Predicting Malignancy Using Endoluminal Ultrasound Characteristics in Mediastinal Lymph Nodes (CT0024)
|ClinicalTrials.gov Identifier: NCT01329575|
Recruitment Status : Completed
First Posted : April 6, 2011
Last Update Posted : March 30, 2018
There is no single method to investigate mediastinal LN invasion. Hence, a patient may have to undergo several tests and procedures. Noninvasive and invasive approaches are employed. Within the invasive techniques, endoscopic ultrasonography with needle aspiration (EUS-FNA) and endobronchial ultrasonography with transbronchial needle aspiration (EBUS-TBNA) are gaining importance in mediastinal staging.5 They provide ultrasonographic images and permit needle aspiration under direct vision for cytology specimen analysis. As more evidence is being accumulated on these staging approaches, the number of cervical mediastinoscopies, considered as the gold-standard for mediastinal staging, is diminishing.
Color Doppler LN characteristics with endoluminal ultrasound (US) is only mentioned in a small number of studies and needs to be further investigated.13,14 With the good results obtained with superficial US, it seems reasonable to believe that color Doppler characteristics would increase accuracy in detecting malignancy of mediastinal LNs with endoluminal US.
|Condition or disease|
|Neoplasm of Mediastinal Lymph Nodes|
Show Detailed Description
|Study Type :||Observational|
|Actual Enrollment :||184 participants|
|Official Title:||Predicting Malignancy Using Endoluminal Ultrasound Characteristics in Mediastinal Lymph Nodes|
|Study Start Date :||January 2011|
|Actual Primary Completion Date :||December 2016|
|Actual Study Completion Date :||July 2017|
- With a combination of endoluminal ultrasound characteristics, a simple scoring system can be established to help predict malignancy in mediastinal lymph nodes. [ Time Frame: 3 months ]collected characteristics univariate and multivariate logistic regressions will be used to establish a scoring system to predict malignancy. Sensitivity, specificity, positive predictive value, negative predictive value and accuracy will be determined based on the developed model.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT01329575
|Centre Hospitalier de l'Université de Montréal|
|Montreal, Quebec, Canada, H2L 4M1|
|Principal Investigator:||Moishe Liberman, MD, PhD||Centre hospitalier de l'Université de Montréal (CHUM)|