https://doi.org/10.4081/monaldi.2024.2847
A nomogram to predict lung cancer in pulmonary lesions for tuberculosis infection patients
Submitted: November 14, 2023
Accepted: March 1, 2024
Published: March 13, 2024
Accepted: March 1, 2024
Abstract Views: 433
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All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Authors
Similar clinical features make the differential diagnosis difficult, particularly between lung cancer and pulmonary tuberculosis (TB), without pathological evidence for patients with concomitant TB infection. Our study aimed to build a nomogram to predict malignant pulmonary lesions applicable to clinical practice. We retrospectively analyzed clinical characteristics, imaging features, and laboratory indicators of TB infection patients diagnosed with lung cancer or active pulmonary TB at Xiangya Hospital of Central South University. A total of 158 cases from January 1, 2018 to May 30, 2019 were included in the training cohort. Predictive factors for lung cancer were screened by a multiple-stepwise logistic regression analysis. A nomogram model was established, and the discrimination, stability, and prediction performance of the model were analyzed. A total of 79 cases from June 1, 2019, to December 30, 2019, were used as the validation cohort to verify the predictive value of the model. Eight predictor variables, including age, pleural effusion, mediastinal lymph node, the number of positive tumor markers, the T cell spot test for TB, pulmonary lesion morphology, location, and distribution, were selected to construct the model. The corrected C-statistics and the Brier scores were 0.854 and 0.130 in the training cohort, and 0.823 and 0.163 in the validation cohort. Calibration plots showed good performance, and decision curve analysis indicated a high net benefit. In conclusion, the nomogram model provides an effective method to calculate the probability of lung cancer in TB infection patients, and it has excellent discrimination, stability, and prediction performance in detecting a malignant diagnosis of undiagnosed pulmonary lesions.
Lovly CM. Expanding horizons for treatment of early-stage lung cancer. N Engl J Med 2022;386:2050-1.
DOI: https://doi.org/10.1056/NEJMe2203330
Cao M, Chen W. Epidemiology of lung cancer in China. Thorac Cancer 2019;10:3-7.
DOI: https://doi.org/10.1111/1759-7714.12916
Ho JC, Leung CC. Management of co-existent tuberculosis and lung cancer. Lung Cancer 2018;122:83-7.
DOI: https://doi.org/10.1016/j.lungcan.2018.05.030
WHO. Guidelines on the management of latent tuberculosis infection. Available from: https://iris.who.int/bitstream/handle/10665/136471/9789241548908_eng.pdf?sequence=1.
Targeted tuberculin testing and treatment of latent tuberculosis infection. American Thoracic Society. MMWR Recomm Rep 2000;49:1-51.
Ortiz-Brizuela E, Apriani L, Mukherjee T, et al. Assessing the diagnostic performance of new commercial interferon-γ release assays for mycobacterium tuberculosis infection: a systematic review and meta-analysis. Clin Infect Dis 2023;76:1989-99.
DOI: https://doi.org/10.1093/cid/ciad030
Liu H, Huang Y, Wang J, et al. Clinical evaluation of T-SPOT. TB assay in 1 084 tuberculosis suspects. Zhonghua Jie He He Hu Xi Za Zhi 2014;37:192-6. [Article in Chinese].
Santín Cerezales M, Domínguez Benítez J. Diagnosis of tuberculosis infection using interferon-γ-based assays. Enferm Infecc Microbiol Clin 2011;29 Suppl 1:26-33.
DOI: https://doi.org/10.1016/S0213-005X(11)70015-5
Gilani B, Sergent SR. Interferon test. Treasure Island (FL): StatPearls Publishing; 2021.
Zhu M, Zhu Z, Yang J, Hu K. Performance evaluation of IGRA-ELISA and T-SPOT.TB for diagnosing tuberculosis infection. Clin Lab 2019;65.
DOI: https://doi.org/10.7754/Clin.Lab.2019.181109
Mazurek GH, Jereb J, Vernon A, et al. Updated guidelines for using Interferon Gamma release assays to detect mycobacterium tuberculosis infection - United States, 2010. MMWR Recomm Rep 2010;59:1-25.
Vynnycky E, Fine PE. Lifetime risks, incubation period, and serial interval of tuberculosis. Am J Epidemiol 2000;152:247-63.
