{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T10:36:11Z","timestamp":1784025371359,"version":"3.55.0"},"reference-count":38,"publisher":"S. Karger AG","issue":"12","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.karger.com\/Services\/SiteLicenses"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.karger.com\/Services\/SiteLicenses"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Respiration"],"published-print":{"date-parts":[[2022]]},"abstract":"<b><i>Background:<\/i><\/b> 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. <b><i>Objectives:<\/i><\/b> Our objective was to establish a predictive model to evaluate the diagnostic yield before the procedure. <b><i>Method:<\/i><\/b> 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. <b><i>Results:<\/i><\/b> 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\u20130.769). Internal validation using 10-fold stratified cross-validation revealed a mean ROC AUC of 0.734. <b><i>Conclusions:<\/i><\/b> The predictive model using the seven factors revealed a good performance in estimating the diagnostic yield. <\/jats:p>","DOI":"10.1159\/000526574","type":"journal-article","created":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T22:00:36Z","timestamp":1667512836000},"page":"1148-1156","source":"Crossref","is-referenced-by-count":5,"title":["A Diagnostic Predictive Model of Bronchoscopy with Radial Endobronchial Ultrasound for Peripheral Pulmonary Lesions"],"prefix":"10.1159","volume":"101","author":[{"given":"Takayasu","family":"Ito","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0646-858X","authenticated-orcid":false,"given":"Yuji","family":"Matsumoto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shotaro","family":"Okachi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0367-8557","authenticated-orcid":false,"given":"Kazuki","family":"Nishida","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Midori","family":"Tanaka","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6343-5306","authenticated-orcid":false,"given":"Tatsuya","family":"Imabayashi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takaaki","family":"Tsuchida","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2337-629X","authenticated-orcid":false,"given":"Naozumi","family":"Hashimoto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"127","published-online":{"date-parts":[[2022,11,3]]},"reference":[{"key":"ref1"},{"key":"ref2"},{"key":"ref3"},{"key":"ref4"},{"key":"ref5"},{"key":"ref6"},{"key":"ref7"},{"key":"ref8"},{"key":"ref9"},{"key":"ref10"},{"key":"ref11"},{"key":"ref12"},{"key":"ref13"},{"key":"ref14"},{"key":"ref15"},{"key":"ref16"},{"key":"ref17"},{"key":"ref18"},{"key":"ref19"},{"key":"ref20"},{"key":"ref21"},{"key":"ref22"},{"key":"ref23"},{"key":"ref24"},{"key":"ref25"},{"key":"ref26"},{"key":"ref27"},{"key":"ref28"},{"key":"ref29"},{"key":"ref30"},{"key":"ref31"},{"key":"ref32"},{"key":"ref33"},{"key":"ref34"},{"key":"ref35"},{"key":"ref36"},{"key":"ref37"},{"key":"ref38"}],"container-title":["Respiration"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.karger.com\/Article\/Pdf\/526574","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.karger.com\/Article\/Pdf\/526574","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,23]],"date-time":"2025-04-23T15:17:17Z","timestamp":1745421437000},"score":1,"resource":{"primary":{"URL":"https:\/\/karger.com\/article\/doi\/10.1159\/000526574"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":38,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2022,12,1]]},"published-print":{"date-parts":[[2022,12,6]]}},"URL":"https:\/\/doi.org\/10.1159\/000526574","archive":["Portico"],"relation":{"is-supplemented-by":[{"id-type":"doi","id":"10.6084\/m9.figshare.21493617","asserted-by":"subject"}]},"ISSN":["0025-7931","1423-0356"],"issn-type":[{"value":"0025-7931","type":"print"},{"value":"1423-0356","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]}}}