGS, the relative abundance of the number level of the specific sequence to determine whether it is a pathogenic bacterium, a colonizing bacterium or a background bacterium. If a single specimen cannot be determined, a comprehensive determination can be made by combining several different types of specimens. 1.2.5 Statistics SPSS 25.0 software was used for statistical analysis, and the measurement information was expressed as mean (quartiles) and compared using the rank sum test. Count data were expressed as the number of cases (constitutive ratio) and compared using the chi-square test or Fisher's exact probability method. p < 0.05 was considered as statistically significant difference. 2. Results 2.1 Comparison of Basic Data between Two Groups of Patients According to the inclusion and exclusion criteria, lung cancer patients with perfect electronic bronchoscopy and mNGS testing were divided into immunotherapy and non-immunotherapy groups, in which the immunotherapy group used the immune checkpoint inhibitors (ICIs) Sintillimab in 10 cases, Tislelizumab in 8 cases, Atezolizumab in 1 case, Cadonilimab in 1 case, Serplulimab in 1 case, and Pembrolizumab in 3 cases. monoclonal antibody in 1 case, srolizumab in 1 case, and pabolizumab in 3 cases. There were 24 patients in the immunotherapy group, 19 males and 5 females, with a mean age of 61.25 years; 39 patients in the non-immunotherapy group, 27 males and 12 females, with a mean age of 65.49 years. The mean age of the non-immunotherapy group was higher than that of the immunotherapy group, and the difference was not statistically significant (P=0.072). CRP, PCT, IL-6, hospitalization days and hospitalization cost in the immunotherapy group were higher than those in the non-immunotherapy group, and the difference was statistically significant. The difference between immunotherapy and non-immunotherapy groups in leukocytes, lymphocyte percentage, absolute lymphocyte count, albumin, hemoglobin, D-dimer, G test and GM test was not statistically significant. Observations revealed that the differences between the two groups were not statistically significant in clinical symptoms such as fever, cough, sputum, dyspnea, hemoptysis, and chest pain. The difference between the two groups of patients in mNGS and sputum culture detection of pathogens positive rate were not statistically significant. (See Table 1). Table 1 Basic information of two groups of patients Immunotherapy group （n=24） Non immunotherapy group （n=39） P value Gender[n(%)] male 19(79.2) 27(69.2) 0.560 female 5(20.8) 12(30.8) Age [m(P25,p75)] 61.25 [55.75,67.50] 65.49 [60.00-73.00] 0.072 Underlying disease[n(%)] non-breathing 7(29.17) 13(33.33) 0.638 breathing 17(70.83) 24(61.54) N/A 0 2(5.13) Fever[n(%)] Yes 11(45.83) 15(38.5) 0.564 No 13(55.17) 24(61.5) Cough[n(%)] Yes 19(79.2) 34(87.2) 0.398 No 5(20.8) 5(12.8) Expectoration[n(%)] Yes 16(66.7) 23(59.0) 0.541 No 8(33.3) 16(41.0) Breathing difficulties[n(%)] Yes 11(45.8) 16(41.0) 0.708 No 13(54.2) 23(59.0) Hemoptysis[n(%)] Yes 0 4(10.3) 0.105 No 24(100) 35(89.7) Chest pain[n(%)] Yes 0 4(10.3) 0.105 No 24(100) 35(89.7) Prognosis[n(%)] improved 20(83.3) 33(84.6) 0.892 non-improve 4(16.7) 6(15.4) Hospitalization days[m(P25,p75)/d] 24.17 [14.25,30.0] 18.28 [12.0-21.0] 0.006* Hospitalization expenses[m(P25,p75/)CNY] 21472.41 [14141.31,25314.94] 17759.20 [10311.87,20930.28] 0.047* White blood cell count 7.0 5.97 0.506 [m(P25,p75)，10⁹/L] [4.04,8.17] [3.99,7.75] Percentage of neutrophils[m(P25,p75),%] 73.42 [67.30,80.20] 69.74 [60.10,78.10] 0.255 Percentage of lymphocytes[m(P25,p75)，10⁹/L] 16.95 [9.13,22.58] 19.49 [13.50,22.80] 0.323 Absolute lymphocyte count[m(P25,p75)，10⁹/L] 1.02 [0.55,1.42] 1.07 [0.59,1.25] 0.869 Hemoglobin [m(P25,p75)，g/L] 98.63 [79.25,116.50] 109.59 [101.0,121.0] 0.054 Albumin [m(P25,p75)，g/L] 33.41 [28.83,37.53] 36.17 [30.90,41.20] 0.086 D- Dimer [m(P25,p75)，mg/L] 2.86 [0.40,2.70] 1.52 [0.37,1.44] 0.149 CRP [m(P25,p75)，mg/L] 94.41 [23.05,133.40] 51.18 [8.68,96.89] 0.028* PCT [m(P25,p75)，ng/L] 5.53 [0.11,0.43] 0.19 [0.02,0.27] 0.028* IL-6 [m(P25,p75)，pg/mL] 126.84 [31.08,225.65] 44.80 [12.97,60.17] 0.018* (1,3)-β-D-Glucan test [m(P25,p75)，pg/mL] 47.04 [37.5,58.80] 49.53 [37.5,59.96] 0.833 Galactomannan test[m(P25,p75)，S/CO] 0.53 [0.11,0.27] 0.29 [0.10,0.33] 0.940 mNGS positive 23(95.83) 38(97.44) 0.725 negative 1(4.17) 1(2.56) Sputum culture[n(%)] positive 11(45.8) 12(30.8) 0.228 negative 13(54.2) 27(69.2) Note : *P＜0.05. 2.2 mNGS result evaluation 2.2.1 Distribution of pathogens detected by mNGS A total of 63 eligible specimens were sent for testing in this study, of which 61 were positive. Among them, a total of 25 pathogens and 55 strains were detected by mNGS in the immunotherapy group, with 41.81% (23/55) of bacteria, 36.36% (20/55) of fungi, and 21.81% (12/55) of viruses. The top five pathogens were 7 strains of Pneumocystis jiroveci, 7 strains of Aspergillus fumigatus, 7 strains of EBV, 4 strains of Mycobacterium tuberculosis complex, 3 strains of Pseudomonas aeruginosa, and 3 strains of Aspergillus terreus. A total of 40 pathogens and 112 strains were detected by mNGS in the non-immunotherapy group, with 40.18% (45/112) bacteria, 37.50% (42/112) fungi, 20.54% (23/112) viruses, and 1.79% (2/112) atypical pathogens, including one case each of Mycoplasma pneumoniae and Legionella pneumophila. The top five pathogens were Pseudomonas aeruginosa in 12 cases, Aspergillus fumigatus in 10 cases, Aspergillus flavus in 10 cases, Pneumocystis japonicus in 9 cases, and EBV in 7 cases (see Figures 1,2,3). 2.2.2 Characteristics of pathogens co infected in two groups of patients detected by mNGS In 63 patients with lung cancer co-infections, the characteristics of infections were compared between the immunotherapy group (n=24) and the non-immunotherapy group (n=39). There was no statistically significant difference in the incidence of infections and the rates of bacterial, fungal and viral infections between the two groups. Table 2 Composition of Pathogens Detected in mNGS Positive Patients Etiology Immunotherapy group Non immunotherapy group P value Number of case（n=24） % Number of case（n=39） % Bacteria 3 12.5 4 10.26 0.783 Fungus 0 0 4 10.26 0.105 Virus 2 8.33 0 0 0.067 Mixed 18 75 28 71.79 0.781 Residual categories 0 0 2 5.13 0.260 Note : *P＜0.05. For mixed infections with multiple pathogens, there was no statistical difference in the rates of mixed infections, mixed infections containing bacteria and fungi, mixed infections containing bacteria or fungi and mixed infections with viruses between the two groups. Among the mixed infections containing bacteria or fungi were divided into simple mixed infections of multiple fungi, simple mixed infections of multiple bacteria, mixed infections of bacteria and viruses, and mixed infections of fungi and viruses, in which the rate of simple mixed infections of multiple fungi in the immunotherapy group was found to be significantly higher than that in the non-immunotherapy group (20.83% vs. 2.56%, p=0.026) (see Figure 4, Table 3). Table 3 Comparison of mNGS with and without immunotherapy for mixed infections in patients Etiology Immunotherapy group Non immunotherapy group P value Number of case （n=24） % Number of case（n=39） % Mixed infection 18 75 28 71.79 0.781 Mixed infection containing bacteria and fungi 7 29.1 14 35.90 0.582 Bacteria+Fungus 5 20.8 8 20.51 0.976 Bacteria+Fungus+Virus 2 8.33 6 15.38 0.414 Mixed infection containing bacteria or fungi 11 45.8 13 33.33 0.321 Bacteria 2 8.33 6 15.38 0.414 Fungus 5 20.8 1 2.56 0.016* Bacteria+Virus 2 8.33 2 5.13 0.612 Fungus+Virus 2 8.33 4 10.26 0.801 Mixed infection of viruses 0 0 1 2.56 0.429 Note : *P＜0.05. Statistical differences in the infection rates of common bacteria in this study were found between the two groups. There was no statistical difference in the infection rates of Pseudomonas aeruginosa, Streptococcus pneumoniae, Staphylococcus aureus, Mycobacterium tuberculosis complex, Acinetobacter baumannii and Haemophilus influenzae between the two groups (see Figure 6). Statistics on the infection rate of common fungi in this study differed between the two groups. The infection rate of Aspergillus terreus (X2=5.119, P=0.024) was significantly higher in the immunotherapy group than in the non-immunotherapy group. There was no statistically significant difference in the infection rates of Aspergillus fumigatus, Aspergillus flavus, Pneumocystis japonicus, Aspergillus niger and Candida albicans between the two groups (see Figure 7). Statistical differences in the infection rates of common viruses in this study between the two groups. There was no statistical difference in the infection rates of EBV, cytomegalovirus, novel coronavirus, human adenovirus group B, human herpesvirus type 1 and influenza A virus H1N1 between the two groups (see Figure 8). 3. Discussions Lung cancer is one of the malignant tumors with high morbidity and mortality rates worldwide, seriously endangering human life and health. According to statistics, the number of new lung cancer cases is as high as 1.8 million and the number of deaths reaches about 1.6 million every year in the world [10]. It has been found that the traditional chemotherapeutic regimen, although able to reduce tumor size and relieve symptoms in a short time, is prone to drug resistance [11] . The emergence of immunotherapy has brought new hope to patients with advanced lung cancer, as Pual Ehrlich put forward the doctrine of “immunosurveillance” in 1909, which opened a new chapter of immunotherapy, and the first immunotherapeutic drug, Ipilimumab, was approved in the United States in 2011 for the treatment of malignant tumors [12] . Currently, the immunosuppressants that have been approved for the treatment of lung cancer in China include Sintilimab, Tislelizumab and Pembrolizumab [13] . The principle of immunotherapy is that immunosuppressants specifically interact with Programmed Cell Death Protein 1 (PD-1), Programmed Death-Ligand 1 (PD-L1), and Cytotoxic T-lymphocyte-Associated Antigen-4 (Cytotoxic T-). Lymphocyte-Associated Protein 4 (CTLA-4) binding, destroying the immune tolerance of tumor cells and restarting the immune system to kill tumor cells. However, at the same time, immunosuppressants also non-selectively disrupt the negative regulation in immune regulation, and the immune system is over-activated, releasing immune cells and immune factors, which