Youjin Kim1, Chu Hyun Kim2, Ho Yun Lee3, Se-Hoon Lee4, Hong Sook Kim5, Sook Lee3, Hongui Cha5, Sungjun Hong6, Kyunga Kim7, Sang Won Seo8, Jong-Mu Sun9, Myung-Ju Ahn9, Jin Seok Ahn9, Keunchil Park10. 1. Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea; Division of Hematology-Oncology, Department of Medicine, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon, Republic of Korea. 2. Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. 3. Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea; Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Seoul, Republic of Korea. 4. Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea; Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Seoul, Republic of Korea. 5. Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Seoul, Republic of Korea. 6. Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Seoul, Republic of Korea. 7. Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Seoul, Republic of Korea; Statistics and Data Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, Republic of Korea. 8. Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. 9. Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. 10. Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea; Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Seoul, Republic of Korea. Electronic address: kpark@skku.edu.
Abstract
INTRODUCTION: Hyperprogressive disease (HPD), characterized by accelerated tumor progression, has been proposed as a new pattern of progression after immune checkpoint inhibitor (ICI) treatment. The aim of this study was to describe the characteristics of HPD and investigate its predictive markers. METHODS: Clinical and radiological findings of 335 patients with advanced NSCLC treated with ICI monotherapy were retrospectively analyzed. Radiological data were quantitatively and longitudinally analyzed for tumor size and volume by comparing baseline and follow-up computerized tomography results. The findings were matched with individual genomic profiles generated by deep sequencing of 380 genes. RESULTS: Among 135 patients with progressive disease (PD), as assessed by the Response Evaluation Criteria in Solid Tumors version 1.1 criteria, 48 (14.3% of all patients and 35.6% of those with PD) and 44 (13.1% of all patients and 32.6% among those with PD) were found to have HPD by volumetry (HPDV) and assessed by RECIST 1.1 (HPDR), respectively. Patients with HPDV were associated with significantly inferior overall survival (OS) versus that of patients without HPDV with PD (median OS = 4.7 months [95% confidence interval: 3.5-11.9)] versus 7.9 months [95% confidence interval: 6.0-13.5] [p = 0.004]); OS did not differ between patients without and without HPDR. HPDV status was an independent factor in OS. A derived neutrophil-to-lymphocyte ratio greater than 4 and lactate dehydrogenase level greater than the upper limit of normal were significantly associated with HPDV. Moreover, we identified coinciding KRAS and serine/threonine kinase 11 gene (STK11) mutations in the cohort of patients with HPDV (three of 16), whereas none were found in the cohort of patients without HPDV (zero of 28). CONCLUSIONS: Defining HPD treated with ICI on the basis of volumetric measurement is more precise than is defining it on the basis of one-dimensional analysis. Pre-ICI derived neutrophil-to-lymphocyte ratio, lactate dehydrogenase level, and concurrence of STK11 and KRAS mutations could thus be used as potential biomarkers for HPD prediction.
INTRODUCTION: Hyperprogressive disease (HPD), characterized by accelerated tumor progression, has been proposed as a new pattern of progression after immune checkpoint inhibitor (ICI) treatment. The aim of this study was to describe the characteristics of HPD and investigate its predictive markers. METHODS: Clinical and radiological findings of 335 patients with advanced NSCLC treated with ICI monotherapy were retrospectively analyzed. Radiological data were quantitatively and longitudinally analyzed for tumor size and volume by comparing baseline and follow-up computerized tomography results. The findings were matched with individual genomic profiles generated by deep sequencing of 380 genes. RESULTS: Among 135 patients with progressive disease (PD), as assessed by the Response Evaluation Criteria in Solid Tumors version 1.1 criteria, 48 (14.3% of all patients and 35.6% of those with PD) and 44 (13.1% of all patients and 32.6% among those with PD) were found to have HPD by volumetry (HPDV) and assessed by RECIST 1.1 (HPDR), respectively. Patients with HPDV were associated with significantly inferior overall survival (OS) versus that of patients without HPDV with PD (median OS = 4.7 months [95% confidence interval: 3.5-11.9)] versus 7.9 months [95% confidence interval: 6.0-13.5] [p = 0.004]); OS did not differ between patients without and without HPDR. HPDV status was an independent factor in OS. A derived neutrophil-to-lymphocyte ratio greater than 4 and lactate dehydrogenase level greater than the upper limit of normal were significantly associated with HPDV. Moreover, we identified coinciding KRAS and serine/threonine kinase 11 gene (STK11) mutations in the cohort of patients with HPDV (three of 16), whereas none were found in the cohort of patients without HPDV (zero of 28). CONCLUSIONS: Defining HPD treated with ICI on the basis of volumetric measurement is more precise than is defining it on the basis of one-dimensional analysis. Pre-ICI derived neutrophil-to-lymphocyte ratio, lactate dehydrogenase level, and concurrence of STK11 and KRAS mutations could thus be used as potential biomarkers for HPD prediction.
Authors: Roberto Ferrara; Diego Signorelli; Claudia Proto; Arsela Prelaj; Marina Chiara Garassino; Giuseppe Lo Russo Journal: Transl Lung Cancer Res Date: 2021-06