Stratification and management of patients ineligible for lung cancer screening

Respir Med. 2021 Nov:188:106610. doi: 10.1016/j.rmed.2021.106610. Epub 2021 Sep 21.

Abstract

This study identifies participants ineligible for lung cancer screening with the greatest likelihood of future eligibility. Lung cancer risk in participants enrolled in longitudinal lung screening was assessed using the Prostate, Lung, Colorectal and Ovarian lung cancer risk calculator (PLCOm2012) at two timepoints: baseline (T1) and follow-up (T2). Separate analyses were performed on four PLCOm2012 eligibility thresholds (3.25%, 2.00%, 1.50%, and 1.00%); only participants with a T1 risk less than the threshold were included in that analysis. Cox-models identified T1 risk factors associated with screen-eligibility at T2. Three models, applying differing assumptions of participant behavior, predicted future eligibility and were benchmarked against the observed cohort. Nine hundred and fifty-six participants had a T1 risk <3.25%; at 2.00% n= 755; at 1.50% n= 652; at 1.00% n= 484. Lung cancer risk increased over time in most screen-ineligible participants. However, risk increased much faster in participants who became screen-eligible at T2 compared to those who remained screen-ineligible (median per-year increase of 0.35% versus 0.02%, when using a 3.25% threshold). Participants smoking for >30 years, current smokers, less educated participants, and those with chronic obstructive pulmonary disease (COPD) at T1 were significantly more likely to become screen-eligible. New diagnoses of COPD and/or non-lung cancers between T1 and T2 precipitated eligibility in a subset of participants. The prediction model that assumed health behaviors observed at T1 continued to T2 reasonably predicted changes in lung cancer risk. This prediction model and the identified baseline risk factors can identify screen-ineligible participants who should be closely followed for future eligibility.

Keywords: Computed tomography; Lung cancer; Mass screening; Patient selection; Risk assessment; Statistical models.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Canada
  • Early Detection of Cancer
  • Educational Status
  • Eligibility Determination / statistics & numerical data*
  • Humans
  • Longitudinal Studies
  • Lung Neoplasms / diagnosis*
  • Mass Screening / statistics & numerical data*
  • Middle Aged
  • Patient Selection*
  • Pulmonary Disease, Chronic Obstructive / complications
  • Risk Assessment
  • Smoking / adverse effects