Back to search

Article

A Predictive Model of EGFR Mutation Status in Patients with Lung Adenocarcinoma Based on PET/CT Metabolic Indexes and Clinicopathological Variables

2020-12-01

Abstract excerpt

<h4>Purpose: </h4> The purpose of this study was to create a mathematical model based on the metabolic parameters of PET/CT with clinicopathological characteristics to predict the EGFR mutation status of patients with lung adenocarcinoma.MethodsThis study retrospectively enrolled patients with lung adenocarcinoma who underwent surgical treatment at two centres in China between January 2012 and December 2015. PET/C...

Topics

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

Identifiers and source

Literature Corpus work
cc2d82e7-5fd9-5cad-bded-32ef1e88bdf6
DOI
10.21203/rs.3.rs-115858/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
A Predictive Model of EGFR Mutation Status in Patients with Lung Adenocarcinoma Based on PET/CT Metabolic Indexes and Clinicopathological VariablesDOI 10.21203/rs.3.rs-115858/v1
Lung adenocarcinoma: development of nomograms based on PET/CT images for prediction of epidermal growth factor receptor mutation status and subtypes.Semantic proximity
Prediction model based on 18F-FDG PET/CT radiomic features and clinical factors of EGFR mutations in lung adenocarcinoma.Semantic proximity
The role of metabolic tumor volume (MTV) measured by [18F] FDG PET/CT in predicting EGFR gene mutation status in non-small cell lung cancer.Semantic proximity
Establishment and Evaluation of EGFR Mutation Prediction Model Based on Tumor Markers and CT Features in NSCLC.Semantic proximity
The value of dynamic FDG PET/CT in the differential diagnosis of lung cancer and predicting EGFR mutations.Semantic proximity
The value of dynamic FDG PET/CT in the differential diagnosis of lung cancer and predicting EGFR mutationsSemantic proximity
Development and validation of a multivariable predictive model for EGFR gene mutation status in patients with lung adenocarcinoma.Semantic proximity
Nomogram Based on Preoperative CT Imaging Predicts The EGFR Mutation Status in Lung AdenocarcinomaSemantic proximity
Using Multi-phase CT Radiomics Features to Predict EGFR Mutation Status in Lung Adenocarcinoma Patients.Semantic proximity
Frequent EGFR Mutations and Better Prognosis in Positron Emission Tomography-Negative, Solid-Type Lung Cancer.Semantic proximity
Impact assessment of [18F]FDG PET/CT in predicting EGFR gene mutation status in patients with lung adenocarcinoma using recovery coefficient-based correction of semi-quantitative and volume-based PET metrics.Semantic proximity
Computed tomography and clinical features associated with epidermal growth factor receptor mutation status in stage I/II lung adenocarcinoma.Semantic proximity
Select a neighboring publication to make it the new centre.