A multivariate analysis of low-dose CT lung cancer screening in a Michigan community hospital network.

Authors

null

Jason Law

Michigan State University, Lansing, MI

Jason Law , Borys Hrinczenko

Organizations

Michigan State University, Lansing, MI

Research Funding

No funding received
None.

Background: Lung cancer is the leading cause of cancer deaths in the United States. The USPSTF recommended screening for lung cancer with low-dose chest computer tomography (LDCT) in 2013. This was based on the National Lung Screening Trial (NLST) which showed a 20% relative reduction in mortality from LDCT compared with chest radiography in high-risk individuals. The major NLST eligibility criteria were age 55-74, a 30 + pack year smoking history and current smoking status or having quit in the last 15 years. The impact of other risk factors on screening results besides inclusion criteria is unknown. We sought to identify other factors for the risk of lung cancer detection in screened individuals. Methods: This was a retrospective cohort study employing a Michigan based McLaren Hospital Network Lung Cancer Screening Program (LCSP) database from 2015-2022. Participant eligibility in screening was the USPSTF criteria except for an age range of 50-80. Analyses were stratified by BMI, smoking pack-years, insurance status, smoking status, sex, other CT findings, pre- vs. during COVID pandemic (before and after January 2020). Multivariate logistic regression analysis was used for odds ratios (OR) with 95% confidence intervals (CI) as estimates of the relative risk of an elevated Lung-RADS category ≥3 (high risk of detecting lung cancer). Results: A total of 2638 subjects, 49.91% females, 50.09% males, mean BMI 29.50 ± 7.17 (SD), pack-years 44.52 ±18.29, Medicaid 6.66%, Medicare 32.01%, Private Insurance 57.62%, Self-pay /unknown 3.71%. Current smoker 65.49%, Former smoker 34.51%, other CT findings 51.99%, pre-COVID 46.08%, during COVID pandemic 53.92%. Lung-RADS category 0 (0.04%), 1 (35.33%), 2, (50.61%), 3 (6.56%), 4a (4.85%), 4b (1.55%), 4x (1.06%). A statistically significant association with a Lung-RADS category ≥3 was found with lower BMI, OR=0.980 (95% CI, 0.969-0.991), p=0.0005, and female gender, OR=1.232 (95% CI, 1.039-1.462), p=0.0166 (Table). Conclusions: In our study cohort a lower-than-average BMI and also female gender were statistically correlated with an elevated Lung-RADS category ≥3. These findings might be incorporated into a risk stratification model, however further larger studies are needed to validate our findings.

Multivariate logistic regression predicting Lung-RADS ≥3 among all patients (n=2,638).

Odds Ratio Estimates
EffectPoint Estimate95% Wald Confidence LimitsP-values
BMI, below vs above mean0.9800.9690.9910.0005
Smoking pack-years0.9990.9951.0040.7867
Insurance, Medicare vs Medicaid1.0160.7211.4340.9258
Insurance, Private vs Medicaid1.1670.8371.6270.3633
Insurance, Unknown/Self-pay vs Medicaid0.8620.5151.4440.5738
Smoking status, Current vs Former1.1780.9931.3970.0602
Sex, Female vs Male1.2321.0391.4620.0166
Other CT findings, No vs Yes1.3750.9621.9650.0802
After Jan 2020 vs Before Jan 20201.4130.9802.0380.0643

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Abstract Details

Meeting

2023 ASCO Annual Meeting

Session Type

Poster Session

Session Title

Prevention, Risk Reduction, and Hereditary Cancer

Track

Prevention, Risk Reduction, and Genetics

Sub Track

Etiology/Epidemiology

Citation

J Clin Oncol 41, 2023 (suppl 16; abstr 10576)

DOI

10.1200/JCO.2023.41.16_suppl.10576

Abstract #

10576

Poster Bd #

209

Abstract Disclosures

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