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About this Publication
Title
Impact of Comorbidities on Lung Cancer Screening Evaluation.
Pubmed ID
35641376 (View this publication on the PubMed website)
Digital Object Identifier
Publication
Clin Lung Cancer. 2022 Jul; Volume 23 (Issue 5): Pages 402-409
Authors
Robinson EM, Liu BY, Sigel K, Yin C, Wisnivesky J, Kale MS
Affiliations
  • Division of General Internal Medicine, Icahn School of Medicine at Mount Sinai, New York, NY. Electronic address: Eric.Robinson@icahn.mssm.edu.
  • Division of General Internal Medicine, Icahn School of Medicine at Mount Sinai, New York, NY.
Abstract

OBJECTIVES: We used data from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial to examine the impact of self-reported chronic obstructive pulmonary disease, coronary artery disease, stroke, and diabetes mellitus on diagnostic complications in lung cancer screening evaluation.

METHODS: In our analysis, we included individuals from the usual care and intervention (annual chest x-ray) of the lung cancer screening trial with equal or greater than 55 years of age with a 20 pack-year smoking history who had undergone an invasive procedure. We performed multivariate logistic regression analysis to estimate the association of comorbidity on procedure complication. Our primary outcome was the incidence of major or moderate complications.

RESULTS: Features associated with high-risk complication included older age (OR = 1.03 per year, P = .001), history of coronary artery disease (OR = 1.40, P = .03), history of diabetes mellitus (OR = 0.41, P < .001, current smoking status (OR = 1.46, P ≤ .001), surgical biopsy (OR = 7.39, P < .001), needle biopsy (OR = 1.94, P < .001), and other invasive procedure (OR = 1.58, P < .001). We did not find an associated with complication and history of stroke (OR = 0.84, P = .53) or chronic obstructive pulmonary disease (OR = 1.27, P = .06).

CONCLUSION: Patient and procedure-level factors may alter the benefits of lung cancer screening. Data concerning individual risk factors and high-risk complications should therefore be incorporated into diagnostic algorithms to optimize clinical benefit and minimize harm. Further study and validation of the risk factors identified herein are warranted.

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