destroys the alveolar epithelial cells, leading to an increased incidence of infections in lung cancer patients [14] . A retrospective cohort study was designed to assess the incidence of serious infections in lung cancer patients after treatment with ICIs and to further analyze the independent risk factors associated with them. The study found that 191 (26.86%) of the 711 lung cancer patients ultimately enrolled developed serious infections during the follow-up period. The main site of infection was the lungs (75.61%), and the aetiologic analysis showed that bacterial infections were predominant (82.05%) predominantly, followed by Mycobacterium tuberculosis (6.47%), viral (4.98%) and fungal (3.48%) infections. Chronic obstructive pulmonary disease (COPD), asthma, systemic glucocorticoid use, low lymphocyte counts and low CD4/CD8 ratio were identified as significant independent risk factors [15] . Therefore, focused monitoring of these high-risk patients and timely prophylactic treatment should be performed in clinical management to reduce the incidence of infection and improve prognosis. mNGS is a novel sequencing technology with broad coverage and no bias, and its sensitivity and specificity are superior to traditional pathogen detection methods [16] . It has been reported that mNGS has less impact on the prophylactic antibiotic use population, can more accurately detect pathogens in mixed and rare infections, and its results may accelerate clinical decision-making in immunocompromised populations [17] . In this study, by comparing the number of hospitalization days and hospitalization costs between the two groups of patients, it was found that the number of hospitalization days and hospitalization costs of patients in the immunotherapy group were significantly higher than those in the non-immunotherapy group. And the related inflammatory indexes, such as CRP, PCT, IL-6, etc., were compared between the two groups, and it was found that the immunotherapy group was higher than the non-immunotherapy group, and the difference was statistically significant. This indicates that the condition of patients with lung cancer immunotherapy combined with lung infection progresses rapidly, and the disability and mortality rates are higher, so that respiratory failure and severe pneumonia occur, and even death occurs, which causes a serious economic burden to the patient's family [18] . Therefore, after immunotherapy for lung cancer, patients should be monitored early for relevant inflammatory indexes and mNGS to effectively identify complex pathogens and reasonably use antibiotics, so as to improve the prognosis, shorten the treatment time and cost, and accelerate the recovery of patients. In this study bacteria and fungi were most frequently detected in patients in the immunotherapy group, where the most frequently detected pathogen among bacteria was Mycobacterium tuberculosis complex.FAN et al [19] summarized the relevant case studies in the last few years, where 8 cases were treated with Nivolumab and 6 with Pembrolizumab, all patients were not screened for latent tuberculosis infection (LTBI) before immunotherapy, and it was not clear whether the infected tuberculosis was primary or secondary. None of the patients had been screened for latent tuberculosis infection (LTBI) before immunotherapy, and it was not clear whether the TB infection was primary or secondary. Tuberculosis was diagnosed during the course of immunotherapy and regular anti-tuberculosis treatment was administered. 14 patients were suggested to have reactivation of tuberculosis as a well-defined adverse effect [20] . It has also been found that treatment of the tumor itself (e.g., chemotherapy, etc.) may also be a source of immunosuppression, thereby increasing the risk of TB. Among solid tumors, lung cancer has the highest incidence of TB reactivation [21,22] . The exact mechanism leading to TB reactivation in patients is unclear and requires further study. However, it has been found that in PD-1-deficient mice and PD-1-blocked populations, increased interferon production by CD4+ T cells after infection with Mycobacterium tuberculosis promotes bacterial replication and tissue destruction [23] . Therefore, the application of ICIs during immunotherapy can complicate the infection, and the possibility of tuberculosis should be prioritized when new lesions appear in clinical workups, especially in patients with lung cancer, lymphoma, or a history of exposure to tuberculosis, and timely LTBI screening or mNGS testing should be necessary, which is essential for the rapid diagnosis of tuberculosis and adjustment of the treatment regimen. Lung fungal infection is one of the common complications in lung cancer patients, which not only affects the life and health of patients, but also can hinder the treatment process, thus affecting the therapeutic effect [24] . A study enrolled 167 patients with non-small cell lung cancer who were concurrently treated with Nivolumab immunotherapy, and found that 33 (19.2%) patients developed infections, including 25 bacterial infections, 2 fungal infections, and 6 viral infections [25] . Another report found a case of acute exacerbation of pre-existing chronic progressive pulmonary aspergillosis after receiving 20 courses of nabulizumab [26] . In this study, we found a significantly higher rate of simple mixed infections of multiple fungi in lung cancer patients undergoing immunotherapy (20.83% vs. 2.56%, p=0.016), with a higher detection rate of Aspergillus hyodysenteriae than in the non-immunotherapy group. Although there was no statistically significant difference in the infection rates of Pneumocystis jiroveci and Aspergillus fumigatus between the two groups, an elevated detection rate could be detected in the immunotherapy group compared to the non-immunotherapy group. It has been reported that ICIs treatment can induce acute exacerbation of chronic invasive pulmonary aspergillosis as well as fungal sinusitis [27] .ICIs treatment leads to an abnormal immune state of the organism, causing excessive immune response of colonized fungi, and promoting the growth of fungi, which is in line with this study. And in clinical practice, new fungal infections during immunotherapy are sometimes more difficult to distinguish from tumor progression. Therefore, clinicians should monitor early during immunotherapy and need to be alert to the emergence of fungal infections when patients develop infections and use antifungal drugs reasonably. 4. Conclusion In this study, the incidence of mixed fungal infections was increased in lung cancer patients undergoing immunotherapy, especially those of Mycobacterium smegmatis. Bacterial infections were dominated by Mycobacterium tuberculosis complex, fungal infections were dominated by Aspergillus fumigatus and Pneumocystis japonicus, and viral infections were dominated by EBV. mNGS demonstrated good applicability in the population of lung cancer undergoing immunotherapy and had a large impact on treatment. However, there are some limitations in this study. The sample size is small, resulting in some risk of bias in some data, and mNGS also suffers from adulteration of background bacteria, low detection rate of intracellular bacteria and thick-walled microorganisms. In this study, we proposed that the incidence of infection in lung cancer patients after immunotherapy was increased, and the incidence of mixed fungal infection was significantly higher. Therefore, clinical workers should pay attention to identifying the type of infection occurrence in the process of diagnosis and treatment, and timely apply mNGS and other detection means to adjust the anti-infection treatment program and improve the prognosis. Abbreviations mNGS metagenomic next-generation sequencing ICIs immune checkpoint inhibitors CRP C-reactive protein interleukin-6 (IL-6) IL-6 interleukin-6 PCT Procalcitonin GM (1,3)-β-D-Glucan G Galactomannan HHV-4 Epstein-Barr virus HHV-5 Cytomegalovirus HHV-1 Human herpesvirus 1 HHV-6 Human herpesvirus 6B HHV-7 Human herpesvirus 7 IAV H1N1 Influenza A virus subtype H1N1 IAV H3N2 Influenza A virus subtype H3N2 SARS-CoV-2 Severe acute respiratory syndrome coronavirus 2 HAdV-B Human mastadenovirus B EV-C Enterovirus C HPyV5 Human polyomavirus 5 RSV Respiratory syncytial virus HSV-1 Herpes simplex virus 1 PD-1 Programmed Cell Death Protein 1 PD-L1 Programmed Death Ligand 1 CTLA-4 Cytotoxic T-Lymphocy-Associated Protein 4 COPD Chronic obstructive pulmonary disease LTBI latent tuberculosis infection Declarations Acknowledgements Not applicable. Authors ´ contributions YQZ and QQZ conceived and designed the study. YQZ was a major contribu tor in writing the manuscript and performed part of the data analysis. QQZ performed the major part of data collection and analysis. YQZ and QQZ revised the manuscript with assistance from HY. All authors reviewed and approved the final manuscript. Funding This work was supported by the "Medical and Health Talent Training Program" (023YZ09) of the Medical Department of Yangtze University's Science and Technology Assistance to Tibet. Data availability The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Ethics approval and consent to participate This study achieved formal approval from the Ethics Committee of The First Affiliated Hospital of Yangtze University (ethical number: YJ202427).This study was retrospective, and the Ethics Committee of The First Affiliated Hospital of Yangtze Universitl waived the requirement of extra patient consent statements because written informed consent was obtained from all patients admitted to allow their medical records to be used in clinical observational studies.All identifying information was removed to protect patient confidentiality according to the requirement of the Ethics Committee of The First Affiliated Hospital of Yangtze University. This study was designed and conducted in accord ance with the Declaration of Helsinki and local institutional standards. Consent for publication Not applicable. Competing interests The authors declare no competing interests. References Hayashi H, Nakagawa K. 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Diagnostic value of metagenomic next-generation sequencing of bronchoalveolar lavage fluid for the diagnosis of suspected pneumonia in immunocompromised patients. BMC Infect Dis. 2022;22(1):416. Tang W, Zhang Y, Luo C, et al. Clinical Application of Metagenomic Next-Generation Sequencing for Suspected Infections in Patients With Primary Immunodeficiency Disease. Front Immunol. 