Clinical decision support for chemotherapy-induced neutropenia using a hybrid pharmacodynamic/machine learning model.

ABSTRACT: Consensus guidelines recommend use of granulocyte colony stimulating factor in patients deemed at risk of chemotherapy-induced neutropenia, however, these risk models are limited in the factors they consider and miss some cases of neutropenia. Clinical decision making could be supported using models that better tailor their predictions to the individual patient using the wealth of data available in electronic health records (EHRs). Here, we present a hybrid pharmacokinetic/pharmacodynamic (PKPD)/machine learning (ML) approach that uses predictions and individual Bayesian parameter estimates from a PKPD model to enrich an ML model built on her data. We demonstrate this approach using models developed on a large real-world data set of 9121 patients treated for lymphoma, breast, or thoracic c

SUBMITTER: Hughes JH 

PROVIDER: S-EPMC10681461 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature