Improved risk prediction of chemotherapy-induced neutropenia-model development and validation with real-world data.
Mikko S VenäläinenEetu HeerväOuti HirvonenSohrab SaraeiTomi SuomiToni MikkolaMaarit BärlundSirkku JyrkkiöTarja LaitinenLaura L EloPublished in: Cancer medicine (2021)
Our study demonstrates that real-world NI risk prediction can be improved with machine learning and that every difference in patient or treatment characteristics can have a significant impact on model performance. Here we outline a novel, externally validated approach which may hold potential to facilitate more targeted use of G-CSFs in the future.