Statistics in medicine
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Statistics in medicine · Jul 2010
Joint modeling of progression-free survival and death in advanced cancer clinical trials.
Progression-related endpoints (such as time to progression or progression-free survival) and time to death are common endpoints in cancer clinical trials. It is of interest to study the link between progression-related endpoints and time to death (e.g. to evaluate the degree of surrogacy). However, current methods ignore some aspects of the definitions of progression-related endpoints. ⋯ We also argue that interval-censoring needs to be taken into account to more closely match the latent disease evolution. The joint distribution and an expression for Kendall's tau are derived. The model is applied to data from a clinical trial in advanced metastatic ovarian cancer.
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Statistics in medicine · Jul 2010
Comparative StudyA comparison of United States and United Kingdom EQ-5D health states valuations using a nonparametric Bayesian method.
Cost-effectiveness analysis of alternative medical treatments relies on having a measure of effectiveness, and many regard the quality adjusted life year (QALY) to be the current 'gold standard.' In order to compute QALYs, we require a suitable system for describing a person's health state, and a utility measure to value the quality of life associated with each possible state. There are a number of different health state descriptive systems, and we focus here on one known as the EQ-5D. Data for estimating utilities for different health states have a number of features that mean care is necessary in statistical modelling. ⋯ The data set is the US and UK EQ-5D valuation studies where a sample of 42 states defined by the EQ-5D was valued by representative samples of the general population from each country using the time trade-off technique. We estimate a utility function across both countries which explicitly accounts for the differences between them, and is estimated using the data from both countries. The article discusses the implications of these results for future applications of the EQ-5D and for further work in this field.
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Statistics in medicine · Jun 2010
Strength of evidence of non-inferiority trials-The adjustment of the type I error rate in non-inferiority trials with the synthesis method.
In non-inferiority trials that employ the synthesis method several types of dependencies among test statistics occur due to sharing of the same information from the historical trial. The conditions under which the dependencies appear may be divided into three categories. The first case is when a new drug is approved with single non-inferiority trial. ⋯ We show that the unconditional across-trial type I error rate increases dramatically as does the correlation between two non-inferiority tests when a new drug is approved based on the positive results of two non-inferiority trials. We conclude that the conditional across-trial type I error rate involves the unknown treatment effect in the historical trial. The formulae of the conditional across-trial type I error rates provide us with a way of investigating the conditional across-trial type I error rates for various assumed values of the treatment effect in the historical trial.