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Reference datasets for bioequivalence trials in a two-group parallel design.

ABSTRACT: In order to help companies qualify and validate the software used to evaluate bioequivalence trials with two parallel treatment groups, this work aims to define datasets with known results. This paper puts a total 11 datasets into the public domain along with proposed consensus obtained via evaluations from six different software packages (R, SAS, WinNonlin, OpenOffice Calc, Kinetica, EquivTest). Insofar as possible, datasets were evaluated with and without the assumption of equal variances for the construction of a 90% confidence interval. Not all software packages provide functionality for the assumption of unequal variances (EquivTest, Kinetica), and not all packages can handle datasets with more than 1000 subjects per group (WinNonlin). Where results could be obtained across all packages, one showed questionable results when datasets contained unequal group sizes (Kinetica). A proposal is made for the results that should be used as validation targets.

SUBMITTER: Fuglsang A

PROVIDER: S-EPMC4365103 | biostudies-other | 2015 Mar

REPOSITORIES: biostudies-other

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Reference datasets for bioequivalence trials in a two-group parallel design.

Fuglsang Anders A Schütz Helmut H Labes Detlew D

The AAPS journal 20141209 2

In order to help companies qualify and validate the software used to evaluate bioequivalence trials with two parallel treatment groups, this work aims to define datasets with known results. This paper puts a total 11 datasets into the public domain along with proposed consensus obtained via evaluations from six different software packages (R, SAS, WinNonlin, OpenOffice Calc, Kinetica, EquivTest). Insofar as possible, datasets were evaluated with and without the assumption of equal variances for ...[more]

PMID: 25488055

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Project description:BackgroundThe smallest difference to be detected in superiority trials or the largest difference to be ruled out in noninferiority trials is a key determinant of sample size, but little guidance exists to help researchers in their choice. The objectives were to examine the distribution of differences that researchers aim to detect in clinical trials and to verify that those differences are smaller in noninferiority compared to superiority trials.MethodsCross-sectional study based on a random sample of two hundred two-arm, parallel group superiority (100) and noninferiority (100) randomized clinical trials published between 2004 and 2009 in 27 leading medical journals. The main outcome measure was the smallest difference in favor of the new treatment to be detected (superiority trials) or largest unfavorable difference to be ruled out (noninferiority trials) used for sample size computation, expressed as standardized difference in proportions, or standardized difference in means. Student t test and analysis of variance were used.ResultsThe differences to be detected or ruled out varied considerably from one study to the next; e.g., for superiority trials, the standardized difference in means ranged from 0.007 to 0.87, and the standardized difference in proportions from 0.04 to 1.56. On average, superiority trials were designed to detect larger differences than noninferiority trials (standardized difference in proportions: mean 0.37 versus 0.27, P = 0.001; standardized difference in means: 0.56 versus 0.40, P = 0.006). Standardized differences were lower for mortality than for other outcomes, and lower in cardiovascular trials than in other research areas.ConclusionsSuperiority trials are designed to detect larger differences than noninferiority trials are designed to rule out. The variability between studies is considerable and is partly explained by the type of outcome and the medical context. A more explicit and rational approach to choosing the difference to be detected or to be ruled out in clinical trials may be desirable.

Project description:IntroductionSomapacitan is a long-acting growth hormone (GH) derivative being developed for once-weekly dosing in patients with GH deficiency (GHD). Our objective was to evaluate the impact of kidney or hepatic impairment on somapacitan exposure in adults.MethodsIn two open-label, parallel-group, single-center, 6-week trials, eligible subjects (18-75 years of age, body mass index 18.5-34.9 kg/m2, GH-naïve, without GHD) were divided into five kidney (total n = 44) or three hepatic (n = 34) function groups. Subjects with normal kidney/hepatic function were matched to those with kidney/hepatic impairment by age, sex, and body weight. Subjects received three subcutaneous somapacitan administrations (0.08 mg/kg) on days 1, 8, and 15. Blood samples were collected before each dose, at 28 time points throughout 2 weeks after the last dose, and at follow-up (3-4 weeks after the last dose). The primary endpoint was area under the somapacitan serum concentration-time curve up to 1 week after the last dose (AUC0-168 h), while secondary endpoints included AUC0-168 h of insulin-like growth factor (IGF)-I.ResultsIn the kidney impairment trial, somapacitan AUC0-168 h was higher in groups with severe kidney impairment and requiring hemodialysis versus the normal kidney function group (estimated ratio and 90% confidence interval 1.75 [1.00-3.06] and 1.63 [1.01-2.61], respectively). AUC0-168 h of IGF-I was increased in the moderate impairment group (1.35 [1.09-1.66]), severe impairment group (1.40 [1.10-1.78]), and requiring hemodialysis group (1.24 [1.01-1.52]), compared with the normal function group. In the hepatic impairment trial, somapacitan AUC0-168 h was significantly higher in the moderate impairment group compared with the normal hepatic function group (4.69 [2.92-7.52]). IGF-I AUC0-168 h was lower in both hepatic impairment groups (0.85 [0.67-1.08] for the mild impairment group and 0.75 [0.60-0.95] for the moderate impairment group) compared with the normal function group. No new safety or tolerability issues were observed.ConclusionsIn summary, somapacitan exposure increased with level of kidney/hepatic impairment. Clinically, this will be taken into account when treating adults with GHD with somapacitan, as doses should be individually titrated.Clinical trial registrationNCT03186495 (kidney impairment trial, registered 12 June 2017); NCT03212131 (hepatic impairment trial, registered 30 June 2017).

Project description:Currently, a growing placebo response rate has been observed in clinical trials for antidepressant drugs, a phenomenon that has made it increasingly difficult to demonstrate efficacy. The sequential parallel comparison design (SPCD) is a clinical trial design that was proposed to address this issue. The SPCD theoretically has the potential to reduce the sample-size requirement for a clinical trial and to simultaneously enrich the study population to be less responsive to the placebo.Because the basic SPCD already reduces the placebo response by removing placebo responders between the first and second phases of a trial, the purpose of this study was to examine whether we can further improve the efficiency of the basic SPCD and whether we can do so when the projected underlying drug and placebo response rates differ considerably from the actual ones.Three adaptive designs that used interim analyses to readjust the length of study duration for individual patients were tested to reduce the sample-size requirement or increase the statistical power of the SPCD. Various simulations of clinical trials using the SPCD with interim analyses were conducted to test these designs through calculations of empirical power.From the simulations, we found that the adaptive designs can recover unnecessary resources spent in the traditional SPCD trial format with overestimated initial sample sizes and provide moderate gains in power. Under the first design, results showed up to a 25% reduction in person-days, with most power losses below 5%. In the second design, results showed up to a 8% reduction in person-days with negligible loss of power. In the third design using sample-size re-estimation, up to 25% power was recovered from underestimated sample-size scenarios.Given the numerous possible test parameters that could have been chosen for the simulations, the study's results are limited to situations described by the parameters that were used and may not generalize to all possible scenarios. Furthermore, dropout of patients is not considered in this study.It is possible to make an already complex design such as the SPCD adaptive, and thus more efficient, potentially overcoming the problem of placebo response at lower cost. Ultimately, such a design may expedite the approval of future effective treatments.

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Reference datasets for bioequivalence trials in a two-group parallel design.

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Reference datasets for bioequivalence trials in a two-group parallel design.

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