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

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...

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Bibliographic Details
Published in:Radiological physics and technology 2023-06, Vol.16 (2), p.262-271
Main Authors: Oguma, Kohei, Magome, Taiki, Someya, Masanori, Hasegawa, Tomokazu, Sakata, Koh-ichi
Format: Article
Language:English
Subjects:
Cancer
Clinical trials
Confidence intervals
Extrapolation
Humans
Imaging
Interpolation
Machine learning
Male
Medical and Radiation Physics
Medicine
Medicine & Public Health
Neoplasm Staging
Nuclear Medicine
Oropharyngeal Neoplasms
Prediction models
Prostate
Prostatic Neoplasms - radiotherapy
Radiation therapy
Radiology
Radiotherapy
Research Article
Statistical analysis
Training
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Summary: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  
ISSN:1865-0333
1865-0341
DOI:10.1007/s12194-023-00715-4