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Optimizing adjuvant treatment options for patients with glioblastoma
4
Zitationen
7
Autoren
2024
Jahr
Abstract
Background: This study focused on minimizing the costs and toxic effects associated with unnecessary chemotherapy. We sought to optimize the adjuvant therapy strategy, choosing between radiotherapy (RT) and chemoradiotherapy (CRT), for patients based on their specific characteristics. This selection process utilized an innovative deep learning method. Methods: ), the difference in restricted mean survival time (dRMST), and the number needed to treat (NNT). Results: = 0.06). Males, older patients, and those whose tumor invasion is confined to the ventricular system were more frequently advised to undergo RT. Conclusion: Our study suggests that BITES can effectively identify GBM patients likely to benefit from CRT. These ML models show promise in transforming the complex heterogeneity of real-world clinical practice into precise, personalized treatment recommendations.
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