Literature DB >> 20739334

Investigating variability in patient response to treatment--a case study from a replicate cross-over study.

Stephen Senn1, Katie Rolfe, Steven A Julious.   

Abstract

It is a common belief that individual variation in response to treatment is an important explanation for the variation in observed outcomes in clinical trials. If such variation is large, it seems reasonable to suppose that progress in treating disease will be advanced by classifying patients according to their abilities or not to 'respond' to particular treatments. We consider that there is currently a lost opportunity in drug development. There is a great deal of talk about individual response to treatment and tailor-made drugs. However, relatively little work is being done to formally investigate, using suitable designs, where individual response to treatment may be important. Through a case study from a replicate cross-over study we show how, given suitable replication, it is possible to isolate the component of variation corresponding to patient-by-treatment interaction and hence investigate the possibility of individual response to treatment.

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Year:  2010        PMID: 20739334     DOI: 10.1177/0962280210379174

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  17 in total

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Authors:  Scott J Dankel; Jeremy P Loenneke
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5.  Monitoring training and recovery responses with heart rate measures during standardized warm-up in elite badminton players.

Authors:  Christoph Schneider; Thimo Wiewelhove; Shaun J McLaren; Lucas Röleke; Hannes Käsbauer; Anne Hecksteden; Michael Kellmann; Mark Pfeiffer; Alexander Ferrauti
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6.  Demonstrating Heterogeneity of Treatment Effects Among Patients: An Overlooked but Important Step Toward Precision Medicine.

Authors:  Jennifer S Gewandter; Michael P McDermott; Hua He; Shan Gao; Xueya Cai; John T Farrar; Nathaniel P Katz; John D Markman; Stephen Senn; Dennis C Turk; Robert H Dworkin
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7.  Exercise training response heterogeneity: statistical insights.

Authors:  Greg Atkinson; Philip Williamson; Alan M Batterham
Journal:  Diabetologia       Date:  2017-11-15       Impact factor: 10.122

8.  Inter-Individual Responses of Maximal Oxygen Uptake to Exercise Training: A Critical Review.

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Journal:  Sports Med       Date:  2017-08       Impact factor: 11.136

Review 9.  Perspective: Application of N-of-1 Methods in Personalized Nutrition Research.

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10.  Mastering variation: variance components and personalised medicine.

Authors:  Stephen Senn
Journal:  Stat Med       Date:  2015-09-28       Impact factor: 2.373

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