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Home/ All Articles/ The i2b2 Temporal Data-Mining Solution for Automated Reconstruction of Different Breast C…

Abstract & Article Details

Research Article • Vol.5, Issue 6 • ISSN: 2766-2276 • Open Access • CC BY 4.0

Open Access Research Article Vol.5, Issue 6 June 21, 2024

The i2b2 Temporal Data-Mining Solution for Automated Reconstruction of Different Breast Cancer Patterns of Care over a Decade of Observation

DOI: 10.37871/jbres1935
Authors
Alberto Zambelli, Flavia Jacobs*, Arianna Ghirardi, Lorenzo Chiudinelli, Mauro Bucalo, Nicola Barbarini, Sara Du2019Alessandro3, Arianna Masciulli, Vittoria Fotia, Riccardo Bellazzi and Carlo Tondini

Abstract

Background: In oncology, Patterns of Care (PoC) provide a detailed overview of all cancer-treatment interventions and recapitulate the entire patient’s journey. While manual-chart PoC reviewing is time-consuming, the use of Electronic Health Records (EHRs) enables the creation of data-mining solutions to automatically reconstruct the whole cancer trajectory with different granularity.

Methods: We tested the ability of the i2b2 (Informatics for Integrating Biology and Bedside) solution to support the automatic reconstruction of the PoC for consecutive and unselected HER2+ and TNBC breast cancer patients through a retrospective EHRs analysis over a decade of observations.

Results: From 2008 to 2017, 561 HER2+ and 412 TNBC patients were retrospectively identified by i2b2 platform at the Papa Giovanni XXIII Hospital in Bergamo. Most patients, 74.3% in the HER2 group and 71.8% in the TNBC group, received a (neo) adjuvant chemotherapy, with anti-HER2 drugs whenever indicated. Among the HER2 cohort, the 5-year Time to Treatment Change (TTC) and Overall Survival (OS) were 69.4% and 77.4% respectively, with 25% of patients receiving up to 3 lines of treatment in metastatic setting. Among the TNBC cohort, the 5-year TTC and OS were 59.3% and 69.4% respectively, with only 2% of patients receiving active treatment as third line of therapy. The consistency of the automated PoC reconstruction had to be reviewed in 1/3 of cases to clean conflicting data.

Conclusion: The i2b2 solution has the potential to provide a retrospective, automated reconstruction of the different PoC, with limited manual-chart review refinement and might contribute to support investigations in the field of real-world data.

Research Topics

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How to Cite

Alberto Zambelli, Flavia Jacobs*, Arianna Ghirardi, Lorenzo Chiudinelli, Mauro Bucalo, Nicola Barbarini, Sara Du2019Alessandro3, Arianna Masciulli, Vittoria Fotia, Riccardo Bellazzi and Carlo Tondini (2024). The i2b2 Temporal Data-Mining Solution for Automated Reconstruction of Different Breast Cancer Patterns of Care over a Decade of Observation. Journal of Biomedical Research & Environmental Sciences, 5(6). https://doi.org/10.37871/jbres1935

Article Information

JournalJournal of Biomedical Research & Environmental Sciences (JBRES)
ISSN2766-2276
DOI DOI 10.37871/jbres1935
Volume / IssueVol. 5, Issue 6
ReceivedJune 14, 2024
AcceptedJune 21, 2024
PublishedJune 21, 2024
Article TypeResearch Article
Pages630-639
LicenseCC BY 4.0 — Open Access
PublisherSciRes Literature LLC, Sheridan, WY, USA
LanguageEnglish
Creative Commons BY 4.0

Published under CC BY 4.0 — free to share, copy, adapt, and redistribute with attribution.

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