Physiologically-Based Mathematical Modelling of Neutrophil Dynamics during Concurrent Chemotherapy and Filgrastim Support
Notice bibliographique
Résumé
Abstract A common and dose-limiting side effect of chemotherapy is the development of neutropenia (a reduction in neutrophil numbers). To avoid or mitigate drops in absolute neutrophil counts (ANCs), patients are typically given recombinant human granulocyte colony-stimulating factor (rhG-CSF/filgrastim) to minimise the myelosuppressive nature of anti-cancer treatments. Dosing recommendations for filgrastim after chemotherapy suggest treatment begin one day post-chemotherapy and continue for a given amount of time or until ANCs rise sufficiently. Indeed, filgrastim support in a given chemotherapy cycle can sometimes reach seven to ten days in a 14-day period. Due to the intricacy of neutrophil production from the hematopoeitic stem cells in addition to the complexity of the interactions of cytokines and their receptors, a complete understanding of the mechanisms underlying myelopoiesis remains elusive. Mathematical modelling of these processes is a method which provides a global view of the dynamics of blood cell production and helps to elucidate the implications of concurrent chemotherapy and rhG-CSF support upon the blood production system. Moreover, the mathematical treatment of myelopoiesis can suggest novel dosing regimens that may be more beneficial than current schedules by supporting currently-held hypotheses and/or revealing previously unstudied relationships and dynamics. In this study, we construct a physiologically-based model of myelopoiesis which incorporates an up-to-date understanding of the production of neutrophils with our group's previously published model of blood cell dynamics. This model is combined with pharmacokinetic and pharmcodynamic (PKPD) models of Zalypsis (PM00104), an anti-cancer drug currently in phase II clinical trials, and filgrastim, a myelostimulant. The physiological model of myelopoiesis directly relates observable delays in neutrophil production to temporal lags in the model through the use of delay differential equations. All parameters are comprehensively defined for an average patient by utilising previously published physiological and PKPD studies. The model is numerically implemented and simulated to compare its predictions to ANC time series of patients undergoing the CHOP14 protocol. Able to recreate previously published data, we then investigated the optimal timing of filgrastim administrations post-chemotherapy during 14-day periodic chemotherapy and examined the number of filgrastim administrations necessary to ward off neutropenia using this optimised timing. Our results indicate that delaying rhG-CSF administrations by six or seven days after the administration of chemotherapy lessens the myelosuppressive impact of anti-cancer treatment. In addition, we found that if filgrastim administration are started seven days post-chemotherapy, as few as three or four doses of rhG-CSF during a 14-day cycle would improve the ANC nadir experienced by an average patient during myelosuppressive chemotherapy. In all, our results suggest that it is possible to lessen the hematopoietic burden of chemotherapy on patients and that detailed physiological modelling of myelopoiesis is a useful tool to clinicians and researchers alike. Disclosures Off Label Use: We look at optimal dosing regimens of filgrastim during periodic chemotherapy in the context of physiological mathematical models. No clinical trials were undertaken and no patients underwent any regimen changes..
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».