Development and validation of claims-based algorithms to identify interstitial lung disease among Japanese patients with cancer in routine clinical practice using real-world data sources - Takeaways - MDSpire
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Creation and assessment of claims-based algorithms for detecting interstitial lung disease in Japanese cancer patients utilizing real-world data in standard clinical settings

  • By

  • Yu-Jing Huang

  • Toshihiro Takeda

  • Yoshie Shimai

  • Taizo Murata

  • Kento Sugimoto

  • Yoshito Takeda

  • Haruhiko Hirata

  • Makoto Yamamoto

  • Midori Yoneda

  • Seigo Minami

  • Masahiro Higashi

  • Alan James Michael Brnabic

  • Zbigniew Kadziola

  • Tsutomu Kawaguchi

  • Yucherng Chen

  • Yasushi Matsumura

  • September 9, 2026

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  • 1

    A claims-based algorithm was developed to identify interstitial lung disease (ILD) in Japanese cancer patients using machine-learning modeling.

  • 2

    The study analyzed data from 13,601 patients, with 415 classified as ILD cases through natural language processing of CT reports.

  • 3

    The LASSO reduced model achieved a sensitivity of 33.5% and specificity of 99.3%, indicating its performance in identifying true-positive ILD cases.

  • 4

    External validation of the algorithm showed a sensitivity of 19.8% and specificity of 99.4%, demonstrating its applicability in different datasets.

  • 5

    The algorithm may assist in case confirmation for retrospective studies evaluating ILD risk associated with various cancer treatments.

Original Source(s)

Development and validation of claims-based algorithms to identify interstitial lung disease among Japanese patients with cancer in routine clinical practice using real-world data sources

  • by Yu-Jing Huang, Toshihiro Takeda, Yoshie Shimai, Taizo Murata, Kento Sugimoto, Yoshito Takeda, Haruhiko Hirata, Makoto Yamamoto, Midori Yoneda, Seigo Minami, Masahiro Higashi, Alan James Michael Brnabic, Zbigniew Kadziola, Tsutomu Kawaguchi, Yucherng Chen, Yasushi Matsumura

  • September 9, 2026

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