Combination of Baseline LDH, Performance Status and Age as Integrated Algorithm to Identify Solid Tumor Patients with Higher Probability of Response to Anti PD-1 and PD-L1 Monoclonal Antibodies

Abstract

Predictive biomarkers of response to immune-checkpoint inhibitors (ICIs) are an urgent clinical need. The aim of this study is to identify manageable parameters to use in clinical practice to select patients with higher probability of response to ICIs. Two-hundred-and-seventy-one consecutive metastatic solid tumor patients, treated from 2013 until 2017 with anti- Programmed death-ligand 1 (PD-L1)/programmed cell death protein 1 (PD-1) ICIs, were evaluated for baseline lactate dehydrogenase (LDH) serum level, performance status (PS), age, neutrophil-lymphocyte ratio, type of immunotherapy, number of metastatic sites, histology, and sex. A training and validation set were used to build and test models, respectively. The variables’ effects were assessed through odds ratio estimates (OR) and area under the receive operating characteristic curves (AUC), from univariate and multivariate logistic regression models. A final multivariate model with LDH, age and PS showed significant ORs and an AUC of 0.771. Results were statistically validated and used to devise an Excel algorithm to calculate the patient’s response probabilities. We implemented an interactive Excel algorithm based on three variables (baseline LDH serum level, age and PS) which is able to provide a higher performance in response prediction to ICIs compared with LDH alone. This tool could be used in a real-life setting to identify ICIs in responding patients.

Lactate dehydrogenase: a marker of diminished antitumor immunity

“…However, retrospective data support a relationship between LDH levels and clinical outcome following immunotherapy in other tumor types (Table 1). [6][7][8][9][10][11] In this review, we describe mechanisms that may result in elevated LDH levels in cancer patients. Elevated LDH levels are the product of enhanced glycolytic activity of the tumor and tumor necrosis due to hypoxia, the latter being associated with high tumor burden.…”

Integrated genomic analysis identifies a genetic mutation model predicting response to immune checkpoint inhibitors in melanoma

“…42 Cona et al found that the combination of baseline LDH serum level, performance status, and age provided better prediction of response to ICIs in solid tumors compared with LDH alone. 43 In this study, we also evaluated the potential for combining ITS with TMB or LDH to jointly predict response to ICIs in melanoma. Interestingly, our findings indicated that a specific population with high ITS might benefit from ICIs therapy even if TMB was low or LDH was elevated.…”

Novel risk group stratification for metastatic urothelial cancer patients treated with immune checkpoint inhibitors

“…The final prognostic factor included in the Emory Risk Scoring System for UC patients is ECOG PS, which is a widely used method for assessing functional status of cancer patients. A patient's ECOG PS can be used to predict their ability to tolerate therapy and has consistently shown to be highly correlated with survival, including in patients receiving ICI . Determining a UC patient's ECOG PS requires no more than an assessment of their ability to perform activities of daily living (ADLs) and should be determined prior to treatment initiation.…”