Use of Patient Health Records to Quantify Drug-Related Pro-arrhythmic Risk.
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アブストラクト There is an increasing expectation that computational approaches may supplement existing human decision-making. Frontloading of models for cardiac safety prediction is no exception to this trend, and ongoing regulatory initiatives propose use of high-throughput in vitro data combined with computational models for calculating proarrhythmic risk. Evaluation of these models requires robust assessment of the outcomes. Using FDA Adverse Event Reporting System reports and electronic healthcare claims data from the Truven-MarketScan US claims database, we quantify the incidence rate of arrhythmia in patients and how this changes depending on patient characteristics. First, we propose that such datasets are a complementary resource for determining relative drug risk and assessing the performance of cardiac safety models for regulatory use. Second, the results suggest important determinants for appropriate stratification of patients and evaluation of additional drug risk in prescribing and clinical support algorithms and for precision health. ジャーナル名 Cell reports. Medicine 投稿日 2020/11/19 投稿者 Davies, Mark R; Martinec, Michael; Walls, Robert; Schwarz, Roman; Mirams, Gary R; Wang, Ken; Steiner, Guido; Surinach, Andy; Flores, Carlos; Lave, Thierry; Singer, Thomas; Polonchuk, Liudmila 組織名 QT-Informatics Ltd., Macclesfield, UK.;PHC Data Science, Personalized Healthcare, Product Development, F. Hoffmann-La;Roche AG, Basel, Switzerland.;Safety Analytics and Reporting, Drug Safety, Pharmaceutical Development, F.;Hoffmann-La Roche AG, Basel, Switzerland.;Centre for Mathematical Medicine & Biology, School of Mathematical Sciences,;University of Nottingham, Nottingham NG7 2RD, UK.;Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences,;Roche Innovation Center Basel, F. Hoffmann-La Roche AG, Basel, Switzerland.;Genesis Research, Hoboken, NJ, USA. Pubmed リンク https://www.ncbi.nlm.nih.gov/pubmed/33205069/ -
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