2021;12:696403. Fan N, Jiang DR, Wang Y. Progress in the treatment of PD-1/PD-L1 inhibitors in lung cancer complicated with pulmonary tuberculosis disease. Lab Med Clin. 2025;22(7):998–1002. Picchi H, Mateus C, Chouaid C, et al. Infectious complications associated with the use of immune checkpoint inhibitors in oncology: reactivation of tuberculosis after anti PD-1 treatment. Clin Microbiol Infect. 2018;24(3):216–8. Giller D, Giller B, Scherbakova G, et al. Extensive tracheal resection in lung cancer and tuberculosis: a case report. BMC Pulm Med. 2020;20(1):197. Dobler CC, Cheung K, Nguyen J et al. Risk of tuberculosis in patients with solid cancers and haematological malignancies: a systematic review and meta-analysis. Eur Respir J, 2017,50(2). Barber DL, Sakai S, Kudchadkar RR et al. Tuberculosis following PD-1 blockade for cancer immunotherapy. Sci Transl Med, 2019,11(475). Shimizu T, Okachi S, Imai N, et al. Risk factors for pulmonary infection after diagnostic bronchoscopy in patients with lung cancer. Nagoya J Med Sci. 2020;82(1):69–77. Fujita K, Kim YH, Kanai O, et al. Emerging concerns of infectious diseases in lung cancer patients receiving immune checkpoint inhibitor therapy. Respir Med. 2019;146:66–70. Lu WY, Zhang L, Li Y, et al. Recommendation of diagnosis and management for the infection related to immune checkpoint inhibitors. Chin lung cancer. 2019;22(10):666–70. Morelli T, Fujita K, Redelman-Sidi G, et al. Infections due to dysregulated immunity: an emerging complication of cancer immunotherapy. Thorax. 2022;77(3):304–11. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 23 Oct, 2025 Read the published version in BMC Cancer → Version 1 posted Editorial decision: Revision requested 12 Aug, 2025 Reviews received at journal 07 Aug, 2025 Reviewers agreed at journal 30 Jul, 2025 Reviews received at journal 29 Jul, 2025 Reviewers agreed at journal 29 Jul, 2025 Reviewers agreed at journal 29 Jul, 2025 Reviewers invited by journal 29 Jul, 2025 Editor invited by journal 27 Jul, 2025 Editor assigned by journal 20 Jun, 2025 Submission checks completed at journal 19 Jun, 2025 First submitted to journal 19 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6906725","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":493314763,"identity":"6dbbc420-45b2-4962-b9cd-51eaa3735364","order_by":0,"name":"Yaqin Zhang","email":"","orcid":"","institution":"The First Affiliated Hospital of Yangtze University","correspondingAuthor":false,"prefix":"","firstName":"Yaqin","middleName":"","lastName":"Zhang","suffix":""},{"id":493314764,"identity":"ed336699-a3d3-41a5-9a9f-dac0bbcc6481","order_by":1,"name":"Qiangqiang Zhang","email":"","orcid":"","institution":"The First Affiliated Hospital of Yangtze University","correspondingAuthor":false,"prefix":"","firstName":"Qiangqiang","middleName":"","lastName":"Zhang","suffix":""},{"id":493314765,"identity":"12e48ebc-8eed-4d94-b3e9-3443af40d0fa","order_by":2,"name":"Yan Hu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5UlEQVRIiWNgGAWjYBACAwbmBgiLB8j4YGBjR4QWRpgWxgbGGQVpyaRpYeb5cAjGxQ3M2RsbHxf8uSNv3nOw8bGNwQFmBvbDRzfg02LZc7DZeGbbM8M5ZxubjXMM7vAx8KSl3cDrsBuJbdK8DYcZZ/AztknnGDxjZpDgMcOv5f7D9t88fw7bA7W0/7YwOMzYQFDLDcY2Zh62w4kzeBvbmBmI0nImsVmat+1Z8gyeg82SPQZpyWwE/XL88MHPPH/u2M7gST744ccfGzt+9sPH8GqBggMIJhsRytG0jIJRMApGwShABwA9FU9WthQiWwAAAABJRU5ErkJggg==","orcid":"","institution":"The First Affiliated Hospital of Yangtze University","correspondingAuthor":true,"prefix":"","firstName":"Yan","middleName":"","lastName":"Hu","suffix":""}],"badges":[],"createdAt":"2025-06-16 14:53:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6906725/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6906725/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12885-025-15045-4","type":"published","date":"2025-10-23T16:16:36+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":88099996,"identity":"5efbf24f-6b52-47ae-8aa1-f064856cb49f","added_by":"auto","created_at":"2025-08-01 11:19:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":232578,"visible":true,"origin":"","legend":"\u003cp\u003eFrequency statistics of bacterial infections in two groups of patients\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6906725/v1/a494b9e8ea9faec8c774d109.png"},{"id":88097222,"identity":"57a49dfd-1b35-4248-9815-d3f4aba37060","added_by":"auto","created_at":"2025-08-01 11:03:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":127689,"visible":true,"origin":"","legend":"\u003cp\u003eFrequency statistics of fungal infections in two groups of patients\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6906725/v1/95440cc53af250bd9c8d9c82.png"},{"id":88098887,"identity":"5b86513f-621c-4619-8587-2949c63e00e4","added_by":"auto","created_at":"2025-08-01 11:11:32","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":97658,"visible":true,"origin":"","legend":"\u003cp\u003eFrequency statistics of viral infections in two groups of patients\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003eHHV-4(Epstein-Barr virus); HHV-5(Cytomegalovirus); HHV-1(Human herpesvirus 1); HHV-6B(Human herpesvirus 6B); HHV-7(Human herpesvirus 7); IAV H1N1(Influenza A virus subtype H1N1); IAV H3N2(Influenza A virus subtype H3N2); SARS-CoV-2(Severe acute respiratory syndrome coronavirus 2); HAdV-B(Human mastadenovirus B); EV-C(Enterovirus C); HPyV5(Human polyomavirus 5); RSV(Respiratory syncytial virus); HSV-1(Herpes simplex virus 1).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6906725/v1/f012047bf441ca98eaa267e5.png"},{"id":88098888,"identity":"3d879e28-5b6c-46e1-a863-0ed0cfd8fd1e","added_by":"auto","created_at":"2025-08-01 11:11:33","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":104486,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of mixed infections in patients with or without immunotherapy\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6906725/v1/e4de7f9944fd436343896c3e.png"},{"id":88101215,"identity":"7f4adda3-3730-4ea2-bbca-2e200bf2c2a8","added_by":"auto","created_at":"2025-08-01 11:27:33","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":114926,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of Partial Bacterial Infections between Two Groups of Patients\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e:The infection rate of Pseudomonas aeruginosa was 30.77% vs 12.50%, p=0.098; The infection rate of Streptococcus pneumoniae was 15.38% vs 8.33%; p=0.414； The infection rate of Staphylococcus aureus was 12.82% vs 8.33%; p=0.582；Infection rate of Mycobacterium tuberculosis complex; 10.26% vs 16.67%，p=0.458； Baumann Acinetobacter infection rate, 5.13% vs 0%, p=0.260; The infection rate of Haemophilus influenzae was 12.82% vs 4.17%, p=0.256.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6906725/v1/8d1ce4bc6e8966aea0793c55.png"},{"id":88098890,"identity":"80b73cc2-4420-4187-8775-a8ba8352e349","added_by":"auto","created_at":"2025-08-01 11:11:33","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":94356,"visible":true,"origin":"","legend":"\u003cp\u003ecompares the infection rates of some fungi in two groups of patients\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e:The infection rate of Aspergillus fumigatus was 25.64% vs 29.17%, p=0.759; The infection rate of Aspergillus flavus was 25.64% vs 8.33%; p=0.089； The infection rate of Pneumocystis jirovecii was 23.07% vs 29.17%; p=0.590；Infection rate of Aspergillus niger; 5.13% vs 0%，p=0.260； Candida albicans infection rate, 12.82% vs 0%, p=0.068; Aspergillus infection rate, 0% vs 12.5%, p=0.024.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-6906725/v1/aefef836b7f0406c7a6bedea.png"},{"id":88101216,"identity":"14b3941e-0866-42f3-ad20-c12363af65bf","added_by":"auto","created_at":"2025-08-01 11:27:33","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":77947,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of Partial Virus Infection Rates between Two Groups of Patients\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e:EB virus infection rate, 19.75% vs 29.17%, p=0.298; Cytomegalovirus infection rate, 2.56% vs 8.33%; p=0.296； The infection rate of novel coronavirus was 2.56% vs 8.33%; p=0.296；Infection rate of human adenovirus B group; 2.56% vs 4.17%，p=0.725； Human herpesvirus type 1 infection rate, 5.13% vs 0%, p=0.260; The infection rate of H1N1 influenza virus is 5.13% vs 0%, p=0.260.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-6906725/v1/98bd9b0f568980b3b9d5be15.png"},{"id":94490775,"identity":"256289be-3cbd-44c0-9a8d-d48d934d94d1","added_by":"auto","created_at":"2025-10-27 17:15:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1701354,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6906725/v1/7a240d30-40ba-4cf4-a856-e0dd92048a66.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The value of second-generation gene sequencing in lung cancer immunotherapy with concurrent infections","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLung cancer is one of the common malignant tumors, and its incidence and mortality rates rank among the top malignant tumors worldwide \u003csup\u003e[1]\u003c/sup\u003e. According to the China Cancer Center, the number of new lung cancer cases in 2015 was 787,000, and the number of deaths was 630,000, and according to the JMIR Health and Detection data, it is predicted that China will attract a large number of new lung cancer patients in 2035\u003csup\u003e[2,3]\u003c/sup\u003e.Currently, chemotherapy, radiotherapy, targeted therapy and immunotherapy are the main treatment options for lung cancer patients. In recent years, the emergence of immunotherapy has significantly prolonged the survival and improved the prognosis of patients.Clinical studies such as KEYNOTE-189 and IMpower-150 have found that the objective remission rate of patients treated with immunotherapy in combination with other medications is significantly higher than that of the chemotherapy group alone (P \u0026lt; 0.01) \u003csup\u003e[4, 5]\u003c/sup\u003e. However, at the same time, immunotherapy can lead to over-activation of the immune system, triggering the occurrence of immune-related adverse events, especially serious infections\u003csup\u003e[6]\u003c/sup\u003e. Metagenomic next-generation sequencing (mNGS) is a novel test with the advantages of high throughput, short time-consumption, and unbiased identification of common as well as rare pathogenic microorganisms, which can provide reference for early and precise anti-infective treatment, improve the prognosis of patients, and effectively shorten the number of hospital days and hospitalization costs \u003csup\u003e[7]\u003c/sup\u003e. In this study, we observed the clinical characteristics of patients after lung cancer immunotherapy combined with infection, explored the connection between infection characteristics and clinical characteristics of the two groups of patients, and compared the detection of pathogens in the two groups of patients.