{"title":"Adaptive platform trials: the impact of common controls on type one error and power.","authors":"Quynh Nguyen, Katharina Hees, Benjamin Hofner","doi":"10.1080/10543406.2023.2275765","DOIUrl":null,"url":null,"abstract":"<p><p>Platform trials offer a framework to study multiple interventions in one trial with the opportunity of opening and closing arms. The use of common controls can increase efficiency as compared to individual controls. The need for multiplicity adjustment because of common controls is currently a debate among researchers, pharmaceutical companies, and regulators. The impact of common controls on the type one error in a fixed platform trial, i.e. when all treatments start and end recruitment at the same time, has been discussed in the literature before. We complement these findings by investigating the impact of a common control on the type one error and power in a flexible platform trial, i.e. when one arm joins the platform later. We derived the correlation of test statistics to assess the impact of the overlap and compared the results to a trial with individual controls. Furthermore, we evaluate the power, and the impact of multiplicity adjustment on the power in fixed and flexible platform trials. These methodological considerations are complemented by a regulatory guideline review. With multiple arms, the FWER is inflated when no multiplicity adjustment is applied. However, the FWER inflation is smaller with common controls than with individual controls. Even after multiplicity adjustment, a trial with common controls is often beneficial in terms of sample size and power. However, in some cases, the trial with common controls loses the efficiency gain and it might be advisable to run a separate trial rather than joining a platform trial.</p>","PeriodicalId":54870,"journal":{"name":"Journal of Biopharmaceutical Statistics","volume":" ","pages":"719-736"},"PeriodicalIF":1.2000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Biopharmaceutical Statistics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/10543406.2023.2275765","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/11/21 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0
Abstract
Platform trials offer a framework to study multiple interventions in one trial with the opportunity of opening and closing arms. The use of common controls can increase efficiency as compared to individual controls. The need for multiplicity adjustment because of common controls is currently a debate among researchers, pharmaceutical companies, and regulators. The impact of common controls on the type one error in a fixed platform trial, i.e. when all treatments start and end recruitment at the same time, has been discussed in the literature before. We complement these findings by investigating the impact of a common control on the type one error and power in a flexible platform trial, i.e. when one arm joins the platform later. We derived the correlation of test statistics to assess the impact of the overlap and compared the results to a trial with individual controls. Furthermore, we evaluate the power, and the impact of multiplicity adjustment on the power in fixed and flexible platform trials. These methodological considerations are complemented by a regulatory guideline review. With multiple arms, the FWER is inflated when no multiplicity adjustment is applied. However, the FWER inflation is smaller with common controls than with individual controls. Even after multiplicity adjustment, a trial with common controls is often beneficial in terms of sample size and power. However, in some cases, the trial with common controls loses the efficiency gain and it might be advisable to run a separate trial rather than joining a platform trial.
期刊介绍:
The Journal of Biopharmaceutical Statistics, a rapid publication journal, discusses quality applications of statistics in biopharmaceutical research and development. Now publishing six times per year, it includes expositions of statistical methodology with immediate applicability to biopharmaceutical research in the form of full-length and short manuscripts, review articles, selected/invited conference papers, short articles, and letters to the editor. Addressing timely and provocative topics important to the biostatistical profession, the journal covers:
Drug, device, and biological research and development;
Drug screening and drug design;
Assessment of pharmacological activity;
Pharmaceutical formulation and scale-up;
Preclinical safety assessment;
Bioavailability, bioequivalence, and pharmacokinetics;
Phase, I, II, and III clinical development including complex innovative designs;
Premarket approval assessment of clinical safety;
Postmarketing surveillance;
Big data and artificial intelligence and applications.