Research & Innovation
Publications
MLR and dMLR Predict Locoregional Control and Progression-Free Survival in Unresectable NSCLC Stage III Patients
PMU Authors
Alexandra Hochreiter, Markus Stana, Elvis Ruznic, Brane Grambozov, Josef Karner, Raphaela Moosbrugger, Falk Roder, Franz Zehentmayr
All Authors
Alexandra Hochreiter, Markus Stana, Marisa Klebermass, Elvis Ruznic, Brane Grambozov, Josef Karner, Martin Heilmann, Danijela Minasch, Ayurzana Purevdorj, Georg Gruber, Raphaela Moosbrugger, Falk Roder, Franz Zehentmayr
Journal association
Journal of Clinical Medicine
Abstract
Background: As demonstrated by the PACIFIC trial, biomarker-driven patient selection is crucial. While treatment based on programmed death ligand-1 (PD-L1) and mutational status have become routine, tests for biomarkers available from pretherapeutic blood samples are currently a topic of scientific interest. Methods: This analysis was conducted on patients from the ALLSTAR RWD study, which is a nationwide, prospective registry for inoperable non-small cell lung cancer (NSCLC) stage III. Patients were amenable if they had a full routine pre-treatment blood sample, from which the following biomarkers were extracted: neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (dNLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), derived monocyte-to-lymphocyte ratio (dMLR) and lactate dehydrogenase (LDH) levels. The intention was to find a cutoff for each of these biomarkers to predict locoregional control (LRC), progression-free survival (PFS) and overall survival (OS). Results: MLR and dMLR demonstrated their predictive potential with cutoff values of 0.665 and 0.945, respectively. Stratifying the whole cohort by means of these cutoffs demonstrated significantly better locoregional control for patients below the threshold, both in the whole cohort (N = 175; 55.7% vs. 75.5%; p-value = 0.018) and in the Durvalumab subgroup (N = 106; 57.5% vs. 77.3%; p-value = 0.030). Similar findings were observed for PFS in the whole cohort (N = 175; 20.5% vs. 56.1%; p-value p < 0.001) and in the Durvalumab subgroup (N = 106; 31.2% vs. 64.6%, p-value < 0.001). dMLR could also significantly predict PFS (N = 173; 17.4% vs. 56.3%; p-value < 0.001), which was corroborated in the Durvalumab subgroup (N = 108; 23.1% vs. 64.1%; p-value = 0.003). Conclusions: This explorative analysis demonstrates the predictive potential of MLR and dMLR for LRC and PFS. These blood biomarkers can be readily integrated into clinical routines since they are easily available.
Keywords
Durvalumab, Non-small cell lung cancer, Allstar, Mlr, Rwd, Blood biomarkers, dMLR