Cross-Domain Text Mining to Predict Adverse Events from Tyrosine Kinase Inhibitors for Chronic Myeloid Leukemia

SIMPLE SUMMARY: Tyrosine kinase inhibitor (TKI) therapy is often taken indefinitely by chronic myeloid leukemia (CML) patients. However, little is known about the long-term or under-reported TKI side effects due to limited longitudinal clinical data on these relatively new drugs. We utilize novel cross-domain text mining and machine learning to comprehensively assess relationships between TKIs and possible adverse events (AEs) across 30+ million PubMed publications. The top 10% of predicted AEs were mapped to ten physiological function-based foci: hematology, glucose, iron, cardiovascular, thyroid, inflammation, kidney, gastrointestinal, neuromuscular, and others. Study results provided new insight into the breadth of adverse events with TKI usage. Results-based recommendations were devised for proactive patient monitoring protocols as a function of perceived AE risk. Additionally, AEs were mapped to specific TKI types to assist in personalized TKI selection. ABSTRACT: Tyrosine kinase inhibitors (TKIs) are prescribed for chronic myeloid leukemia (CML) and some other cancers. The objective was to predict and rank TKI-related adverse events (AEs), including under-reported or preclinical AEs, using novel text mining. First, k-means clustering of 2575 clinical CML TKI abstracts separated TKIs by significant (p < 0.05) AE type: gastrointestinal (bosutinib); edema (imatinib); pulmonary (dasatinib); diabetes (nilotinib); cardiovascular (ponatinib). Next, we propose a novel cross-domain text mining method utilizing a knowledge graph, link prediction, and hub node network analysis to predict new relationships. Cross-domain text mining of 30+ million articles via SemNet predicted and ranked known and novel TKI AEs. Three physiology-based tiers were formed using unsupervised rank aggregation feature importance. Tier 1 ranked in the top 1%: hematology (anemia, neutropenia, thrombocytopenia, hypocellular marrow); glucose (diabetes, insulin resistance, metabolic syndrome); iron (deficiency, overload, metabolism), cardiovascular (hypertension, heart failure, vascular dilation); thyroid (hypothyroidism, hyperthyroidism, parathyroid). Tier 2 ranked in the top 5%: inflammation (chronic inflammatory disorder, autoimmune, periodontitis); kidney (glomerulonephritis, glomerulopathy, toxic nephropathy). Tier 3 ranked in the top 10%: gastrointestinal (bowel regulation, hepatitis, pancreatitis); neuromuscular (autonomia, neuropathy, muscle pain); others (secondary cancers, vitamin deficiency, edema). Results suggest proactive TKI patient AE surveillance levels: regular surveillance for tier 1, infrequent surveillance for tier 2, and symptom-based surveillance for tier 3.