1,721,370 research outputs found
Commentary on Bamat et al
No full textSaad, ED (corresponding author), Int Inst Drug Dev, Ave Prov 3, Louvain La Neuve, Belgium.
[email protected]
Response to the letter to the editor 'Reply to "Statistical controversies in clinical research: end points other than survival are vital for regulatory approval of anticancer agents" by H. K. van Halteren'
No full text6. Yoon SH, Kim KW, Goo JM, Kim DW, Hahn S. Observer variability in RECIST-based tumour burden measurements: a meta-analysis. Eur J Cancer 2016; 53: 5-15. 7. Marten K, Auer F, Schmidt S et al. Inadequacy of manual measurements compared to automated CT volumetry in assessment of treatment response of pulmonary metastases using RECIST criteria. Eu
From non-inferiority to superiority: the shift towards patient-centric outcomes
No full textThe recently published REC-CAGEFREEI trial 1 provides an interesting example of non-inferiority vs. superiority design of clinical trials. The trial failed to show non-inferiority (P = 0.65) of drug-coated balloon angioplasty (with the option of rescue stenting) to the intended deployment of drug-eluting stents on the primary composite endpoint of car-diovascular death, target vessel myocardial infarction, and target lesion revascularization. However, not the result, but the motivation and reporting on the trial draw our attention (Figure 1). Non-inferiority designs aim to show that a novel therapy is not worse than a standard of care by more than a pre-specified non-inferiority margin on an efficacy outcome. This margin represents an acceptable loss on efficacy, which is justified by a putative advantage of the novel therapy on patient outcomes other than efficacy, such as improved safety, better quality of life, more convenient administration, or lower cost. A non-inferiority design should thus be motivated by a clear advantage. In stent trials, for example, a short-term reduction i
Acoramidis in Transthyretin Amyloid Cardiomyopathy
No full textTo the Editor: In a phase 3 trial of acoramidis for transthyretin amyloid cardiomyopathy, Gillmore et al. (Jan. 11 issue)(1) used the Finkelstein-Schoenfeld test to assess the hierarchical composite primary outcome. They expressed the treatment effect as a win ratio, thereby following the initial presentation of the analysis of a prioritized outcome.(2) However, the generalized pairwise comparison method, to which the Finkelstein-Schoenfeld test and the win ratio belong, has evolved substantially since this first application.(3) To aid the interpretation of the results, it is now recommended that the proportions of wins and losses for each outcome are reported to understand the . .
A Poisson approach to the validation of failure time surrogate endpoints in individual patient data meta-analyses
No full textSurrogate endpoints are often used in clinical trials instead of well-established hard endpoints for practical convenience. The meta-analytic approach relies on two measures of surrogacy: one at the individual level and one at the trial level. In the survival data setting, a two-step model based on copulas is commonly used. We present a new approach which employs a bivariate survival model with an individual random effect shared between the two endpoints and correlated treatment-by-trial interactions. We fit this model using auxiliary mixed Poisson models. We study via simulations the operating characteristics of this mixed Poisson approach as compared to the two-step copula approach. We illustrate the application of the methods on two individual patient data meta-analyses in gastric cancer, in the advanced setting (4069 patients from 20 randomized trials) and in the adjuvant setting (3288 patients from 14 randomized trials).The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The present work has been supported by the Institut National du Cancer (INCa), Grant SHS 2014-141, and by the Ligue Nationale Contre le Cancer. The study sponsors had no involvement in either the study design; the collection, analysis, and interpretation of data; the writing of the manuscript; nor in the decision to submit the manuscript for publication
Challenges in the methodology for the validation of surrogate endpoints in randomized trials
No full textThe validation of surrogate endpoints has been studied by Prentice (1989). He presented a definition as well as a set of criteria that are equivalent if the surrogate and true endpoints are binary. Freedman (1992) supplemented these
criteria with the so-called proportion explained. Buyse and Molenberghs (1998) proposed to replace the proportion explained by two quantities: (1) the relative effect linking the effect of treatment on both endpoints and (2) the adjusted association, an individual-level measure of agreement between both endpoints. In this paper, we argue that a meta-analytic approach should be adopted because
it overcomes difficulties which necessarily surround validation efforts based on a single trial
Evaluation of failure time surrogate endpoints in individual patient data meta-analyses of randomized clinical trials. A poisson approach
No full textDetection of Outlying Correlation Coefficients in Multicenter Clinical Trials
No full textCentral statistical monitoring aims at finding centers whose data distribution differs significantly from the other centers in multicentric clinical trials. Such differences may point to data quality issues due to negligence, misconduct, or fraud. Data distributions can be compared across centers in many different ways, depending on the type of data (e.g., numerical or categorical), whether a univariate or a multivariate comparison is performed, and so on. In that framework, we present two methods aimed at detecting centers with outlying bivariate Pearson correlation coefficients. One of the methods directly compares the correlations across centers. The other method conditions the test on one of the marginal standard deviations, which makes the test on correlation independent of the centers' standard deviations. Both methods are shown to perform equally well on simulated data. They are also applied on real world data, where they identify centers with outlying correlations. The findings of the two tests are compared, showing that they concord for centers with average standard deviations, but differ for centers with extreme standard deviations. While the focus here is on central statistical monitoring, the methods are general and can be used in other settings.The authors thank Drs Akhtar-Danesh and Dehghan-Kooshkghazi for providing the datasets of fabricated data used in Section 5.1 of this paper
Challenges in the methodology for the validation of surrogate endpoints in randomized trials
No full textThe validation of surrogate endpoints has been studied by Prentice (1989). He presented a definition as well as a set of criteria that are equivalent if the surrogate and true endpoints are binary. Freedman (1992) supplemented these
criteria with the so-called proportion explained. Buyse and Molenberghs (1998) proposed to replace the proportion explained by two quantities: (1) the relative effect linking the effect of treatment on both endpoints and (2) the adjusted association, an individual-level measure of agreement between both endpoints. In this paper, we argue that a meta-analytic approach should be adopted because
it overcomes difficulties which necessarily surround validation efforts based on a single trial
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