A new strategy for the diagnosis of tuberculosis based on secreted antigens: evaluation of the efficacy of alveolar lavage ESAT-6 and CFP-10 tests

A new strategy for the diagnosis of tuberculosis based on secreted antigens: evaluation of the efficacy of alveolar lavage ESAT-6 and CFP-10 tests | 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 A new strategy for the diagnosis of tuberculosis based on secreted antigens: evaluation of the efficacy of alveolar lavage ESAT-6 and CFP-10 tests Shiyu Fang, JinXiong Jiang, Jie Sun, FengJun Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6842949/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Nov, 2025 Read the published version in European Journal of Medical Research → Version 1 posted 15 You are reading this latest preprint version Abstract Objective: To assess the diagnostic value of Mycobacterium tuberculosis (MTB)-specific secreted antigens ESAT-6 and CFP-10 in alveolar lavage fluid (BALF), and to explore novel adjunctive diagnostic strategies to enhance the diagnostic rate of pulmonary tuberculosis (PTB). Methods: 104 patients with PTB (59 confirmed cases and 45 clinically diagnosed cases) and 72 patients with non-tuberculosis lung diseases (control group), hospitalized from May 2021 to July 2023, underwent bronchoscopy. The concentrations of ESAT-6 and CFP-10 antigens were detected by enzyme-linked immunosorbent assay (ELISA). Optimal cut-off values were determined by receiver operating characteristic (ROC) curves to evaluate antigen diagnostic capability for active PTB, compared with acid-fast bacilli (AFB) and Xpert MTB/RIF. Results: Antigen expression characteristics: Concentrations of ESAT-6 and CFP-10 were significantly higher in the PTB group compared to controls (both P0.05), whereas CFP-10 concentrations were significantly higher in confirmed cases (P=0.045). Comparison of diagnostic efficacy: Sensitivities of AFB and Xpert MTB/RIF were 26.92% (95% CI: 18.6-37.2%) and 56.73% (95% CI: 46.1-66.8%), respectively, with specificity at 100%. ESAT-6 and CFP-10 demonstrated significantly higher sensitivities (77.89%, 95% CI: 68.5-85.1%; 67.31%, 95% CI: 57.3-76.0%) compared to AFB (Δ=50.97%, P<0.001; Δ=40.39%, P<0.001) and Xpert MTB/RIF (Δ=21.16%, P<0.001; Δ=10.58%, P=0.021), but had lower specificity (P<0.001). Combined testing strategy: Parallel testing (either antigen positive) yielded sensitivity of 94.23% (95% CI: 87.4-97.6%) and negative predictive value of 99.2%, while tandem testing (both antigens positive) provided specificity of 95.83% (95% CI: 88.1-98.6%). Subgroup analysis: No statistically significant difference was observed in antigen sensitivities between bacteriologically positive and negative PTB groups (P>0.05). Conclusion: (1) ESAT-6 and CFP-10 detection in BALF significantly improves PTB diagnostic sensitivity, unaffected by bacterial load, particularly benefiting the diagnosis of bacteriologically negative PTB. (2) Combined antigen testing strategies (parallel/tandem) optimally balance sensitivity and specificity, meeting clinical requirements for ruling out or confirming PTB diagnosis. Pulmonary tuberculosis Tuberculosis antigen Enzyme-linked immunosorbent assay Acid fast bacteria Xpert MTB/RIF Figures Figure 1 Figure 2 Figure 3 1. Introduction Tuberculosis (PTB) is a chronic infectious disease caused by Mycobacterium tuberculosis infection and has surpassed AIDS as the world's leading cause of death from infectious diseases. China is among the countries with the highest PTB burden. According to the World Health Organization's (WHO) Global Tuberculosis Report 2024[ 1 ], there were approximately 10.8 million new PTB cases globally in 2023, with China accounting for 741,000 cases, ranking third among the 30 high-burden countries. In 2014, WHO initiated the End TB Strategy, aiming to reduce TB incidence to less than 10 per 100,000 population by 2035[ 2 ]. A core component of this strategy is "early and accurate diagnosis," crucial for breaking the transmission chain. Epidemiological data indicate that over 60% of global PTB cases are initially diagnosed in primary healthcare centers (PHCs)[ 1 ], highlighting the importance of PHCs in PTB control. However, current primary diagnostic methods, primarily sputum smear microscopy, suffer from low sensitivity, missing 35–40% of cases, thus exacerbating delays in diagnosis and increasing risks for secondary drug resistance. Therefore, there is an urgent need to identify highly sensitive, cost-effective, and user-friendly diagnostic tools to bridge this diagnostic gap and facilitate the implementation of the End TB Strategy. Currently, tuberculosis diagnosis relies on identifying etiological evidence, primarily through MTB acid-fast bacilli (AFB) smears or mycobacterial cultures. AFB smear microscopy is economical and efficient but exhibits low sensitivity, particularly in patients with low bacterial loads, and cannot differentiate between non-tuberculous mycobacteria (NTM) and MTB[ 3 ]. Mycobacterial culture, considered the gold standard, offers superior sensitivity but faces significant practical and technical limitations, including prolonged incubation periods and stringent biosafety requirements, delaying timely diagnosis and treatment initiation[ 4 , 5 ]. Molecular diagnostic techniques, notably polymerase chain reaction (PCR), have significantly improved PTB diagnosis due to their high sensitivity, specificity, rapidity, and cost-effectiveness[ 6 ]. Advanced molecular diagnostics such as Xpert MTB/RIF and Xpert MTB/RIF Ultra have further enhanced MTB detection, particularly in HIV-positive patients, and enabled rapid identification of drug-resistant strains[ 7 ]. Nevertheless, the high costs and strict operational requirements limit their widespread adoption in primary care settings[ 8 ]. Immunological tests, detecting host immune responses to MTB-specific antigens, also play a significant auxiliary role in PTB diagnosis. Gamma-interferon release assays (IGRA) and the tuberculin skin test (TST) are commonly utilized for detecting latent MTB infection (LPTBI) by assessing T-cell responses to MTB-specific antigens ESAT-6 and CFP-10[ 9 ]. However, these tests have limitations in distinguishing active PTB from LPTBI, influenced by factors such as the host's immune status and prior infection history[ 10 ]. Given the high diagnostic potential of ESAT-6 and CFP-10, this study aimed to directly quantify these antigens in alveolar lavage fluid using ELISA. The sensitivity and specificity of ELISA-based antigen detection were systematically compared with traditional AFB and Xpert MTB/RIF assays to evaluate its utility in PTB diagnosis and provide a novel diagnostic approach for clinical practice. 2. Materials and methods 2.1. Study design and participants This was a retrospective, single-center clinical study conducted at the Affiliated Hospital of Chuanbei Medical College between May 2021 and July 2023. The study included patients who underwent fiberoptic bronchoscopy. Clinical history data and bronchoalveolar lavage fluid samples were systematically collected. Patients were classified into pulmonary tuberculosis (PTB) and non-pulmonary tuberculosis (non-PTB) groups based on diagnoses. The PTB group was further subdivided into bacteriologically confirmed cases of pulmonary tuberculosis (BC-PTB) and clinically diagnosed cases of pulmonary tuberculosis (CD-PTB). Patients in the PTB group met the following conditions: (1) fulfill the diagnostic criteria outlined in WS288-2017[ 11 ]; and (2) exhibit effectiveness after standardized anti-tuberculosis treatment. To ensure accurate microbiological test results, BALF samples from all PTB patients were collected before initiating anti-tuberculosis therapy. Inclusion criteria for the non-PTB group were: (1) no history or exposure to tuberculosis; (2) definitive diagnosis of pulmonary tumors by pathological examination or other pulmonary infections with confirmed etiological evidence; and (3) negative IGRA results. Additionally, all study participants were tested to exclude hepatitis C virus, hepatitis B virus, and HIV infections. 