2008/09/30 by Alexia Iasonos, Andrew S. Wilton, Elyn Riedel +2 · 1 citation
Mathematics · #Statistical Methods in Clinical Trials #Advanced Causal Inference Techniques #Statistical Methods and Bayesian Inference
paper · doi:10.1177/1740774508096474
openalex publication_date 2008/09/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
BACKGROUND: An extensive literature has covered the statistical properties of the Continual Reassessment Method (CRM) and the modifications of this method. While there are some applications of CRM designs in recent Phase I trials, the standard method (SM) of escalating doses after three patients with an option for an additional three patients SM remains very popular, mainly due to its simplicity. From a practical perspective, clinicians are interested in designs that can estimate the MTD using fewer patients for a fixed number of doses, or can test more dose levels for a given sample size. PURPOSE: This article compares CRM-based methods with the SM in terms of the number of patients needed to reach the MTD, total sample size required, and trial duration. METHODS: The comparisons are performed under two alternative schemes: a fixed or a varying sample approach with the implementation of a stopping rule. The stopping rule halts the trial if the confidence interval around the MTD is within a pre-specified bound. Our simulations evaluated several CRM-based methods under different scenarios by varying the number of dose levels from five to eight and the location of the true MTD. RESULTS: CRM and SM are comparable in terms of how fast they reach the MTD and the total sample size required when testing a limited number of dose levels (<or=5), but as the number of dose levels increases, CRM reaches the MTD in fewer patients when used with a fixed sample of 20 patients. However, a sample size of 20-25 patients is not sufficient to achieve a narrow precision around the estimated toxicity rate at the MTD. LIMITATIONS: We focused on methods with practical design features that are of interest to clinicians. However, there are several alternative CRM-based designs that are not investigated in this manuscript, and hence our results are not generalizable to other designs. CONCLUSIONS: We show that CRM-based methods are an improvement over the SM in terms of accuracy and optimal dose allocation in almost all cases, except when the true dose is among the lower levels.