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Prognostic Nutritional Index Predicts Outcome of PD-L1 Negative and MSS Advanced Cancer Treated with PD-1 Inhibitors

PURPOSE: Tumor mutational burden (TMB), microsatellite instability-high (MSI-H), and expression of programmed death ligand-1 (PD-L1) have emerged as predictive biomarkers for responsiveness to immune checkpoint inhibitors (ICIs) in several cancer types. However, for patients with negative PD-L1 expr...

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Detalles Bibliográficos
Autores principales: Zhang, Yan, Jin, Jun, Tang, Min, Li, Ping, Zhou, Li-Na, Du, Yi-Ping, Chen, Min-Bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9192216/
https://www.ncbi.nlm.nih.gov/pubmed/35707390
http://dx.doi.org/10.1155/2022/6743126
Descripción
Sumario:PURPOSE: Tumor mutational burden (TMB), microsatellite instability-high (MSI-H), and expression of programmed death ligand-1 (PD-L1) have emerged as predictive biomarkers for responsiveness to immune checkpoint inhibitors (ICIs) in several cancer types. However, for patients with negative PD-L1 expression, or microsatellite stability (MSS), some cases may experience favorable response to immunotherapy, and there is currently a lack of good relevant predictors. We tried to introduce several peripheral blood markers for predicting treatment outcome and immune-related adverse events (irAEs) in PD-L1 negative and MSS patients. METHODS: A retrospective study of 142 PD-L1 negative and MSS patients was carried out. The association of peripheral blood markers including lactate dehydrogenase (LDH), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), albumin-to-globulin ratio (AGR), prognostic nutrition index (PNI), and other factors with clinicopathological characters and prognosis were assessed by Cox regression and Kaplan-Meier methods. RESULTS: Lower level of PNI and poor performance status (ECOG score of 2) was correlated with significantly shorter overall survival (OS) and worse outcome of ICIs. The multivariate analysis revealed that PNI (for OS HR = 0.465, 95% CI: 0.236–0.916, p = 0.027; for PFS HR = 0.493, 95% CI: 0.251–0.936, p = 0.031) and ECOG score (for OS HR = 4.601, 95% CI: 2.676–7.910, p < 0.001; for PFS HR = 2.830, 95% CI: 1.707–4.691, p < 0.001) were independent prognostic factors for OS and PFS. NLR was related to the onset of irAEs. CONCLUSIONS: Pretreatment level of PNI and NLR, beyond PD-L1 expression and MSS, can improve the predictive accuracy for immunotherapy outcomes and has the potential to expand the candidate pool of patients for treatment with ICIs.