The Use of Model-Based Tumor-Size Metrics to Predict Survival

Benjamin Ribba; Nick Holford; France Mentré

The Use of Model-Based Tumor-Size Metrics to Predict Survival: Analysis of survival using model-based tumor-size metrics

Benjamin Ribba ^{1, *} Nick Holford ² France Mentré ³

* Corresponding author

1 NUMED - Numerical Medicine

UMPA-ENSL - Unité de Mathématiques Pures et Appliquées, Inria Grenoble - Rhône-Alpes

2 Department of Pharmacology

3 IAME - Infection, Anti-microbiens, Modélisation, Evolution

Abstract : Mixed-effect models are increasingly being used to analyze the time-course of tumor size and to identify tumor size metrics as predictors of overall survival in cancer patients. However, caution is needed interpreting the results of such analyses and applying them to clinical research. Sparse individual tumor data as a result of patient mortality can lead to falsely conclusions about tumor size metrics as predictors of overall survival.

Document type :

Journal articles

Domain :

Life Sciences [q-bio] / Quantitative Methods [q-bio.QM]

Complete list of metadatas

https://www.hal.inserm.fr/inserm-01084276
Contributor : Emmanuelle Comets <>
Submitted on : Tuesday, November 18, 2014 - 9:46:10 PM
Last modification on : Wednesday, November 20, 2019 - 8:10:05 AM
Long-term archiving on : Thursday, February 19, 2015 - 12:25:41 PM

CPT_Ribba_14.pdf

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The Use of Model-Based Tumor-Size Metrics to Predict Survival: Analysis of survival using model-based tumor-size metrics

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