The Predictive Value of Pretreatment Lactate Dehydrogenase and Derived Neutrophil-to-Lymphocyte Ratio in Advanced Non-Small Cell Lung Cancer Patients Treated With PD-1/PD-L1 Inhibitors: A Meta-Analysis

Background

The Lung Immune Prognostic Index (LIPI) combines the lactate dehydrogenase (LDH) level and the derived neutrophil-to-lymphocyte ratio (dNLR). A lot of studies have shown that LDH and dNLR are associated with the prognosis of advanced non-small cell lung cancer (NSCLC) in patients treated with programmed cell death protein 1 (PD-1) or programmed death-ligand 1 (PD-L1) inhibitors. However, previous results were inconsistent, and the conclusions remain unclear. This meta-analysis aimed to investigate the predictive value of pretreatment LDH and dNLR for NSCLC progression in patients treated with PD-1/PD-L1 inhibitors.

Methods

PubMed, Embase, and the Cochrane Library were searched by two researchers independently for related literature before March 2020. Hazard ratios (HRs) with 95% confidence intervals (CIs) for progression-free survival (PFS) and overall survival (OS) were extracted to assess the predictive value of LDH and dNLR. STATA 15. 0 was used to perform the meta-analysis.

Results

A total of 3,429 patients from 26 studies were included in this meta-analysis. The results revealed that high pretreatment LDH was related to poor OS (HR = 1.19, 95%CI = 1.11–1.24, p < 0.001), but not closely related to poor PFS (HR = 1.02, 95%CI = 1.00–1.04, p = 0.023 < 0.05). The pooled results for dNLR suggested that high pretreatment dNLR was related to poor OS (HR = 1.55, 95%CI = 1.33–1.80, p < 0.001) and PFS (HR = 1.33, 95%CI = 1.16–1.54, p < 0.001).

Conclusion

Both pretreatment LDH and dNLR have the potential to serve as peripheral blood biomarkers for patients with advanced NSCLC treated with PD-1/PD-L1 inhibitors. However, more studies on LDH are needed to evaluate its predictive value for PFS in patients with NSCLC.

Choosing tumor mutational burden wisely for immunotherapy: A hard road to explore

Immunotherapy has revolutionized the treatment of cancer due to its remarkable efficacy and extensive survival benefit in multiple tumor types. However, predictive biomarkers are required to identify patients who are likely to respond to immunotherapy. Recently, tumor mutational burden (TMB) has been shown to be associated with clinical outcomes in diverse cancers, such as melanoma, non-small-cell lung cancer and colorectal cancer. Several studies have demonstrated that high TMB can effectively predict the objective response rate and progression-free survival, but the ability of TMB to predict overall survival is limited. Thus, the clinical utility of TMB as a predictive and prognostic biomarker in immunotherapy is currently controversial. Importantly, multiple factors can affect the accurate assessment of TMB and further interfere with its prediction of clinical outcomes. These factors include preanalytical factors such as sample status, analytical factors such as differences in platforms and methods for determining TMB and variability of cutoff values, and postanalytical factors such as inconsistent interpretation and reporting of results. In addition, the optimal definition and quantification of TMB are unclear and require harmonization and standardization for reliable clinical application. This review elaborates on the factors affecting TMB status in primary tumors, summarizes the clinical utility of TMB as a biomarker in immunotherapy, and evaluates the impact of each analysis stage on the accurate estimation of TMB, especially its quantification, aiming to facilitate TMB assessment in routine clinical settings.