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Chu Hyun Kim
OA14 - Update of Phase 3 Trials and the Role of HPD (ID 148)
- Event: WCLC 2019
- Type: Oral Session
- Track: Immuno-oncology
- Presentations: 1
- Now Available
OA14.07 - Clinical and Genetic Characterization of Hyperprogression Based on Volumetry in Advanced NSCLC Treated with Immunotherapy (Now Available) (ID 1067)
11:30 - 13:00 | Author(s): Chu Hyun Kim
Hyperprogressive disease (HPD), characterized by accelerated tumor progression, has been proposed as a new pattern of progression following immune checkpoint inhibitor (ICI) treatment. The aim of this study was to describe the characteristics of HPD and investigate its predictive markers.Method
Clinical and radiological findings of 335 advanced non-small cell lung cancer (NSCLC) patients 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 to individual genomic profiles generated by deep sequencing of 380 genes.Result
Among 135 patients with progressive disease (PD), as assessed by RECIST, 48 (14·3% of total and 35·6% among PD) and 44 (13·1% of total and 32·6% among PD) were found to have HPD by volumetric (HPDV) and one-dimensional (HPDR) analysis, respectively. HPDV patients were associated with significantly inferior overall survival (OS) compared with non-HPDV PD patients (median OS (months), 4·7 [95% confidence interval (CI), 3·5–11·9)] vs. 7·9 [95% CI, 6·0–13·5], p=0·004); OS did not differ between HPDR and non-HPDR patients. HPDV status was an independent OS factor. Derived neutrophil-to-lymphocyte ratio (dNLR) greater than 4 and lactate dehydrogenase (LDH) greater than the upper normal limit were significantly associated with HPDV. Moreover, we identified coinciding KRAS and STK11 mutations in the HPDV cohort (3/16), while none were found in the non-HPDV cohort (0/28).Conclusion
Defining HPD treated with ICI based on volumetric measurement is more precise than that based on one-dimensional analysis. Pre-ICI dNLR, LDH, and concurrence of STK11 and KRAS mutations could, thus, be used as potential biomarkers for HPD prediction.
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