Development of a hemoptysis risk prediction model for patients following CT-guided transthoracic lung biopsy
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RESEARCH ARTICLE
Open Access
Development of a hemoptysis risk prediction model for patients following CTguided transthoracic lung biopsy Saibin Wang1* , Ke Dong2 and Wei Chen3*
Abstract Background: Computed tomography-guided transthoracic needle biopsy (CT-TNB) is a widely used method for diagnosis of lung diseases; however, CT-TNB-induced bleeding is usually unexpected and this complication can be life-threatening. The aim of this study was to develop and validate a predictive model for hemoptysis following CT-TNB. Methods: A total of 436 consecutive patients who underwent CT-TNB from June 2016 to December 2017 at a tertiary hospital in China were divided into derivation (n = 307) and validation (n = 129) cohorts. We used LASSO regression to reduce the data dimension, select variables and determine which predictors were entered into the model. Multivariate logistic regression was used to develop the predictive model. The discrimination capacity of the model was evaluated by the area under the receiver operating characteristic curve (AUROC), the calibration curve was used to test the goodness-of-fit of the model, and decision curve analysis was conducted to assess its clinical utility. Results: Five predictive factors (diagnosis of the lesion, lesion characteristics, lesion diameter, procedure time, and puncture distance) selected by LASSO regression analysis were applied to construct the predictive model. The AUC was 0.850 (95% confidence interval [CI], 0.808–0.893) in the derivation, and 0.767 (95% CI, 0.684– 0.851) in the validation. The model showed good calibration consistency (p > 0.05). Moreover, decision curve analysis indicated its clinical usefulness. Conclusion: We established a predictive model that incorporates lesion features and puncture parameters, which may facilitate the individualized preoperative prediction of hemoptysis following CT-TNB. Keywords: Lung, Biopsy, Hemoptysis, Nomogram
* Correspondence: [email protected]; [email protected] 1 Department of Respiratory Medicine, Jinhua Municipal Central Hospital, No. 365, East Renmin Road, Jinhua 321000, Zhejiang Province, China 3 Department of Radiology, the Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou 325027, Zhejiang Province, China Full list of author information is available at the end of the article © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or e
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