Continual reassessment method with regularization in phase I clinical trials. Issue 6 (1st November 2020)

• Record Type: Journal Article
• Authors: Li, Xiang; Ivanova, Anastasia; Tian, Hong; Lim, Pilar; Liu, Kevin
• Is Part Of: Journal of biopharmaceutical statistics. Volume 30:Issue 6(2020)
• Page Start: 964
• Page End: 978
• Publication Date: 2020-11-01
• Subjects: Continual reassessment method -- dose-expansion -- dose-finding -- regularization; Pharmacy -- Statistical methods -- Periodicals; Drugs -- Testing -- Statistical methods -- Periodicals; Biometry -- Periodicals; Biopharmaceutics -- Periodicals; Pharmacokinetics -- Periodicals; 615.19
• DOI: 10.1080/10543406.2020.1818251
• Languages: English
• ISSNs: 1054-3406

Abstract

ABSTRACT: Many Phase I trial designs have been developed to improve upon the standard 3 + 3 design. These designs can be classified as long-memory designs, for example, the continual reassessment method (CRM), and short-memory designs such as the modified toxicity probability interval (mTPI) design. Long-term memory designs use all data but their performance can be negatively affected by the model misspecification. Short-term memory designs only use data at the current dose and might lose efficiency as a result. To overcome these issues, we propose a regularized CRM (rCRM). The rCRM offers a trade-off between long-term memory and short-term memory methods. The rCRM gives more weight to data obtained at the doses with the estimated probability of toxicity closer to the target toxicity rate. The addition of a regularization term has an effect of shrinking the dimension of the model and leads to improved performance of the 2-parameter CRM. The rCRM is a good design choice to guide assignments in an expansion cohort phase of a dose-finding trial since dose assignments do not seem to change as often as in corresponding CRMs.