Forced randomization: the what, why, and how
Abstract Background When running a randomized controlled trial (RCT), a clinical site may face a situation when an eligible trial participant is to be randomized to the treatment that is not available at the site. In this case, there are two options: not to enroll the participant, or, without disclo...
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2024-10-01
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| author | Kerstine Carter Olga Kuznetsova Volodymyr Anisimov Johannes Krisam Colin Scherer Yevgen Ryeznik Oleksandr Sverdlov |
| author_facet | Kerstine Carter Olga Kuznetsova Volodymyr Anisimov Johannes Krisam Colin Scherer Yevgen Ryeznik Oleksandr Sverdlov |
| author_sort | Kerstine Carter |
| collection | DOAJ |
| description | Abstract Background When running a randomized controlled trial (RCT), a clinical site may face a situation when an eligible trial participant is to be randomized to the treatment that is not available at the site. In this case, there are two options: not to enroll the participant, or, without disclosing to the site, allocate the participant to a treatment arm with drug available at the site using a built-in feature of the interactive response technology (IRT). In the latter case, one has employed a “forced randomization” (FR). There seems to be an industry-wide consensus that using FR can be acceptable in confirmatory trials provided there are “not too many” instances of forcing. A better understanding of statistical properties of FR is warranted. Methods We described four different IRT configurations with or without FR and illustrated them using a simple example. We discussed potential merits of FR and outlined some relevant theoretical risks and risk mitigation strategies. We performed a search using Cortellis Regulatory Intelligence database (IDRAC) ( www.cortellis.com ) to understand the prevalence of FR in clinical trial practice. We also proposed a structured template for development and evaluation of randomization designs featuring FR and showcased an application of this template for a hypothetical multi-center 1:1 RCT under three experimental settings (“base case”, “slower recruitment”, and “faster recruitment”) to explore the effect of four different IRT configurations in combination with three different drug supply/re-supply strategies on some important operating characteristics of the trial. We also supplied the Julia code that can be used to reproduce our simulation results and generate additional results under user-specified experimental scenarios. Results FR can eliminate refusals to randomize patients, which can cause frustration for patients and study site personnel, improve the study logistics, drug supply management, cost-efficiency, and recruitment time. Nevertheless, FR carries some potential risks that should be reviewed at the study planning stage and, ideally, prospectively addressed through risk mitigation planning. The Cortellis search identified only 9 submissions that have reported the use of FR; typically, the FR option was documented in IRT specifications. Our simulation evidence showed that under the considered realistic experimental settings, the percentage of FR is expected to be low. When FR with backfilling was used in combination with high re-supply strategy, the final treatment imbalance was negligibly small, the proportion of patients not randomized due to the lack of drug supply was close to zero, and the time to complete recruitment was shortened compared to the case when FR was not allowed. The drug overage was primarily determined by the intensity of the re-supply strategy and to a smaller extent by the presence or absence of the FR feature in IRT. Conclusion FR with a carefully chosen drug supply/re-supply strategy can result in quantifiable improvements in the patients’ and site personnel experience, trial logistics and efficiency while preventing an undesirable refusal to randomize a patient and a consequential unblinding at the site. FR is a useful design feature of multi-center RCTs provided it is properly planned for and carefully implemented. |
| format | Article |
| id | doaj-art-6409d535618d494eb89ff5cf9a7acc55 |
| institution | OA Journals |
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| language | English |
| publishDate | 2024-10-01 |
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| spelling | doaj-art-6409d535618d494eb89ff5cf9a7acc552025-08-20T02:22:24ZengBMCBMC Medical Research Methodology1471-22882024-10-0124112210.1186/s12874-024-02340-0Forced randomization: the what, why, and howKerstine Carter0Olga Kuznetsova1Volodymyr Anisimov2Johannes Krisam3Colin Scherer4Yevgen Ryeznik5Oleksandr Sverdlov6Boehringer-Ingelheim Pharmaceuticals IncMerck & Co., Inc.Amgen Ltd.Boehringer-Ingelheim Pharma GmbH & Co. KGRensselaer Polytechnic InstituteDepartment of Pharmacy, Uppsala UniversityNovartis Pharmaceuticals CorporationAbstract Background When running a randomized controlled trial (RCT), a clinical site may face a situation when an eligible trial participant is to be randomized to the treatment that is not available at the site. In this case, there are two options: not to enroll the participant, or, without disclosing to the site, allocate the participant to a treatment arm with drug available at the site using a built-in feature of the interactive response technology (IRT). In the latter case, one has employed a “forced randomization” (FR). There seems to be an industry-wide consensus that using FR can be acceptable in confirmatory trials provided there are “not too many” instances of forcing. A better understanding of statistical properties of FR is warranted. Methods We described four different IRT configurations with or without FR and illustrated them using a simple example. We discussed potential merits of FR and outlined some relevant theoretical risks and risk mitigation strategies. We performed a search using Cortellis Regulatory Intelligence database (IDRAC) ( www.cortellis.com ) to understand the prevalence of FR in clinical trial practice. We also proposed a structured template for development and evaluation of randomization designs featuring FR and showcased an application of this template for a hypothetical multi-center 1:1 RCT under three experimental settings (“base case”, “slower recruitment”, and “faster recruitment”) to explore the effect of four different IRT configurations in combination with three different drug supply/re-supply strategies on some important operating characteristics of the trial. We also supplied the Julia code that can be used to reproduce our simulation results and generate additional results under user-specified experimental scenarios. Results FR can eliminate refusals to randomize patients, which can cause frustration for patients and study site personnel, improve the study logistics, drug supply management, cost-efficiency, and recruitment time. Nevertheless, FR carries some potential risks that should be reviewed at the study planning stage and, ideally, prospectively addressed through risk mitigation planning. The Cortellis search identified only 9 submissions that have reported the use of FR; typically, the FR option was documented in IRT specifications. Our simulation evidence showed that under the considered realistic experimental settings, the percentage of FR is expected to be low. When FR with backfilling was used in combination with high re-supply strategy, the final treatment imbalance was negligibly small, the proportion of patients not randomized due to the lack of drug supply was close to zero, and the time to complete recruitment was shortened compared to the case when FR was not allowed. The drug overage was primarily determined by the intensity of the re-supply strategy and to a smaller extent by the presence or absence of the FR feature in IRT. Conclusion FR with a carefully chosen drug supply/re-supply strategy can result in quantifiable improvements in the patients’ and site personnel experience, trial logistics and efficiency while preventing an undesirable refusal to randomize a patient and a consequential unblinding at the site. FR is a useful design feature of multi-center RCTs provided it is properly planned for and carefully implemented.https://doi.org/10.1186/s12874-024-02340-0Drug supply chain managementInteractive response technology (IRT)Multi-center clinical trialPoisson-gamma model |
| spellingShingle | Kerstine Carter Olga Kuznetsova Volodymyr Anisimov Johannes Krisam Colin Scherer Yevgen Ryeznik Oleksandr Sverdlov Forced randomization: the what, why, and how BMC Medical Research Methodology Drug supply chain management Interactive response technology (IRT) Multi-center clinical trial Poisson-gamma model |
| title | Forced randomization: the what, why, and how |
| title_full | Forced randomization: the what, why, and how |
| title_fullStr | Forced randomization: the what, why, and how |
| title_full_unstemmed | Forced randomization: the what, why, and how |
| title_short | Forced randomization: the what, why, and how |
| title_sort | forced randomization the what why and how |
| topic | Drug supply chain management Interactive response technology (IRT) Multi-center clinical trial Poisson-gamma model |
| url | https://doi.org/10.1186/s12874-024-02340-0 |
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