Clinical factors associated with high PD‐L1 expression in patients with early‐stage non‐small cell lung cancer
Abstract Background Superior outcomes have been obtained for neoadjuvant treatment with immune checkpoint inhibitors (ICI) plus chemotherapy over neoadjuvant chemotherapy alone, especially in patients with high programmed cell death ligand 1 (PD‐L1) expression. However, it is not always possible to...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-11-01
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| Series: | Thoracic Cancer |
| Subjects: | |
| Online Access: | https://doi.org/10.1111/1759-7714.15453 |
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| Summary: | Abstract Background Superior outcomes have been obtained for neoadjuvant treatment with immune checkpoint inhibitors (ICI) plus chemotherapy over neoadjuvant chemotherapy alone, especially in patients with high programmed cell death ligand 1 (PD‐L1) expression. However, it is not always possible to obtain sufficient tumor specimens for biomarker testing before surgery. In this study, we explored clinical factors that can predict high PD‐L1 expression. Methods We retrospectively enrolled 340 lung cancer patients who received pulmonary resection between 2014 and 2023 and who had PD‐L1 expression data. Chi‐squared tests and logistic regression analyses were used to identify clinical factors associated with high PD‐L1 status. Results Univariable and multivariable analyses revealed that smoking, high maximum standardized uptake value (SUVmax) of 18F‐fluorodeoxyglucose positron emission computed tomography (18F‐FDG PET/CT), and high plasma fibrinogen are independent predictors of high PD‐L1 expression. A predictive score for high PD‐L1 expression (ranging from 0 to 3) was developed based on these parameters. Notably, only 5% of patients with a score of 0 exhibited high PD‐L1 expression, whereas this proportion increased to 53% for patients with a score of 3. Conclusion These results showed that plasma fibrinogen, smoking history, and SUVmax are predictors of high PD‐L1 expression, providing a basis for identifying patients expected to benefit from neoadjuvant ICI treatment. |
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| ISSN: | 1759-7706 1759-7714 |