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- Miller, Frank, 1971-, et al.
(författare)
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Sample size re-estimation and continuous monitoring of the variance in longitudinal trials
- 2014
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Ingår i: Adaptive Designs & Multiple Testing Procedures. ; , s. 21-21
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- In many clinical trials, frequent longitudinal data is collected from each patient. For example in chronic pain trials, daily pain measurements of the patients can be collected during several weeks which leads to a large number of highly correlated post-baseline measurements for each patient.Blinded sample size re-estimation or continuous monitoring of the variance (Friede and Miller, 2012) can deal with situations where uncertainty regarding the true variance exists. In trials with longitudinal data, the situation is common that at interim looks a restricted number of patients have completed the study but a large number has started treatment and first post-baseline data is collected but endpoint data is not yet available. Nevertheless, it is reasonable that the partial data available from these patients gives useful information about the variance of the endpoint (Wüst and Kieser, 2003; Wachtlin and Kieser, 2013).In this talk, we first quantify the gain of including partial data from patients when estimating the variance. Variability of sample size is often reduced but the amount of reduction depends on the correlation between measurements. Then, our main interest is to investigate the usefulness of a parametric model assumption for the covariance structure. We quantify the gain from the model assumption when the assumed model is correct and discuss consequences when a wrong model is assumed.
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| 2. |
- Ondra, Thomas, et al.
(författare)
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Methods for identification and confirmation of targeted subgroups in clinical trials : A systematic review
- 2016
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Ingår i: Journal of Biopharmaceutical Statistics. - : Informa UK Limited. - 1054-3406 .- 1520-5711. ; 26:1, s. 99-119
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Tidskriftsartikel (refereegranskat)abstract
- Important objectives in the development of stratified medicines include the identification and confirmation of subgroups of patients with a beneficial treatment effect and a positive benefit-risk balance. We report the results of a literature review on methodological approaches to the design and analysis of clinical trials investigating a potential heterogeneity of treatment effects across subgroups. The identified approaches are classified based on certain characteristics of the proposed trial designs and analysis methods. We distinguish between exploratory and confirmatory subgroup analysis, frequentist, Bayesian and decision-theoretic approaches and, last, fixed-sample, group-sequential, and adaptive designs and illustrate the available trial designs and analysis strategies with published case studies.
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