100,949 research outputs found
Blinded Sample Size Reestimation with Negative Binomial Counts in Superiority and Non-inferiority Trials
No full textSummary
Background: In the planning of clinical trials with count outcomes such as the number of exacerbations in chronic obstructive pulmonary disease (COPD) often considerable uncertainty exists with regard to the overall event rate and the level of overdispersion which are both crucial for sample size calculations.
Objectives: To develop a sample size reestimation strategy that maintains the blinding of the trial, controls the type I error rate and is robust against misspecification of the nuisance parameters in the planning phase in that the actual power is close to the target.
Methods: The operation characteristics of the developed sample size reestimation procedure are investigated in a Monte Carlo simulation study.
Results: Estimators of the overall event rate and the overdispersion parameter that do not require unblinding can be used to effectively adjust the sample size without inflating the type I error rate while providing power values close to the target.
Conclusions: If only little information is available regarding the size of the overall event rate and the overdispersion parameter in the design phase of a trial, we recommend the use of a design with sample size reestimation as the one suggested here. Trials in COPD are expected to benefit from the proposed sample size reestimation strategy.</jats:p
Blinded sample size reestimation with count data: Methods and applications in multiple sclerosis
No full textSample size estimation in clinical trials depends critically on nuisance parameters, such as variances or overall event rates, which have to be guessed or estimated from previous studies in the planning phase of a trial. Blinded sample size reestimation estimates these nuisance parameters based on blinded data from the ongoing trial, and allows to adjust the sample size based on the acquired information. In the present paper, this methodology is developed for clinical trials with count data as the primary endpoint. In multiple sclerosis such endpoints are commonly used in phase 2 trials (lesion counts in magnetic resonance imaging (MRI)) and phase 3 trials (relapse counts). Sample size adjustment formulas are presented for both Poisson-distributed data and for overdispersed Poisson-distributed data. The latter arise from sometimes considerable between-patient heterogeneity, which can be observed in particular in MRI lesion counts. The operation characteristics of the procedure are evaluated by simulations and recommendations on how to choose the size of the internal pilot study are given. The results suggest that blinded sample size reestimation for count data maintains the required power without an increase in the type I error. Copyright (C) 2010 John Wiley & Sons, Ltd
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No full textdel Sige. TelemannScore: 6f., Manuscript copy: 1723 (1723p), Schreiber: Copyist [Ascertained], 11 parts - S, A, T, B, vl 1, 2, vlc (2x), bc, ob 1, 2 - 1, 1, 2, 2, 2, 2, 2, 2, 2, 1, 1f., Manuscript copy: 1723 (1723p); 21 (21,5) x 33,5 (35) cm, Schreiber: Bodinus, Johann Christoph , 2 parts - vla, org, Manuscript copy: 1723 (1723p), Schreiber: Copyist, part - org, Manuscript copy, Schreiber: Seibert, Johann Conrad . - Besetzung: S, A, T, B, vl (2), vla, vlc, ob (2), org. - Bemerkungen: org in A und G, bc in G. - Bemerkungen zu den Aufführungen: Performance date: 1724 Hamburg (Quelle: RISM)Friede, Friede! Jesus lebtFriede, Jesus leb
Sample size reestimation for clinical trials with longitudinal negative binomial counts including time trends
No full textIn some diseases, such as multiple sclerosis, lesion counts obtained from magnetic resonance imaging (MRI) are used as markers of disease progression. This leads to longitudinal, and typically overdispersed, count data outcomes in clinical trials. Models for such data invariably include a number of nuisance parameters, which can be difficult to specify at the planning stage, leading to considerable uncertainty in sample size specification. Consequently, blinded sample size re‐estimation procedures are used, allowing for an adjustment of the sample size within an ongoing trial by estimating relevant nuisance parameters at an interim point, without compromising trial integrity. To date, the methods available for re‐estimation have required an assumption that the mean count is time‐constant within patients. We propose a new modeling approach that maintains the advantages of established procedures but allows for general underlying and treatment‐specific time trends in the mean response. A simulation study is conducted to assess the effectiveness of blinded sample size re‐estimation methods over fixed designs. Sample sizes attained through blinded sample size re‐estimation procedures are shown to maintain the desired study power without inflating the Type I error rate and the procedure is demonstrated on MRI data from a recent study in multiple sclerosis.Deutsche Forschungsgemeinschaft https://doi.org/10.13039/50110000165
