Prediction of Early Response to Immune Checkpoint Inhibition Using FDG-PET/CT in Melanoma Patients.

Abstract

Simple SummaryMelanoma has become the most rapidly increasing cancer in Caucasian populations, causing 90% of skin cancer mortality. FDG-PET/CT has been recommended by the European 2019 guidelines for melanoma for staging and treatment response assessment in advanced melanoma highlighting the need for new outcome predictive biomarkers. In the context of melanoma, the evidence on the predictive value of semiquantitative parameters derived from FDG-PET/CT is still very limited. We here provide evidence, in a large cohort of metastatic melanoma patients, that FDG-PET/CT can be used to predict the early response to immune checkpoint inhibition. On a patient-basis, total tumor volume and semiquantitative parameters, such as total metabolic tumor volume MTV and total lesion glycolysis TLG of all metastases three months after treatment start are promising predictive biomarkers for the outcome in metastatic melanoma patients. Also, early complete response on a metastasis- and patient-level seems to be predictive for lasting complete response.We aimed to investigate, whether 18F-2-fluoro-2-desoxy-D-glucose positron emission tomography/computed tomography (FDG-PET/CT) scans performed at baseline (time point 0; TP 0) and three months after initiation of immunotherapy (time point 1; TP 1) can be used on a metastasis- and patient-level to predict the response to immune-checkpoint inhibition using FDG-PET/CT six months after treatment start (time point 2; TP 2) in metastatic melanoma patients. This single-center retrospective study considered metastatic melanoma patients treated with immune checkpoint inhibition from TP 0 to TP 2. An analysis on a metastasis- and patient-level was carried out. Tumor volume, standardized uptake values SUV (mean, maximum, and peak), metabolic tumor volume MTV and total lesion glycolysis TLG of each included metastasis were recorded at each time point, respectively TP 0, TP 1 and TP 2. Total tumor volume, total metabolic tumor volume and total lesion glycolysis per patient were also calculated at TP 0, TP 1 and TP 2. Treatment response was assessed at metastasis- and patient-level based on FDG-PET/CT scans at TP 2. 612 melanoma metastases in 111 patients were included. The analysis on a metastasis-level showed that metastatic SUVpeak at TP 1 and volume variation between TP 0 and TP 1 were the strongest negative predictive biomarkers for response. However, at TP 0, metastatic SUVmean and SUVpeak indicated a low negative prediction power, whereas initial metastatic volume was not a predictive biomarker. Also, melanoma metastases located in bone structures had a negative influence on the outcome at TP 2, particularly in women. The analysis on a patient-level showed, that total tumor volume, total metastatic tumor volume and total lesion glycolysis of all metastases three months after treatment initiation were strong negative predictive biomarkers for response to immunotherapy six months after initiation. Age and female sex were also found to be negative predictive biomarkers with lower predictive power. Interestingly, total tumor volume at TP 0 and number of metastases at TP 0 as well as the occurrence of early immune-related adverse events between TP 0 and TP 2 did not have any predictive value for early treatment response. FDG-PET/CT performed for treatment response assessment three months after initiation of immune checkpoint inhibition in metastatic melanoma patients can also be used to predict early response to treatment. On a metastasis-level SUV peak and volume variation of metastases are strong outcome predictive biomarkers. On a patient-level total tumor volume and semiquantitative parameters such as total metabolic tumor volume MTV and total lesion glycolysis TLG of all metastases are promising outcome predictive biomarkers. Also, early complete response on a metastasis- and patient-level seems to be predictive for lasting complete response.