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Article: Incorporating external controls in the design of randomized clinical trials: a case study in solid tumors

TitleIncorporating external controls in the design of randomized clinical trials: a case study in solid tumors
Authors
KeywordsClinical trials
Historical controls
Hybrid clinical trials
Real world data
Issue Date1-Nov-2024
PublisherBioMed Central
Citation
BMC Medical Research Methodology, 2024, v. 24, n. 1 How to Cite?
AbstractBackground: The use of historical external control data in clinical trials has grown in interest and needs when considering the design of future trials. Hybrid control designs can be more efficient to achieve the same power with fewer patients and limited resources. The literature is sparse on appropriate statistical methods which can account for the differences between historical external controls and the control patients in a study. In this article, we illustrate the analysis framework of a clinical trial if a hybrid control design was used after determining an RCT may not be feasible. Methods: We utilize two previously completed RCTs in nonsquamous NSCLC and a nationwide electronic health record derived de-identified database as examples and compare 5 analysis methods on each trial, as well as a set of simulations to determine operating characteristics of such designs. Results: In single trial estimation, the Case Weighted Adaptive Power Prior provided estimated treatment hazard ratios consistent with the original trial’s conclusions with narrower confidence intervals. The simulation studies showed that the Case Weighted Adaptive Power Prior achieved the highest power (and well controlled type-1 error) across all 5 methods with consistent study sample size. Conclusions: By following the proposed hybrid control framework, one can design a hybrid control trial transparently and accounting for differences between control groups while controlling type-1 error and still achieving efficiency gains from the additional contribution from external controls.
Persistent Identifierhttp://hdl.handle.net/10722/364218

 

DC FieldValueLanguage
dc.contributor.authorDamone, Emily M.-
dc.contributor.authorZhu, Jiawen-
dc.contributor.authorPang, Herbert-
dc.contributor.authorLi, Xiao-
dc.contributor.authorZhao, Yinqi-
dc.contributor.authorKwiatkowski, Evan-
dc.contributor.authorCarey, Lisa A.-
dc.contributor.authorIbrahim, Joseph G.-
dc.date.accessioned2025-10-29T00:35:18Z-
dc.date.available2025-10-29T00:35:18Z-
dc.date.issued2024-11-01-
dc.identifier.citationBMC Medical Research Methodology, 2024, v. 24, n. 1-
dc.identifier.urihttp://hdl.handle.net/10722/364218-
dc.description.abstractBackground: The use of historical external control data in clinical trials has grown in interest and needs when considering the design of future trials. Hybrid control designs can be more efficient to achieve the same power with fewer patients and limited resources. The literature is sparse on appropriate statistical methods which can account for the differences between historical external controls and the control patients in a study. In this article, we illustrate the analysis framework of a clinical trial if a hybrid control design was used after determining an RCT may not be feasible. Methods: We utilize two previously completed RCTs in nonsquamous NSCLC and a nationwide electronic health record derived de-identified database as examples and compare 5 analysis methods on each trial, as well as a set of simulations to determine operating characteristics of such designs. Results: In single trial estimation, the Case Weighted Adaptive Power Prior provided estimated treatment hazard ratios consistent with the original trial’s conclusions with narrower confidence intervals. The simulation studies showed that the Case Weighted Adaptive Power Prior achieved the highest power (and well controlled type-1 error) across all 5 methods with consistent study sample size. Conclusions: By following the proposed hybrid control framework, one can design a hybrid control trial transparently and accounting for differences between control groups while controlling type-1 error and still achieving efficiency gains from the additional contribution from external controls.-
dc.languageeng-
dc.publisherBioMed Central-
dc.relation.ispartofBMC Medical Research Methodology-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectClinical trials-
dc.subjectHistorical controls-
dc.subjectHybrid clinical trials-
dc.subjectReal world data-
dc.titleIncorporating external controls in the design of randomized clinical trials: a case study in solid tumors-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1186/s12874-024-02383-3-
dc.identifier.pmid39487399-
dc.identifier.scopuseid_2-s2.0-85208290447-
dc.identifier.volume24-
dc.identifier.issue1-
dc.identifier.eissn1471-2288-
dc.identifier.issnl1471-2288-

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