Assessing surrogacy from the joint modelling of multivariate longitudinal data and survival: Application to clinical trial data on chronic lymphocytic leukaemia.

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Assessing surrogacy from the joint modelling of multivariate longitudinal data

and survival: Application to clinical trial data on chronic lymphocytic

leukaemia.

Emmanuelle Deslandes and Sylvie Chevret

Stat Med, December 3, 2007; 26(30): 5411-5421.

Département de Biostatistique et Informatique Médicale, Hôpital Saint?Louis,

AP?HP, Paris, France.

In clinical research, we are often interested in assessing how a biomarker

changes with time, and whether it could be used as a surrogate marker when

evaluating the efficacy of a new drug. However, when the longitudinal marker is

correlated with survival, linear mixed models for longitudinal data may be

inappropriate. By contrast, it may be possible to recover information from the

so-called informative censoring by modelling both the longitudinal information

and the survival process. The objective of this work is to jointly model

longitudinal and survival data to assess surrogacy. Two competitive modelling

strategies were used, either a multistate model summarizing the course of

longitudinal data and occurrence of disease progression or death, or a joint

longitudinal-survival model. We present both analyses based on a case study from

two randomized clinical trials that enrolled patients with stage A chronic

lymphocytic leukaemia (CLL) in order to obtain further insights into these

different approaches. Copyright © 2007 Wiley & Sons, Ltd.

PMID: 18058850