ArticleScientific reports2019
Prediction of leukocyte counts during paediatric acute lymphoblastic leukaemia maintenance therapy.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 5 citations in OpenAlex.
- Model-Based Simulation of Maintenance Therapy of Childhood Acute Lymphoblastic Leukemia.Frontiers in physiology · 2020Article
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Authors and funding
3 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
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.
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