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Selecting the risk cut off for the LLP model.

Principal Investigator

Name
Kevin ten Haaf

Degrees
MSc

Institution
Erasmus MC

Position Title
Researcher

Email
k.tenhaaf@erasmusmc.nl

About this CDAS Project

Study
NLST (Learn more about this study)

Project ID
NLST-343

Initial CDAS Request Approval
Aug 27, 2017

Title
Selecting the risk cut off for the LLP model.

Summary
The application of risk prediction models for the selection of individuals for lung cancer (LC) screening requires risk thresholds to distinguish between individuals eligible and ineligible for screening. In a previous project, the NLST and PLCO datasets were used to evaluate a number of risk prediction models [1]. The sensitivity and specificity for each model was evaluated for risk thresholds that selected a similar number of individuals as the NLST criteria in the PLCO [1].

However, little is known about the performance of risk prediction models across different risk thresholds. The UKLS trial utilised the Liverpool Lung Project risk model (LLPv2) with a risk threshold of 5% for 5-year LC incidence as the selection criteria in the trial [2]. The UKLS yielded a 1.7% LC detection rate at baseline, which was higher than the NLST or NELSON trials [3]. This study evaluates the performance of different risk thresholds for the selection of individuals for lung cancer screening utilising the LLPv2 model.

References:
[1] ten Haaf, Risk prediction models for selection of lung cancer screening candidates: A retrospective validation study, PLOS Medicine, 2017
[2] Baldwin, UK Lung Screen (UKLS) nodule management protocol: modelling of a single screen randomised controlled trial of low-dose CT screening for lung cancer, Thorax, 2011.
[3] Field, UK Lung Cancer RCT Pilot Screening Trial: baseline findings from the screening arm provide evidence for the potential implementation of lung cancer screening , Thorax, 2016

Aims

Specific aims
To investigate the performance of the LLPv2 model thresholds for the selection of individuals for lung cancer screening over a range of risk thresholds.

Collaborators

Harry J. de Koning (Erasmus Medical Center)
John K. Field (University of Liverpool)

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