Literature DB >> 23715625

Modeling tumor growth kinetics after treatment with pazopanib or placebo in patients with renal cell carcinoma.

Peter L Bonate1, A Benjamin Suttle.   

Abstract

PURPOSE: The purpose of this study is to characterize tumor growth kinetics in patients with renal cell carcinoma (RCC) after treatment with pazopanib or placebo and to identify predictive patient-specific covariates.
METHODS: Different tumor growth models that included patient-specific covariates were fit to tumor growth data from Phase 2 (n = 220) and Phase 3 (n = 423) clinical trials using nonlinear mixed-effects modeling. Logistic regression was used to determine whether individual model parameters or covariates were related to occurrence of new lesions.
RESULTS: A modified Wang model that included a quadratic growth term and a mixture model adequately described the data. Patients in Group 1 (93 %) showed treatment-dependent tumor shrinkage followed by treatment-independent regrowth. Patients in Group 2 (7 %) showed treatment-independent tumor shrinkage that did not regrow. In Group 1, pazopanib 800 mg increased the tumor shrinkage rate by 267 % compared to placebo. Baseline tumor size was dependent on baseline hemoglobin, baseline lactate dehydrogenase, study, and prior nephrectomy. Logistic regression analysis showed that prior radiotherapy, baseline tumor size, tumor shrinkage rate, tumor regrowth rate, study, and treatment (P < 0.01 for all) were all important predictors of new lesions. Patients treated with placebo were approximately twice as likely to develop new lesions than patients treated with pazopanib.
CONCLUSIONS: Mathematical modeling of tumor growth kinetics can quantify the effect of anticancer therapies. Pazopanib 800 mg was shown to be an effective treatment for RCC that increased the tumor shrinkage rate by 267 % compared with placebo and reduced the likelihood of developing new lesions.

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Year:  2013        PMID: 23715625     DOI: 10.1007/s00280-013-2191-0

Source DB:  PubMed          Journal:  Cancer Chemother Pharmacol        ISSN: 0344-5704            Impact factor:   3.333


  9 in total

1.  Establishing the Quantitative Relationship Between Lanreotide Autogel®, Chromogranin A, and Progression-Free Survival in Patients with Nonfunctioning Gastroenteropancreatic Neuroendocrine Tumors.

Authors:  Núria Buil-Bruna; Marion Dehez; Amandine Manon; Thi Xuan Quyen Nguyen; Iñaki F Trocóniz
Journal:  AAPS J       Date:  2016-02-23       Impact factor: 4.009

2.  Preclinical Modeling of Tumor Growth and Angiogenesis Inhibition to Describe Pazopanib Clinical Effects in Renal Cell Carcinoma.

Authors:  A Ouerdani; H Struemper; A B Suttle; D Ouellet; B Ribba
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2015-11-03

Review 3.  A Review of Modeling Approaches to Predict Drug Response in Clinical Oncology.

Authors:  Kyungsoo Park
Journal:  Yonsei Med J       Date:  2017-01       Impact factor: 2.759

Review 4.  Clinical Pharmacokinetics and Pharmacodynamics of Pazopanib: Towards Optimized Dosing.

Authors:  Remy B Verheijen; Jos H Beijnen; Jan H M Schellens; Alwin D R Huitema; Neeltje Steeghs
Journal:  Clin Pharmacokinet       Date:  2017-09       Impact factor: 6.447

Review 5.  A Review of Mathematical Models for Tumor Dynamics and Treatment Resistance Evolution of Solid Tumors.

Authors:  Anyue Yin; Dirk Jan A R Moes; Johan G C van Hasselt; Jesse J Swen; Henk-Jan Guchelaar
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2019-08-09

6.  Early predictions of response and survival from a tumor dynamics model in patients with recurrent, metastatic head and neck squamous cell carcinoma treated with immunotherapy.

Authors:  Ignacio González-García; Vadryn Pierre; Vincent F S Dubois; Nassim Morsli; Stuart Spencer; Paul G Baverel; Helen Moore
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2021-02-13

7.  A Joint Model for the Kinetics of CTC Count and PSA Concentration During Treatment in Metastatic Castration-Resistant Prostate Cancer.

Authors:  M Wilbaux; M Tod; J De Bono; D Lorente; J Mateo; G Freyer; B You; E Hénin
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2015-04-24

8.  A review of mixed-effects models of tumor growth and effects of anticancer drug treatment used in population analysis.

Authors:  B Ribba; N H Holford; P Magni; I Trocóniz; I Gueorguieva; P Girard; C Sarr; M Elishmereni; C Kloft; L E Friberg
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2014-05-07

9.  Comparison of Various Phase I Combination Therapy Designs in Oncology for Evaluation of Early Tumor Shrinkage Using Simulations.

Authors:  Jérémy Seurat; Pascal Girard; Kosalaram Goteti; France Mentré
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2020-11-05
  9 in total

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