DDMODEL00000214: Executable_HFSmodel

  public model
Short description:
Longitudinal model to predict Hand and Foot Syndrome grades dynamics in patients with solid tumors receiving capecitabine in two phase III studies.
Original code
  • A Dynamic Model of Hand-and-Foot Syndrome in Patients Receiving Capecitabine
  • E. Hénin, B. You, E. VanCutsem, P.M. Hoff, J. Cassidy, C. Twelves, K.P. Zuideveld, F. Sirzen, C. Dartois, G. Freyer, M.Tod, P. Girard
  • Clinical Pharmacology & Therapeutics, 4/2009, Volume 85, Issue 4, pages: 418-425
  • Université de Lyon, Lyon, France; Université Lyon, EA3738, Ciblage Thérapeutique en Oncologie, Faculté de Médecine Lyon Sud, Oullins, France; Service d’Oncologie Médicale, Centre Hospitalier Lyon Sud, Hospices Civils de Lyon, Pierre-Bénite, France; Univer
  • For the purpose of developing a longitudinal model to predict hand-and-foot syndrome (HFS) dynamics in patients receiving capecitabine, data from two large phase III studies were used. Of 595 patients in the capecitabine arms, 400 patients were randomly selected to build the model, and the other 195 were assigned for model validation. A score for risk of developing HFS was modeled using the proportional odds model, a sigmoidal maximum effect model driven by capecitabine accumulation as estimated through a kinetic–pharmacodynamic model and a Markov process. The lower the calculated creatinine clearance value at inclusion, the higher was the risk of HFS. Model validation was performed by visual and statistical predictive checks. The predictive dynamic model of HFS in patients receiving capecitabine allows the prediction of toxicity risk based on cumulative capecitabine dose and previous HFS grade. This dose–toxicity model will be useful in developing Bayesian individual treatment adaptations and may be of use in the clinic.
Maria Luisa Sardu
Context of model development: Disease Progression model;
Long technical model description: Longitudinal model to predict Hand and Foot Syndrome grades dynamics in patients with solid tumors receiving capecitabine in two phase III studies. HFS grades are ordered categorical data from 0 no toxicity to 3 maximum toxicity.The model describes the risk of developing HFS using proportional odds model including a sigmoidal maximum effect driven by capecitabine exposure. As HFS grades are not independent from one point to the other, a Markov model was used to define transition probabilities. To describe Capecitabine exposure the (kinetic-pharmacodynamic) K-PD approach was used. Only baseline-calculated serum creatinine clearance (CRCL) was included as model covariate.;
Model compliance with original publication: Yes;
Model implementation requiring submitter’s additional knowledge: No;
Modelling context description: Predict Hand and Foot Syndrome dynamics in cancer patients receiving capecitabine from 2 phase III studies.;
Modelling task in scope: estimation;
Nature of research: Approval phase/Registration trial (Phase III);
Therapeutic/disease area: Oncology;
Annotations are correct.
This model is not certified.
  • Model owner: Maria Luisa Sardu
  • Submitted: Oct 4, 2016 9:53:55 AM
  • Last Modified: Oct 4, 2016 9:53:55 AM
  • Version: 4 public model Download this version
    • Submitted on: Oct 4, 2016 9:53:55 AM
    • Submitted by: Maria Luisa Sardu
    • With comment: change name of the files