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"1. Data and Methods","content":"\u003cp\u003e\u003cstrong\u003e1.1 General\u0026nbsp;\u003c/strong\u003eFrom December 2022 to April 2025, the First People's Hospital of Jingzhou City diagnosed and treated 63 patients with lung cancer co-infection, which were divided into 24 cases in the immunotherapy group and 39 cases in the non-immunotherapy group according to whether they underwent immunotherapy or not, among which there were 19 males and 5 females in the immunotherapy group with the ages of 38-77 years old, and 27 males and 12 females in the non-immunotherapy group with the ages of 43-82 years old. age.\u0026nbsp;\u003cstrong\u003eInclusion criteria:\u003c/strong\u003e a. Age ≥18 years old; b. Clear pathological diagnosis of lung cancer by biopsy pathology (fiberoptic bronchoscopy, percutaneous lung puncture or tumor resection surgery, etc.) before treatment; c. All patients were required to meet the diagnostic criteria of community-acquired pneumonia/hospital-acquired pneumonia in China\u003csup\u003e[8]\u003c/sup\u003e; d. All patients and/or authorizers had signed the relevant informed consent forms, including the bronchoscopy consent form; e. All patients in each group have completed the relevant pathogenicity testing and mNGS delivery as required; f. Pathogens have not been clarified by traditional laboratory testing methods; g. Empirical anti-infective treatment for ≥3 days (including the time of anti-infective treatment has been in an outside hospital) without remission; h. Patients' clinical medical records, tests and other data are complete.\u0026nbsp;\u003cstrong\u003eExclusion criteria:\u0026nbsp;\u003c/strong\u003ea. Pregnant women or age \u0026lt;18 years old; b. Radiation pneumonia, immunopneumonia, etc. have been diagnosed before the use of immunotherapy or combined with serious lung infections; c. Patients who did not sign the relevant informed consent and did not improve the relevant pathogenicity testing; d. Those who have incomplete clinical medical records, tests and other data. This study was approved by the Medical Ethics Committee of the First People's Hospital of Jingzhou City.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.2 Method \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.2.1 Observation indicators\u0026nbsp;\u003c/strong\u003eBasic information, basic diseases, clinical symptoms, blood routine, blood biochemistry, thrombosis index, procalcitonin, C-reactive protein (CRP), interleukin-6 (IL-6), sputum culture, mNGS, G test ((1,3)-β-Dlucan test), and GM test (Galactomannan test), etc., were collected from the included cases. Sputum culture, mNGS, G test ((1)-β-D-Glucan test), and GM test (Galactomannan test) were performed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.2.2 mNGS detection method and sputum culture\u0026nbsp;\u003c/strong\u003eThe enrolled patients were operated in strict accordance with the standards of electronic bronchoscopy and alveolar lavage, and the alveolar lavage specimens of the patients were collected and immediately sent to the same third-party testing organization for genome sequencing and biological information analysis, and at the same time, sent to the laboratory of our hospital for microbial culture, G test and GM test. Sputum smear and sputum culture were retained according to the traditional sputum culture method, and the experimental results were observed and recorded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.2.3 mNGS detection\u0026nbsp;\u003c/strong\u003eCollect 0.5ml of alveolar lavage specimen from patients, extract DNA, construct DNA library, and then sequencing. Finally, low quality and short reads were removed, and the human host sequences were identified and excluded from the human reference genome by comparison with the microbial large database for data analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.2.4 Determination of pathogen detection results\u0026nbsp;\u003c/strong\u003emNGS positive determination criteria\u003csup\u003e[9]\u003c/sup\u003e: analyze the quality of the report, determine the credibility of the results and grade them, according to the clinical characteristics and laboratory examination results, combined with the microbial species detected by mNGS, the relative abundance of the number level of the specific sequence to determine whether it is a pathogenic bacterium, a colonizing bacterium or a background bacterium. If a single specimen cannot be determined, a comprehensive determination can be made by combining several different types of specimens.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.2.5 Statistics\u0026nbsp;\u003c/strong\u003eSPSS 25.0 software was used for statistical analysis, and the measurement information was expressed as mean (quartiles) and compared using the rank sum test. Count data were expressed as the number of cases (constitutive ratio) and compared using the chi-square test or Fisher's exact probability method. p \u0026lt; 0.05 was considered as statistically significant difference.\u003c/p\u003e"},{"header":"2. Results","content":"\u003cp\u003e\u003cstrong\u003e2.1 Comparison of Basic Data between Two Groups of Patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccording to the inclusion and exclusion criteria, lung cancer patients with perfect electronic bronchoscopy and mNGS testing were divided into immunotherapy and non-immunotherapy groups, in which the immunotherapy group used the immune checkpoint inhibitors (ICIs) Sintillimab in 10 cases, Tislelizumab in 8 cases, Atezolizumab in 1 case, Cadonilimab in 1 case, Serplulimab in 1 case, and Pembrolizumab in 3 cases. monoclonal antibody in 1 case, srolizumab in 1 case, and pabolizumab in 3 cases. There were 24 patients in the immunotherapy group, 19 males and 5 females, with a mean age of 61.25 years; 39 patients in the non-immunotherapy group, 27 males and 12 females, with a mean age of 65.49 years. The mean age of the non-immunotherapy group was higher than that of the immunotherapy group, and the difference was not statistically significant (P=0.072). CRP, PCT, IL-6, hospitalization days and hospitalization cost in the immunotherapy group were higher than those in the non-immunotherapy group, and the difference was statistically significant. The difference between immunotherapy and non-immunotherapy groups in leukocytes, lymphocyte percentage, absolute lymphocyte count, albumin, hemoglobin, D-dimer, G test and GM test was not statistically significant. Observations revealed that the differences between the two groups were not statistically significant in clinical symptoms such as fever, cough, sputum, dyspnea, hemoptysis, and chest pain. The difference between the two groups of patients in mNGS and sputum culture detection of pathogens positive rate were not statistically significant. (See Table 1).\u003c/p\u003e\n\u003cp\u003eTable 1 Basic information of two groups of patients\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"598\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 201px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Immunotherapy group\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;（n=24）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eNon immunotherapy group\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;（n=39）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;P value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eGender[n(%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003emale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp; 19(79.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 27(69.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 0.560 \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003efemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp; 5(20.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 12(30.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003cp\u003e[m(P25,p75)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;61.25\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; [55.75,67.50]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;65.49\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;[60.00-73.00] \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 0.072 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eUnderlying disease[n(%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003enon-breathing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;7(29.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 13(33.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 0.638\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003ebreathing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;17(70.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 24(61.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 2(5.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eFever[n(%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;11(45.83) \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 15(38.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;0.564 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;13(55.17) \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 24(61.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eCough[n(%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;19(79.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 34(87.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;0.398\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;5(20.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 5(12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eExpectoration[n(%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;16(66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 23(59.