2.2 Collection and Preservation of Bronchoalveolar Lavage Fluid After obtaining informed consent, bronchoalveolar lavage fluid (BALF) collection strictly adhered to technical guidelines provided by the European Respiratory Society[ 12 ] and standard operating procedures. Alveolar lavage involved three lavages using sterile saline, each with a volume of 10–20 mL, totaling 50–60 mL. Fluid recovery was conducted at a negative pressure of -13.3 kPa to -19.95 kPa after each lavage, achieving a recovery rate of 30%-50%. The collected fluid from all three lavages was thoroughly mixed, aliquoted into sterile frozen tubes pretreated with silicone oil, and immediately stored at -20°C. To prevent sample degradation, each sample underwent a single freeze-thaw cycle, with thawing performed overnight at 4°C before use. 2.3 Optimal Sample Dilution Identification Checkerboard titration was performed to determine optimal sample dilution. Three samples with the highest acid-fast bacilli content (smear results ranging from +++ to ++++) were pre-tested at dilution ratios of 1:1, 1:5, 1:10, and 1:20. The optimal dilution was identified by calculating the ratio (P/N value) of absorbance between positive samples and negative controls. Experimental results indicated that undiluted samples provided the highest P/N value and thus were used in subsequent assays. 2.4 ELISA detection of BALF BALF supernatant was analyzed using a Mycobacterium tuberculosis antigen ELISA kit (Camilo Biological Co., Nanjing, China) in strict accordance with the manufacturer’s instructions. Briefly, the kit was equilibrated to room temperature for 20 min before use. Lyophilized ESAT-6 and CFP-10 standards were reconstituted in 1 mL of standard diluent to yield stock concentrations of 100 ng/mL (ESAT-6) and 20 ng/mL (CFP-10). Serial twofold dilutions (100–1.5%) were prepared to construct the standard curves. Standards and BALF samples (100 µL/well, in duplicate) were loaded onto antibodycoated microplates and incubated at 37°C for 90 min. After two washes, 100 µL of 1:100diluted biotinylated detection antibody was added, followed by incubation at 37°C for 60 min. Plates were washed three times, and 100 µL of horseradishperoxidase conjugate was applied for 30 min at 37°C in the dark. Following five washes, 100 µL of substrate solution was added and the reaction was stopped with 2 M H₂SO₄ when adequate color developed. Optical density (OD) was measured at 450 nm with a 630 nm reference, blankcorrected, and antigen concentrations were interpolated from the standard curves using ELISACalc software. 2.5 Clinical data collection in patients with and without PTB For PTB participants, demographic and clinical data—including age, sex, ethnicity, comorbidities, HIV status, chest CT findings (presence or absence of cavities), prior PTB history, and response to antituberculosis therapy—were recorded. For nonPTB participants, age and sex were collected. 2.6 Statistical analysis Statistical analyses were performed using SPSS version 25 (IBM Corp.). Receiver operating characteristic (ROC) curves were generated to assess diagnostic performance, with optimal cutoff values determined by maximizing Youden’s index. Data normality was evaluated using the Shapiro–Wilk test. Normally distributed variables are presented as mean ± standard deviation and compared with the independentsamples t test. Nonnormally distributed data are expressed as median (interquartile range) and compared using the Mann–Whitney U test. Categorical variables were analyzed with Pearson’s χ² test. A twosided P value < 0.05 was considered statistically significant. GraphPad Prism 8.0.1 was used for data visualization. 3. Results 3.1 Basic characteristics of study participants Between May 2021 and July 2023, 104 patients with PTB (59 bacteriologically confirmed [BC‑PTB] and 45 clinically diagnosed [CD‑PTB]) underwent bronchoscopy and were enrolled. All PTB cases responded to standard anti‑tuberculosis therapy. The control cohort comprised 72 patients with non‑tuberculous pulmonary diseases confirmed by microbiological testing. Baseline characteristics are summarized in Table 1. Participant ages ranged from 13 to 85 years (median 50 years), and 75.3 % were male. Cough was the most common symptom (69.3 %), and diabetes mellitus was the most frequent PTB comorbidity (11.5 %). Table1. Baseline demographic and microbiological characteristics of the study participants (n = 80). PTB group (n=104) non-PTB group (n=72) p-value Median age [IQR] years 44 [13-78] 58.5 [16-85] 0.0001 * Men (%) 75 (72.1 per cent) 48 (66.7 per cent) 0.370 *** Previous pulmonary tuberculosis (%) 1 (0.96 per cent) 0 (0 per cent) 1.00 ** Cough (%) 68 (65.3 per cent) 54 (75.0 per cent) 0.174 *** Fever(%) 14 (13.4 per cent) 23 (31.9 per cent) 0.003 *** Weight loss(%) 19 (18.2 per cent) 11 (15.2 per cent) 0.604 *** Night sweats(%) 27 (25.9 per cent) 5 (6.9 per cent) 0.001 *** Diabetes mellitus (%) 12 (11.5 per cent) 9 (12.5 per cent) 0.843 *** Hypertension (%) 2 (1.9 per cent) 9 (12.5 per cent) 0.018 ** Extrapulmonary tuberculosis (%) 7 (6.7 per cent) 0 (0 per cent) 0.045 ** Lung tumor (%) 3 (2.9 per cent) 8 (11.1 per cent) 0.045 ** Sepsis (%) 1 (1.0 per cent) 1 (1.4 per cent) 1.00 ** Connective tissue disease (%) 0 (0 per cent) 5 (6.9 per cent) 0.018 ** *Mann-Whitney U test ** Fisher's exact test *** Chi-square test 3.2 BALF ESAT‑6 and CFP‑10 Concentrations Median BALF concentrations of ESAT‑6 and CFP‑10 were significantly higher in both BC‑PTB and CD‑PTB groups than in the non‑PTB group (P < 0.001; Figure 1). ESAT‑6 concentrations did not differ between BC‑PTB and CD‑PTB (P = 0.056), whereas CFP‑10 levels were higher in BC‑PTB (P = 0.045). ROC analysis yielded areas under the curve of 0.856 for ESAT‑6 and 0.805 for CFP‑10. Optimal cut‑off values were 24.54 ng/mL for ESAT‑6 and 4.895 ng/mL for CFP‑10. 3.3 Diagnostic Performance of ESAT‑6 and CFP‑10 Using these cut‑offs, ESAT‑6 achieved a sensitivity of 77.9 % and a specificity of 79.2 %, while CFP‑10 achieved 67.3 % and 77.8 %, respectively (Table 2; Figure 3). Both antigens were significantly more sensitive than acid‑fast bacilli (AFB) smear (26.9 %) and Xpert MTB/RIF (56.7 %), albeit with reduced specificity (P < 0.001 for ESAT‑6; P < 0.05 for CFP‑10). Positive and negative predictive values were 84.4 % and 71.3 % for ESAT‑6 and 81.4 % and 62.2 % for CFP‑10. Table 2. Diagnostic performance of ESAT‑6, CFP‑10, sputum acid‑fast bacillus smear, and Xpert MTB/RIF for active pulmonary tuberculosis (n = 176). PTB (n=104) non-PTB (n=72) Sensitivity (per cent) Specificity (per cent) PPV (per cent) NPV (per cent) AFB + 28 0 26.92 (18.69~36.51) 100.00 (95.01 to 100) 100.00 (87.66-100) 48.65 (40.36~ 56.99) - 76 72 GeneXpert MTB/RIF + 59 0 56.73 (46.65~66.41) 100.00 (95.01 to 100) 100.00 (93.94~100) 61.54 (52.09~70.38) - 45 72 ESAT-6 + 81 15 77.89 (68.47~ 85.19) 79.1 8 (67.67~87.50) 84.38 (75.22~ 90.70) 71.25 (59.88~ 80.55) - 23 57 CFP-10 + 70 16 67.31 (57.32~ 76.00) 77.78 (66.15~ 86.39) 81.39 (71.25~ 88.67) 62.22 (51.34~ 72.05) - 34 56 Abbreviations: Positive Predictive Value (PPV); Negative Predictive Value (NPV). 