Comparison of continuous, binary, and ordinal endpoints

Selecting the primary endpoint has been one of the most challenging tasks in the design of clinical trials. Typical endpoints include binary, continuous or time-to-event endpoints. The primary endpoint for many clinical trials is binary and is defined based on a threshold of a continuous endpoint. Many such trials could lack study power. It could be challenging to decide the appropriate threshold to define the binary endpoints; the best guess could be wrong, and the study will lose its power when that happens. For this reason, we propose to use an ordinal endpoint defined by two or more cut points as a primary or secondary efficacy endpoint when facing such challenges, to spread the risk from comparing treatment differences at a single cut point to multiple cut points. This way the study could maintain its power even if the results differ from the initial expectations. In this paper, we evaluate the performance of continuous, binary, and ordinal endpoints via extensive simulation studies. Furthermore, we compare the three types of endpoints across many clinical trials. Overall, we demonstrate that there may be some situations where the use of ordinal categorical endpoints, based on clinical and statistical considerations, could offer advantages as a primary or secondary efficacy endpoint.Disclaimer: This article has been reviewed by FDA and determined not to be consistent with the Agency's views or policies. It reflects only the views and opinions of the authors.

Authors

Institutions

Publication Details

Journal
Journal of Biopharmaceutical Statistics
Published
2025-04-26
DOI
https://doi.org/10.1080/10543406.2025.2489288
Primary Topic
Retinal Imaging and Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comparison of continuous, binary, and ordinal endpoints

Guoxing Soon, F. M. Smith, Jing Zhai
Journal of Biopharmaceutical Statistics
Retinal Imaging and Analysis
article

Comparison of continuous, binary, and ordinal endpoints

Guoxing Soon, F. M. Smith, Jing Zhai
article en

Abstract

Selecting the primary endpoint has been one of the most challenging tasks in the design of clinical trials. Typical endpoints include binary, continuous or time-to-event endpoints. The primary endpoint for many clinical trials is binary and is defined based on a threshold of a continuous endpoint. Many such trials could lack study power. It could be challenging to decide the appropriate threshold to define the binary endpoints; the best guess could be wrong, and the study will lose its power when that happens. For this reason, we propose to use an ordinal endpoint defined by two or more cut points as a primary or secondary efficacy endpoint when facing such challenges, to spread the risk from comparing treatment differences at a single cut point to multiple cut points. This way the study could maintain its power even if the results differ from the initial expectations. In this paper, we evaluate the performance of continuous, binary, and ordinal endpoints via extensive simulation studies. Furthermore, we compare the three types of endpoints across many clinical trials. Overall, we demonstrate that there may be some situations where the use of ordinal categorical endpoints, based on clinical and statistical considerations, could offer advantages as a primary or secondary efficacy endpoint.Disclaimer: This article has been reviewed by FDA and determined not to be consistent with the Agency's views or policies. It reflects only the views and opinions of the authors.

Journal of Biopharmaceutical StatisticsVol. 35(6)
Food and Drug Administration (TH)
Openalex Percentile: Top 86%
Retinal Imaging and Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.