Publication-only abstracts (abstract number preceded by an "e"), published in conjunction with the 2019 ASCO Annual Meeting but not presented at the Meeting, can be found online only.
Clinical insights for hematological malignancies from an artificial intelligence decision-support tool.
Cancer Prevention, Hereditary Genetics, and Epidemiology
2019 ASCO Annual Meeting
J Clin Oncol 37, 2019 (suppl; abstr e13023)
Author(s): Miyoung Kim, Jane Snowdon, S Dilhan Weeraratne, Winnie Felix, Lionel Lim, Irene Dankwa-Mullan, Young Kyung Lee, Eunyup Lee, Kibum Jeon, Jee-Soo Lee, Dae Young Zang, Hyo Jung Kim, Ho Young Kim, Boram Han; Department of Laboratory Medicine, Hallym University Sacred Heart Hospital, Anyang, South Korea; IBM Watson Health, Cambridge, MA; IBM Watson Health, Silver Spring, MD; IBM Watson Health, Singapore, Singapore; Division of Hemato-Oncology, Department of Internal Medicine, Hallym University Medical Center, Seoul, South Korea; Department of Hematology-Oncology, Hallym University medical center, Anyang, South Korea; Department of Internal Medicine, Hallym University Medical Center, Hallym University College of Medicine, Anyang, South Korea; Department of Internal Medicine, Hallym University Medical Center, Anyang, South Korea
Background: Next generation sequencing (NGS) in hematological tumors is increasingly shaping clinical treatment decisions at the point of care. While the impact of NGS panels in solid tumors is largely therapeutic, targeted sequencing in hematological tumors can additionally provide diagnostic and prognostic insights. Additional data generated in hematological tumor sequencing makes manual interpretation and annotation of variants tedious and non-scalable. In this study we compared hematological tumor variant interpretation using an artificial intelligence decision-support system, Watsonä for Genomics (WfG), with expert guided manual curation. Methods: Patients with hematological tumors at Hallym University, College of Medicine between December 2017 and December 2018, were sequenced using the 54 gene Illumina TruSight Myeloid Panel. WfG interpreted and annotated all patients’ sequencing results, a subset of which were assessed manually to ascertain concordance. Results: 54 South Korean patients with hematological malignancies were analyzed (23 Acute Myeloid Leukemia, 12 myeloproliferative neoplasm, 5 myelodysplastic syndrome, 5 multiple myeloma and 9 others). Comparison of manual and WfG interpretation of 10 randomly selected cases yielded 90% (9/10) concordance and identification of 9 clinically actionable variants (33%) not found in manual interpretation. In total, WfG identified that 71% (38/54) of all cases had at least one clinically actionable therapeutic alteration (a variant targeted by a US FDA approved drug, off-label drug, or clinical trial). 33% (18/54) of cases had genes that were targeted by a US FDA approved therapy including JAK2, IDH1, IDH2, and FLT3. In cases without therapeutic alterations, WfG identified diagnostic or prognostic insights in an additional 20% (11/54) of patients. 9% (5/54) had no clinically actionable information. Conclusions: WfG variant interpretation correlated well with manually curated expert opinion and identified clinically actionable insights missed by manual interpretation. WfG has obviated the need for labor-intensive manual curation of clinical trials and therapy, enabling our center to exponentially scale our NGS operations.