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Screening of anticancer drugs to detect drug‐induced interstitial pneumonia using the accumulated data in the electronic medical record

Because drug‐induced interstitial pneumonia (DIP) is a serious adverse drug reaction, its quantitative risk with individual medications should be taken into due consideration when selecting a medicine. We developed an algorithm to detect DIP using medical record data accumulated in a hospital. Chest...

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Autores principales: Shimai, Yoshie, Takeda, Toshihiro, Okada, Katsuki, Manabe, Shirou, Teramoto, Kei, Mihara, Naoki, Matsumura, Yasushi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6043691/
https://www.ncbi.nlm.nih.gov/pubmed/30009034
http://dx.doi.org/10.1002/prp2.421
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author Shimai, Yoshie
Takeda, Toshihiro
Okada, Katsuki
Manabe, Shirou
Teramoto, Kei
Mihara, Naoki
Matsumura, Yasushi
author_facet Shimai, Yoshie
Takeda, Toshihiro
Okada, Katsuki
Manabe, Shirou
Teramoto, Kei
Mihara, Naoki
Matsumura, Yasushi
author_sort Shimai, Yoshie
collection PubMed
description Because drug‐induced interstitial pneumonia (DIP) is a serious adverse drug reaction, its quantitative risk with individual medications should be taken into due consideration when selecting a medicine. We developed an algorithm to detect DIP using medical record data accumulated in a hospital. Chest computed tomography (CT) is mainly used for the diagnosis of IP, and chest X‐ray reports, KL‐6, and SP‐D values are used to support the diagnosis. The presence of IP in the reports was assessed by a method using natural language‐processing, in which IP was estimated according to the product of the likelihood ratio of characteristic keywords in each report. The sensitivity and the specificity of the method for chest CT reports were 0.92 and 0.97, while those for chest X‐ray reports were 0.83 and 1, respectively. The occurrence of DIP was estimated by the patterns of presence of IP before, during, and after the administration of the target medicine. The occurrence rate of DIP in cases administered Gefitinib; Methotrexate (MTX); Tegafur, Gimeracil, and Oteracil potassium (TS‐1); and Tegafur and Uracil (UTF) was 6.0%, 2.3%, 1.4%, and 0.7%, respectively. The estimated DIP cases were checked by having the medical records independently reviewed by medical doctors. By chart review, the positive predictive values of DIP against Gefitinib, MTX, TS‐1, and UFT were 69.2%, 44.4%, 58.6%, and 77.8%, respectively. Although the cases extracted by this method included some that did not have DIP, this method can estimate the relative risk of DIP between medicines.
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spelling pubmed-60436912018-07-15 Screening of anticancer drugs to detect drug‐induced interstitial pneumonia using the accumulated data in the electronic medical record Shimai, Yoshie Takeda, Toshihiro Okada, Katsuki Manabe, Shirou Teramoto, Kei Mihara, Naoki Matsumura, Yasushi Pharmacol Res Perspect Original Articles Because drug‐induced interstitial pneumonia (DIP) is a serious adverse drug reaction, its quantitative risk with individual medications should be taken into due consideration when selecting a medicine. We developed an algorithm to detect DIP using medical record data accumulated in a hospital. Chest computed tomography (CT) is mainly used for the diagnosis of IP, and chest X‐ray reports, KL‐6, and SP‐D values are used to support the diagnosis. The presence of IP in the reports was assessed by a method using natural language‐processing, in which IP was estimated according to the product of the likelihood ratio of characteristic keywords in each report. The sensitivity and the specificity of the method for chest CT reports were 0.92 and 0.97, while those for chest X‐ray reports were 0.83 and 1, respectively. The occurrence of DIP was estimated by the patterns of presence of IP before, during, and after the administration of the target medicine. The occurrence rate of DIP in cases administered Gefitinib; Methotrexate (MTX); Tegafur, Gimeracil, and Oteracil potassium (TS‐1); and Tegafur and Uracil (UTF) was 6.0%, 2.3%, 1.4%, and 0.7%, respectively. The estimated DIP cases were checked by having the medical records independently reviewed by medical doctors. By chart review, the positive predictive values of DIP against Gefitinib, MTX, TS‐1, and UFT were 69.2%, 44.4%, 58.6%, and 77.8%, respectively. Although the cases extracted by this method included some that did not have DIP, this method can estimate the relative risk of DIP between medicines. John Wiley and Sons Inc. 2018-07-12 /pmc/articles/PMC6043691/ /pubmed/30009034 http://dx.doi.org/10.1002/prp2.421 Text en © 2018 The Authors. Pharmacology Research & Perspectives published by John Wiley & Sons Ltd, British Pharmacological Society and American Society for Pharmacology and Experimental Therapeutics. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Shimai, Yoshie
Takeda, Toshihiro
Okada, Katsuki
Manabe, Shirou
Teramoto, Kei
Mihara, Naoki
Matsumura, Yasushi
Screening of anticancer drugs to detect drug‐induced interstitial pneumonia using the accumulated data in the electronic medical record
title Screening of anticancer drugs to detect drug‐induced interstitial pneumonia using the accumulated data in the electronic medical record
title_full Screening of anticancer drugs to detect drug‐induced interstitial pneumonia using the accumulated data in the electronic medical record
title_fullStr Screening of anticancer drugs to detect drug‐induced interstitial pneumonia using the accumulated data in the electronic medical record
title_full_unstemmed Screening of anticancer drugs to detect drug‐induced interstitial pneumonia using the accumulated data in the electronic medical record
title_short Screening of anticancer drugs to detect drug‐induced interstitial pneumonia using the accumulated data in the electronic medical record
title_sort screening of anticancer drugs to detect drug‐induced interstitial pneumonia using the accumulated data in the electronic medical record
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6043691/
https://www.ncbi.nlm.nih.gov/pubmed/30009034
http://dx.doi.org/10.1002/prp2.421
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