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. 2022 Apr 24;12(5):679.
doi: 10.3390/jpm12050679.

Clinical and Biological Variables Influencing Outcome in Patients with Advanced Non-Small Cell Lung Cancer (NSCLC) Treated with Anti-PD-1/PD-L1 Antibodies: A Prospective Multicentre Study

Affiliations

Clinical and Biological Variables Influencing Outcome in Patients with Advanced Non-Small Cell Lung Cancer (NSCLC) Treated with Anti-PD-1/PD-L1 Antibodies: A Prospective Multicentre Study

Erica Quaquarini et al. J Pers Med. .

Abstract

Introduction: Immune checkpoint inhibitors (ICIs) have become the standard of treatment for patients with non-small cell lung cancer (NSCLC). However, there are still many uncertainties regarding the selection of the patient who could benefit more from this treatment. This study aims to evaluate the prognostic and predictive role of clinical and biological variables in unselected patients with advanced NSCLC candidates to receive ICIs.

Methods: This is an observational and prospective study. The primary objective is the evaluation of the relationship between clinical and biological variables and the response to ICIs. Secondary objectives included: safety; assessment of the relationship between clinical and biological parameters/concomitant treatments and progression-free survival at 6 months and overall survival at 6 and 12 months. Nomograms to predict these outcomes have been generated.

Results: A total of 166 patients were included. An association with response was found in the presence of the high immunohistochemical PD-L1 expression, squamous cell histotype, and early line of treatment, whereas a higher probability of progression was seen in the presence of anemia, high LDH values and neutrophil/lymphocyte ratio (NLR), pleural involvement, and thrombosis before treatment. The nomogram showed that anemia, PD-L1 expression, NLR, and LDH represented the most informative predictor as regards the three parameters of interest.

Conclusions: In the era of personalized medicine, the results are useful for stratifying the patients and tailoring the treatments, considering both the histological findings and the clinical features of the patients.

Keywords: advance stage; anemia; immune checkpoint inhibitors; non-small cell lung cancer.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Nomogram for PFS prediction. Each variable’s value is associated with a score (points bar on the upper part of the nomogram, Supplementary Table S4). By summing the points corresponding to the different variables included, it is possible to calculate the subject’s total score.
Figure 2
Figure 2
Kaplan–Meier curves of high and low risk of progression patients based on PFS nomograms predictions. Survival profiles of patients at high risk of progression (characterized by total points from the PFS nomogram ≥ 104) and low risk of progression (characterized by total points from the PFS nomogram <104) in the ICSM and OSM datasets, respectively. p = p-value from the log-rank test. Graphical representation was truncated at 36 months.
Figure 3
Figure 3
Nomogram for OS prediction. Each variable’s value is associated with a score (points bar on the upper part of the nomogram, Supplementary Table S4). By summing the points corresponding to the different variables included, it is possible to calculate the subject’s total score.
Figure 4
Figure 4
Kaplan–Meier curves of high and low risk of death patients based on OS nomograms predictions. Survival profiles of patients at high risk of death (characterized by total points from the OS nomogram ≥ 87) and low risk of progression (characterized by total points from the OS nomogram < 87) in the ICSM and OSM datasets, respectively. p = p-value from the log-rank test. Graphical representation was truncated at 36 months.

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