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Virtual clinical trial based on outcome modeling with iteratively redistributed extrapolation data

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Abstract

Virtual clinical trials (VCTs) can potentially simulate clinical trials on a computer, but their application with a limited number of past clinical cases is challenging due to the biased estimation of the statistical population. In this study, we developed ExMixup, a novel training technique based on machine learning, using iteratively redistributed extrapolated data. Information obtained from 100 patients with prostate cancer and 385 patients with oropharyngeal cancer was used to predict the recurrence after radiotherapy. Model performance was evaluated by developing outcome prediction models based on three types of training methods: training with original data (baseline), interpolation data (Mixup), and interpolation + extrapolation data (ExMixup). Two types of VCTs were conducted to predict the treatment response of patients with distinct characteristics compared to the training data obtained from patient cohorts categorized under risk classification or cancer stage. The prediction models developed with ExMixup yielded concordance indices (95% confidence intervals) of 0.751 (0.719–0.818) and 0.752 (0.734–0.785) for VCTs on the prostate and oropharyngeal cancer datasets, respectively, which significantly outperformed the baseline and Mixup models (P < 0.01). The proposed approach could enhance the ability of VCTs to predict treatment results in patients excluded from past clinical trials.

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Funding

This work was supported by JSPS KAKENHI (Grant Number 18K15604).

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Authors and Affiliations

  1. Graduate Division of Health Sciences, Komazawa University, 1-23-1, Komazawa, Setagaya-Ku, Tokyo, 154-8525, Japan

    Kohei Oguma & Taiki Magome

  2. Department of Radiology, Sapporo Medical University School of Medicine, Sapporo, Japan

    Masanori Someya, Tomokazu Hasegawa & Koh-ichi Sakata

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  1. Kohei Oguma
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  2. Taiki Magome
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  3. Masanori Someya
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  4. Tomokazu Hasegawa
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Correspondence to Taiki Magome.

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This retrospective study was approved by the Institutional Review Board of Komazawa University (No. 18–7).

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Oguma, K., Magome, T., Someya, M. et al. Virtual clinical trial based on outcome modeling with iteratively redistributed extrapolation data. Radiol Phys Technol 16, 262–271 (2023). https://doi.org/10.1007/s12194-023-00715-4

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  • DOI: https://doi.org/10.1007/s12194-023-00715-4

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