CT radiomics compared to a clinical model for predicting checkpoint inhibitor treatment outcomes in patients with advanced melanoma.
European journal of cancer (Oxford, England : 1990)(2023)
Abstract
The radiomics model achieved a moderate predictive value of clinical benefit, which was statistically significant. However, a radiomics approach was unable to add value to a simpler clinical model, most likely due to the overlap in predictive information learned by both models. Future research should focus on the application of deep learning, spectral CT-derived radiomics, and a multimodal approach for accurately predicting benefit to checkpoint inhibitor treatment in advanced melanoma.
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Key words
Checkpoint inhibition,Computed tomography,Machine learning,Metastatic melanoma,Radiomics,Response prediction
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