RESUMEN
BACKGROUND: To speed up the evaluation of new therapies, the multi-arm, multi-stage trial design was suggested previously by the authors. METHODS: In this paper, we evaluate the performance of the two-stage, multi-arm design using four cancer trials conducted at the MRC CTU. The performance of the design at fictitious interim analyses is assessed using a conditional bootstrap approach. RESULTS: Two main aims are addressed: the error rate of correctly carrying on/stopping the trial at an interim analysis as well as quantifying the gains in terms of resources by employing this design. Furthermore, we make suggestions for the best timing of this interim analysis. CONCLUSION: Multi-arm, multi-stage trials are an effective way of speeding up the therapy evaluation process. The design performs well in terms of the type I and II error rates.
Asunto(s)
Antineoplásicos/uso terapéutico , Neoplasias/tratamiento farmacológico , Ensayos Clínicos Controlados Aleatorios como Asunto/métodos , Proyectos de Investigación , Supervivencia sin Enfermedad , Humanos , Neoplasias/mortalidad , Análisis de Supervivencia , Factores de Tiempo , Resultado del TratamientoRESUMEN
We present a general framework for sample size calculation in survival studies based on comparing two or more survival distributions using any one of a class of tests including the logrank test. Incorporated within this framework are the possible presence of non-uniform staggered patient entry, non-proportional hazards, loss to follow-up and treatment changes including cross-over between treatment arms. The framework is very general in nature and is based on using piecewise exponential distributions to model the survival distributions. We illustrate the use of the approach and explore its validity using simulation studies. These studies have shown that not adjusting for loss to follow-up, non-proportional hazards or cross-over can lead to significant alterations in power or equivalently, a marked effect on sample size. The approach has been implemented in the freely available program ART (for Stata). Our investigations suggest that ART is the first software to allow incorporation of all these elements. Further extensions to the methodology such as non-local alternatives for the logrank test are also considered.