Prospective Evaluation of Lung Cancer Screening Eligibility Criteria and Lung Cancer Detection in the Yorkshire Lung Screening Trial.

Abstract

Introduction: Low-dose computed tomography screening for lung cancer reduces lung cancer mortality, but there is a lack of international consensus regarding the optimal eligibility criteria for screening. The Yorkshire Lung Screening Trial was designed to evaluate lung cancer screening (LCS) implementation, and a primary objective was prospective evaluation of three predefined eligibility criteria.

Methods: Individuals who had ever smoked, aged 55 to 80 years, who responded to written invitation, underwent telephone risk assessment and if eligible by at least one criterion (PLCO_M2012 ≥ 1.51%, LLP_v2 ≥ 5%, USPSTF₂₀₁₃) were offered biennial low-dose computed tomography screening.

Results: Of 44,957 individuals invited, 22,814 responded and underwent eligibility assessment, of whom a total of 7826 were eligible according to any of the three LCS criteria. Comparing PLCO_M2012 ≥ 1.51%, LLP_v2 ≥ 5%, and USPSTF₂₀₁₃, the proportions of responders eligible for screening were 28.0%, 20.5%, and 18.9%, respectively (p < 0.0001 for each comparison), and the proportion of all cancers detected 91.1%, 77.0%, and 62.8%, respectively (p ≤ 0.0002 for each comparison). When risk thresholds were selected to result in equivalent numbers of people eligible for screening, cancer detection proportions were higher for PLCO_M2012 (74.5%) and LLP_v2 (71.3%) than USPSTF₂₀₁₃ (62.8%) (p = 0.0002 and p = 0.032, respectively), but there was no significant difference between the two risk models. Reducing the LLPv2 risk threshold from 5% to 2.5% (as currently used in the English LCS program) and reducing the pack-year requirement for the USPSTF₂₀₂₁ versus the USPSTF₂₀₁₃ criteria increased the numbers eligible for screening, but subsequent cancer yield was not measured in this study.

Conclusion: The PLCO_M2012 ≥ 1.51% criteria identified more people eligible for screening in Yorkshire Lung Screening Trial and resulted in more screen-detected lung cancers than LLP_v2 ≥ 5% or USPSTF₂₀₁₃. When compared in equivalent populations, there was no significant difference between risk models in terms of lung cancer detection and each appeared more efficient at screening population selection than USPSTF₂₀₁₃.