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Buyse M.,International Drug Development Institute | Buyse M.,Hasselt University
Statistics in Medicine | Year: 2010

This paper extends the idea behind the U-statistic of the Wilcoxon-Mann-Whitney test to perform generalized pairwise comparisons between two groups of observations. The observations are outcomes captured by a single variable, possibly repeatedly measured, or by several variables of any type (e.g. discrete, continuous, time to event). When several outcomes are considered, they must be prioritized. We show that generalized pairwise comparisons extend well-known non-parametric tests, and illustrate their interest using data from two randomized clinical trials. We also show that they lead to a general measure of the difference between the groups called the 'proportion in favor of treatment', denoted Δ, which is related to traditional measures of treatment effect for a single variable. Copyright © 2010 John Wiley & Sons, Ltd. Source


Buyse M.,International Drug Development Institute | Buyse M.,Hasselt University | Michiels S.,Institute Gustave Roussy
Current Opinion in Oncology | Year: 2013

PURPOSE OF REVIEW: The derivation of signatures using-omics technologies is increasingly integrated in the design of clinical trials in oncology. In this review, we investigate the clinical trial designs for the validation of prognostic and predictive signatures. RECENT FINDINGS: Using real-life breast cancer trial examples, we highlight the pros and cons of clinical utility designs for prognostic signatures. For predictive signatures, we first review alternative procedures to test the effect of treatment in the overall population as well as in the signature-positive or signature-negative subgroup. We proceed to show why the recent literature on signature-based strategy designs discourages the use of this design. We conclude by discussing adaptive signature designs to identify and validate a signature in a single trial using cross-validation techniques. SUMMARY: Use of-omics technologies should not be an add-on to clinical trials, it must become an integral part of their design. © 2013 Wolters Kluwer Health | Lippincott Williams &Wilkins. Source


Jackson T.L.,Kings College London | Shusterman E.M.,Oraya Therapeutics, Inc | Arnoldussen M.,Oraya Therapeutics, Inc | Chell E.,Oraya Therapeutics, Inc | And 2 more authors.
Retina | Year: 2015

PURPOSE:: To determine which patients respond best to stereotactic radiotherapy (SRT) for neovascular age-related macular degeneration. METHODS:: Participants (n = 230) receiving intravitreal anti-vascular endothelial growth factor injections for neovascular age-related macular degeneration enrolled in a randomized, double-masked sham-controlled trial comparing 16 Gray, 24 Gray, or Sham SRT. In a post hoc analysis, participants were grouped according to their baseline characteristics, to determine if these influenced SRT efficacy. RESULTS:: At 52 weeks, SRT was most effective for lesions ≤4 mm in greatest linear dimension and with a macular volume greater than the median value of 7.4 mm. For 26% of the participants with both these characteristics, SRT resulted in 55% fewer ranibizumab injections (2.08 vs. 4.60; P = 0.0002), a mean visual acuity change that was 5.33 letters superior to sham (+2.18 vs. -3.15 letters; P = 0.0284), and a 71.1-μm greater reduction in mean central subfield thickness (-122.6 vs. -51.5 μm; P = 0.027). Other features associated with a positive response to SRT included pigment epithelial detachment and the absence of fibrosis. CONCLUSION:: Stereotactic radiotherapy is most effective for neovascular age-related macular degeneration lesions that are actively leaking at the time of treatment, and no larger than the 4-mm treatment zone. Copyright © by Ophthamic Communications Society. Source


Buyse M.,International Drug Development Institute | Sargent D.J.,Cancer Center Statistics | Grothey A.,Rochester College | Matheson A.,Fondation ARCAD | De Gramont A.,HOpital Saint Antoine
Nature Reviews Clinical Oncology | Year: 2010

Biomarkers and surrogate end points have great potential for use in clinical oncology, but their statistical validation presents major challenges, and few biomarkers have been robustly confirmed. Provisional supportive data for prognostic biomarkers, which predict the likely outcome independently of treatment, is possible through small retrospective studies, but it has proved more difficult to achieve robust multi-site validation. Predictive biomarkers, which predict the likely response of patients to specific treatments, require more extensive data for validation, specifically large randomized clinical trials and meta-analysis. Surrogate end points are even more challenging to validate, and require data demonstrating both that the surrogate is prognostic for the true end point independently of treatment, and that the effect of treatment on the surrogate reliably predicts its effect on the true end point. In this Review, we discuss the nature of prognostic and predictive biomarkers and surrogate end points, and examine the statistical techniques and designs required for their validation. In cases where the statistical requirements for validation cannot be rigorously achieved, the biological plausibility of an end point or surrogate might support its adoption. No consensus yet exists on processes or standards for pragmatic evaluation and adoption of biomarkers and surrogate end points in the absence of robust statistical validation. © 2010 Macmillan Publishers Limited. All rights reserved. Source


Saad E.D.,University of Sao Paulo | Buyse M.,International Drug Development Institute
Acta Oncologica | Year: 2012

Background. Determining the non-inferiority margin is an essential step in the design and interpretation of non-inferiority trials, and this margin should be preferably justified on clinical and statistical grounds. Methods. After a PubMed search for phase III trials in advanced breast cancer (BC) or non-small cell lung cancer (NSCLC) published between January 1998 and December 2009 in 11 leading journals, non-inferiority trials were selected by manual search of the full papers. Results. Twenty-four of 195 trials had a primary non-inferiority hypothesis. When the two six-year study periods were compared, there were time trends within BC and NSCLC, with most non-inferiority trials in BC reported in the first six-year period, and vice-versa for NSCLC. The median sample size was larger for non-inferiority than superiority trials (p <0.01). The choice of a non-inferiority margin was reportedly justified in only five cases. Non-inferiority trials were more likely than superiority trials to yield positive results (p <0.001), as were trials in breast cancer (p 0.02). Conclusions. Non-inferiority margins for cancer trials appear to be chosen mostly on historical grounds. Since nearly three-quarters of non-inferiority trials achieve their primary objective, the extent to which the choice of margins has influence on trial results remains to be determined. © 2012 Informa Healthcare. Source

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