Prediction of the Complication Risk in Drug-Resistant Tuberculosis After Surgery: Development and Assessment of a Novel Nomogram

Background: Surgery is increasingly accepted as an adjunctive approach to treat multidrug-resistant tuberculosis (MDR-TB) or extensively drug-resistant tuberculosis (XDR-TB). However, a model that includes all factors to predict the risk of postoperative complications is lacking. Methods: We develop...

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Published inFrontiers in surgery Vol. 8; p. 689742
Main Authors Wu, Liwei, Dai, Xiyong, Wang, Haijiang, Huang, Chaolin, Xia, Fan, Song, Yanzheng, Wang, Lin
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LanguageEnglish
Published Frontiers Media S.A 09.08.2021
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Abstract Background: Surgery is increasingly accepted as an adjunctive approach to treat multidrug-resistant tuberculosis (MDR-TB) or extensively drug-resistant tuberculosis (XDR-TB). However, a model that includes all factors to predict the risk of postoperative complications is lacking. Methods: We developed a prediction model based on 138 patients who had undergone surgery as treatment for drug-resistant tuberculosis (DR-TB) after 24 months. Clinical features on the lesion type (L), treatment history (T), physiologic status of the body (B), and surgical approach (S) were evaluated. Multivariable logistic regression analysis was conducted by clinical features selected in the least absolute shrinkage and selection operator (LASSO) to build a nomogram. The discrimination, calibration, and clinical usefulness of the nomogram were assessed using the C-Index, calibration plots, and decision curves. Internal validation was assessed using bootstrapping. Results: The nomogram contained the features L, B, T, cavitary, recurrent chest infection (RCI) and MDR-TB/XDR-TB. The model displayed good discrimination with a C-Index of 0.879 (95% CI: 0.799–0.967). A high C-Index of 0.824 was achieved in the interval validation. Decision-curve analysis showed that the nomogram was clinically useful if intervention was decided at the non-adherence possibility threshold of 4%. Conclusion: Our novel nomogram could be used conveniently to predict postoperative complication risk in DR-TB patients.
AbstractList Background: Surgery is increasingly accepted as an adjunctive approach to treat multidrug-resistant tuberculosis (MDR-TB) or extensively drug-resistant tuberculosis (XDR-TB). However, a model that includes all factors to predict the risk of postoperative complications is lacking. Methods: We developed a prediction model based on 138 patients who had undergone surgery as treatment for drug-resistant tuberculosis (DR-TB) after 24 months. Clinical features on the lesion type (L), treatment history (T), physiologic status of the body (B), and surgical approach (S) were evaluated. Multivariable logistic regression analysis was conducted by clinical features selected in the least absolute shrinkage and selection operator (LASSO) to build a nomogram. The discrimination, calibration, and clinical usefulness of the nomogram were assessed using the C-Index, calibration plots, and decision curves. Internal validation was assessed using bootstrapping. Results: The nomogram contained the features L, B, T, cavitary, recurrent chest infection (RCI) and MDR-TB/XDR-TB. The model displayed good discrimination with a C-Index of 0.879 (95% CI: 0.799–0.967). A high C-Index of 0.824 was achieved in the interval validation. Decision-curve analysis showed that the nomogram was clinically useful if intervention was decided at the non-adherence possibility threshold of 4%. Conclusion: Our novel nomogram could be used conveniently to predict postoperative complication risk in DR-TB patients.
Background: Surgery is increasingly accepted as an adjunctive approach to treat multidrug-resistant tuberculosis (MDR-TB) or extensively drug-resistant tuberculosis (XDR-TB). However, a model that includes all factors to predict the risk of postoperative complications is lacking.Methods: We developed a prediction model based on 138 patients who had undergone surgery as treatment for drug-resistant tuberculosis (DR-TB) after 24 months. Clinical features on the lesion type (L), treatment history (T), physiologic status of the body (B), and surgical approach (S) were evaluated. Multivariable logistic regression analysis was conducted by clinical features selected in the least absolute shrinkage and selection operator (LASSO) to build a nomogram. The discrimination, calibration, and clinical usefulness of the nomogram were assessed using the C-Index, calibration plots, and decision curves. Internal validation was assessed using bootstrapping.Results: The nomogram contained the features L, B, T, cavitary, recurrent chest infection (RCI) and MDR-TB/XDR-TB. The model displayed good discrimination with a C-Index of 0.879 (95% CI: 0.799–0.967). A high C-Index of 0.824 was achieved in the interval validation. Decision-curve analysis showed that the nomogram was clinically useful if intervention was decided at the non-adherence possibility threshold of 4%.Conclusion: Our novel nomogram could be used conveniently to predict postoperative complication risk in DR-TB patients.
Author Wang, Haijiang
Song, Yanzheng
Wu, Liwei
Xia, Fan
Dai, Xiyong
Wang, Lin
Huang, Chaolin
AuthorAffiliation 1 Department of Thoracic Surgery, Shanghai Public Health Clinical Center, Fudan University , Shanghai , China
5 Department of Pulmonary Disease, 905Th Hospital of PLA Navy , Shanghai , China
4 Department of Thoracic Surgery, Wuhan Jinyintan Hospital , Wuhan , China
6 TB Center, Shanghai Emerging and Re-emerging Infectious Disease Institute, Fudan University , Shanghai , China
2 Department of Surgery, Wuhan Pulmonary Hospital , Wuhan , China
3 Department of Thoracic Surgery, The Third People's Hospital of Shenzhen , Shenzhen , China
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This article was submitted to Thoracic Surgery, a section of the journal Frontiers in Surgery
These authors have contributed equally to this work
Edited by: Nuria Maria Novoa, University of Salamanca Health Care Complex, Spain
Reviewed by: Maria Rodriguez, Clínica Universidad de Navarra, Spain; Piotr Yablonskii, St-Petersburg Research Institute of Phthisiopulmonology, Russia
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Snippet Background: Surgery is increasingly accepted as an adjunctive approach to treat multidrug-resistant tuberculosis (MDR-TB) or extensively drug-resistant...
Background: Surgery is increasingly accepted as an adjunctive approach to treat multidrug-resistant tuberculosis (MDR-TB) or extensively drug-resistant...
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SubjectTerms drug resistance tuberculosis
LTBS classification system
nomogram
Surgery
tuberculosis
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Title Prediction of the Complication Risk in Drug-Resistant Tuberculosis After Surgery: Development and Assessment of a Novel Nomogram
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