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Trends In Lung Cancer Incidence
And Treatment Across The US
2019-2023

Background

We analyzed patterns in incidence, treatment, and patient characteristics including time to treatment, age, sex, race, stage, histological type, and geographical location in lung cancer patients utilizing data from the Q-Centrix Clinical Data Warehouse, a proprietary database of de-identified clinical data produced through expert-driven human abstraction.


Methods

24,360 lung cancer patients diagnosed from January of 2019 to December of 2023 were extracted from the Q-Centrix Clinical Data Warehouse. The data set used in this analysis contains de-identified patient data from 64 hospitals, health systems, and cancer centers across the United States. All patients diagnosed at these hospitals from 2019-2023 are included in this database. The data were analyzed by diagnosis year. Chi-square tests were run to compare differences in traits across the 4 diagnosis years. A p-value of < 0.05 was considered significant. Post-hoc pairwise chi-square tests were run with a Bonferroni correction to control for multiple tests. All statistical analysis was conducted in R version 4.4.0. The research protocol went through Q-Centrix’s formal review process, including review by an internal senior clinical research lead prior to the start of the analysis, as well as review by an external senior research specialist post-analysis.

4.70%

Decrease in the proportion of patients being treated across the country within 30 days of diagnosis

Conclusion

This analysis portrays an increase in the proportion of lung cancer patient diagnoses in the Midwest region in recent years. Specifically, a 3.7% increase in the proportion of overall diagnoses in the Midwest from 2022 to 2023 is noted. We also observe an average year-over-year decrease of 4.7% in the proportion of patients being treated across the country within 30 days of diagnosis. Further investigation will evaluate treatment outcomes to assess the impact of the delay in time to treatment.


This abstract was originally published digitally as part of the 2025 ASCO Annual Meeting.

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