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Population Dose-Response Time Model for Lymphocytopenia Following Chemotherapy in Breast Cancer Patients
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. University of Navarra. (Pharmacometrics & Systems Pharmacology)
2018 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Background Chemotherapy is associated with numerous toxicities, one of the most common being myelosuppression. White blood cell and especially neutrophil suppression has been documented extensively as a dose-limiting adverse event. Lymphocyte depletion following chemotherapy has also been documented, although the clinical significance of this adverse event is still debatable. Dose-limiting adverse events in chemotherapy are of great discomfort to the patients reducing their quality of life. Furthermore, decreasing the intensity of chemotherapy might hamper the therapeutic outcome. Therefore, it is of great value working towards optimal treatments for each patient, predicting their maximum tolerated dose before treatment commencement. Population pharmacokinetic pharmacodynamic modelling is considered a tool for such a task.

Aim The aim was to identify commonly experienced and dose-limiting adverse events in a population consisting of 76 non-metastatic HER2-negative breast cancer patients treated pre-surgery with chemotherapy. Among the identified adverse events, the one considered most adequate for modeling was to be used in model building. This work was carried out to generate building blocks for the larger goal of establishing an individual utility function that can be used to individualize chemotherapy for HER2-negative non-metastatic breast cancer patients.

Materials and Methods Patient records routinely gathered in the clinic setting were used to develop the kinetics-pharmacodynamics model using the population approach with NONMEM v7.3. All patients were treated with four cycles cyclophosphamide and epirubicin every two weeks, followed by four cycles of docetaxel every three weeks. The time course of absolute blood cell counts was modelled using the semi-mechanistic framework initially proposed by Friberg and coauthors (2002). As no concentration levels of any of the drugs were available the K-PD approach was taken. Model building was driven mainly by visual exploration of the goodness of fit plots and the minimum value of objective function. The selected model was evaluated and externally validated using simulation-based diagnosis.

Results A 40 % of the patients experienced grade III or IV lymphocytopenia during treatment. The selected model in the current evaluation described adequately the median tendency of the data and predicted the time course of the response in another group of patients. Model parameters were estimated in general precisely. None of the individual patient characteristics showed a significant covariate effects in any of the parameters of the model. The magnitude of the unexplained inter-individual variability ranged from 25.4 to 45.9 %.

Conclusions A descriptive and predictive model linking treatment intensity and schedule with lymphocytes counts over time has been developed and can be used in conjunction with a tumor response model to individualize dosing. Despite the mechanistic structure of the model, given the sparse nature of the data some parameters of the model might not represent real physiology. The models predictive power is considered limited to the study design occupied for the patients studied.

Abstract [sv]

Cytostatikabehandling innebär oftast en mängd olika biverkningar som kan begränsa vilken dos som går att administrera till en patient med bröstcancer. En sänkning av dosen kan vidare leda till sämre svar på behandlingen, det är en balansgång. I det här projektarbetet utvecklades en modell av hur antalet lymfocyter, en del av immunförsvaret, påverkas utav behandling med cytostatika. Denna modell är ett steg framåt i riktningen för att i framtiden kunna skräddarsy cytostatikabehandling till varje enskild bröstcancerpatient. Modellen är byggd på kliniska data från bröstcancerpatienter som blev behandlade på Pamplonas universitetssjukhus. Modellen kan beskriva hur lymfocytantalet förändrades under behandlingen för 76 individer. Modellen visade sig även kunna förutse hur lymfocytantalet förändrades under behandlingens gång för nya individer, som hade erhållit liknande behandling och hade en liknande sjukdomsbild.

Tidigare kunskap om hur vita blodkroppar utvecklas i benmärgen och så småningom når blodbanan användes för att bygga modellen. Läkemedlens närvaro beskrevs utifrån hur lymfocytantalet ändrades med tiden. En sänkning av lymfocyter i cirkulationen antogs innebära att läkemedlen hade varit närvarande där effekten utövades. Med ytterligare förbättringar skulle denna modell i framtiden kunna kombineras med en effektmodell för tumörstorlek och förutspå optimal dosering av cytostatika för varje individuell patient.

Place, publisher, year, edition, pages
2018. , p. 31
Keywords [en]
breast cancer, HER2-negative, pharmacometrics, K-PD approach, lymphocytopenia, sparse data
National Category
Pharmaceutical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-355951OAI: oai:DiVA.org:uu-355951DiVA, id: diva2:1231893
Subject / course
Pharmacokinetics
Educational program
Master of Science Programme in Pharmacy
Presentation
2018-05-28, 13:15
Supervisors
Examiners
Available from: 2018-10-02 Created: 2018-07-09 Last updated: 2018-10-02Bibliographically approved

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