Trial reportBritish journal of clinical pharmacology2016
Models for change in tumour size, appearance of new lesions and survival probability in patients with advanced epithelial ovarian cancer.
Trial report in British journal of clinical pharmacology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed, 25 citations in OpenAlex.
- A New Method to Model and Predict Progression Free Survival Based on Tumor Growth Dynamics.CPT: pharmacometrics & systems pharmacology · 2020Trial
- Models for change in tumour size, appearance of new lesions and survival probability in patients with advanced epithelial ovarian cancer.British journal of clinical pharmacology · 2016Trial
- Development of a Joint Tumor Size-Overall Survival Modeling and Simulation Framework Supporting Oncology Development Decision-Making.CPT: pharmacometrics & systems pharmacology · 2025Article
- Longitudinal and time-to-event modeling for the survival of advanced pancreatic ductal adenocarcinoma patients.Acta pharmacologica Sinica · 2025Article
- A prognostic baseline blood biomarker and tumor growth kinetics integrated model in paclitaxel/platinum treated advanced non-small cell lung cancer patients.CPT: pharmacometrics & systems pharmacology · 2023Article
- Prediction of overall survival in patients across solid tumors following atezolizumab treatments: A tumor growth inhibition-overall survival modeling framework.CPT: pharmacometrics & systems pharmacology · 2021Article
- Tumor growth inhibition modeling of individual lesion dynamics and interorgan variability in HER2-negative breast cancer patients treated with docetaxel.CPT: pharmacometrics & systems pharmacology · 2021Article
- A clinical model to predict the risk of liver metastases in newly diagnosed ovarian cancer: a population-based study.Translational cancer research · 2020Article
- Progress and Opportunities to Advance Clinical Cancer Therapeutics Using Tumor Dynamic Models.Clinical cancer research : an official journal of the American Association for Cancer Research · 2020Review
- Impact of tumour size measurement inter-operator variability on model-based drug effect evaluation.Cancer chemotherapy and pharmacology · 2020Article
- A Review of Mathematical Models for Tumor Dynamics and Treatment Resistance Evolution of Solid Tumors.CPT: pharmacometrics & systems pharmacology · 2019Review
- Translational Framework Predicting Tumour Response in Gemcitabine-Treated Patients with Advanced Pancreatic and Ovarian Cancer from Xenograft Studies.The AAPS journal · 2019Article
- Tumor Size and Overall Survival in Patients With Platinum-Resistant Ovarian Cancer Treated With Chemotherapy and Bevacizumab.Clinical Medicine Insights. Oncology · 2019Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimsThe aims of this study were (i) to develop a modelling framework linking change in tumour size during treatment to survival probability in metastatic ovarian cancer; and (ii) to model the appearance of new lesions and investigate their relationship with survival and disease characteristics.
methodsData from a randomized Phase III clinical trial comparing carboplatin monotherapy to gemcitabine plus carboplatin combotherapy in 336 patients with metastatic ovarian cancer were used. A population model describing change in tumour size based on drug treatment information was established and its relationship with time to appearance of new lesions and survival were investigated with time to event models.
resultsThe tumour size profiles were well characterized as evaluated by visual predictive checks. Metastasis in the liver at enrolment and change in tumour size up to week 12 were predictors of time to appearance of new lesions. Survival was predicted based on the patient tumour size and ECOG performance status at enrolment and on appearance of new lesions during treatment and change in tumour size up to week 12. Tumour size and survival data from a separate study were adequately predicted.
conclusionsThe proposed models simulate tumour dynamics following treatment and provide a link to the probability of developing new lesions as well as to survival. The models have potential to be used for optimizing the design of late phase clinical trials in metastatic ovarian cancer based on early phase clinical study results and simulation.
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