A single-arm study design with non-inferiority and superiority time-to-event endpoints: a tool for proof-of-concept and de-intensification strategies in breast cancer

De-escalation trials in oncology evaluate therapies that aim to improve the quality of life of patients with low-risk cancer by avoiding overtreatment. Non-inferiority randomized trials are commonly used to investigate de-intensified regimens with similar efficacy to that of standard regimens but wi...

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Bibliographic Details
Published in:Frontiers in oncology 2023-07, Vol.13, p.1048242-1048242
Main Authors: Sampayo-Cordero, Miguel, Miguel-Huguet, Bernat, Malfettone, Andrea, López-Miranda, Elena, Gion, María, Abad, Elena, Alcalá-López, Daniel, Pérez-Escuredo, Jhudit, Pérez-García, José Manuel, Llombart-Cussac, Antonio, Cortés, Javier
Format: Article
Language:English
Subjects:
clinical trial
non-inferiority
Oncology
phase II
single-arm
superiority
time-to-event
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Summary:De-escalation trials in oncology evaluate therapies that aim to improve the quality of life of patients with low-risk cancer by avoiding overtreatment. Non-inferiority randomized trials are commonly used to investigate de-intensified regimens with similar efficacy to that of standard regimens but with fewer adverse effects (ESMO evidence tier A). In cases where it is not feasible to recruit the number of patients needed for a randomized trial, single-arm prospective studies with a hypothesis of non-inferiority can be conducted as an alternative. Single-arm studies are also commonly used to evaluate novel treatment strategies (ESMO evidence tier B). A single-arm design that includes both non-inferiority and superiority primary objectives will enable the ranking of clinical activity and other parameters such as safety, pharmacokinetics, and pharmacodynamics data. Here, we describe the statistical principles and procedures to support such a strategy. The non-inferiority margin is calculated using the fixed margin method. Sample size and statistical analyses are based on the maximum likelihood method for exponential distributions. We present example analyses in metastatic and adjuvant settings to illustrate the usefulness of our methodology. We also explain its implementation with nonparametric methods. Single-arm designs with non-inferiority and superiority analyses are optimal for proof-of-concept and de-escalation studies in oncology.
ISSN:2234-943X
2234-943X
DOI:10.3389/fonc.2023.1048242