Conditional power and information fraction calculations at an interim analysis for random coefficient models

© 2023 John Wiley & Sons Ltd..

Random coefficient (RC) models are commonly used in clinical trials to estimate the rate of change over time in longitudinal data. Trials utilizing a surrogate endpoint for accelerated approval with a confirmatory longitudinal endpoint to show clinical benefit is a strategy implemented across various therapeutic areas, including immunoglobulin A nephropathy. Understanding conditional power (CP) and information fraction calculations of RC models may help in the design of clinical trials as well as provide support for the confirmatory endpoint at the time of accelerated approval. This paper provides calculation methods, with practical examples, for determining CP at an interim analysis for a RC model with longitudinal data, such as estimated glomerular filtration rate (eGFR) assessments to measure rate of change in eGFR slope.

Medienart:

E-Artikel

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

Zur Gesamtaufnahme - volume:23

Enthalten in:

Pharmaceutical statistics - 23(2024), 2 vom: 01. März, Seite 276-283

Sprache:

Englisch

Beteiligte Personen:

Lewis, Sandra A [VerfasserIn]
Carroll, Kevin J [VerfasserIn]
DeVries, Todd [VerfasserIn]
Barratt, Jonathan [VerfasserIn]

Links:

Volltext

Themen:

Biomarkers
Conditional power
IgA nephropathy
Information fraction
Interim analysis
Journal Article
Longitudinal data
Random coefficients model

Anmerkungen:

Date Completed 08.03.2024

Date Revised 08.03.2024

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1002/pst.2345

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM364111275