Prediction of Response to Immune Checkpoint Inhibitor Therapy Using Early-Time-Point (18)F-FDG PET/CT Imaging in Patients with Advanced Melanoma

利用早期(18)F-FDG PET/CT成像预测晚期黑色素瘤患者对免疫检查点抑制剂治疗的反应

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Abstract

The purpose of this study was to evaluate (18)F-FDG PET/CT scanning as an early predictor of response to immune checkpoint inhibitors (ICIs) in patients with advanced melanoma. Methods: Twenty patients with advanced melanoma receiving ICI prospectively underwent (18)F-FDG PET/CT at 3 scan intervals: before treatment initiation (SCAN-1), at days 21-28 (SCAN-2), and at 4 mo (SCAN-3). This study was approved by the institutional review board, and informed consent was received from all patients who were enrolled between April 2012 and December 2013. Tumor response at each posttreatment time point was assessed according to RECIST 1.1, immune-related response criteria, PERCIST (PERCIST 1.0), and European Organization for Research and Treatment of Cancer (EORTC) criteria. Performance characteristics of each metric to predict best overall response (BOR) at ≥ 4 mo were assessed. Results: Twenty evaluable patients were treated with ipilimumab (n = 16), BMS-936559 (n = 3), or nivolumab (n = 1). BOR at ≥ 4 mo included complete response (n = 2), partial response (n = 2), stable disease (n = 1), and progressive disease (n = 15). Response evaluations at SCAN-2 using RECIST 1.1, immune-related response criteria, PERCIST, and EORTC criteria demonstrated accuracies of 75%, 70%, 70%, and 65%, respectively, to predict BOR at ≥ 4 mo. Interestingly, the optimal PERCIST and EORTC threshold values at SCAN-2 to predict BOR were >15.5% and >14.7%, respectively. By combining anatomic and functional imaging data collected at SCAN-2, we developed criteria to predict eventual response to ICI with 100% sensitivity, 93% specificity, and 95% accuracy. Conclusion: Combining functional and anatomic imaging parameters from (18)F-FDG PET/CT scans performed early in ICI appears predictive for eventual response in patients with advanced melanoma. These findings require validation in larger cohorts.

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