TY - JOUR
T1 - A Diagnostic Predictive Model of Bronchoscopy with Radial Endobronchial Ultrasound for Peripheral Pulmonary Lesions
AU - Ito, Takayasu
AU - Matsumoto, Yuji
AU - Okachi, Shotaro
AU - Nishida, Kazuki
AU - Tanaka, Midori
AU - Imabayashi, Tatsuya
AU - Tsuchida, Takaaki
AU - Hashimoto, Naozumi
N1 - Publisher Copyright:
© 2022
PY - 2022/12/1
Y1 - 2022/12/1
N2 - Background: Several factors have been reported to affect the diagnostic yield of bronchoscopy with radial endobronchial ultrasound (R-EBUS) for peripheral pulmonary lesions (PPLs). However, it is difficult to accurately predict the diagnostic potential of bronchoscopy for each PPL in advance. Objectives: Our objective was to establish a predictive model to evaluate the diagnostic yield before the procedure. Method: We retrospectively analysed consecutive patients who underwent diagnostic bronchoscopy with R-EBUS between April 2012 and October 2015. We assessed the factors that were predictive of successful bronchoscopic diagnosis of PPLs with R-EBUS using a multivariable logistic regression model. The accuracy of the predictive model was evaluated using the receiver operator characteristic area under the curve (ROC AUC). Internal validation was analysed using 10-fold stratified cross-validation. Results: We analysed a total of 1,634 lesions; the median lesion size was 25.0 mm. Of these, 1,138 lesions (69.6%) were successfully diagnosed. In the predictive logistic model, significant factors affecting the diagnostic yield were lesion size, lesion structure, bronchus sign, and visible on chest X-ray. The predictive model consisted of seven factors: lesion size, lesion lobe, lesion location from the hilum, lesion structure, bronchus sign, visibility on chest X-ray, and background lung. The ROC AUC of the predictive model was 0.742 (95% confidence interval: 0.715-0.769). Internal validation using 10-fold stratified cross-validation revealed a mean ROC AUC of 0.734. Conclusions: The predictive model using the seven factors revealed a good performance in estimating the diagnostic yield.
AB - Background: Several factors have been reported to affect the diagnostic yield of bronchoscopy with radial endobronchial ultrasound (R-EBUS) for peripheral pulmonary lesions (PPLs). However, it is difficult to accurately predict the diagnostic potential of bronchoscopy for each PPL in advance. Objectives: Our objective was to establish a predictive model to evaluate the diagnostic yield before the procedure. Method: We retrospectively analysed consecutive patients who underwent diagnostic bronchoscopy with R-EBUS between April 2012 and October 2015. We assessed the factors that were predictive of successful bronchoscopic diagnosis of PPLs with R-EBUS using a multivariable logistic regression model. The accuracy of the predictive model was evaluated using the receiver operator characteristic area under the curve (ROC AUC). Internal validation was analysed using 10-fold stratified cross-validation. Results: We analysed a total of 1,634 lesions; the median lesion size was 25.0 mm. Of these, 1,138 lesions (69.6%) were successfully diagnosed. In the predictive logistic model, significant factors affecting the diagnostic yield were lesion size, lesion structure, bronchus sign, and visible on chest X-ray. The predictive model consisted of seven factors: lesion size, lesion lobe, lesion location from the hilum, lesion structure, bronchus sign, visibility on chest X-ray, and background lung. The ROC AUC of the predictive model was 0.742 (95% confidence interval: 0.715-0.769). Internal validation using 10-fold stratified cross-validation revealed a mean ROC AUC of 0.734. Conclusions: The predictive model using the seven factors revealed a good performance in estimating the diagnostic yield.
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U2 - 10.1159/000526574
DO - 10.1159/000526574
M3 - Article
C2 - 36327951
AN - SCOPUS:85143200705
SN - 0025-7931
VL - 101
SP - 1148
EP - 1156
JO - Respiration
JF - Respiration
IS - 12
ER -