Immune-checkpoint inhibitors (ICIs) have been proven to have great efficacy in non-small cell lung cancer (NSCLC) as single agents or in combination therapy, being capable to induce deep and durable remission. However, severe adverse events may occur and about 40% of patients do not benefit from the treatment. Predictive factors of response to ICIs are needed in order to customize treatment. The aim of this study is to evaluate the correlation between quantitative positron emission tomography (PET) parameters defined before starting ICI therapy and responses to treatment and patient outcome. We retrospectively analyzed 92 NSCLC patients treated with nivolumab, pem-brolizumab or atezolizumab. Basal PET/computed tomography (CT) scan parameters (whole-body metabolic tumor volume—wMTV, total lesion glycolysis—wTLG, higher standardized uptake volume maximum and mean—SUVmax and SUVmean) were calculated for each patient and correlated with outcomes. Patients who achieved disease control (complete response + partial response + stable disease) had significantly lower MTV median values than patients who had not (progressive disease) (77 vs. 160.2, p = 0.039). Furthermore, patients with MTV and TLG values lower than the median values had improved OS compared to patients with higher MTV and TLG (p = 0.03 and 0.05, respec-tively). No relation was found between the other parameters and outcome. In conclusion, baseline metabolic tumor burden, measured with MTV, might be an independent predictor of treatment response to ICI and a prognostic biomarker in NSCLC patients.

Monaco, L., Gemelli, M., Gotuzzo, I., Bauckneht, M., Crivellaro, C., Genova, C., et al. (2021). Metabolic parameters as biomarkers of response to immunotherapy and prognosis in non-small cell lung cancer (Nsclc): A real world experience. CANCERS, 13(7) [10.3390/cancers13071634].

Metabolic parameters as biomarkers of response to immunotherapy and prognosis in non-small cell lung cancer (Nsclc): A real world experience

Monaco L.;Gotuzzo I.
;
Crivellaro C.;Cortinovis D.;Bernasconi D. P.;Guerra L.
2021

Abstract

Immune-checkpoint inhibitors (ICIs) have been proven to have great efficacy in non-small cell lung cancer (NSCLC) as single agents or in combination therapy, being capable to induce deep and durable remission. However, severe adverse events may occur and about 40% of patients do not benefit from the treatment. Predictive factors of response to ICIs are needed in order to customize treatment. The aim of this study is to evaluate the correlation between quantitative positron emission tomography (PET) parameters defined before starting ICI therapy and responses to treatment and patient outcome. We retrospectively analyzed 92 NSCLC patients treated with nivolumab, pem-brolizumab or atezolizumab. Basal PET/computed tomography (CT) scan parameters (whole-body metabolic tumor volume—wMTV, total lesion glycolysis—wTLG, higher standardized uptake volume maximum and mean—SUVmax and SUVmean) were calculated for each patient and correlated with outcomes. Patients who achieved disease control (complete response + partial response + stable disease) had significantly lower MTV median values than patients who had not (progressive disease) (77 vs. 160.2, p = 0.039). Furthermore, patients with MTV and TLG values lower than the median values had improved OS compared to patients with higher MTV and TLG (p = 0.03 and 0.05, respec-tively). No relation was found between the other parameters and outcome. In conclusion, baseline metabolic tumor burden, measured with MTV, might be an independent predictor of treatment response to ICI and a prognostic biomarker in NSCLC patients.
Articolo in rivista - Articolo scientifico
Immunotherapy; Metabolic tumor volume; NSCLC; OS; PET/CT; PFS; Quan-tification; Response to therapy;
English
1-apr-2021
2021
13
7
1634
open
Monaco, L., Gemelli, M., Gotuzzo, I., Bauckneht, M., Crivellaro, C., Genova, C., et al. (2021). Metabolic parameters as biomarkers of response to immunotherapy and prognosis in non-small cell lung cancer (Nsclc): A real world experience. CANCERS, 13(7) [10.3390/cancers13071634].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/312468
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