ArticleCancer chemotherapy and pharmacology2017
Model-based prediction of myelosuppression and recovery based on frequent neutrophil monitoring.
Article in Cancer chemotherapy and pharmacology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.
- Can posttreatment blood inflammatory markers predict poor survival in gynecologic cancer?: a systematic review and meta-analysis.Frontiers in immunology · 2025Pooled it
- Model-informed precision dosing of carboplatin in cancer patients by leveraging myelosuppression data from electronic health records.British journal of clinical pharmacology · 2026Article
- Semi-Mechanistic PK/PD Modeling of Platelets and Spleen Volume With Navitoclax in Combination With Ruxolitinib in Patients With Myelofibrosis.CPT: pharmacometrics & systems pharmacology · 2026Article
- Clinical decision support for chemotherapy-induced neutropenia using a hybrid pharmacodynamic/machine learning model.CPT: pharmacometrics & systems pharmacology · 2023Article
- Generation and application of avatars in pharmacometric modelling.Journal of pharmacokinetics and pharmacodynamics · 2023Article
- Article
- Pediatric oncology drug development and dosage optimization.Frontiers in oncology · 2023Review
- Should personalised dosing have a role in cancer treatment?Frontiers in oncology · 2023Article
- Splenic irradiation contributes to grade ≥ 3 lymphopenia after adjuvant chemoradiation for stomach cancer.Clinical and translational radiation oncology · 2022Article
- A continued learning approach for model-informed precision dosing: Updating models in clinical practice.CPT: pharmacometrics & systems pharmacology · 2022Article
- Reinforcement learning and Bayesian data assimilation for model-informed precision dosing in oncology.CPT: pharmacometrics & systems pharmacology · 2021Article
- Machine Learning Approach to Forecast Chemotherapy-Induced Haematological Toxicities in Patients with Rhabdomyosarcoma.Cancers · 2020Article
- Prediction of exposure-driven myelotoxicity of continuous infusion 5-fluorouracil by a semi-physiological pharmacokinetic-pharmacodynamic model in gastrointestinal cancer patients.Cancer chemotherapy and pharmacology · 2020Article
- Bayesian Data Assimilation to Support Informed Decision Making in Individualized Chemotherapy.CPT: pharmacometrics & systems pharmacology · 2020Article
- Mathematical models for cytarabine-derived myelosuppression in acute myeloid leukaemia.PloS one · 2019Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo investigate whether a more frequent monitoring of the absolute neutrophil counts (ANC) during myelosuppressive chemotherapy, together with model-based predictions, can improve therapy management, compared to the limited clinical monitoring typically applied today.
methodsDaily ANC in chemotherapy-treated cancer patients were simulated from a previously published population model describing docetaxel-induced myelosuppression. The simulated values were used to generate predictions of the individual ANC time-courses, given the myelosuppression model. The accuracy of the predicted ANC was evaluated under a range of conditions with reduced amount of ANC measurements.
resultsThe predictions were most accurate when more data were available for generating the predictions and when making short forecasts. The inaccuracy of ANC predictions was highest around nadir, although a high sensitivity (≥90%) was demonstrated to forecast Grade 4 neutropenia before it occurred. The time for a patient to recover to baseline could be well forecasted 6 days (±1 day) before the typical value occurred on day 17.
conclusionsDaily monitoring of the ANC, together with model-based predictions, could improve anticancer drug treatment by identifying patients at risk for severe neutropenia and predicting when the next cycle could be initiated.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.