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. 2020 Sep 4;10:1268. doi: 10.3389/fonc.2020.01268

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Copyright © 2020 Liu, Liu, Zhang, Yu, Liu, Hu, Xu, Tang and Fu.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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DCA for the radiomics nomogram. The y-axis shows the net benefit. The red line represents the radiomics nomogram. The blue line indicates the hypothesis that all patients had small cell lung cancer. The black line represents the hypothesis that no patients had small cell lung cancer. The x-axis shows the threshold probability, which is where the expected benefit of treatment is equal to the expected benefit of not undergoing treatment. The decision curves indicate that when the threshold probability is between 0.1 and 1, using the radiomics nomogram to predict small cell lung cancer adds more benefit than treating either all or no patients.