Learning to detect and understand drug discontinuation events from clinical narratives

OBJECTIVE: Identifying drug discontinuation (DDC) events and understanding their reasons are important for medication management and drug safety surveillance. Structured data resources are often incomplete and lack reason information. In this article, we assessed the ability of natural language processing (NLP) systems to unlock DDC information from clinical narratives automatically. MATERIALS AND METHODS: We collected 1867 de-identified providers\u27 notes from the University of Massachusetts Medical School hospital electronic health record system. Then 2 human experts chart reviewed those clinical notes to annotate DDC events and their reasons. Using the annotated data, we developed and evaluated NLP systems to automatically identify drug discontinuations and reasons at the sentence level using a novel semantic enrichment-based vector representation (SEVR) method for enhanced feature representation. RESULTS: Our SEVR-based NLP system achieved the best performance of 0.785 (AUC-ROC) for detecting discontinuation events and 0.745 (AUC-ROC) for identifying reasons when testing this highly imbalanced data, outperforming 2 state-of-the-art non-SEVR-based models. Compared with a rule-based baseline system for discontinuation detection, our system improved the sensitivity significantly (57.75% vs 18.31%, absolute value) while retaining a high specificity of 99.25%, leading to a significant improvement in AUC-ROC by 32.83% (absolute value). CONCLUSION: Experiments have shown that a high-performance NLP system can be developed to automatically identify DDCs and their reasons from providers\u27 notes. The SEVR model effectively improved the system performance showing better generalization and robustness on unseen test data. Our work is an important step toward identifying reasons for drug discontinuation that will inform drug safety surveillance and pharmacovigilance

Structure of Blood Coagulation Factor VIII in Complex with Anti-C2 Domain Inhibitory Antibody

Factor VIII (fVIII) is a procoagulant protein that binds to activated factor IX (fIXa) on platelet surfaces to form the intrinsic tenase complex. Due to the high immunogenicity of fVIII, generation of antibody inhibitors is a common occurrence in patients during hemophilia A treatment and spontaneously occurs in acquired hemophilia A patients. Non-classical antibody inhibitors, which block fVIII activation by thrombin and formation of the tenase complex, are the most common anti-C2 domain pathogenic inhibitors in hemophilia A murine models and have been identified in patient plasmas. In this study, we report on the X-ray crystal structure of a B domain-deleted bioengineered fVIII bound to the non classical antibody inhibitor, G99. While binding to G99 does not disrupt the overall domain architecture of fVIII, the C2 domain undergoes an ~8 Å translocation that is concomitant with breaking multiple domain-domain interactions. Analysis of normalized B-factor values revealed several solvent-exposed loops in the C1 and C2 domains which experience a decrease in thermal motion in the presence of inhibitory antibodies. Our results enhance our understanding on the structural nature of binding non-classical inhibitors and provide a structural dynamics-based rationale for cooperativity between anti-C domain inhibitors

Structure of Blood Coagulation Factor VIII in Complex With an Anti-C2 Domain Non-Classical, Pathogenic Antibody Inhibitor

Factor VIII (fVIII) is a procoagulant protein that binds to activated factor IX (fIXa) on platelet surfaces to form the intrinsic tenase complex. Due to the high immunogenicity of fVIII, generation of antibody inhibitors is a common occurrence in patients during hemophilia A treatment and spontaneously occurs in acquired hemophilia A patients. Non-classical antibody inhibitors, which block fVIII activation by thrombin and formation of the tenase complex, are the most common anti-C2 domain pathogenic inhibitors in hemophilia A murine models and have been identified in patient plasmas. In this study, we report on the X-ray crystal structure of a B domain-deleted bioengineered fVIII bound to the non-classical antibody inhibitor, G99. While binding to G99 does not disrupt the overall domain architecture of fVIII, the C2 domain undergoes an ~8 Å translocation that is concomitant with breaking multiple domain-domain interactions. Analysis of normalized B-factor values revealed several solvent-exposed loops in the C1 and C2 domains which experience a decrease in thermal motion in the presence of inhibitory antibodies. These results enhance our understanding on the structural nature of binding non-classical inhibitors and provide a structural dynamics-based rationale for cooperativity between anti-C1 and anti-C2 domain inhibitors