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

Maria Silvia Cona, Mara Lecchi, Sara Cresta, Silvia Damian, Michele Del Vecchio, Andrea Necchi, Marta Maria Poggi, Daniele Raggi, Giovanni Randon, Raffaele Ratta, Diego Signorelli, Claudio Vernieri, Filippo de Braud, Paolo Verderio, Massimo Di Nicola

Research output: Contribution to journalArticle

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.

Original languageEnglish
Article number223
JournalCancers
Volume11
Issue number2
DOIs
Publication statusPublished - Feb 2019

Keywords

  • Biomarkers
  • Immune-checkpoint inhibitors
  • LDH

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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