A web application for the design of multi-arm clinical trials
Abstract Background Multi-arm designs provide an effective means of evaluating several treatments within the same clinical trial. Given the large number of treatments now available for testing in many disease areas, it has been argued that their utilisation should increase. However, for any given cl...
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| Format: | Article |
| Language: | English |
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BMC
2020-01-01
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| Series: | BMC Cancer |
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| Online Access: | https://doi.org/10.1186/s12885-020-6525-0 |
| _version_ | 1818331111948812288 |
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| author | Michael J. Grayling James MS. Wason |
| author_facet | Michael J. Grayling James MS. Wason |
| author_sort | Michael J. Grayling |
| collection | DOAJ |
| description | Abstract Background Multi-arm designs provide an effective means of evaluating several treatments within the same clinical trial. Given the large number of treatments now available for testing in many disease areas, it has been argued that their utilisation should increase. However, for any given clinical trial there are numerous possible multi-arm designs that could be used, and choosing between them can be a difficult task. This task is complicated further by a lack of available easy-to-use software for designing multi-arm trials. Results To aid the wider implementation of multi-arm clinical trial designs, we have developed a web application for sample size calculation when using a variety of popular multiple comparison corrections. Furthermore, the application supports sample size calculation to control several varieties of power, as well as the determination of optimised arm-wise allocation ratios. It is built using the Shiny package in the R programming language, is free to access on any device with an internet browser, and requires no programming knowledge to use. It incorporates a variety of features to make it easier to use, including help boxes and warning messages. Using design parameters motivated by a recently completed phase II oncology trial, we demonstrate that the application can effectively determine and evaluate complex multi-arm trial designs. Conclusions The application provides the core information required by statisticians and clinicians to review the operating characteristics of a chosen multi-arm clinical trial design. The range of designs supported by the application is broader than other currently available software solutions. Its primary limitation, particularly from a regulatory agency point of view, is its lack of validation. However, we present an approach to efficiently confirming its results via simulation. |
| first_indexed | 2024-12-13T13:14:40Z |
| format | Article |
| id | doaj.art-f6a70e9dd2ad451592a8e85e7561d168 |
| institution | Directory Open Access Journal |
| issn | 1471-2407 |
| language | English |
| last_indexed | 2024-12-13T13:14:40Z |
| publishDate | 2020-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Cancer |
| spelling | doaj.art-f6a70e9dd2ad451592a8e85e7561d1682022-12-21T23:44:35ZengBMCBMC Cancer1471-24072020-01-0120111210.1186/s12885-020-6525-0A web application for the design of multi-arm clinical trialsMichael J. Grayling0James MS. Wason1Population Health Sciences InstitutePopulation Health Sciences InstituteAbstract Background Multi-arm designs provide an effective means of evaluating several treatments within the same clinical trial. Given the large number of treatments now available for testing in many disease areas, it has been argued that their utilisation should increase. However, for any given clinical trial there are numerous possible multi-arm designs that could be used, and choosing between them can be a difficult task. This task is complicated further by a lack of available easy-to-use software for designing multi-arm trials. Results To aid the wider implementation of multi-arm clinical trial designs, we have developed a web application for sample size calculation when using a variety of popular multiple comparison corrections. Furthermore, the application supports sample size calculation to control several varieties of power, as well as the determination of optimised arm-wise allocation ratios. It is built using the Shiny package in the R programming language, is free to access on any device with an internet browser, and requires no programming knowledge to use. It incorporates a variety of features to make it easier to use, including help boxes and warning messages. Using design parameters motivated by a recently completed phase II oncology trial, we demonstrate that the application can effectively determine and evaluate complex multi-arm trial designs. Conclusions The application provides the core information required by statisticians and clinicians to review the operating characteristics of a chosen multi-arm clinical trial design. The range of designs supported by the application is broader than other currently available software solutions. Its primary limitation, particularly from a regulatory agency point of view, is its lack of validation. However, we present an approach to efficiently confirming its results via simulation.https://doi.org/10.1186/s12885-020-6525-0False discovery rateFamilywise error-rateMultiple comparisonsOptimal designPowerSample size |
| spellingShingle | Michael J. Grayling James MS. Wason A web application for the design of multi-arm clinical trials BMC Cancer False discovery rate Familywise error-rate Multiple comparisons Optimal design Power Sample size |
| title | A web application for the design of multi-arm clinical trials |
| title_full | A web application for the design of multi-arm clinical trials |
| title_fullStr | A web application for the design of multi-arm clinical trials |
| title_full_unstemmed | A web application for the design of multi-arm clinical trials |
| title_short | A web application for the design of multi-arm clinical trials |
| title_sort | web application for the design of multi arm clinical trials |
| topic | False discovery rate Familywise error-rate Multiple comparisons Optimal design Power Sample size |
| url | https://doi.org/10.1186/s12885-020-6525-0 |
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