Artikel ; Online: Biomarkers and factors in small cell lung cancer patients treated with immune checkpoint inhibitors: A meta-analysis.
2023 Band 12, Heft 10, Seite(n) 11211–11233
Abstract: Objective: The aim of this meta-analysis was to summarize the available results of immunotherapy predictors for small cell lung cancer (SCLC) and to provide evidence-based information for their potential predictive value of efficacy.: Methods: We ... ...
Abstract | Objective: The aim of this meta-analysis was to summarize the available results of immunotherapy predictors for small cell lung cancer (SCLC) and to provide evidence-based information for their potential predictive value of efficacy. Methods: We searched PubMed, EMBASE, Web of Science, The Cochrane Library, and ClinicalTrials (from January 1, 1975 to November 1, 2021). The hazard ratios (HR) and its 95% confidence intervals (CIs) and tumor response rate of the included studies were extracted. Results: Eleven studies were eventually included and the pooled results showed that programmed cell death ligand 1 (PD-L1) positive: objective response rate (ORR) (relative risk [RR] = 1.39, 95% CI [0.48, 4.03], p = 0.54), with high heterogeneity (p = 0.05, I Conclusion: The available research results do not support the recommendation of PD-L1 positive and TMB-H as predictors for the application of immune checkpoint inhibitors (ICIs) in SCLC patients. LDH, baseline liver metastasis and CNS metastasis may be used as markers/influencing factors for predicting the efficacy of ICIs in SCLC patients. Non-Asian SCLC patients had better efficacy with ICIs in our results. |
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Mesh-Begriff(e) | Humans ; Small Cell Lung Carcinoma/drug therapy ; Immune Checkpoint Inhibitors/therapeutic use ; B7-H1 Antigen ; Biomarkers ; Carcinoma, Non-Small-Cell Lung ; L-Lactate Dehydrogenase ; Liver Neoplasms ; Neoplasms, Second Primary ; Lung Neoplasms/drug therapy |
Chemische Substanzen | Immune Checkpoint Inhibitors ; B7-H1 Antigen ; Biomarkers ; L-Lactate Dehydrogenase (EC 1.1.1.27) |
Sprache | Englisch |
Erscheinungsdatum | 2023-05-10 |
Erscheinungsland | United States |
Dokumenttyp | Meta-Analysis ; Journal Article ; Research Support, Non-U.S. Gov't |
ZDB-ID | 2659751-2 |
ISSN | 2045-7634 ; 2045-7634 |
ISSN (online) | 2045-7634 |
ISSN | 2045-7634 |
DOI | 10.1002/cam4.5800 |
Datenquelle | MEDical Literature Analysis and Retrieval System OnLINE |
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