Use of likelihood estimates for variances for the design and evaluation of multiregional clinical trials with heterogeneous variances
Abstract Globalized drug development studies, such as multiregional clinical trials (MRCTs), have attracted much attention due to their ability to expedite drug development and shorten the time lag of drug release. While observing the overall effect of a new drug, the region‐specific effects to support drug registration in constituent regions can also be evaluated. Several challenges arise in conducting MRCTs, such as the heterogeneity in the variability of the primary endpoint across regions. However, most of the existing statistical methods assume a common variability, which may not be valid in practice due to differences across regions (eg, diversities in ethnicity or disparities in medical culture/practice). We present a statistical method for the design and evaluation of MRCTs to consider the heterogeneous variability across regions. We assessed the overall sample size requirement and addressed the region‐specific sample size determination to establish the consistency of treatment effects between the specific region and the entire group. We demonstrate the proposed approach with numerical examples..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:41 |
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| Enthalten in: |
Statistics in Medicine - 41(2022), 1, Seite 87-107 |
| Beteiligte Personen: |
Wu, Yuh‐Jenn [VerfasserIn] |
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| BKL: |
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| Anmerkungen: |
© 2022 John Wiley & Sons, Ltd. |
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| Umfang: |
21 |
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| doi: |
10.1002/sim.9224 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a Abstract Globalized drug development studies, such as multiregional clinical trials (MRCTs), have attracted much attention due to their ability to expedite drug development and shorten the time lag of drug release. While observing the overall effect of a new drug, the region‐specific effects to support drug registration in constituent regions can also be evaluated. Several challenges arise in conducting MRCTs, such as the heterogeneity in the variability of the primary endpoint across regions. However, most of the existing statistical methods assume a common variability, which may not be valid in practice due to differences across regions (eg, diversities in ethnicity or disparities in medical culture/practice). We present a statistical method for the design and evaluation of MRCTs to consider the heterogeneous variability across regions. We assessed the overall sample size requirement and addressed the region‐specific sample size determination to establish the consistency of treatment effects between the specific region and the entire group. We demonstrate the proposed approach with numerical examples. | ||
| 700 | 1 | |a Cheng, Yu‐Chieh |4 aut | |
| 700 | 1 | |a Chiang, Chieh |4 aut | |
| 700 | 1 | |a Cheng, Li‐Hsueh |4 aut | |
| 700 | 1 | |a Liu, Ching‐Ti |4 aut | |
| 700 | 1 | |a Hsiao, Chin‐Fu |4 aut | |
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