PLCO risk assessment formula
Principal Investigator
Name
Aharona Shuali
Degrees
MD, MBA
Institution
Nucleix
Position Title
VP MEdical
Email
About this CDAS Project
Study
PLCO
(Learn more about this study)
Project ID
PLCO-441
Initial CDAS Request Approval
Jan 15, 2019
Title
PLCO risk assessment formula
Summary
Identifying patients at-risk with high accuracy allows for cost-effective implementation of ling cancer screening. The project will analyze the PLCO (Lung Cancer) data in order to estimate the relationship between individual risk parameters and a total risk score, which will provide information on the amount of variance explained in total score by individual items. Additionally, each item as well as the total score will be related to risk in the general at-risk population, as well as in subgroups defined by variables of interest such as gender. Analyses will be done by using classical statistical techniques (e.g. linear regression, logistic regression, Pearson correlation) as well as newer methodologies such as neural networks and nonparametric regression.
Aims
The project’s aim is to explore the relationship between individual risk components, and their relationship to the patient overall risk of developing lung cancer. Additionally, we wish to examine the overall risk and its individual items’ relationship to subgroups in the at-risk population (e.g. by gender). This should provide information on:
a) Identifying those parameters most associated with risk for lung cancer
b) Identifying the relative contribution of the different items to overall risk
c) The relative utility of a risk scale in different subgroups
d) Identifying potential factors mitigating risk (e.g. being male or female)
Collaborators
Yulia Gavrilov, Technostat