Article

Comparing Modalities for Risk Assessment in Patients with Pulmonary Lesions and Nondiagnostic Bronchoscopy for Suspected Lung Cancer

2022-04-08

Abstract excerpt

<h4>Background: </h4> Bronchoscopy is commonly utilized for non-surgical sampling of indeterminant pulmonary lesions, but nondiagnostic procedures are common. Accurate assessment of the risk of malignancy is essential for decision making in these patients, yet we lack tools that perform well across this heterogeneous group of patients. We sought to evaluate the accuracy of three previously validated risk models an...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 7979672c-14e5-5cf5-85f3-776993b3cfe9
DOI: 10.21203/rs.3.rs-1347143/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Comparing Modalities for Risk Assessment in Patients with Pulmonary Lesions and Nondiagnostic Bronchoscopy for Suspected Lung CancerDOI 10.21203/rs.3.rs-1347143/v1Read

Percepta Genomic Sequencing Classifier And Decision-Making In Patients With High-Risk Lung Nodules: A Decision Impact StudySemantic proximity Read

Solitary Pulmonary Nodule Malignancy Predictive Models Applicable to Routine Clinical Practice: A Systematic Review Semantic proximity Read

Enhancing the differential diagnosis of small pulmonary nodules: a comprehensive model integrating plasma methylation, protein biomarkers, and LDCT imaging featuresSemantic proximity Read

A Multirepresentation Model for Pulmonary Nodule Malignancy Risk Assessment and Model-Derived Risk Grouping on Routine Chest CT: a retrospective diagnostic modeling studySemantic proximity Read

Circulating Proteome for Pulmonary Nodule MalignancySemantic proximity Read

A comprehensive review of benign tumors in the lung.Semantic proximity Read

Detecting pulmonary malignancy against benign nodules using noninvasive cell-free DNA fragmentomics assaySemantic proximity Read

Unexpectedly Benign Pulmonary Nodules Using Machine LearningSemantic proximity Read

Improving lung cancer risk stratification leveraging whole transcriptome RNA sequencing and machine learning across multiple cohorts.Semantic proximity Read

Computer-Aided Nodule Assessment and Risk Yield (CANARY) may facilitate non-invasive prediction of EGFR mutation status in lung adenocarcinomas.Semantic proximity Read

A clinically effective model based on cell-free DNA methylation and low-dose CT for risk stratification of pulmonary nodulesSemantic proximity Read

TP53 mutation prevalence in normal airway epithelium as a biomarker for lung cancer riskSemantic proximity Read