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;0.541\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;8(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 16(41.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eBreathing difficulties[n(%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;11(45.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 16(41.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;0.708\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;13(54.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 23(59.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eHemoptysis[n(%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 4(10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;0.105\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;24(100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 35(89.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eChest pain[n(%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 4(10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;0.105\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;24(100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 35(89.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003ePrognosis[n(%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eimproved\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;20(83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 33(84.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;0.892\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003enon-improve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e4(16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 6(15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eHospitalization days[m(P25,p75)/d]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp; 24.17\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e[14.25,30.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 18.28\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;[12.0-21.0] \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;0.006* \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eHospitalization expenses[m(P25,p75/)CNY]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e21472.41\u003c/p\u003e\n \u003cp\u003e[14141.31,25314.94]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e17759.20\u003c/p\u003e\n \u003cp\u003e[10311.87,20930.28]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.047*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eWhite blood cell count\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 5.97 \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; 0.506\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e[m(P25,p75)，10⁹/L]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e[4.04,8.17]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;[3.99,7.75]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003ePercentage of neutrophils[m(P25,p75),%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;73.42\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;[67.30,80.20]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;69.74\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; [60.10,78.10]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; 0.255\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003ePercentage of lymphocytes[m(P25,p75)，10⁹/L]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 43px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;16.95\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;[9.13,22.58]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;19.49\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; [13.50,22.80]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; 0.323\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eAbsolute lymphocyte count[m(P25,p75)，10⁹/L]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;1.02\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;[0.55,1.42]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;1.07\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; [0.59,1.25]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; 0.869\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eHemoglobin\u003c/p\u003e\n \u003cp\u003e[m(P25,p75)，g/L]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;98.63\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; [79.25,116.50]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e109.59\u003c/p\u003e\n \u003cp\u003e[101.0,121.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; 0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eAlbumin\u003c/p\u003e\n \u003cp\u003e[m(P25,p75)，g/L]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;33.41\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; [28.83,37.53]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e36.17\u003c/p\u003e\n \u003cp\u003e[30.90,41.20]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; 0.086\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eD-\u003c/strong\u003eDimer\u003c/p\u003e\n \u003cp\u003e[m(P25,p75)，mg/L]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;2.86\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; [0.40,2.70]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e1.52\u003c/p\u003e\n \u003cp\u003e[0.37,1.44]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; 0.149\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003cp\u003e[m(P25,p75)，mg/L]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;94.41\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;[23.05,133.40]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; 51.18\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;[8.68,96.89]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;0.028*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003ePCT\u003c/p\u003e\n \u003cp\u003e[m(P25,p75)，ng/L]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;5.53\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; [0.11,0.43]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;0.19\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;[0.02,0.27]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;0.028*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eIL-6\u003c/p\u003e\n \u003cp\u003e[m(P25,p75)，pg/mL]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e126.84\u003c/p\u003e\n \u003cp\u003e[31.08,225.65]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp;44.80\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; [12.97,60.17]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;0.018*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e(1,3)-\u0026beta;-D-Glucan test\u003c/p\u003e\n \u003cp\u003e[m(P25,p75)，pg/mL]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;47.04\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; [37.5,58.80]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;49.53\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; [37.5,59.96]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; 0.833\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eGalactomannan test[m(P25,p75)，S/CO]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;0.53\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; [0.11,0.27]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003cp\u003e[0.10,0.33]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp; 0.940\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003emNGS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003epositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e23(95.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e38(97.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;0.725\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003enegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e1(4.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e1(2.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eSputum culture[n(%)]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003epositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e11(45.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e12(30.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;0.228\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003enegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e13(54.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e27(69.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e: *P＜0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 \u0026nbsp;mNGS result evaluation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.1 Distribution of pathogens detected by mNGS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 63 eligible specimens were sent for testing in this study, of which 61 were positive. Among them, a total of 25 pathogens and 55 strains were detected by mNGS in the immunotherapy group, with 41.81% (23/55) of bacteria, 36.36% (20/55) of fungi, and 21.81% (12/55) of viruses. The top five pathogens were 7 strains of Pneumocystis jiroveci, 7 strains of Aspergillus fumigatus, 7 strains of EBV, 4 strains of Mycobacterium tuberculosis complex, 3 strains of Pseudomonas aeruginosa, and 3 strains of Aspergillus terreus. A total of 40 pathogens and 112 strains were detected by mNGS in the non-immunotherapy group, with 40.18% (45/112) bacteria, 37.50% (42/112) fungi, 20.54% (23/112) viruses, and 1.79% (2/112) atypical pathogens, including one case each of Mycoplasma pneumoniae and Legionella pneumophila. The top five pathogens were Pseudomonas aeruginosa in 12 cases, Aspergillus fumigatus in 10 cases, Aspergillus flavus in 10 cases, Pneumocystis japonicus in 9 cases, and EBV in 7 cases (see Figures 1,2,3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.2 Characteristics of pathogens co infected in two groups of patients detected by mNGS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn 63 patients with lung cancer co-infections, the characteristics of infections were compared between the immunotherapy group (n=24) and the non-immunotherapy group (n=39). There was no statistically significant difference in the incidence of infections and the rates of bacterial, fungal and viral infections between the two groups.\u003c/p\u003e\n\u003cp\u003eTable 2 Composition of Pathogens Detected in mNGS Positive Patients\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"544\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eEtiology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eImmunotherapy group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eNon immunotherapy group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;P value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eNumber of case（n=24）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eNumber of case（n=39）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003eBacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e10.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e0.783\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003eFungus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e10.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e0.105\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003eVirus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e8.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e71.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e0.781\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003eResidual categories\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e5.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e0.260\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e: *P＜0.05.\u003c/p\u003e\n\u003cp\u003eFor mixed infections with multiple pathogens, there was no statistical difference in the rates of mixed infections, mixed infections containing bacteria and fungi, mixed infections containing bacteria or fungi and mixed infections with viruses between the two groups. Among the mixed infections containing bacteria or fungi were divided into simple mixed infections of multiple fungi, simple mixed infections of multiple bacteria, mixed infections of bacteria and viruses, and mixed infections of fungi and viruses, in which the rate of simple mixed infections of multiple fungi in the immunotherapy group was found to be significantly higher than that in the non-immunotherapy group (20.83% vs. 2.56%, p=0.026) (see Figure 4, Table 3).\u003c/p\u003e\n\u003cp\u003eTable 3 Comparison of mNGS with and without immunotherapy for mixed infections in patients\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"642\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eEtiology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eImmunotherapy group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eNon immunotherapy group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp; Number of case\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; （n=24）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eNumber of case（n=39）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp; %\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003eMixed infection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;71.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.781\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003eMixed infection containing bacteria and fungi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e29.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 35.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.582\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003eBacteria+Fungus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e20.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 20.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.976\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003eBacteria+Fungus+Virus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e8.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 15.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.414\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003eMixed infection containing bacteria or fungi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e45.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 33.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.321\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003eBacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e8.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 6\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;15.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.414\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003eFungus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e20.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 2.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;0.016*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003eBacteria+Virus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e8.33 \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;5.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.612\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003eFungus+Virus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e8.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;10.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.801\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eMixed infection of viruses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp; 0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;2.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.429\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e: *P＜0.05.\u003c/p\u003e\n\u003cp\u003eStatistical differences in the infection rates of common bacteria in this study were found between the two groups. There was no statistical difference in the infection rates of Pseudomonas aeruginosa, Streptococcus pneumoniae, Staphylococcus aureus, Mycobacterium tuberculosis complex, Acinetobacter baumannii and Haemophilus influenzae between the two groups (see Figure 6).\u003c/p\u003e\n\u003cp\u003eStatistics on the infection rate of common fungi in this study differed between the two groups. The infection rate of Aspergillus terreus (X2=5.119, P=0.024) was significantly higher in the immunotherapy group than in the non-immunotherapy group. There was no statistically significant difference in the infection rates of Aspergillus fumigatus, Aspergillus flavus, Pneumocystis japonicus, Aspergillus niger and Candida albicans between the two groups (see Figure 7).\u003c/p\u003e\n\u003cp\u003eStatistical differences in the infection rates of common viruses in this study between the two groups. There was no statistical difference in the infection rates of EBV, cytomegalovirus, novel coronavirus, human adenovirus group B, human herpesvirus type 1 and influenza A virus H1N1 between the two groups (see Figure 8).\u003c/p\u003e"},{"header":"3. Discussions","content":"\u003cp\u003eLung cancer is one of the malignant tumors with high morbidity and mortality rates worldwide, seriously endangering human life and health. According to statistics, the number of new lung cancer cases is as high as 1.8 million and the number of deaths reaches about 1.6 million every year in the world [10]. It has been found that the traditional chemotherapeutic regimen, although able to reduce tumor size and relieve symptoms in a short time, is prone to drug resistance\u003csup\u003e[11]\u003c/sup\u003e. The emergence of immunotherapy has brought new hope to patients with advanced lung cancer, as Pual Ehrlich put forward the doctrine of\u0026nbsp;“immunosurveillance”\u0026nbsp;in 1909, which opened a new chapter of immunotherapy, and the first immunotherapeutic drug, Ipilimumab, was approved in the United States in 2011 for the treatment of malignant tumors\u003csup\u003e[12]\u003c/sup\u003e. Currently, the immunosuppressants that have been approved for the treatment of lung cancer in China include Sintilimab, Tislelizumab and Pembrolizumab\u003csup\u003e[13]\u003c/sup\u003e. The principle of immunotherapy is that immunosuppressants specifically interact with Programmed Cell Death Protein 1 (PD-1), Programmed Death-Ligand 1 (PD-L1), and Cytotoxic T-lymphocyte-Associated Antigen-4 (Cytotoxic T-). Lymphocyte-Associated Protein 4 (CTLA-4) binding, destroying the immune tolerance of tumor cells and restarting the immune system to kill tumor cells. However, at the same time, immunosuppressants also non-selectively disrupt the negative regulation in immune regulation, and the immune system is over-activated, releasing immune cells and immune factors, which destroys the alveolar epithelial cells, leading to an increased incidence of infections in lung cancer patients\u003csup\u003e[14]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eA retrospective cohort study was designed to assess the incidence of serious infections in lung cancer patients after treatment with ICIs and to further analyze the independent risk factors associated with them. The study found that 191 (26.86%) of the 711 lung cancer patients ultimately enrolled developed serious infections during the follow-up period. The main site of infection was the lungs (75.61%), and the aetiologic analysis showed that bacterial infections were predominant (82.05%) predominantly, followed by Mycobacterium tuberculosis (6.47%), viral (4.98%) and fungal (3.48%) infections. Chronic obstructive pulmonary disease (COPD), asthma, systemic glucocorticoid use, low lymphocyte counts and low CD4/CD8 ratio were identified as significant independent risk factors\u003csup\u003e[15]\u003c/sup\u003e. Therefore, focused monitoring of these high-risk patients and timely prophylactic treatment should be performed in clinical management to reduce the incidence of infection and improve prognosis.\u003c/p\u003e\n\u003cp\u003emNGS is a novel sequencing technology with broad coverage and no bias, and its sensitivity and specificity are superior to traditional pathogen detection methods\u003csup\u003e[16]\u003c/sup\u003e. It has been reported that mNGS has less impact on the prophylactic antibiotic use population, can more accurately detect pathogens in mixed and rare infections, and its results may accelerate clinical decision-making in immunocompromised populations\u003csup\u003e[17]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn this study, by comparing the number of hospitalization days and hospitalization costs between the two groups of patients, it was found that the number of hospitalization days and hospitalization costs of patients in the immunotherapy group were significantly higher than those in the non-immunotherapy group. And the related inflammatory indexes, such as CRP, PCT, IL-6, etc., were compared between the two groups, and it was found that the immunotherapy group was higher than the non-immunotherapy group, and the difference was statistically significant. This indicates that the condition of patients with lung cancer immunotherapy combined with lung infection progresses rapidly, and the disability and mortality rates are higher, so that respiratory failure and severe pneumonia occur, and even death occurs, which causes a serious economic burden to the patient's family\u003csup\u003e[18]\u003c/sup\u003e. Therefore, after immunotherapy for lung cancer, patients should be monitored early for relevant inflammatory indexes and mNGS to effectively identify complex pathogens and reasonably use antibiotics, so as to improve the prognosis, shorten the treatment time and cost, and accelerate the recovery of patients.