Disparities in Tumor Mutational Burden, Immunotherapy Use, and Outcomes Based on Genomic Ancestry in Non–Small-Cell Lung Cancer Article Swipe
Otis W. Brawley
,
Patricia Luhn
,
Deonna Reese-White
,
Uzor C. Ogbu
,
Sriraman Madhavan
,
Gerren Wilson
,
Meghan Cox
,
Altovise Ewing
,
Christian Hammer
,
Nicole Richie
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1200/go.21.00309
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1200/go.21.00309
PURPOSE In patients with advanced non–small-cell lung cancer (aNSCLC), tumor mutational burden (TMB) may vary by genomic ancestry; however, its impact on treatment outcomes is unclear. This retrospective, observational study describes treatment patterns of patients with aNSCLC by genomic ancestry and electronic health record (EHR)-reported race and/or ethnicity and evaluates differences in TMB, cancer immunotherapy (CIT) access, and treatment outcomes across racial and ancestral groups. METHODS Patients diagnosed with aNSCLC after January 1, 2011, were selected from a real-world deidentified clinicogenomics database and EHR-derived database; continuously enrolled patients were evaluated. Race and/or ethnicity was recorded using variables from the EHR database; genomic ancestry was classified by single-nucleotide polymorphisms on a next-generation sequencing panel. A threshold of 16 mutations per megabase was used to categorize TMB status. RESULTS Of 59,559 patients in the EHR-derived database and 7,548 patients in the clinicogenomics database, 35,016 (58.8%) and 4,392 (58.2%) were continuously enrolled, respectively. CIT use was similar across EHR-reported race groups, ranging from 34.4% to 37.3% for non-Hispanic Asian and non-Hispanic Black patients, respectively. TMB levels varied significantly across ancestry groups ( P < .001); patients of African ancestry had the highest median TMB (8.75 mutations per megabase; interquartile range, 4.35-14.79). In patients who had received CIT, high TMB was associated with improved overall survival compared with low TMB (20.89 v 11.83 months; hazard ratio, 0.60; 95% CI, 0.51 to 0.70) across genomic ancestral groups. CONCLUSION These results suggest that equitable access to next-generation sequencing may improve aNSCLC outcome disparities in racially and ancestrally diverse populations.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1200/go.21.00309
- https://ascopubs.org/doi/pdfdirect/10.1200/GO.21.00309?role=tab
- OA Status
- gold
- Cited By
- 22
- References
- 43
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3212043884
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3212043884Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1200/go.21.00309Digital Object Identifier
- Title
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Disparities in Tumor Mutational Burden, Immunotherapy Use, and Outcomes Based on Genomic Ancestry in Non–Small-Cell Lung CancerWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-11-09Full publication date if available
- Authors
-
Otis W. Brawley, Patricia Luhn, Deonna Reese-White, Uzor C. Ogbu, Sriraman Madhavan, Gerren Wilson, Meghan Cox, Altovise Ewing, Christian Hammer, Nicole RichieList of authors in order
- Landing page
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https://doi.org/10.1200/go.21.00309Publisher landing page
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https://ascopubs.org/doi/pdfdirect/10.1200/GO.21.00309?role=tabDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://ascopubs.org/doi/pdfdirect/10.1200/GO.21.00309?role=tabDirect OA link when available
- Concepts
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Medicine, Hazard ratio, Lung cancer, Internal medicine, Interquartile range, Oncology, Genetic genealogy, Cancer, Population, Confidence interval, Environmental healthTop concepts (fields/topics) attached by OpenAlex
- Cited by
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22Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 11, 2023: 6, 2022: 3Per-year citation counts (last 5 years)
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43Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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