A conditional error function approach for adaptive enrichment designs with continuous endpoints
No full textAdaptive enrichment designs offer an efficient and flexible way to demonstrate the efficacy of a treatment in a clinically defined full population or in, eg, biomarker‐defined subpopulations while controlling the family‐wise Type I error rate in the strong sense. Frequently used testing strategies in designs with two or more stages include the combination test and the conditional error function approach. Here, we focus on the latter and present some extensions. In contrast to previous work, we allow for multiple subgroups rather than one subgroup only. For nested as well as nonoverlapping subgroups with normally distributed endpoints, we explore the effect of estimating the variances in the subpopulations. Instead of using a normal approximation, we derive new t ‐distribution–based methods for two different scenarios. First, in the case of equal variances across the subpopulations, we present exact results using a multivariate t ‐distribution. Second, in the case of potentially varying variances across subgroups, we provide some improved approximations compared to the normal approximation. The performance of the proposed conditional error function approaches is assessed and compared to the combination test in a simulation study. The proposed methods are motivated by an example in pulmonary arterial hypertension.Bundesministerium für Bildung und Forschung https://doi.org/10.13039/501100002347Deutsches Zentrum für Herz-Kreislaufforschung https://doi.org/10.13039/10001044
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A comparison of methods for treatment selection in seamless phase II/III clinical trials incorporating information on short-term endpoints
No full textIn an adaptive seamless phase II/III clinical trial interim
analysis data are used for treatment selection, enabling resources to be focussed on comparison of more effective treatment(s) with a control. In this paper we compare two methods recently proposed to enable use of short-term endpoint data for decision-making at the interim analysis. The comparison focusses on the power and the probability of correctly identifying the most promising treatment. We show that the choice of method depends on how well short-term data predict the best treatment, which may be measured by the correlation between treatment effects on short-term and long-term endpoints
T-wave loop area from a pre-implant 12-lead ECG is associated with appropriate ICD shocks
No full textAims:
In implantable cardioverter-defibrillator (ICD) patients, predictors of ICD shocks and mortality are needed to improve patient selection. Electrocardiographic (ECG) markers are simple to obtain and have been demonstrated to predict mortality. We aimed to assess the association of T-wave loop area and circularity with ICD shocks.
Methods:
The study investigated patients with ICDs implanted between 1998 and 2010 for whom digital 12-lead ECGs (Schiller CS200 ECG-Network) of sufficient quality were obtained within 1 month prior to the implantation. T-wave loop area and circularity were calculated. Follow-up data of appropriate shocks were obtained during ICD clinic visits that included reviews of device stored electrograms.
Results:
A total of 605 patients (82% males) were included; 68% had ischemic cardiomyopathy and 72% were treated for primary prevention. Over 3.8±1.4 years of follow-up, 114 patients (19%) experienced appropriate shock(s). Those with smaller T-wave loop area received fewer shocks (TLA, hazard ratio, HR, per increase of 1 technical unit, 0.71; [95% confidence interval, 0.53–0.94]; P = 0.02) and those with larger T-wave loop circularity (TLC) representing rounder T wave loop received more shocks (HR per 1% TLC increase 2.96; [0.85–10.36]; P = 0.09). When the quartile containing the largest TLA and TLC values, respectively, were compared to the remaining cases, TLA remained significantly associated with fewer and TLC with more frequent shocks also after multivariate adjustment for clinical variables (HR, 0.59 [0.35–0.99], P = 0.044; and 1.64 [1.08–2.49], P = 0.021, respectively).
Conclusions:
The size and shape of the T-wave loop calculated from pre-implantation 12-lead ECGs are associated with appropriate ICD shocks
Idiopatic macular hole: Correlation between optical coherence tomography findings and scanning laser ophthalmoscope mircoperimery data
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