DOI: https://doi.org/10.1093/aje/152.3.247
Guo Z, Xiao D, Wang X, et al. Epidemiological characteristics of pulmonary tuberculosis in mainland China from 2004 to 2015: a model-based analysis. BMC Public Health 2019;19:219.
DOI: https://doi.org/10.1186/s12889-019-6544-4
Zhu C, Liu Z, Li Z, et al. The performance and limitation of T-SPOT.TB for the diagnosis of TB in a high prevalence setting. J Thorac Dis 2014;6:713-9.
Patz EF, Jr., Pinsky P, Gatsonis C, et al. Overdiagnosis in low-dose computed tomography screening for lung cancer. JAMA Intern Med 2014;174:269-74.
DOI: https://doi.org/10.1001/jamainternmed.2013.12738
Takiguchi Y, Sekine I, Iwasawa S. Overdiagnosis in lung cancer screening with low-dose computed tomography. J Thorac Oncol 2013;8:e101-2.
DOI: https://doi.org/10.1097/JTO.0b013e3182a476d4
Bloom CI, Graham CM, Berry MP, et al. Transcriptional blood signatures distinguish pulmonary tuberculosis, pulmonary sarcoidosis, pneumonias and lung cancers. PLoS One 2013;8:e70630.
DOI: https://doi.org/10.1371/journal.pone.0070630
Cui EN, Yu T, Shang SJ, et al. Radiomics model for distinguishing tuberculosis and lung cancer on computed tomography scans. World J Clin Cases 2020;8:5203-12.
DOI: https://doi.org/10.12998/wjcc.v8.i21.5203
Shariat SF, Capitanio U, Jeldres C, Karakiewicz PI. Can nomograms be superior to other prediction tools?. BJU Int 2009;103:492-5; discussion 495-7.
DOI: https://doi.org/10.1111/j.1464-410X.2008.08073.x
Fan WC, Ting WY, Lee MC, et al. Latent TB infection in newly diagnosed lung cancer patients - a multicenter prospective observational study. Lung Cancer 2014;85:472-8.
DOI: https://doi.org/10.1016/j.lungcan.2014.07.001
Tamura A, Fukami T, Hebisawa A, Takahashi F. Recent trends in the incidence of latent tuberculosis infection in Japanese patients with lung cancer: a small retrospective study. J Infect Chemother 2020;26:315-7.
DOI: https://doi.org/10.1016/j.jiac.2019.10.018
Moy MP, Levsky JM, Berko NS, et al. A new, simple method for estimating pleural effusion size on CT scans. Chest 2013;143:1054-9.
DOI: https://doi.org/10.1378/chest.12-1292
Pahal P, Sharma S. PPD skin test. Treasure Island (FL): StatPearls Publishing; 2021.
Harrell FE, Jr., Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 1996;15:361-87.
DOI: https://doi.org/10.1002/(SICI)1097-0258(19960229)15:4<361::AID-SIM168>3.0.CO;2-4
Van Calster B, Wynants L, Verbeek JFM et al. Reporting and Interpreting decision curve analysis: a guide for investigators. Eur Urol 2018;74:796-804.
DOI: https://doi.org/10.1016/j.eururo.2018.08.038
Molina-Romero C, Arrieta O, Hernández-Pando R. Tuberculosis and lung cancer. Salud Publica Mex 2019;61:286-91.
DOI: https://doi.org/10.21149/10090
Maci E, Comito F, Frezza AM, et al. Lung nodule and functional changes in smokers after smoking cessation short-term treatment. Cancer Invest 2014;32:388-93.
DOI: https://doi.org/10.3109/07357907.2014.919308
Bordignon V, Bultrini S, Prignano G, et al. High prevalence of latent tuberculosis infection in autoimmune disorders such as psoriasis and in chronic respiratory diseases, including lung cancer. J Biol Regul Homeost Agents 2011;25:213-20.
Feng B, Li Y, Guo D, et al. Research on the value of the T cell spot test for tuberculosis for the diagnosis of lung cancer combined with pulmonary tuberculosis. Thorac Cancer 2018;9:1231-4.
DOI: https://doi.org/10.1111/1759-7714.12816
Ma Y, Li R, Shen J et al. Clinical effect of T-SPOT.TB test for the diagnosis of tuberculosis. BMC Infect Dis 2019;19:993.
DOI: https://doi.org/10.1186/s12879-019-4597-8
Wu X, Li Q, Liang Y et al. Clinical evaluation of a homemade enzyme-linked immunospot assay for the diagnosis of active tuberculosis in China. Mol Biotechnol 2011;47:18-25.
