Abstract
Febrile neutropenia (FN) is one of the most concerning complications of chemotherapy, and its prediction remains difficult. This study aimed to reveal the risk factors for and build the prediction models of FN using machine learning algorithms. Medical records of hospitalized patients who underwent chemotherapy after surgery for breast cancer between May 2002 and September 2018 were selectively reviewed for development of models. Demographic, clinical, pathological, and therapeutic data were analyzed to identify risk factors for FN. Using machine learning algorithms, prediction models were developed and evaluated for performance. Of 933 selected inpatients with a mean age of 51.8 ± 10.7 years, FN developed in 409 (43.8%) patients. There was a significant difference in FN incidence according to age, staging, taxane-based regimen, and blood count 5 days after chemotherapy. The area under the curve (AUC) built based on these findings was 0.870 on the basis of logistic regression. The AUC improved by machine learning was 0.908. Machine learning improves the prediction of FN in patients undergoing chemotherapy for breast cancer compared to the conventional statistical model. In these high-risk patients, primary prophylaxis with granulocyte colony-stimulating factor could be considered.
Highlights
Febrile neutropenia (FN) is one of the most concerning complications of chemotherapy, and its prediction remains difficult
Chemotherapy-induced FN commonly occurs during the initial cycle of cytotoxic therapy and increases in frequency with both duration and depth of the neutropenia[3]
A important field of uncertainty that is emphasized by these findings is the absence of risk prediction models that estimate the risk of FN in patients reliably[8]
Summary
Febrile neutropenia (FN) is one of the most concerning complications of chemotherapy, and its prediction remains difficult. Machine learning improves the prediction of FN in patients undergoing chemotherapy for breast cancer compared to the conventional statistical model. In these high-risk patients, primary prophylaxis with granulocyte colony-stimulating factor could be considered. Chemotherapy-induced neutropenia is a principal risk factor for infection-related m orbidity[4]. Trials to prevent FN events during chemotherapy administration require an evaluation of risk factors related with the development of critical n eutropenia[12]. This evaluation remains inaccurate[3]. A important field of uncertainty that is emphasized by these findings is the absence of risk prediction models that estimate the risk of FN in patients reliably[8]
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