\u003c/p\u003e\n\u003cp\u003eIn this study bacteria and fungi were most frequently detected in patients in the immunotherapy group, where the most frequently detected pathogen among bacteria was Mycobacterium tuberculosis complex.FAN et al\u003csup\u003e[19]\u0026nbsp;\u003c/sup\u003esummarized the relevant case studies in the last few years, where 8 cases were treated with Nivolumab and 6 with Pembrolizumab, all patients were not screened for latent tuberculosis infection (LTBI) before immunotherapy, and it was not clear whether the infected tuberculosis was primary or secondary. None of the patients had been screened for latent tuberculosis infection (LTBI) before immunotherapy, and it was not clear whether the TB infection was primary or secondary. Tuberculosis was diagnosed during the course of immunotherapy and regular anti-tuberculosis treatment was administered. 14 patients were suggested to have reactivation of tuberculosis as a well-defined adverse effect\u003csup\u003e[20]\u003c/sup\u003e. It has also been found that treatment of the tumor itself (e.g., chemotherapy, etc.) may also be a source of immunosuppression, thereby increasing the risk of TB. Among solid tumors, lung cancer has the highest incidence of TB reactivation\u003csup\u003e[21,22]\u003c/sup\u003e. The exact mechanism leading to TB reactivation in patients is unclear and requires further study. However, it has been found that in PD-1-deficient mice and PD-1-blocked populations, increased interferon production by CD4+ T cells after infection with Mycobacterium tuberculosis promotes bacterial replication and tissue destruction\u003csup\u003e[23]\u003c/sup\u003e. Therefore, the application of ICIs during immunotherapy can complicate the infection, and the possibility of tuberculosis should be prioritized when new lesions appear in clinical workups, especially in patients with lung cancer, lymphoma, or a history of exposure to tuberculosis, and timely LTBI screening or mNGS testing should be necessary, which is essential for the rapid diagnosis of tuberculosis and adjustment of the treatment regimen.\u003c/p\u003e\n\u003cp\u003eLung fungal infection is one of the common complications in lung cancer patients, which not only affects the life and health of patients, but also can hinder the treatment process, thus affecting the therapeutic effect\u003csup\u003e[24]\u003c/sup\u003e. A study enrolled 167 patients with non-small cell lung cancer who were concurrently treated with Nivolumab immunotherapy, and found that 33 (19.2%) patients developed infections, including 25 bacterial infections, 2 fungal infections, and 6 viral infections\u003csup\u003e[25]\u003c/sup\u003e. Another report found a case of acute exacerbation of pre-existing chronic progressive pulmonary aspergillosis after receiving 20 courses of nabulizumab\u003csup\u003e[26]\u003c/sup\u003e. In this study, we found a significantly higher rate of simple mixed infections of multiple fungi in lung cancer patients undergoing immunotherapy (20.83% vs. 2.56%, p=0.016), with a higher detection rate of Aspergillus hyodysenteriae than in the non-immunotherapy group. Although there was no statistically significant difference in the infection rates of Pneumocystis jiroveci and Aspergillus fumigatus between the two groups, an elevated detection rate could be detected in the immunotherapy group compared to the non-immunotherapy group. It has been reported that ICIs treatment can induce acute exacerbation of chronic invasive pulmonary aspergillosis as well as fungal sinusitis\u003csup\u003e[27]\u003c/sup\u003e.ICIs treatment leads to an abnormal immune state of the organism, causing excessive immune response of colonized fungi, and promoting the growth of fungi, which is in line with this study. And in clinical practice, new fungal infections during immunotherapy are sometimes more difficult to distinguish from tumor progression. Therefore, clinicians should monitor early during immunotherapy and need to be alert to the emergence of fungal infections when patients develop infections and use antifungal drugs reasonably.\u003c/p\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eIn this study, the incidence of mixed fungal infections was increased in lung cancer patients undergoing immunotherapy, especially those of Mycobacterium smegmatis. Bacterial infections were dominated by Mycobacterium tuberculosis complex, fungal infections were dominated by Aspergillus fumigatus and Pneumocystis japonicus, and viral infections were dominated by EBV. mNGS demonstrated good applicability in the population of lung cancer undergoing immunotherapy and had a large impact on treatment. However, there are some limitations in this study. The sample size is small, resulting in some risk of bias in some data, and mNGS also suffers from adulteration of background bacteria, low detection rate of intracellular bacteria and thick-walled microorganisms. In this study, we proposed that the incidence of infection in lung cancer patients after immunotherapy was increased, and the incidence of mixed fungal infection was significantly higher. Therefore, clinical workers should pay attention to identifying the type of infection occurrence in the process of diagnosis and treatment, and timely apply mNGS and other detection means to adjust the anti-infection treatment program and improve the prognosis.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003emNGS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; metagenomic next-generation sequencing\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eICIs \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; immune checkpoint inhibitors\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCRP \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; C-reactive protein interleukin-6 (IL-6)\u003c/p\u003e\n\u003cp\u003eIL-6 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; interleukin-6\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePCT \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Procalcitonin\u003c/p\u003e\n\u003cp\u003eGM \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; (1,3)-β-D-Glucan\u003c/p\u003e\n\u003cp\u003eG \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Galactomannan\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHHV-4 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Epstein-Barr virus\u003c/p\u003e\n\u003cp\u003eHHV-5 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Cytomegalovirus\u003c/p\u003e\n\u003cp\u003eHHV-1 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Human herpesvirus 1\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHHV-6 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Human herpesvirus 6B\u003c/p\u003e\n\u003cp\u003eHHV-7 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Human herpesvirus 7\u003c/p\u003e\n\u003cp\u003eIAV H1N1 \u0026nbsp; \u0026nbsp; \u0026nbsp;Influenza A virus subtype H1N1\u003c/p\u003e\n\u003cp\u003eIAV H3N2 \u0026nbsp; \u0026nbsp; \u0026nbsp;Influenza A virus subtype H3N2\u003c/p\u003e\n\u003cp\u003eSARS-CoV-2 \u0026nbsp; \u0026nbsp;Severe acute respiratory syndrome coronavirus 2\u003c/p\u003e\n\u003cp\u003eHAdV-B \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Human mastadenovirus B\u003c/p\u003e\n\u003cp\u003eEV-C \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Enterovirus C\u003c/p\u003e\n\u003cp\u003eHPyV5 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Human polyomavirus 5\u003c/p\u003e\n\u003cp\u003eRSV \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Respiratory syncytial virus\u003c/p\u003e\n\u003cp\u003eHSV-1 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Herpes simplex virus 1\u003c/p\u003e\n\u003cp\u003ePD-1 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Programmed Cell Death Protein 1\u003c/p\u003e\n\u003cp\u003ePD-L1 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Programmed Death Ligand 1\u003c/p\u003e\n\u003cp\u003eCTLA-4 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Cytotoxic T-Lymphocy-Associated Protein 4\u003c/p\u003e\n\u003cp\u003eCOPD \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Chronic obstructive pulmonary disease\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLTBI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;latent tuberculosis infection\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u003c/strong\u003e\u003cstrong\u003e\u0026acute;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYQZ and QQZ conceived and designed the study. YQZ was a major contribu tor in writing the manuscript and performed part of the data analysis. QQZ performed the major part of data collection and analysis. YQZ and QQZ revised the manuscript with assistance from HY. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the \u0026quot;Medical and Health Talent Training Program\u0026quot; (023YZ09) of the Medical Department of Yangtze University\u0026apos;s Science and Technology Assistance to Tibet.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study achieved formal approval from the Ethics Committee of The First Affiliated Hospital of Yangtze University (ethical number: YJ202427).This study was retrospective, and the Ethics Committee of The First Affiliated Hospital of Yangtze Universitl waived the requirement of extra patient consent statements because written informed consent was obtained from all patients admitted to allow their medical records to be used in clinical observational studies.All identifying information was removed to protect patient confidentiality according to the requirement of the Ethics Committee of The First Affiliated Hospital of Yangtze University. This study was designed and conducted in accord ance with the Declaration of Helsinki and local institutional standards.