3.4 Sensitivity in BC‑PTB Versus CD‑PTB ESAT‑6 sensitivities were 84.8 % in BC‑PTB and 71.1 % in CD‑PTB (P > 0.05). CFP‑10 sensitivities were 69.5 % and 64.4 %, respectively (P > 0.05), indicating comparable performance irrespective of bacteriological status (Table 3). Table 3. Sensitivity of ESAT‑6 and CFP‑10 in bacteriologically confirmed (BC‑PTB) versus clinically diagnosed (CD‑PTB) pulmonary tuberculosis groups. antigen Sensitivity of BC-PTB group (number of positives/total cases) Sensitivity of CD-PTB group (number of positives/total cases) P-value ESAT-6 84.75 per cent (50/59) 71.11 per cent (32/45) >0.05 CFP-10 69.49 per cent (41/59) 64.44 per cent (29/45) >0.05 3.5 Combined Antigen Analysis Parallel testing (positive if either antigen exceeded its cut‑off) yielded a sensitivity of 94.2 % (95 % CI, 87.4–97.6) with a negative predictive value of 99.2 %, missing only six PTB cases. Tandem testing (positive only when both antigens were positive) increased specificity to 95.8 % (95 % CI, 88.1–98.6) with a false‑positive rate of 4.2 % (Table 4). Detection Strategy antigen combination Case grouping Performance indicators Results (95% CI) parallel connection ESAT-6 + CFP-10 Tuberculosis group Sensitivity/missing rate 94.23 per cent (87.36 per cent to 97.63 per cent) / 5.77 per cent in series connection (electricity) ESAT-6 + CFP-10 Non-tuberculosis group Specificity/misdiagnosis rate 95.83 per cent (87.50-98.92 per cent) / 4.17 per cent 4. Discussion ESAT‑6 and CFP‑10 are pivotal virulence factors secreted via the ESX‑1 system. Their heterodimer enables immune evasion by binding Toll‑like receptors and CD91 on host phagocytes, activating MAPK/ERK signaling, suppressing lysosomal maturation, and promoting intracellular survival of Mycobacterium tuberculosis (MTB)[13]. Because the ESX‑1 locus is absent from most non‑tuberculous mycobacteria (NTM) and from Bacillus Calmette–Guérin (BCG), ESAT‑6 and CFP‑10 provide high species specificity[15–17]. Current immunodiagnostic assays—including interferon‑γ release assays and ESAT‑6/CFP‑10 skin tests—leverage this specificity to avoid BCG or NTM cross‑reactivity. Consistent with previous reports[18–20], direct quantification of ESAT‑6 and CFP‑10 in BALF markedly improved diagnostic sensitivity relative to AFB smear and Xpert MTB/RIF. Although specificity declined, combining the assays in parallel and tandem configurations balanced sensitivity and specificity to meet distinct clinical objectives—either ruling out disease or confirming diagnosis. Antigen sensitivities were comparable in BC‑PTB and CD‑PTB groups, suggesting that secreted antigen detection is less dependent on bacillary burden than microbiological methods. Secreted proteins can diffuse beyond bacilli and may persist after bacterial lysis, thus complementing culture‑based tests, particularly in paucibacillary disease. Limitations include the absence of healthy controls—bronchoscopy precluded their inclusion—and the single‑center design with a modest sample size. Multicenter studies are warranted to validate cut‑off values and standardize protocols. 5. Conclusions ELISA‑based quantification of ESAT‑6 and CFP‑10 in BALF markedly enhances pulmonary tuberculosis (PTB) diagnostic sensitivity irrespective of bacteriological status. Parallel testing provides a reliable rule‑out strategy, whereas tandem testing offers high specificity for confirming disease. BALF antigen detection is a promising adjcunct to existing diagnostic algorithms, especially in smear‑ or Xpert‑negative PTB. Declarations Author contributions Shiyu Fang and Jinxiong Zhuan were responsible for the ELISA assay of alveolar lavage fluid and wrote the main manuscript, Jie Sun was responsible for the collection of alveolar lavage fluid and the analysis of clinical data, and Fengjun Liu was responsible for the revision of the manuscript and experimental guidance. All authors reviewed the manuscript. Funding This study was supported by a grant from the Sichuan Primary Health Care Development Research Centre (Grant No. SWFZ23-Y-41). Availability of data and materials Data is provided within the manuscript or supplementary information files. Ethics approval and consent to participate The study received ethical approval from the Ethics Committee of the Affiliated Hospital of Chuanbei Medical College (approval number: 2023ER224-1). The rights and interests of the subjects were protected throughout the study. 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Cite Share Download PDF Status: Published Journal Publication published 25 Nov, 2025 Read the published version in European Journal of Medical Research → Version 1 posted Editorial decision: Revision requested 12 Sep, 2025 Reviews received at journal 06 Sep, 2025 Reviews received at journal 03 Sep, 2025 Reviewers agreed at journal 26 Aug, 2025 Reviews received at journal 25 Aug, 2025 Reviewers agreed at journal 25 Aug, 2025 Reviews received at journal 24 Aug, 2025 Reviewers agreed at journal 24 Aug, 2025 Reviewers agreed at journal 24 Aug, 2025 Reviews received at journal 09 Jul, 2025 Reviewers agreed at journal 25 Jun, 2025 Reviewers invited by journal 25 Jun, 2025 Editor assigned by journal 23 Jun, 2025 Submission checks completed at journal 23 Jun, 2025 First submitted to journal 07 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-6842949","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":477518843,"identity":"65d6f171-c494-42eb-944f-c7b41397d7e2","order_by":0,"name":"Shiyu Fang","email":"","orcid":"","institution":"Department of Infectious Diseases, Affiliated Hospital of North Sichuan Medical College","correspondingAuthor":false,"prefix":"","firstName":"Shiyu","middleName":"","lastName":"Fang","suffix":""},{"id":477518845,"identity":"8e2a2a55-b289-417c-be20-4459b31b09de","order_by":1,"name":"JinXiong Jiang","email":"","orcid":"","institution":"Department of Infectious Diseases, Affiliated Hospital of North Sichuan Medical College","correspondingAuthor":false,"prefix":"","firstName":"JinXiong","middleName":"","lastName":"Jiang","suffix":""},{"id":477518846,"identity":"4b714106-f366-459f-85ac-c25d31f727f9","order_by":2,"name":"Jie Sun","email":"","orcid":"","institution":"Department of Infectious Diseases, Affiliated Hospital of North Sichuan Medical College","correspondingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Sun","suffix":""},{"id":477518847,"identity":"edd3a268-ae8a-4fe7-8ba6-1ac8eaca4f72","order_by":3,"name":"FengJun Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAApklEQVRIiWNgGAWjYBACA/mHDw4kVNjw8LM3EKtFgiHxwIMzaTKSPQeI15J88GHLYRuDGw7Ea0k4kNhwnofhBgPjh485xGiRbwBq2XGbh3F2A7PkzG1E23LmNg+zzAE2Zl7itbSd42GTSCBaCwtIywEeHhK0sB04kHAmmUeC52AzcX6xn8Hc/PFHhZ29/fHmgx8+EqMFCTA2kKZ+FIyCUTAKRgFuAAD7Yzk6nnqpIQAAAABJRU5ErkJggg==","orcid":"","institution":"Department of Infectious Diseases, Affiliated Hospital of North Sichuan Medical College","correspondingAuthor":true,"prefix":"","firstName":"FengJun","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2025-06-07 12:53:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6842949/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6842949/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40001-025-03449-8","type":"published","date":"2025-11-25T15:57:08+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":85744382,"identity":"321a1c07-30fe-4560-ae0f-7559b29774b2","added_by":"auto","created_at":"2025-07-01 09:16:57","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":37217,"visible":true,"origin":"","legend":"\u003cp\u003eBox‑plot distributions of BALF ESAT‑6 and CFP‑10 concentrations in CD‑PTB, BC‑PTB, and non‑PTB groups (n = 176).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6842949/v1/57e13406e70797ff5f6f9b02.png"},{"id":85744372,"identity":"3602155a-6a30-42a1-bf2a-9c0b732e8141","added_by":"auto","created_at":"2025-07-01 09:16:57","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":25763,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver‑operating‑characteristic curves for ESAT‑6 and CFP‑10 in the diagnosis of pulmonary tuberculosis (n = 176).