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Cancer Chemotherapy and Pharmacology
Published in: Cancer Chemotherapy and Pharmacology 5/2016

Open Access 01-05-2016 | Original Article

Predicting survival of pancreatic cancer patients treated with gemcitabine using longitudinal tumour size data

Authors: Thierry Wendling, Hitesh Mistry, Kayode Ogungbenro, Leon Aarons

Published in: Cancer Chemotherapy and Pharmacology | Issue 5/2016

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Abstract

Purpose

Measures derived from longitudinal tumour size data have been increasingly utilised to predict survival of patients with solid tumours. The aim of this study was to examine the prognostic value of such measures for patients with metastatic pancreatic cancer undergoing gemcitabine therapy.

Methods

The control data from two Phase III studies were retrospectively used to develop (271 patients) and validate (398 patients) survival models. Firstly, 31 baseline variables were screened from the training set using penalised Cox regression. Secondly, tumour shrinkage metrics were interpolated for each patient by hierarchical modelling of the tumour size time-series. Subsequently, survival models were built by applying two approaches: the first aimed at incorporating model-derived tumour size metrics in a parametric model, and the second simply aimed at identifying empirical factors using Cox regression. Finally, the performance of the models in predicting patient survival was evaluated on the validation set.

Results

Depending on the modelling approach applied, albumin, body surface area, neutrophil, baseline tumour size and tumour shrinkage measures were identified as potential prognostic factors. The distributional assumption on survival times appeared to affect the identification of risk factors but not the ability to describe the training data. The two survival modelling approaches performed similarly in predicting the validation data.

Conclusions

A parametric model that incorporates model-derived tumour shrinkage metrics in addition to other baseline variables could predict reasonably well survival of patients with metastatic pancreatic cancer. However, the predictive performance was not significantly better than a simple Cox model that incorporates only baseline characteristics.
Appendix
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Metadata
Title
Predicting survival of pancreatic cancer patients treated with gemcitabine using longitudinal tumour size data
Authors
Thierry Wendling
Hitesh Mistry
Kayode Ogungbenro
Leon Aarons
Publication date
01-05-2016
Publisher
Springer Berlin Heidelberg
Published in
Cancer Chemotherapy and Pharmacology / Issue 5/2016
Print ISSN: 0344-5704
Electronic ISSN: 1432-0843
DOI
https://doi.org/10.1007/s00280-016-2994-x

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