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHayashi H, Nakagawa K. Combination therapy with PD-1 or PD-L1 inhibitors for cancer. Int J Clin Oncol. 2020;25(5):818\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDiao X, Guo C, Jin Y, et al. Cancer situation in China: an analysis based on the global epidemiological data released in 2024. Cancer Commun (Lond). 2025;45(2):178\u0026ndash;97.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLuo G, Zhang Y, Etxeberria J, et al. 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CA Cancer J Clin. 2020;70(2):86\u0026ndash;104.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen Y, Wang J, Gan X, et al. Application of plasma metagenomic next-generation sequencing improves prognosis in hematology patients with neutropenia or hematopoietic stem cell transplantation for infection. Front Cell Infect Microbiol. 2024;14:1338307.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLanks CW, Musani AI, Hsia DW. Community-acquired Pneumonia and Hospital-acquired Pneumonia. Med Clin North Am. 2019;103(3):487\u0026ndash;501.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e[Consensus of clinical pathways. of metagenomic next-generation sequencing test in diagnosis of lower respiratory tract infections in China. Zhonghua Jie He He Hu Xi Za Zhi. 2023;46(4):322\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang Y, Rumgay H, Li M, et al. Nasopharyngeal Cancer Incidence and Mortality in 185 Countries in 2020 and the Projected Burden in 2040: Population-Based Global Epidemiological Profiling. JMIR Public Health Surveill. 2023;9:e49968.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMa YC, Xie YJ, Zhou YW et al. Research progress and prospects on immunotherapy of extensive-stage small cell lung cancer. Mod Oncol 2025,33(6):1024\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTang B, Chi Z, Guo J. Toripalimab for the treatment of melanoma. Expert Opin Biol Ther. 2020;20(8):863\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLin X, Kang K, Chen P, et al. Regulatory mechanisms of PD-1/PD-L1 in cancers. Mol Cancer. 2024;23(1):108.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQin Q, Wang J, Wang H. [Immune-related Adverse Events Induced by ICIs in Advanced NSCLC: A Meta-analysis and Systematic Review. Zhongguo Fei Ai Za Zhi. 2020;23(9):772\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang X, Wu Y, Hu W, et al. Incidence and risk factors of serious infections occurred in patients with lung cancer following immune checkpoint blockade therapy. BMC Cancer. 2025;25(1):307.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen Y, Feng W, Ye K, et al. Application of Metagenomic Next-Generation Sequencing in the Diagnosis of Pulmonary Infectious Pathogens From Bronchoalveolar Lavage Samples. Front Cell Infect Microbiol. 2021;11:541092.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLin P, Chen Y, Su S, et al. Diagnostic value of metagenomic next-generation sequencing of bronchoalveolar lavage fluid for the diagnosis of suspected pneumonia in immunocompromised patients. BMC Infect Dis. 2022;22(1):416.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTang W, Zhang Y, Luo C, et al. Clinical Application of Metagenomic Next-Generation Sequencing for Suspected Infections in Patients With Primary Immunodeficiency Disease. Front Immunol. 2021;12:696403.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFan N, Jiang DR, Wang Y. Progress in the treatment of PD-1/PD-L1 inhibitors in lung cancer complicated with pulmonary tuberculosis disease. Lab Med Clin. 2025;22(7):998\u0026ndash;1002.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePicchi H, Mateus C, Chouaid C, et al. Infectious complications associated with the use of immune checkpoint inhibitors in oncology: reactivation of tuberculosis after anti PD-1 treatment. Clin Microbiol Infect. 2018;24(3):216\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGiller D, Giller B, Scherbakova G, et al. Extensive tracheal resection in lung cancer and tuberculosis: a case report. BMC Pulm Med. 2020;20(1):197.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDobler CC, Cheung K, Nguyen J et al. Risk of tuberculosis in patients with solid cancers and haematological malignancies: a systematic review and meta-analysis. Eur Respir J, 2017,50(2).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBarber DL, Sakai S, Kudchadkar RR et al. Tuberculosis following PD-1 blockade for cancer immunotherapy. Sci Transl Med, 2019,11(475).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShimizu T, Okachi S, Imai N, et al. Risk factors for pulmonary infection after diagnostic bronchoscopy in patients with lung cancer. Nagoya J Med Sci. 2020;82(1):69\u0026ndash;77.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFujita K, Kim YH, Kanai O, et al. Emerging concerns of infectious diseases in lung cancer patients receiving immune checkpoint inhibitor therapy. Respir Med. 2019;146:66\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLu WY, Zhang L, Li Y, et al. Recommendation of diagnosis and management for the infection related to immune checkpoint inhibitors. Chin lung cancer. 2019;22(10):666\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMorelli T, Fujita K, Redelman-Sidi G, et al. Infections due to dysregulated immunity: an emerging complication of cancer immunotherapy. Thorax. 2022;77(3):304\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Lung cancer, Immunotherapy, Pulmonary infection, Metagenomic second-generation sequencing, pathogen detection","lastPublishedDoi":"10.21203/rs.3.rs-6906725/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6906725/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e To observe the clinical characteristics of patients with lung cancer infection combined with immunotherapy, compare whether there is a difference in the detection of pathogens between the two groups of patients, and explore the diagnostic value of metagenomic next-generation sequencing (mNGS) for patients with lung cancer infection combined with immunotherapy.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e Sixty-three patients with lung cancer co-infections were included in the First People's Hospital of Jingzhou City from December 2022 to April 2025, and were divided into 24 cases in the immunotherapy group and 39 cases in the non-immunotherapy group according to whether they were treated with immunotherapy or not, and underwent electron bronchoscopy and mNGS testing. We collected the detection of pathogens and various clinical information from the enrolled patients, explored the association between the infection characteristics and clinical characteristics of the patients in the two groups, and compared the detection of pathogens in the two groups.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e The CRP, PCT, IL-6, hospitalization days and hospitalization cost of patients in the immunotherapy group were higher than those in the non-immunotherapy group, and the differences were statistically significant (P \u0026lt; 0.05). In the immunotherapy group, 14 cases of bacteria, 14 cases of fungi, 9 cases of viruses and 18 cases of mixed infections were detected. In the non-immunotherapy group, 28 cases of bacteria, 25 cases of fungi, 14 cases of viruses and 28 cases of mixed infections were detected. The detection rate of fungal mixed infections was higher in the immunotherapy group (20.83%) than in the non-immunotherapy group (2.56%) (X\u003csup\u003e2\u003c/sup\u003e=5.755, P=0.016), with the infection rate of Aspergillus terreus in the immunotherapy group significantly higher than that in the non-immunotherapy group (X\u003csup\u003e2\u003c/sup\u003e=5.119, P=0.024). The differences in the detection rates of bacteria, virus and the rest of mixed infections were not statistically significant when compared with non-immunotherapy (P\u0026gt;0.05).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e The incidence of mixed fungal infections increased after immunotherapy in lung cancer patients, in which the detection rate of Mycobacterium hyopneumoniae was significantly higher in the immunotherapy group than in the non-immunotherapy group. Bacterial infections were dominated by Mycobacterium tuberculosis complex, fungal infections were dominated by Aspergillus fumigatus and Pneumocystis japonicus, and viral infections were dominated by EBV. mNGS demonstrated good applicability in the population undergoing immunotherapy for lung cancer and had a greater impact on treatment.\u003c/p\u003e","manuscriptTitle":"The value of second-generation gene sequencing in lung cancer immunotherapy with concurrent infections","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-01 11:03:28","doi":"10.21203/rs.3.rs-6906725/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-12T08:25:08+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-07T09:50:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"326292871844902141786716251826104672292","date":"2025-07-30T16:32:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-29T21:25:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"104346491328191104925284500552270690373","date":"2025-07-29T17:12:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"109250687686691072282958829378044611916","date":"2025-07-29T17:07:48+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-29T16:43:26+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-28T03:29:01+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-20T16:32:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-19T13:43:49+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2025-06-19T13:17:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b3921d28-3448-43ae-b2c6-a957b69de5fa","owner":[],"postedDate":"August 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-27T16:25:46+00:00","versionOfRecord":{"articleIdentity":"rs-6906725","link":"https://doi.org/10.1186/s12885-025-15045-4","journal":{"identity":"bmc-cancer","isVorOnly":false,"title":"BMC Cancer"},"publishedOn":"2025-10-23 16:16:36","publishedOnDateReadable":"October 23rd, 2025"},"versionCreatedAt":"2025-08-01 11:03:28","video":"","vorDoi":"10.1186/s12885-025-15045-4","vorDoiUrl":"https://doi.org/10.1186/s12885-025-15045-4","workflowStages":[]},"version":"v1","identity":"rs-6906725","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6906725","identity":"rs-6906725","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}