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6842949/v1/679fd5d2e593cd7c63be42de.png"},{"id":85746567,"identity":"152bb914-aa09-41c2-a58b-397e0f24caf3","added_by":"auto","created_at":"2025-07-01 09:32:57","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":45638,"visible":true,"origin":"","legend":"\u003cp\u003eComparative sensitivity and specificity of ESAT‑6 and CFP‑10 versus sputum AFB smear and Xpert MTB/RIF.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6842949/v1/b4c61d780d9c0edf948ca64a.png"},{"id":97178382,"identity":"2eb3f5b7-f157-4044-89f9-9fc182de0cd4","added_by":"auto","created_at":"2025-12-01 16:09:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":812090,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6842949/v1/9ef74cb3-749e-4fa6-8d15-ef69d48d0434.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A new strategy for the diagnosis of tuberculosis based on secreted antigens: evaluation of the efficacy of alveolar lavage ESAT-6 and CFP-10 tests","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eTuberculosis (PTB) is a chronic infectious disease caused by Mycobacterium tuberculosis infection and has surpassed AIDS as the world's leading cause of death from infectious diseases. China is among the countries with the highest PTB burden. According to the World Health Organization's (WHO) Global Tuberculosis Report 2024[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], there were approximately 10.8\u0026nbsp;million new PTB cases globally in 2023, with China accounting for 741,000 cases, ranking third among the 30 high-burden countries. In 2014, WHO initiated the End TB Strategy, aiming to reduce TB incidence to less than 10 per 100,000 population by 2035[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. A core component of this strategy is \"early and accurate diagnosis,\" crucial for breaking the transmission chain. Epidemiological data indicate that over 60% of global PTB cases are initially diagnosed in primary healthcare centers (PHCs)[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], highlighting the importance of PHCs in PTB control. However, current primary diagnostic methods, primarily sputum smear microscopy, suffer from low sensitivity, missing 35\u0026ndash;40% of cases, thus exacerbating delays in diagnosis and increasing risks for secondary drug resistance. Therefore, there is an urgent need to identify highly sensitive, cost-effective, and user-friendly diagnostic tools to bridge this diagnostic gap and facilitate the implementation of the End TB Strategy.\u003c/p\u003e \u003cp\u003eCurrently, tuberculosis diagnosis relies on identifying etiological evidence, primarily through MTB acid-fast bacilli (AFB) smears or mycobacterial cultures. AFB smear microscopy is economical and efficient but exhibits low sensitivity, particularly in patients with low bacterial loads, and cannot differentiate between non-tuberculous mycobacteria (NTM) and MTB[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Mycobacterial culture, considered the gold standard, offers superior sensitivity but faces significant practical and technical limitations, including prolonged incubation periods and stringent biosafety requirements, delaying timely diagnosis and treatment initiation[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Molecular diagnostic techniques, notably polymerase chain reaction (PCR), have significantly improved PTB diagnosis due to their high sensitivity, specificity, rapidity, and cost-effectiveness[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Advanced molecular diagnostics such as Xpert MTB/RIF and Xpert MTB/RIF Ultra have further enhanced MTB detection, particularly in HIV-positive patients, and enabled rapid identification of drug-resistant strains[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Nevertheless, the high costs and strict operational requirements limit their widespread adoption in primary care settings[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eImmunological tests, detecting host immune responses to MTB-specific antigens, also play a significant auxiliary role in PTB diagnosis. Gamma-interferon release assays (IGRA) and the tuberculin skin test (TST) are commonly utilized for detecting latent MTB infection (LPTBI) by assessing T-cell responses to MTB-specific antigens ESAT-6 and CFP-10[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, these tests have limitations in distinguishing active PTB from LPTBI, influenced by factors such as the host's immune status and prior infection history[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Given the high diagnostic potential of ESAT-6 and CFP-10, this study aimed to directly quantify these antigens in alveolar lavage fluid using ELISA. The sensitivity and specificity of ELISA-based antigen detection were systematically compared with traditional AFB and Xpert MTB/RIF assays to evaluate its utility in PTB diagnosis and provide a novel diagnostic approach for clinical practice.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study design and participants\u003c/h2\u003e \u003cp\u003eThis was a retrospective, single-center clinical study conducted at the Affiliated Hospital of Chuanbei Medical College between May 2021 and July 2023. The study included patients who underwent fiberoptic bronchoscopy. Clinical history data and bronchoalveolar lavage fluid samples were systematically collected. Patients were classified into pulmonary tuberculosis (PTB) and non-pulmonary tuberculosis (non-PTB) groups based on diagnoses. The PTB group was further subdivided into bacteriologically confirmed cases of pulmonary tuberculosis (BC-PTB) and clinically diagnosed cases of pulmonary tuberculosis (CD-PTB). Patients in the PTB group met the following conditions: (1) fulfill the diagnostic criteria outlined in WS288-2017[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]; and (2) exhibit effectiveness after standardized anti-tuberculosis treatment. To ensure accurate microbiological test results, BALF samples from all PTB patients were collected before initiating anti-tuberculosis therapy. Inclusion criteria for the non-PTB group were: (1) no history or exposure to tuberculosis; (2) definitive diagnosis of pulmonary tumors by pathological examination or other pulmonary infections with confirmed etiological evidence; and (3) negative IGRA results. Additionally, all study participants were tested to exclude hepatitis C virus, hepatitis B virus, and HIV infections.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Collection and Preservation of Bronchoalveolar Lavage Fluid\u003c/h2\u003e \u003cp\u003eAfter obtaining informed consent, bronchoalveolar lavage fluid (BALF) collection strictly adhered to technical guidelines provided by the European Respiratory Society[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and standard operating procedures. Alveolar lavage involved three lavages using sterile saline, each with a volume of 10\u0026ndash;20 mL, totaling 50\u0026ndash;60 mL. Fluid recovery was conducted at a negative pressure of -13.3 kPa to -19.95 kPa after each lavage, achieving a recovery rate of 30%-50%. The collected fluid from all three lavages was thoroughly mixed, aliquoted into sterile frozen tubes pretreated with silicone oil, and immediately stored at -20\u0026deg;C. To prevent sample degradation, each sample underwent a single freeze-thaw cycle, with thawing performed overnight at 4\u0026deg;C before use.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Optimal Sample Dilution Identification\u003c/h2\u003e \u003cp\u003eCheckerboard titration was performed to determine optimal sample dilution. Three samples with the highest acid-fast bacilli content (smear results ranging from +++ to ++++) were pre-tested at dilution ratios of 1:1, 1:5, 1:10, and 1:20. The optimal dilution was identified by calculating the ratio (P/N value) of absorbance between positive samples and negative controls. Experimental results indicated that undiluted samples provided the highest P/N value and thus were used in subsequent assays.