DOI: https://doi.org/10.1007/s12033-010-9307-0
de Lima Corvino DF, Shrestha S, Kosmin AR. Tuberculosis screening. Treasure Island (FL): StatPearls Publishing; 2021.
Wu X, Yang Y, Zhang J, et al. Comparison of antibody responses to seventeen antigens from Mycobacterium tuberculosis. Clin Chim Acta 2010;411:1520-8.
DOI: https://doi.org/10.1016/j.cca.2010.06.014
Samanich K, Belisle JT, Laal S. Homogeneity of antibody responses in tuberculosis patients. Infect Immun 2001;69:4600-9.
DOI: https://doi.org/10.1128/IAI.69.7.4600-4609.2001
Kunnath-Velayudhan S, Salamon H, Wang HY, et al. Dynamic antibody responses to the Mycobacterium tuberculosis proteome. Proc Natl Acad Sci U S A 2010;107:14703-8.
DOI: https://doi.org/10.1073/pnas.1009080107
Bai XJ, Yang YR, Liang JQ, et al. Diagnostic performance and problem analysis of commercial tuberculosis antibody detection kits in China. Mil Med Res 2018;5:10.
DOI: https://doi.org/10.1186/s40779-018-0157-6
WHO. Commercial serodiagnostic tests for diagnosis of tuberculosis: policy statement. Available from: https://iris.who.int/bitstream/handle/10665/44652/9789241502054_eng.pdf?sequence=1; 2011.
Mikačić M, Vasilj I, Vasilj M, et al. Tumor marker CA 125 in the diagnosis of active pulmonary tuberculosis - a study of adults in mostar, B&H. Psychiatr Danub 2017;29 Suppl 4:841-4.
Leng S, Zheng J, Jin Y, et al. Plasma cell-free DNA level and its integrity as biomarkers to distinguish non-small cell lung cancer from tuberculosis. Clin Chim Acta 2018;477:160-5.
DOI: https://doi.org/10.1016/j.cca.2017.11.003
Lang S, Sun J, Wang X, et al. Asymptomatic pulmonary tuberculosis mimicking lung cancer on imaging: a retrospective study. Exp Ther Med 2017;14:2180-8.
DOI: https://doi.org/10.3892/etm.2017.4737
Niyonkuru A, Chen X, Bakari KH et al. Evaluation of the diagnostic efficacy of (18) F-Fluorine-2-Deoxy-D-Glucose PET/CT for lung cancer and pulmonary tuberculosis in a Tuberculosis-endemic Country. Cancer Med 2020;9:931-42.
DOI: https://doi.org/10.1002/cam4.2770
Kim H, Kim HY, Goo JM, Kim Y. Lung cancer CT screening and lung-RADS in a tuberculosis-endemic country: the Korean lung cancer screening project (K-LUCAS). Radiology 2020;296:181-8.
DOI: https://doi.org/10.1148/radiol.2020192283
MacMahon H, Naidich DP, Goo JM, et al. Guidelines for Management of incidental pulmonary nodules detected on CT images: from the Fleischner Society 2017. Radiology 2017;284:228-43.
DOI: https://doi.org/10.1148/radiol.2017161659
Jany B, Welte T. Pleural effusion in adults-etiology, diagnosis, and treatment. Dtsch Arztebl Int 2019;116:377-86.
DOI: https://doi.org/10.3238/arztebl.2019.0377
Valdés L, Ferreiro L, Cruz-Ferro E, et al. Recent epidemiological trends in tuberculous pleural effusion in Galicia, Spain. Eur J Intern Med 2012;23:727-32.
DOI: https://doi.org/10.1016/j.ejim.2012.06.014
Wang XJ, Yang Y, Wang Z, et al. Efficacy and safety of diagnostic thoracoscopy in undiagnosed pleural effusions. Respiration 2015;90:251-5.
DOI: https://doi.org/10.1159/000435962
Ethics Approval
This study was approved by Xiangya Hospital of Central South University (No. 202012230).How to Cite
Xia, Zhi, Xueyao Rong, Qiong Chen, Min Fang, and Jian Xiao. 2024. “A Nomogram to Predict Lung Cancer in Pulmonary Lesions for Tuberculosis Infection Patients”. Monaldi Archives for Chest Disease, March. https://doi.org/10.4081/monaldi.2024.2847.
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