A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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-tekijät tai -toimittajat

Julkaisun tiedot

Julkaisun kaikki tekijät tai toimittajat: Karppinen, Santeri; Lohi, Olli; Vihola, Matti

Lehti tai sarja: Scientific Reports

eISSN: 2045-2322

Julkaisuvuosi: 2019

Volyymi: 9

Artikkelinumero: 18076

Kustantaja: Nature Publishing Group

Julkaisumaa: Britannia

Julkaisun kieli: englanti

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

Julkaisun avoin saatavuus: Avoimesti saatavilla

Julkaisukanavan avoin saatavuus: Kokonaan avoin julkaisukanava

Julkaisu on rinnakkaistallennettu (JYX): https://jyx.jyu.fi/handle/123456789/66732

Tiivistelmä

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.

YSO-asiasanat: syöpätaudit; akuutti lymfaattinen leukemia; lääkehoito; biomarkkerit; valkosolut; ennusteet; tilastolliset mallit; bayesilainen menetelmä; stokastiset prosessit; aikasarjat

Liittyvät organisaatiot

Hankkeet, joissa julkaisu on tehty

OKM-raportointi: Kyllä

Raportointivuosi: 2019

JUFO-taso: 1