Journal of thoracic imaging · 2026
Development and Validation of a Prediction Model of Hemoptysis After Computed Tomography-guided Percutaneous Transthoracic Needle Biopsy.
СтатьяВалидационное исследованиеНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Jang Sowon, Kim Minseon, Lee Jeong Sub, Yoon Sung Hyun, Kim Junghoon, Kim Jihang, Lee Kyung Won
Аннотация
PURPOSE: To develop and validate a nomogram to predict hemoptysis after percutaneous transthoracic needle biopsy (PTNB) by integrating clinical and radiologic data, facilitating pre-biopsy decision-making.
MATERIALS AND METHODS: This single-center, retrospective cohort study included 1383 patients who underwent 1389 PTNB procedures between 2020 and 2022. The participants were randomly allocated to the training and validation cohorts. Logistic regression was performed to discern the independent predictors of hemoptysis within the clinical and radiologic variables. A nomogram was developed based on pre-biopsy variables obtained before the biopsy, and its performance was subsequently evaluated. The goodness of fit of the nomogram was compared with that of another model, which integrated pre-biopsy and post-biopsy variables.
RESULTS: Among the 1389 procedures, hemoptysis was observed in 128 (9.2%) cases. Current smoking status, lesion size of <25 mm, consolidation-type lesions, presence of the computed tomography bronchus sign, and perilesional vascularity were independent predictors of PTNB-related hemoptysis. The nomogram based on the pre-biopsy variables showed fair discrimination abilities (area under the receiver operating characteristic curve = 0.79 and 0.76 in the training and validation cohorts, respectively) and strong calibration agreement in the training and validation cohorts. The model fit was good in both cohorts ( P = 0.41 and 0.55 in the training and validation cohorts, respectively). No significant difference was observed in the model fit between the pre-biopsy nomogram and the model incorporating pre-biopsy and post-biopsy variables ( P = 0.88).
CONCLUSION: The proposed nomogram utilizing pre-biopsy variables could predict hemoptysis before PTNB.
MATERIALS AND METHODS: This single-center, retrospective cohort study included 1383 patients who underwent 1389 PTNB procedures between 2020 and 2022. The participants were randomly allocated to the training and validation cohorts. Logistic regression was performed to discern the independent predictors of hemoptysis within the clinical and radiologic variables. A nomogram was developed based on pre-biopsy variables obtained before the biopsy, and its performance was subsequently evaluated. The goodness of fit of the nomogram was compared with that of another model, which integrated pre-biopsy and post-biopsy variables.
RESULTS: Among the 1389 procedures, hemoptysis was observed in 128 (9.2%) cases. Current smoking status, lesion size of <25 mm, consolidation-type lesions, presence of the computed tomography bronchus sign, and perilesional vascularity were independent predictors of PTNB-related hemoptysis. The nomogram based on the pre-biopsy variables showed fair discrimination abilities (area under the receiver operating characteristic curve = 0.79 and 0.76 in the training and validation cohorts, respectively) and strong calibration agreement in the training and validation cohorts. The model fit was good in both cohorts ( P = 0.41 and 0.55 in the training and validation cohorts, respectively). No significant difference was observed in the model fit between the pre-biopsy nomogram and the model incorporating pre-biopsy and post-biopsy variables ( P = 0.88).
CONCLUSION: The proposed nomogram utilizing pre-biopsy variables could predict hemoptysis before PTNB.