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 ELISA detection of BALF\u003c/h2\u003e \u003cp\u003e BALF supernatant was analyzed using a Mycobacterium tuberculosis antigen ELISA kit (Camilo Biological Co., Nanjing, China) in strict accordance with the manufacturer\u0026rsquo;s instructions. Briefly, the kit was equilibrated to room temperature for 20 min before use. Lyophilized ESAT-6 and CFP-10 standards were reconstituted in 1 mL of standard diluent to yield stock concentrations of 100 ng/mL (ESAT-6) and 20 ng/mL (CFP-10). Serial twofold dilutions (100\u0026ndash;1.5%) were prepared to construct the standard curves. Standards and BALF samples (100 \u0026micro;L/well, in duplicate) were loaded onto antibodycoated microplates and incubated at 37\u0026deg;C for 90 min. After two washes, 100 \u0026micro;L of 1:100diluted biotinylated detection antibody was added, followed by incubation at 37\u0026deg;C for 60 min. Plates were washed three times, and 100 \u0026micro;L of horseradishperoxidase conjugate was applied for 30 min at 37\u0026deg;C in the dark. Following five washes, 100 \u0026micro;L of substrate solution was added and the reaction was stopped with 2 M H₂SO₄ when adequate color developed. Optical density (OD) was measured at 450 nm with a 630 nm reference, blankcorrected, and antigen concentrations were interpolated from the standard curves using ELISACalc software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Clinical data collection in patients with and without PTB\u003c/h2\u003e \u003cp\u003eFor PTB participants, demographic and clinical data\u0026mdash;including age, sex, ethnicity, comorbidities, HIV status, chest CT findings (presence or absence of cavities), prior PTB history, and response to antituberculosis therapy\u0026mdash;were recorded. For nonPTB participants, age and sex were collected.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Statistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using SPSS version 25 (IBM Corp.). Receiver operating characteristic (ROC) curves were generated to assess diagnostic performance, with optimal cutoff values determined by maximizing Youden\u0026rsquo;s index. Data normality was evaluated using the Shapiro\u0026ndash;Wilk test. Normally distributed variables are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation and compared with the independentsamples t test. Nonnormally distributed data are expressed as median (interquartile range) and compared using the Mann\u0026ndash;Whitney U test. Categorical variables were analyzed with Pearson\u0026rsquo;s χ\u0026sup2; test. A twosided P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. GraphPad Prism 8.0.1 was used for data visualization.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Basic characteristics of study participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBetween May 2021 and July 2023, 104 patients with PTB (59 bacteriologically confirmed [BC‑PTB] and 45 clinically diagnosed [CD‑PTB]) underwent bronchoscopy and were enrolled. All PTB cases responded to standard anti‑tuberculosis therapy. The control cohort comprised 72 patients with non‑tuberculous pulmonary diseases confirmed by microbiological testing. Baseline characteristics are summarized in Table 1. Participant ages ranged from 13 to 85 years (median 50 years), and 75.3 % were male. Cough was the most common symptom (69.3 %), and diabetes mellitus was the most frequent PTB comorbidity (11.5 %).\u003c/p\u003e\n\u003cp\u003eTable1. Baseline demographic and microbiological characteristics of the study participants (n = 80).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"548\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003ePTB group (n=104)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003enon-PTB group (n=72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eMedian age [IQR] years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e44 [13-78]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e58.5 [16-85]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e0.0001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eMen (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e75 (72.1 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e48 (66.7 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e0.370 \u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003ePrevious pulmonary tuberculosis (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e1 (0.96 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e0 (0 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e1.00\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eCough (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e68 (65.3 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e54 (75.0 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e0.174 \u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eFever(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e14 (13.4 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e23 (31.9 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e0.003 \u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eWeight loss(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e19 (18.2 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e11 (15.2 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e0.604 \u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eNight sweats(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e27 (25.9 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e5 (6.9 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e0.001 \u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eDiabetes mellitus (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e12 (11.5 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e9 (12.5 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e0.843 \u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eHypertension (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e2 (1.9 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e9 (12.5 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e0.018\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eExtrapulmonary tuberculosis (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e7 (6.7 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e0 (0 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e0.045\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eLung tumor (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e3 (2.9 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e8 (11.1 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e0.045\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eSepsis (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e1 (1.0 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e1 (1.4 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e1.00\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eConnective tissue disease (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e0 (0 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e5 (6.9 per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e0.018\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\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*Mann-Whitney U test\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e** Fisher\u0026apos;s exact test\u003c/p\u003e\n\u003cp\u003e*** Chi-square test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 BALF ESAT‑6 and CFP‑10 Concentrations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMedian BALF concentrations of ESAT‑6 and CFP‑10 were significantly higher in both BC‑PTB and CD‑PTB groups than in the non‑PTB group (P \u0026lt; 0.001; Figure 1). ESAT‑6 concentrations did not differ between BC‑PTB and CD‑PTB (P = 0.056), whereas CFP‑10 levels were higher in BC‑PTB (P = 0.045). ROC analysis yielded areas under the curve of 0.856 for ESAT‑6 and 0.805 for CFP‑10. Optimal cut‑off values were 24.54 ng/mL for ESAT‑6 and 4.895 ng/mL for CFP‑10.