Phenotyping and visualizing infusion-related reactions for breast cancer patients

Deyu Sun; Gopal Sarda; Steven J. Skube; Anne H Blaes; Saif Khairat; Genevieve B Melton-Meaux; Rui Zhang

doi:10.3233/978-1-61499-830-3-599

Phenotyping and visualizing infusion-related reactions for breast cancer patients

Deyu Sun, Gopal Sarda, Steven J. Skube, Anne H Blaes, Saif Khairat, Genevieve B Melton-Meaux, Rui Zhang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Infusion-related reactions (IRRs) are typical adverse events for breast cancer patients. Detecting IRRs and visualizing their occurance associated with the drug treatment would potentially assist clinicians to improve patient safety and help researchers model IRRs and analyze their risk factors. We developed and evaluated a phenotyping algorithm to detect IRRs for breast cancer patients. We also designed a visualization prototype to render IRR patients' medications, lab tests and vital signs over time. By comparing with the 42 randomly selected doses that are manually labeled by a domain expert, the sensitivity, positive predictive value, specificity, and negative predictive value of the algorithms are 69%, 60%, 79%, and 85%, respectively. Using the algorithm, an incidence of 6.4% of patients and 1.8% of doses for docetaxel, 8.7% and 3.2% for doxorubicin, 10.4% and 1.2% for paclitaxel, 16.1% and 1.1% for trastuzumab were identified retrospectively. The incidences estimated are consistent with related studies.

Original language	English (US)
Title of host publication	MEDINFO 2017
Subtitle of host publication	Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics
Editors	Zhao Dongsheng, Adi V. Gundlapalli, Jaulent Marie-Christine
Publisher	IOS Press
Pages	599-603
Number of pages	5
ISBN (Electronic)	9781614998297
DOIs	https://doi.org/10.3233/978-1-61499-830-3-599
State	Published - 2017
Event	16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017 - Hangzhou, China Duration: Aug 21 2017 → Aug 25 2017

Publication series

Name	Studies in Health Technology and Informatics
Volume	245
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Other

Other	16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017
Country/Territory	China
City	Hangzhou
Period	8/21/17 → 8/25/17

Bibliographical note

Publisher Copyright:
© 2017 International Medical Informatics Association (IMIA) and IOS Press.

Keywords

Algorithms
Patient safety
Phenotype

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Publisher link

10.3233/978-1-61499-830-3-599

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Cite this

Sun, D., Sarda, G., Skube, S. J., Blaes, A. H., Khairat, S., Melton-Meaux, G. B., & Zhang, R. (2017). Phenotyping and visualizing infusion-related reactions for breast cancer patients. In Z. Dongsheng, A. V. Gundlapalli, & J. Marie-Christine (Eds.), MEDINFO 2017: Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics (pp. 599-603). (Studies in Health Technology and Informatics; Vol. 245). IOS Press. https://doi.org/10.3233/978-1-61499-830-3-599

Phenotyping and visualizing infusion-related reactions for breast cancer patients. / Sun, Deyu; Sarda, Gopal; Skube, Steven J. et al.
MEDINFO 2017: Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics. ed. / Zhao Dongsheng; Adi V. Gundlapalli; Jaulent Marie-Christine. IOS Press, 2017. p. 599-603 (Studies in Health Technology and Informatics; Vol. 245).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Sun, D, Sarda, G, Skube, SJ, Blaes, AH, Khairat, S, Melton-Meaux, GB & Zhang, R 2017, Phenotyping and visualizing infusion-related reactions for breast cancer patients. in Z Dongsheng, AV Gundlapalli & J Marie-Christine (eds), MEDINFO 2017: Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics. Studies in Health Technology and Informatics, vol. 245, IOS Press, pp. 599-603, 16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017, Hangzhou, China, 8/21/17. https://doi.org/10.3233/978-1-61499-830-3-599

Sun D, Sarda G, Skube SJ, Blaes AH, Khairat S, Melton-Meaux GB et al. Phenotyping and visualizing infusion-related reactions for breast cancer patients. In Dongsheng Z, Gundlapalli AV, Marie-Christine J, editors, MEDINFO 2017: Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics. IOS Press. 2017. p. 599-603. (Studies in Health Technology and Informatics). doi: 10.3233/978-1-61499-830-3-599

Sun, Deyu ; Sarda, Gopal ; Skube, Steven J. et al. / Phenotyping and visualizing infusion-related reactions for breast cancer patients. MEDINFO 2017: Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics. editor / Zhao Dongsheng ; Adi V. Gundlapalli ; Jaulent Marie-Christine. IOS Press, 2017. pp. 599-603 (Studies in Health Technology and Informatics).

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AB - Infusion-related reactions (IRRs) are typical adverse events for breast cancer patients. Detecting IRRs and visualizing their occurance associated with the drug treatment would potentially assist clinicians to improve patient safety and help researchers model IRRs and analyze their risk factors. We developed and evaluated a phenotyping algorithm to detect IRRs for breast cancer patients. We also designed a visualization prototype to render IRR patients' medications, lab tests and vital signs over time. By comparing with the 42 randomly selected doses that are manually labeled by a domain expert, the sensitivity, positive predictive value, specificity, and negative predictive value of the algorithms are 69%, 60%, 79%, and 85%, respectively. Using the algorithm, an incidence of 6.4% of patients and 1.8% of doses for docetaxel, 8.7% and 3.2% for doxorubicin, 10.4% and 1.2% for paclitaxel, 16.1% and 1.1% for trastuzumab were identified retrospectively. The incidences estimated are consistent with related studies.

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Phenotyping and visualizing infusion-related reactions for breast cancer patients

Abstract

Publication series

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Bibliographical note

Keywords

UN SDGs

Publisher link

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