Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA309554 | ENA |
REPOSITORIES: ENA
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Project description:Claret2009 - Predicting phase III overall survival in colorectal cancer
This model is described in the article:
Model-based prediction of
phase III overall survival in colorectal cancer on the basis of
phase II tumor dynamics.
Claret L, Girard P, Hoff PM, Van
Cutsem E, Zuideveld KP, Jorga K, Fagerberg J, Bruno R.
J. Clin. Oncol. 2009 Sep; 27(25):
4103-4108
Abstract:
PURPOSE: We developed a drug-disease simulation model to
predict antitumor response and overall survival in phase III
studies from longitudinal tumor size data in phase II trials.
METHODS: We developed a longitudinal exposure-response
tumor-growth inhibition (TGI) model of drug effect (and
resistance) using phase II data of capecitabine (n = 34) and
historical phase III data of fluorouracil (FU; n = 252) in
colorectal cancer (CRC); and we developed a parametric survival
model that related change in tumor size and patient
characteristics to survival time using historical phase III
data (n = 245). The models were validated in simulation of
antitumor response and survival in an independent phase III
study (n = 1,000 replicates) of capecitabine versus FU in CRC.
RESULTS: The TGI model provided a good fit of longitudinal
tumor size data. A lognormal distribution best described the
survival time, and baseline tumor size and change in tumor size
from baseline at week 7 were predictors (P < .00001).
Predicted change of tumor size and survival time distributions
in the phase III study for both capecitabine and FU were
consistent with observed values, for example, 431 days (90%
prediction interval, 362 to 514 days) versus 401 days observed
for survival in the capecitabine arm. A modest survival
improvement of 39 days (90% prediction interval, -21 to 110
days) versus 35 days observed was predicted for capecitabine.
CONCLUSION: The modeling framework successfully predicted
survival in a phase III trial on the basis of capecitabine
phase II data in CRC. It is a useful tool to support
end-of-phase II decisions and design of phase III studies.
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2017-08-31 | MODEL1708310001 | BioModels