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Factors Associated with Inappropriate Use of Head Imaging in the Staging of Early Stage Non Small Cell Lung Cancer

Principal Investigator

Name
Alex Balekian

Degrees
MD

Institution
USC Keck School of Medicine

Position Title
Principal Investigator

Email
alex.balekian@med.usc.edu

About this CDAS Project

Study
NLST (Learn more about this study)

Project ID
NLST-49

Initial CDAS Request Approval
Jan 27, 2014

Title
Factors Associated with Inappropriate Use of Head Imaging in the Staging of Early Stage Non Small Cell Lung Cancer

Summary
Prior research suggests that head imaging for patients with early stage non-small cell lung cancer (NSCLC) with no reported neurological symptoms is low yield, and in many cases has the potential to overstage a patient with false-positive results. For this reason, the Society of Thoracic Surgeons has recommended against head imaging in this population as part of the Choosing Wisely campaign. The goal of our research is to describe the prevalence of overuse in head imaging in early NSCLC patients and to identify factors associated with its inappropriate use. Using the NLST data, we will perform multivariate logistic regression to describe the association between head CT or MRI use in early stage NSCLC patients and patient demographics and institution-specific variables.

Aims

The specific goal of this retrospective study is quantify the frequency with which individuals diagnosed with early stage (Stage I) non small cell lung cancer are ordered head imaging (CT or MRI) with no presented neurological symptoms. In our data analysis we will try and determine whether specific covariates such as Age, Race/Ethnicity, Gender, Annual Income, and Ordering MD information have any significant correlating relationship with the frequency of inappropriate head imaging.
**Although clinical information such as neurologic symptoms might not be collected in the NLST data, we will use baseline estimates in prior research reporting the prevalence of CNS involvement in radiographic stage I NSCLC and determine via chi-square analysis whether the rate of head imaging is significantly different from this known baseline risk of metastatic CNS disease.

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