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Diagnostic Performance of ESAT‑6 and CFP‑10\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing these cut‑offs, ESAT‑6 achieved a sensitivity of 77.9 % and a specificity of 79.2 %, while CFP‑10 achieved 67.3 % and 77.8 %, respectively (Table 2; Figure 3). Both antigens were significantly more sensitive than acid‑fast bacilli (AFB) smear (26.9 %) and Xpert MTB/RIF (56.7 %), albeit with reduced specificity (P \u0026lt; 0.001 for ESAT‑6; P \u0026lt; 0.05 for CFP‑10). Positive and negative predictive values were 84.4 % and 71.3 % for ESAT‑6 and 81.4 % and 62.2 % for CFP‑10.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eDiagnostic performance of ESAT‑6, CFP‑10, sputum acid‑fast bacillus smear, and Xpert MTB/RIF for active pulmonary tuberculosis (n = 176).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"104%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003ePTB\u003c/p\u003e\n \u003cp\u003e(n=104)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003enon-PTB\u003c/p\u003e\n \u003cp\u003e(n=72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003cp\u003e(per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003cp\u003e(per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003ePPV\u003c/p\u003e\n \u003cp\u003e(per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003eNPV\u003c/p\u003e\n \u003cp\u003e(per cent)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 12px;\"\u003e\n \u003cp\u003eAFB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 14px;\"\u003e\n \u003cp\u003e26.92\u003c/p\u003e\n \u003cp\u003e(18.69~36.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 14px;\"\u003e\n \u003cp\u003e100.00\u003c/p\u003e\n \u003cp\u003e(95.01 to 100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 14px;\"\u003e\n \u003cp\u003e100.00\u003c/p\u003e\n \u003cp\u003e(87.66-100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 14px;\"\u003e\n \u003cp\u003e48.65\u003c/p\u003e\n \u003cp\u003e(40.36~ 56.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 12px;\"\u003e\n \u003cp\u003eGeneXpert MTB/RIF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e56.73\u003c/p\u003e\n \u003cp\u003e(46.65~66.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e100.00\u003c/p\u003e\n \u003cp\u003e(95.01 to 100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e100.00\u003c/p\u003e\n \u003cp\u003e(93.94~100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e61.54\u003c/p\u003e\n \u003cp\u003e(52.09~70.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 12px;\"\u003e\n \u003cp\u003eESAT-6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e77.89\u003c/p\u003e\n \u003cp\u003e(68.47~ 85.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e79.1 8\u003c/p\u003e\n \u003cp\u003e(67.67~87.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e84.38\u003c/p\u003e\n \u003cp\u003e(75.22~ 90.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e71.25\u003c/p\u003e\n \u003cp\u003e(59.88~ 80.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 12px;\"\u003e\n \u003cp\u003eCFP-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e67.31\u003c/p\u003e\n \u003cp\u003e(57.32~ 76.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e77.78\u003c/p\u003e\n \u003cp\u003e(66.15~ 86.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e81.39\u003c/p\u003e\n \u003cp\u003e(71.25~ 88.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e62.22\u003c/p\u003e\n \u003cp\u003e(51.34~ 72.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 3px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: Positive Predictive Value (PPV); Negative Predictive Value (NPV).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 Sensitivity in BC‑PTB Versus CD‑PTB\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eESAT‑6 sensitivities were 84.8 % in BC‑PTB and 71.1 % in CD‑PTB (P \u0026gt; 0.05). CFP‑10 sensitivities were 69.5 % and 64.4 %, respectively (P \u0026gt; 0.05), indicating comparable performance irrespective of bacteriological status (Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Sensitivity of ESAT‑6 and CFP‑10 in bacteriologically confirmed (BC‑PTB) versus clinically diagnosed (CD‑PTB) pulmonary tuberculosis groups.\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"90%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003eantigen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 200px;\"\u003e\n \u003cp\u003eSensitivity of BC-PTB group (number of positives/total cases)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 202px;\"\u003e\n \u003cp\u003eSensitivity of CD-PTB group (number of positives/total cases)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003eESAT-6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 200px;\"\u003e\n \u003cp\u003e84.75 per cent (50/59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 202px;\"\u003e\n \u003cp\u003e71.11 per cent (32/45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026gt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003eCFP-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 200px;\"\u003e\n \u003cp\u003e69.49 per cent (41/59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 202px;\"\u003e\n \u003cp\u003e64.44 per cent (29/45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026gt;0.05\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\u003e3.5 Combined Antigen Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParallel testing (positive if either antigen exceeded its cut‑off) yielded a sensitivity of 94.2 % (95 % CI, 87.4\u0026ndash;97.6) with a negative predictive value of 99.2 %, missing only six PTB cases. Tandem testing (positive only when both antigens were positive) increased specificity to 95.8 % (95 % CI, 88.1\u0026ndash;98.6) with a false‑positive rate of 4.2 % (Table 4).\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"114%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eDetection Strategy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003eantigen combination\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eCase grouping\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003ePerformance indicators\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 195px;\"\u003e\n \u003cp\u003eResults (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eparallel connection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003eESAT-6 + CFP-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eTuberculosis group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003eSensitivity/missing rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 195px;\"\u003e\n \u003cp\u003e94.23 per cent (87.36 per cent to 97.63 per cent) / 5.77 per cent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003ein series connection (electricity)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003eESAT-6 + CFP-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eNon-tuberculosis group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\n \u003cp\u003eSpecificity/misdiagnosis rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 195px;\"\u003e\n \u003cp\u003e95.83 per cent (87.50-98.92 per cent) / 4.17 per cent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"4.