Rights statement: This is an Accepted Manuscript of an article published by Taylor & Francis in Statistics in Biopharmaceutical Research on 02/08/2022, available online: http://www.tandfonline.com/10.1080/19466315.2022.2107565
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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - An alternative to traditional sample size determination for small patient populations
AU - Jackson, Holly
AU - Jaki, Thomas
N1 - This is an Accepted Manuscript of an article published by Taylor & Francis in Statistics in Biopharmaceutical Research on 02/08/2022, available online: http://www.tandfonline.com/10.1080/19466315.2022.2107565
PY - 2023/7/3
Y1 - 2023/7/3
N2 - The majority of phase III clinical trials use a 2-arm randomized controlled trial with 50% allocation between the control treatment and experimental treatment. The sample size calculated for these clinical trials normally guarantee a power of at least 80% for a certain Type I error, usually 5%. However, these sample size calculations, do not typically take into account the total patient population that may benefit from the treatment investigated. In this article, we discuss two methods, which optimize the sample size of phase III clinical trial designs, to maximize the benefit to patients for the total patient population. We do this for trials that use a continuous endpoint, when the total patient population is small (i.e., for rare diseases). One approach uses a point estimate for the treatment effect to optimize the sample size and the second uses a distribution on the treatment effect in order to account for the uncertainty in the estimated treatment effect. Both one-stage and two-stage clinical trials, using three different stopping boundaries are investigated and compared, using efficacy and ethical measures. A completed clinical trial in patients with anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis is used to demonstrate the use of the method. Supplementary materials for this article are available online.
AB - The majority of phase III clinical trials use a 2-arm randomized controlled trial with 50% allocation between the control treatment and experimental treatment. The sample size calculated for these clinical trials normally guarantee a power of at least 80% for a certain Type I error, usually 5%. However, these sample size calculations, do not typically take into account the total patient population that may benefit from the treatment investigated. In this article, we discuss two methods, which optimize the sample size of phase III clinical trial designs, to maximize the benefit to patients for the total patient population. We do this for trials that use a continuous endpoint, when the total patient population is small (i.e., for rare diseases). One approach uses a point estimate for the treatment effect to optimize the sample size and the second uses a distribution on the treatment effect in order to account for the uncertainty in the estimated treatment effect. Both one-stage and two-stage clinical trials, using three different stopping boundaries are investigated and compared, using efficacy and ethical measures. A completed clinical trial in patients with anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis is used to demonstrate the use of the method. Supplementary materials for this article are available online.
KW - continuous response
KW - patient benefit
KW - rare disease
KW - sequential design
U2 - 10.1080/19466315.2022.2107565
DO - 10.1080/19466315.2022.2107565
M3 - Journal article
VL - 15
SP - 596
EP - 607
JO - Statistics in Biopharmaceutical Research
JF - Statistics in Biopharmaceutical Research
SN - 1946-6315
IS - 3
ER -