Designing therapeutic cancer vaccine trials with delayed treatment effect: Z. XU ET AL.
Open accessAbstract
Arming the immune system against cancer has emerged as a powerful tool in oncology during recent years. Instead of poisoning a tumor or destroying it with radiation, therapeutic cancer vaccine, a type of cancer immunotherapy, unleashes the immune system to combat cancer. This indirect mechanism-of-action of vaccines poses the possibility of a delayed onset of clinical effect, which results in a delayed separation of survival curves between the experimental and control groups in therapeutic cancer vaccine trials with time-to-event endpoints. This violates the proportional hazard assumption. As a result, the conventional study design based on the regular log-rank test ignoring the delayed effect would lead to a loss of power. In this paper, we propose two innovative approaches for sample size and power calculation using the piecewise weighted log-rank test to properly and efficiently incorporate the delayed effect into the study design. Both theoretical derivations and empirical studies demonstrate that the proposed methods, accounting for the delayed effect, can reduce sample size dramatically while achieving the target power relative to a standard practice. Copyright © 2016 John Wiley & Sons, Ltd.
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A stratified constant piecewise weighted log-rank test (weight 0 for weeks 0 to 8 after randomization and weight 1 after that period) was used to compare the trial groups because both groups received the same treatments during the bridging period.
“We used a stratified constant piecewise weighted log-rank test (in which a weight of 0 was assigned for the log-rank statistic for weeks 0 to 8 after randomization and a weight of 1 after that period) 22,23 to compare the trial groups, because both groups received the same treatments during the bridging period.”
From Cilta-cel or Standard Care in Lenalidomide-Refractory Multiple Myeloma. (2023) · cites this paper as [22]
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References 22 · Cited by 76
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- Authors
- Xu, Z., Zhen, B., Park, Y., & Zhu, B.
- Affiliations
- Center for Biologics Evaluation and Research (US)
- University of Pittsburgh (US)
- National Cancer Institute (US)
- Corresponding author
- Xu, Zhenzhen
- ORCID
- Venue
- Statistics in Medicine
- Publisher
- Wiley
- Published
- 2016-11-02
- Volume
- 36
- Issue
- 4
- Pages
- 592-605
- ISSN
- 0277-6715 (ISSN-L)
- PMC
- PMC5512569
- OpenAlex
- W2548723506
- Cited by
- 76
- References
- 22
- Citations by year
- 2026: 3 · 2025: 7 · 2024: 10 · 2023: 13 · 2022: 3 · 2021: 10 · 2020: 13 · 2019: 6 · 2018: 9 · 2017: 2
- FWCI
- 6.08
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Statistics in Medicine (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (Z99 CA999999)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Life Sciences › Immunology and Microbiology › Immunology › Immunotherapy and Immune Responses
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Keywords
- therapeutic cancer vaccines, cancer immunotherapy, delayed treatment effect, sample size determination, statistical power, proportional hazards assumption, time-to-event outcomes, survival analysis, clinical trial design
- MeSH terms
- Data Interpretation, Statistical, Humans, Neoplasms, Statistics as Topic, Time Factors, Models, Statistical, Proportional Hazards Models, Survival Analysis, Randomized Controlled Trials as Topic, Cancer Vaccines, Kaplan-Meier Estimate
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