\tDiscussion","content":"\u003cp\u003eESAT‑6 and CFP‑10 are pivotal virulence factors secreted via the ESX‑1 system. Their heterodimer enables immune evasion by binding Toll‑like receptors and CD91 on host phagocytes, activating MAPK/ERK signaling, suppressing lysosomal maturation, and promoting intracellular survival of Mycobacterium tuberculosis (MTB)[13]. Because the ESX‑1 locus is absent from most non‑tuberculous mycobacteria (NTM) and from Bacillus Calmette–Guérin (BCG), ESAT‑6 and CFP‑10 provide high species specificity[15–17]. Current immunodiagnostic assays—including interferon‑γ release assays and ESAT‑6/CFP‑10 skin tests—leverage this specificity to avoid BCG or NTM cross‑reactivity.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Consistent with previous reports[18–20], direct quantification of ESAT‑6 and CFP‑10 in BALF markedly improved diagnostic sensitivity relative to AFB smear and Xpert MTB/RIF. Although specificity declined, combining the assays in parallel and tandem configurations balanced sensitivity and specificity to meet distinct clinical objectives—either ruling out disease or confirming diagnosis.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Antigen sensitivities were comparable in BC‑PTB and CD‑PTB groups, suggesting that secreted antigen detection is less dependent on bacillary burden than microbiological methods. Secreted proteins can diffuse beyond bacilli and may persist after bacterial lysis, thus complementing culture‑based tests, particularly in paucibacillary disease.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Limitations include the absence of healthy controls—bronchoscopy precluded their inclusion—and the single‑center design with a modest sample size. Multicenter studies are warranted to validate cut‑off values and standardize protocols.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"5.\tConclusions","content":"\u003cp\u003eELISA‑based quantification of ESAT‑6 and CFP‑10 in BALF markedly enhances pulmonary tuberculosis (PTB) diagnostic sensitivity irrespective of bacteriological status. Parallel testing provides a reliable rule‑out strategy, whereas tandem testing offers high specificity for confirming disease. BALF antigen detection is a promising adjcunct to existing diagnostic algorithms, especially in smear‑ or Xpert‑negative PTB.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eShiyu Fang and Jinxiong Zhuan were responsible for the ELISA assay of alveolar lavage fluid and wrote the main manuscript, Jie Sun was responsible for the collection of alveolar lavage fluid and the analysis of clinical data, and Fengjun Liu was responsible for the revision of the manuscript and experimental guidance. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by a grant from the Sichuan Primary Health Care Development Research Centre (Grant No. SWFZ23-Y-41).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData is provided within the manuscript or supplementary information files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study received ethical approval from the Ethics Committee of the Affiliated Hospital of Chuanbei Medical College (approval number: 2023ER224-1). The rights and interests of the subjects were protected throughout the study. Participants provided written informed consent, and their privacy and confidentiality were strictly maintained. Data collected were used exclusively for this research and were not shared or used without authorization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the participants provided written informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eOrganization WHO. Global tuberculosis report 2024[M/OL]. https://www.who.int/teams/global-tuberculosis-programme/tb-reports/global-tuberculosis-report-2024.[J].\u003c/li\u003e\n \u003cli\u003eUplekar M, Weil D, Lonnroth K, et al. WHO\u0026rsquo;s new End TB Strategy[J]. The Lancet, 2015, 385(9979): 1799-1801.\u003c/li\u003e\n \u003cli\u003eVilch\u0026egrave;ze C, Kremer L. Acid-Fast Positive and Acid-Fast Negative Mycobacterium tuberculosis: The Koch Paradox[J]. Microbiology Spectrum, 2017, 5(2): 5.2.15.\u003c/li\u003e\n \u003cli\u003eSomosk\u0026ouml;vi \u0026Aacute;, K\u0026ouml;dm\u0026ouml;n C, Lantos \u0026Aacute;, et al. Comparison of Recoveries of Mycobacterium tuberculosis Using the Automated BACTEC MGIT 960 System, the BACTEC 460 TB System, and L\u0026ouml;wenstein-Jensen Medium[J]. Journal of Clinical Microbiology, 2000, 38(6): 2395-2397.\u003c/li\u003e\n \u003cli\u003eLu W, Feng Y, Wang J, et al. Evaluation of MTBDRplus and MTBDRsl in Detecting Drug-Resistant Tuberculosis in a Chinese Population[J]. Disease Markers, 2016, 2016: 1-9.\u003c/li\u003e\n \u003cli\u003eMirzayev F, Viney K, Linh N N, et al. World Health Organization recommendations on the treatment of drug-resistant tuberculosis, 2020 update[J]. European Respiratory Journal, 2021, 57(6): 2003300.\u003c/li\u003e\n \u003cli\u003eOpota O, Mazza-Stalder J, Greub G, et al. The rapid molecular test Xpert MTB/RIF ultra: towards improved tuberculosis diagnosis and rifampicin resistance detection[J]. Clinical Microbiology and Infection, 2019, 25(11): 1370-1376.\u003c/li\u003e\n \u003cli\u003eKolia-Diafouka P, Godreuil S, Bourdin A, et al. Optimized Lysis-Extraction Method Combined With IS6110-Amplification for Detection of Mycobacterium tuberculosis in Paucibacillary Sputum Specimens[J]. Frontiers in Microbiology, 2018, 9: 2224.\u003c/li\u003e\n \u003cli\u003eLatent Mycobacterium tuberculosis Infection and Interferon-Gamma Release Assays | Microbiology Spectrum[EB/OL]. [2025-03-08]. https://journals.asm.org/doi/10.1128/microbiolspec.tbtb2-0023-2016.\u003c/li\u003e\n \u003cli\u003eAuguste P, Tsertsvadze A, Pink J, et al. Comparing interferon-gamma release assays with tuberculin skin test for identifying latent tuberculosis infection that progresses to active tuberculosis: systematic review and meta-analysis[J]. BMC Infectious Diseases, 2017, 17(1): 200.\u003c/li\u003e\n \u003cli\u003eDiagnosis of Pulmonary Tuberculosis WS 288\u0026mdash;2017[Z]. Chinese Journal of Infection Control, 2018.[J].\u003c/li\u003e\n \u003cli\u003eTechnical recommendations and guidelines for bronchoalveolar lavage (BAL). Report of the European Society of Pneumology Task Group[J]. European Respiratory Journal, 2(6): 561.\u003c/li\u003e\n \u003cli\u003eOsman M M, Shanahan J K, Chu F, et al. The C terminus of the mycobacterium ESX-1 secretion system substrate ESAT-6 is required for phagosomal membrane damage and virulence[J]. Proceedings of the National Academy of Sciences, 2022, 119(11): e2122161119.\u003c/li\u003e\n \u003cli\u003eZhang Q, Lu X, Gao L, et al. In Vitro and In Vivo Antigen Presentation and Diagnosis Development of Recombinant Overlapping Peptides Corresponding to Mtb ESAT-6/CFP-10[J]. Frontiers in Immunology, 2022, 13: 872676.\u003c/li\u003e\n \u003cli\u003eTiwari S, Casey R, Goulding C W, et al. Infect and Inject: How Mycobacterium tuberculosis Exploits Its Major Virulence-Associated Type VII Secretion System, ESX-1[J]. Microbiology Spectrum, 2019, 7(3): 7.3.18.\u003c/li\u003e\n \u003cli\u003eLiu C, Zhao Z, Fan J, et al. Quantification of circulating Mycobacterium tuberculosis antigen peptides allows rapid diagnosis of active disease and treatment monitoring[J]. Proceedings of the National Academy of Sciences, 2017, 114(15): 3969-3974.\u003c/li\u003e\n \u003cli\u003ePym A S, Brodin P, Brosch R, et al. Loss of RD1 contributed to the attenuation of the live tuberculosis vaccines Mycobacterium bovis BCG and Mycobacterium microti[J]. Molecular Microbiology, 2002, 46(3): 709-717.\u003c/li\u003e\n \u003cli\u003ePassos B B S, Ara\u0026uacute;jo-Pereira M, Vinhaes C L, et al. The role of ESAT-6 in tuberculosis immunopathology[J]. Frontiers in Immunology, 2024, 15: 1383098.\u003c/li\u003e\n \u003cli\u003eSeele P P, Dyan B, Skepu A, et al. Development of Gold-Nanoparticle-Based Lateral Flow Immunoassays for Rapid Detection of TB ESAT-6 and CFP-10[J]. Biosensors, 2023, 13(3): 354.\u003c/li\u003e\n \u003cli\u003eChen X, Duan S, Zhou X, et al. Diagnostic value of tuberculosis-specific antigens ESAT-6 and CFP10 in lymph node tuberculosis[J]. Heliyon, 2024, 10(8): e29251.