Sample Size for Multivariate Time-to-event Data

NCT03964402 | Completed

• 1 other identifier: IB2018-SAMPLE-SIZE-SURVIVAL
• Study Type: observational
• Target: 500
• Locations: 1 country
• Sites: 1

Brief Summary

Most of randomized clinical trials (RCT) using time-to-event criteria as the primary endpoint are designed, powered and analyzed based on an hypothetical hazard ratio (HR) corresponding to the targeted effect size between experimental and control arms. Usually, one assumes that populations are homogeneous within each treatment arm, that is, within each arm, (i) the baseline risk is identical for all patients, and (ii) the treatment effect is identical for all patients. This assumption however may not hold in all circumstances. This project aims at providing a statistical method for the estimation of sample size in RCT, in the presence of heterogenous populations, such as assuming populations with distinct underlying baseline risks or assuming different treatment effects.

Conditions

Clinical Trials

Keywords

sample size, survival, randomized clinical trials, statistical test

Outcome Measures

Primary Outcomes (1)

• Overall survival

  time from randomization to death

  2 years

Study Arms (1)

Clinical trial

Corresponds to a comparative clinical trial for which our new statistical methods will be applied to estimate sample size

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Any comparative clinical trial for which modern statistical methods are required to estimate sample size, in particular, it can be clinical trials : * with heterogeneous populations, * with recurrent event data, * involving a biomarker-Strategy Designs With Multiple Treatments.

Any comparative clinical trial for which modern statistical methods are required to estimate sample size

Contact the study team to discuss eligibility requirements. They can help determine if this study is right for you.

Sponsors & Collaborators

• Institut Bergonié: lead
• Institut National de la Santé Et de la Recherche Médicale, France: collaborator

Study Sites (1)

Institut Bergonié, Comprehensive Cancer Center

Bordeaux, 33400, France

Location

Related Publications (3)

• Dinart D, Bellera C, Rondeau V. Sample size estimation for cancer randomized trials in the presence of heterogeneous populations. Biometrics. 2022 Dec;78(4):1662-1673. doi: 10.1111/biom.13527. Epub 2021 Sep 3.

  PMID: 34242412 BACKGROUND

• Dinart D, Bellera C, Rondeau V. Sample size estimation for recurrent event data using multifrailty and multilevel survival models. J Biopharm Stat. 2025 Mar;35(2):241-256. doi: 10.1080/10543406.2024.2310306. Epub 2024 Feb 9.

  PMID: 38334044 BACKGROUND

• Dinart D, Rondeau V, Bellera C. Sample Size Estimation Using a Partially Clustered Frailty Model for Biomarker-Strategy Designs With Multiple Treatments. Pharm Stat. 2024 Nov-Dec;23(6):1084-1094. doi: 10.1002/pst.2407. Epub 2024 Jul 16.

  PMID: 39014905 BACKGROUND

Study Officials

• Carine Bellera, PhD

  Institut Bergonié

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: OTHER
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: May 23, 2019
• First Posted: May 28, 2019
• Study Start: January 1, 2019
• Primary Completion: December 31, 2024
• Study Completion: December 31, 2024
• Last Updated: September 17, 2025

Record last verified: 2025-09

Data Sharing

• IPD Sharing: Will not share

Locations

FR (1)