{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T05:16:58Z","timestamp":1788239818497,"version":"build-2803163510"},"reference-count":31,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>\n                      Antimicrobial resistance in\n                      <jats:italic>Mycobacterium tuberculosis<\/jats:italic>\n                      (\n                      <jats:italic>M.tb<\/jats:italic>\n                      ) poses a major threat to global tuberculosis (TB) control, limiting treatment options and increasing mortality. The prevalence and risk factors for drug-resistant TB (DR-TB) vary by socioeconomic and demographic context. Shenzhen, a rapidly developing megacity in China with a large migrant population, provides a critical setting for investigating this issue. This study aimed to analyze the DR-TB trends and risk factors in Shenzhen using a nine-year retrospective analysis.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We retrospectively analyzed 16,466 TB patients managed at Shenzhen Third People\u2019s Hospital from January 2017 and December 2025. Risk factors for DR-TB were identified using univariate and multivariate logistic regression. Based on these factors, we constructed four prediction models (demographic, demographic+clinical symptom, demographic+clinical symptom+diagnostic, and demographic+clinical symptom+diagnostic+treatment delay), and evaluated their performance using Receiver Operating Characteristic (ROC) curves and calibration curves.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The prevalence of DR-TB decreased from 11.36% in 2017 to 10.42% in 2019, dropped sharply to 7.9% in 2020\u20132021 (likely due to COVID-19 disruptions), rebounded to 14.63% in 2022 (above pre-pandemic levels), peaked in 2023, and then gradually declined after 2024. Multivariate logistic regression identified multiple factors significantly associated with drug resistance: gender (female), age (25\u201344, 45\u201364, \u226565\u202fyears), occupation (unemployed, family workers, business\/service providers, office workers, students), HIV\/AIDS comorbidity, clinical symptoms (cough, sputum production), \u22651 negative etiological test result, re-treatment status, concurrent extra pulmonary TB, time from symptom onset to first medical visit (28\u201342\u202fdays), and time from first visit to diagnosis (\u226542\u202fdays). The AUC values for the four models were 0.571, 0.599, 0.760, and 0.787, respectively (all\n                      <jats:italic>p<\/jats:italic>\n                      \u202f&amp;lt;\u202f0.001). Hosmer-Lemeshow\n                      <jats:italic>\u03c7<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      values were 14.014, 13.402, 9.618 and 8.612, respectively (\n                      <jats:italic>p<\/jats:italic>\n                      \u202f&amp;gt;\u202f0.05).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>We successfully developed a DR-TB risk prediction model with good discrimination and calibration. Early identification of risk factors is crucial for improving clinical awareness and management of DR-TB. Enhancing early diagnosis and treatment is essential for controlling the disease.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Clinical trial registration<\/jats:title>\n                    <jats:p>\n                      <jats:ext-link>https:\/\/www.chictr.org.cn\/showproj.html?proj=188950<\/jats:ext-link>\n                      , Identifier [ChiCTR2300067585].\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1875521","type":"journal-article","created":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T04:27:01Z","timestamp":1788236821000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Risk factors and prediction modeling for drug-resistant tuberculosis in Shenzhen: a 9-year retrospective study"],"prefix":"10.3389","volume":"14","author":[{"given":"Jin","family":"Wang","sequence":"first","affiliation":[{"name":"Shenzhen Third People\u2019s Hospital, The Second Affiliated Hospital of Southern University of Science and Technology","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Moru","family":"Chen","sequence":"additional","affiliation":[{"name":"National Clinical Research Center for Infectious Disease of Shenzhen, Shenzhen Third People\u2019s Hospital, The Second Affiliated Hospital of Southern University of Science and Technology","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoliang","family":"Zha","sequence":"additional","affiliation":[{"name":"Shenzhen Third People\u2019s Hospital, The Second Affiliated Hospital of Southern University of Science and Technology","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feng","family":"Ding","sequence":"additional","affiliation":[{"name":"National Clinical Research Center for Infectious Disease of Shenzhen, Shenzhen Third People\u2019s Hospital, The Second Affiliated Hospital of Southern University of Science and Technology","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"He","family":"Zhang","sequence":"additional","affiliation":[{"name":"National Clinical Research Center for Infectious Disease of Shenzhen, Shenzhen Third People\u2019s Hospital, The Second Affiliated Hospital of Southern University of Science and Technology","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shui-hua","family":"Lu","sequence":"additional","affiliation":[{"name":"National Clinical Research Center for Infectious Disease of Shenzhen, Shenzhen Third People\u2019s Hospital, The Second Affiliated Hospital of Southern University of Science and Technology","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangxiang","family":"Liu","sequence":"additional","affiliation":[{"name":"National Clinical Research Center for Infectious Disease of Shenzhen, Shenzhen Third People\u2019s Hospital, The Second Affiliated Hospital of Southern University of Science and Technology","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,1]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"850","DOI":"10.1016\/S0140-6736(24)02479-6","article-title":"Tuberculosis","volume":"405","author":"Trajman","year":"2025","journal-title":"Lancet"},{"key":"ref2","volume-title":"Global Tuberculosis Report 2025","year":"2025"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"943545","DOI":"10.3389\/fcimb.2022.943545","article-title":"Drug resistant tuberculosis: implications 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