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Point and Interval Estimators of the Target Dose in Clinical Dose-Finding Studies with Active Control.

Helms HJ, Benda N, Friede T - J Biopharm Stat (2014)

Bottom Line: The main focus of such studies often lies on the estimation of a target dose that leads to the same efficacy as the control.This article investigates the finite sample properties of the maximum likelihood estimation of the target dose and compares several approaches for constructing corresponding confidence intervals under the assumption of a linear dose-response curve and normal error terms.Furthermore, the impact of deviations from the model assumptions regarding the error distribution is explored.

View Article: PubMed Central - PubMed

Affiliation: a Department of Medical Statistics , University Medical Center Göttingen , Humboldtallee , Göttingen , Germany.

ABSTRACT
In a clinical dose finding study with active control a new drug with several dose levels is compared with an active comparator drug. The main focus of such studies often lies on the estimation of a target dose that leads to the same efficacy as the control. This article investigates the finite sample properties of the maximum likelihood estimation of the target dose and compares several approaches for constructing corresponding confidence intervals under the assumption of a linear dose-response curve and normal error terms. Furthermore, the impact of deviations from the model assumptions regarding the error distribution is explored.

No MeSH data available.


Related in: MedlinePlus

Voids/24 h decrease from baseline of the experimental drug dose levels and active control at the end of the study displayed as mean ± standard error (SE) reported in Chapple et al. (2004).
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Figure 0007: Voids/24 h decrease from baseline of the experimental drug dose levels and active control at the end of the study displayed as mean ± standard error (SE) reported in Chapple et al. (2004).

Mentions: In this section the methods introduced above are illustrated by a dose-finding study including placebo, four dose levels of Solifenacin (0, 2.5, 5, 10, 20 mg) and 2 mg Tolterodine as active control with sample sizes n = (n1,…, n5)′ = (36, 40, 37, 33, 34) and nac = 37 (Chapple et al., 2004). The primary endpoint is the reduction in “Voids/24 h” after 6 weeks from baseline. For the different dose levels and the active control only the mean values of the reduction in “Voids/24 h” are reported in Chapple et al. (2004). The standard deviation (SD) of the error terms is not displayed but can be calculated using the reported p-values of the test statistics which lead to σ ∈ [1.9, 2.5]. We used σ = 2 to evaluate this example. For the log(1+dose) the results of the study are summarized in Fig. 7 as mean responses and SEs. Even though the individual patient data are not available it is possible to calculate the estimator of the target dose as well as the confidence intervals of the ∆-method, the method of F&S, and the parametric bootstrap (Bootstrap) which only need the sample sizes, the mean responses, and the SD by using the SAS macro “DF_AC_LIN_MEAN.” The results of the confidence interval methods are shown in Table 2 for the target dose estimator . For some of the confidence intervals the lower interval limit was set to zero to guarantee a positive dose range. Further it is not possible to calculate the profile likelihood based interval on basis of the mean values alone. Therefore, a dataset was generated with identical mean responses and SD. It is somewhat surprising that with a total sample size of N = 217 it is only possible to exclude the maximum dose as potential target dose. The SAS macros for the linear dose-finding problem based on the raw data (DF_AC_LIN) as well as based on the mean values as presented here are available in the supplementary material.Table 2


Point and Interval Estimators of the Target Dose in Clinical Dose-Finding Studies with Active Control.

Helms HJ, Benda N, Friede T - J Biopharm Stat (2014)

Voids/24 h decrease from baseline of the experimental drug dose levels and active control at the end of the study displayed as mean ± standard error (SE) reported in Chapple et al. (2004).
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4566885&req=5

Figure 0007: Voids/24 h decrease from baseline of the experimental drug dose levels and active control at the end of the study displayed as mean ± standard error (SE) reported in Chapple et al. (2004).
Mentions: In this section the methods introduced above are illustrated by a dose-finding study including placebo, four dose levels of Solifenacin (0, 2.5, 5, 10, 20 mg) and 2 mg Tolterodine as active control with sample sizes n = (n1,…, n5)′ = (36, 40, 37, 33, 34) and nac = 37 (Chapple et al., 2004). The primary endpoint is the reduction in “Voids/24 h” after 6 weeks from baseline. For the different dose levels and the active control only the mean values of the reduction in “Voids/24 h” are reported in Chapple et al. (2004). The standard deviation (SD) of the error terms is not displayed but can be calculated using the reported p-values of the test statistics which lead to σ ∈ [1.9, 2.5]. We used σ = 2 to evaluate this example. For the log(1+dose) the results of the study are summarized in Fig. 7 as mean responses and SEs. Even though the individual patient data are not available it is possible to calculate the estimator of the target dose as well as the confidence intervals of the ∆-method, the method of F&S, and the parametric bootstrap (Bootstrap) which only need the sample sizes, the mean responses, and the SD by using the SAS macro “DF_AC_LIN_MEAN.” The results of the confidence interval methods are shown in Table 2 for the target dose estimator . For some of the confidence intervals the lower interval limit was set to zero to guarantee a positive dose range. Further it is not possible to calculate the profile likelihood based interval on basis of the mean values alone. Therefore, a dataset was generated with identical mean responses and SD. It is somewhat surprising that with a total sample size of N = 217 it is only possible to exclude the maximum dose as potential target dose. The SAS macros for the linear dose-finding problem based on the raw data (DF_AC_LIN) as well as based on the mean values as presented here are available in the supplementary material.Table 2

Bottom Line: The main focus of such studies often lies on the estimation of a target dose that leads to the same efficacy as the control.This article investigates the finite sample properties of the maximum likelihood estimation of the target dose and compares several approaches for constructing corresponding confidence intervals under the assumption of a linear dose-response curve and normal error terms.Furthermore, the impact of deviations from the model assumptions regarding the error distribution is explored.

View Article: PubMed Central - PubMed

Affiliation: a Department of Medical Statistics , University Medical Center Göttingen , Humboldtallee , Göttingen , Germany.

ABSTRACT
In a clinical dose finding study with active control a new drug with several dose levels is compared with an active comparator drug. The main focus of such studies often lies on the estimation of a target dose that leads to the same efficacy as the control. This article investigates the finite sample properties of the maximum likelihood estimation of the target dose and compares several approaches for constructing corresponding confidence intervals under the assumption of a linear dose-response curve and normal error terms. Furthermore, the impact of deviations from the model assumptions regarding the error distribution is explored.

No MeSH data available.


Related in: MedlinePlus