A1 Journal article (refereed)
Prediction of leukocyte counts during paediatric acute lymphoblastic leukaemia maintenance therapy (2019)

Karppinen, S., Lohi, O., & Vihola, M. (2019). Prediction of leukocyte counts during paediatric acute lymphoblastic leukaemia maintenance therapy. Scientific Reports, 9, Article 18076. https://doi.org/10.1038/s41598-019-54492-5

JYU authors or editors

Publication details

All authors or editors: Karppinen, Santeri; Lohi, Olli; Vihola, Matti

Journal or series: Scientific Reports

eISSN: 2045-2322

Publication year: 2019

Volume: 9

Article number: 18076

Publisher: Nature Publishing Group

Publication country: United Kingdom

Publication language: English

DOI: https://doi.org/10.1038/s41598-019-54492-5

Publication open access: Openly available

Publication channel open access: Open Access channel

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/66732


Maintenance chemotherapy with oral 6-mercaptopurine and methotrexate remains a cornerstone of modern therapy for acute lymphoblastic leukaemia. The dosage and intensity of therapy are based on surrogate markers such as peripheral blood leukocyte and neutrophil counts. Dosage based leukocyte count predictions could provide support for dosage decisions clinicians face trying to find and maintain an appropriate dosage for the individual patient. We present two Bayesian nonlinear state space models for predicting patient leukocyte counts during the maintenance therapy. The models simplify some aspects of previously proposed models but allow for some extra flexibility. Our second model is an extension which accounts for extra variation in the leukocyte count due to a treatment adversity, infections, using C-reactive protein as a surrogate. The predictive performances of our models are compared against a model from the literature using time series cross-validation with patient data. In our experiments, our simplified models appear more robust and deliver competitive results with the model from the literature.

Keywords: cancerous diseases; acute lymphocytic leukemia; pharmacotherapy; markers; white blood cells; forecasts; statistical models; Bayesian analysis; stochastic processes; time series

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Ministry reporting: Yes

Reporting Year: 2019

JUFO rating: 1

Last updated on 2021-09-06 at 20:45