\u003c/li\u003e\n \u003cli\u003eZhou W, Li H, Zhang Y, et al. Diagnostic Value of Galactomannan Antigen Test in Serum and Bronchoalveolar Lavage Fluid Samples from Patients with Nonneutropenic Invasive Pulmonary Aspergillosis[J]. Journal of Clinical Microbiology, 2017, 55(7): 2153-2161.\u003c/li\u003e\n \u003cli\u003eNisa A, Kipper F C, Panigrahy D, et al. Different modalities of host cell death and their impact on Mycobacterium tuberculosis infection[J]. American Journal of Physiology-Cell Physiology, 2022, 323(5): C1444-C1474.\u003c/li\u003e\n \u003cli\u003eHousden N G, Webby M N, Lowe E D, et al. Toxin import through the antibiotic efflux channel TolC[J]. Nature Communications, 2021, 12(1): 4625.\u003c/li\u003e\n \u003cli\u003eSun J, Zhou X, Yu J, et al. Diagnostic value of tuberculosis-Specific antigens Ag85B, ESAT-6 and CFP10 in pulmonary tuberculosis[J]. Journal of Clinical Tuberculosis and Other Mycobacterial Diseases, 2024, 37: 100486.\u003c/li\u003e\n \u003cli\u003eChe N, Qu Y, Zhang C, et al. Double staining of bacilli and antigen Ag85B improves the accuracy of the pathological diagnosis of pulmonary tuberculosis[J]. Journal of Clinical Pathology, 2016, 69(7): 600-606.\u003c/li\u003e\n \u003cli\u003eErnst J D, Cornelius A, Bolz M. Dynamics of Mycobacterium tuberculosis Ag85B Revealed by a Sensitive Enzyme-Linked Immunosorbent Assay[J]. mBio, 2019, 10(2): e00611-19.\u003c/li\u003e\n \u003cli\u003eGolichenari B, Velonia K, Nosrati R, et al. Label-free nano-biosensing on the road to tuberculosis detection[J]. Biosensors and Bioelectronics, 2018, 113: 124-135.\u003c/li\u003e\n\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":"european-journal-of-medical-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejmr","sideBox":"Learn more about [European Journal of Medical Research](http://eurjmedres.biomedcentral.com)","snPcode":"40001","submissionUrl":"https://submission.nature.com/new-submission/40001/3","title":"European Journal of Medical Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Pulmonary tuberculosis, Tuberculosis antigen, Enzyme-linked immunosorbent assay, Acid fast bacteria, Xpert MTB/RIF","lastPublishedDoi":"10.21203/rs.3.rs-6842949/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6842949/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e To assess the diagnostic value of Mycobacterium tuberculosis (MTB)-specific secreted antigens ESAT-6 and CFP-10 in alveolar lavage fluid (BALF), and to explore novel adjunctive diagnostic strategies to enhance the diagnostic rate of pulmonary tuberculosis (PTB).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003e104 patients with PTB (59 confirmed cases and 45 clinically diagnosed cases) and 72 patients with non-tuberculosis lung diseases (control group), hospitalized from May 2021 to July 2023, underwent bronchoscopy. The concentrations of ESAT-6 and CFP-10 antigens were detected by enzyme-linked immunosorbent assay (ELISA). Optimal cut-off values were determined by receiver operating characteristic (ROC) curves to evaluate antigen diagnostic capability for active PTB, compared with acid-fast bacilli (AFB) and Xpert MTB/RIF.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eAntigen expression characteristics: Concentrations of ESAT-6 and CFP-10 were significantly higher in the PTB group compared to controls (both P\u0026lt;0.001). ESAT-6 levels did not differ significantly between confirmed and clinically diagnosed cases (P\u0026gt;0.05), whereas CFP-10 concentrations were significantly higher in confirmed cases (P=0.045).\u003c/p\u003e\n\u003cp\u003eComparison of diagnostic efficacy: Sensitivities of AFB and Xpert MTB/RIF were 26.92% (95% CI: 18.6-37.2%) and 56.73% (95% CI: 46.1-66.8%), respectively, with specificity at 100%. ESAT-6 and CFP-10 demonstrated significantly higher sensitivities (77.89%, 95% CI: 68.5-85.1%; 67.31%, 95% CI: 57.3-76.0%) compared to AFB (Δ=50.97%, P\u0026lt;0.001; Δ=40.39%, P\u0026lt;0.001) and Xpert MTB/RIF (Δ=21.16%, P\u0026lt;0.001; Δ=10.58%, P=0.021), but had lower specificity (P\u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003eCombined testing strategy: Parallel testing (either antigen positive) yielded sensitivity of 94.23% (95% CI: 87.4-97.6%) and negative predictive value of 99.2%, while tandem testing (both antigens positive) provided specificity of 95.83% (95% CI: 88.1-98.6%).\u003c/p\u003e\n\u003cp\u003eSubgroup analysis: No statistically significant difference was observed in antigen sensitivities between bacteriologically positive and negative PTB groups (P\u0026gt;0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e (1) ESAT-6 and CFP-10 detection in BALF significantly improves PTB diagnostic sensitivity, unaffected by bacterial load, particularly benefiting the diagnosis of bacteriologically negative PTB. (2) Combined antigen testing strategies (parallel/tandem) optimally balance sensitivity and specificity, meeting clinical requirements for ruling out or confirming PTB diagnosis.\u003c/p\u003e","manuscriptTitle":"A new strategy for the diagnosis of tuberculosis based on secreted antigens: evaluation of the efficacy of alveolar lavage ESAT-6 and CFP-10 tests","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-01 09:16:52","doi":"10.21203/rs.3.rs-6842949/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-12T09:06:58+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-06T05:30:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-03T13:45:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"246784573789204538834665748649464897960","date":"2025-08-26T07:40:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-25T19:54:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"113782483941979765845563588543862718169","date":"2025-08-25T04:54:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-24T15:19:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"36034795973046594124874350862802196982","date":"2025-08-24T14:48:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"300734835034681405435584974913211586870","date":"2025-08-24T06:48:38+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-09T16:20:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"139564112853566931577334535796739279662","date":"2025-06-25T17:41:20+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-25T15:53:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-23T14:40:48+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-23T12:22:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Medical Research","date":"2025-06-07T12:44:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-medical-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejmr","sideBox":"Learn more about [European Journal of Medical Research](http://eurjmedres.biomedcentral.com)","snPcode":"40001","submissionUrl":"https://submission.nature.com/new-submission/40001/3","title":"European Journal of Medical Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a81a4aa4-eba1-4af3-ba0d-4a9889ff3584","owner":[],"postedDate":"July 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-01T16:01:39+00:00","versionOfRecord":{"articleIdentity":"rs-6842949","link":"https://doi.org/10.1186/s40001-025-03449-8","journal":{"identity":"european-journal-of-medical-research","isVorOnly":false,"title":"European Journal of Medical Research"},"publishedOn":"2025-11-25 15:57:08","publishedOnDateReadable":"November 25th, 2025"},"versionCreatedAt":"2025-07-01 09:16:52","video":"","vorDoi":"10.1186/s40001-025-03449-8","vorDoiUrl":"https://doi.org/10.1186/s40001-025-03449-8","workflowStages":[]},"version":"v1","identity":"rs-6842949","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6842949","identity":"rs-6842949","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}