Literature DB >> 25823596

True and false interindividual differences in the physiological response to an intervention.

Greg Atkinson1, Alan M Batterham1.   

Abstract

NEW
FINDINGS: What is the topic of this review? In 'personalized medicine', various plots and analyses are purported to quantify individual differences in intervention response, identify responders/non-responders and explore response moderators or mediators. What advances does it highlight? We highlight the impact of within-subject random variation, which is inevitable even with 'gold-standard' measurement tools/protocols and sometimes so substantial that it explains all apparent individual response differences. True individual response differences are quantified only by comparing the SDs of changes between intervention and comparator arms. When these SDs are similar, true individual response differences are clinically unimportant and further analysis unwarranted. Within the 'hot topic' of personalized medicine, we scrutinize common approaches for presenting and quantifying individual differences in the physiological response to an intervention. First, we explain how popular plots used to present individual differences in response are contaminated by random within-subject variation and the regression to the mean artefact. Using a simulated data set of blood pressure measurements, we show that large individual differences in physiological response can be suggested by some plots and analyses, even when the true magnitude of response is exactly the same in all individuals. Second, we present the appropriate designs and analysis approaches for quantifying the true interindividual variation in physiological response. It is imperative to include a comparator arm/condition (or derive information from a prior relevant repeatability study) to quantify true interindividual differences in response. The most important statistic is the SD of changes in the intervention arm, which should be compared with the same SD in the comparator arm or from a prior repeatability study in the same population conducted over the same duration as the particular intervention. Only if the difference between these SDs is clinically relevant is it logical to go on to explore any moderators or mediators of the intervention effect that might explain the individual response. To date, very few researchers have compared these SDs before making claims about individual differences in physiological response and their importance to personalized medicine.
© 2015 The Authors. Experimental Physiology © 2015 The Physiological Society.

Entities:  

Mesh:

Year:  2015        PMID: 25823596     DOI: 10.1113/EP085070

Source DB:  PubMed          Journal:  Exp Physiol        ISSN: 0958-0670            Impact factor:   2.969


  59 in total

1.  True Interindividual Variability Exists in Postprandial Appetite Responses in Healthy Men But Is Not Moderated by the FTO Genotype.

Authors:  Fernanda R Goltz; Alice E Thackray; Greg Atkinson; Lorenzo Lolli; James A King; James L Dorling; Monika Dowejko; Sarabjit Mastana; David J Stensel
Journal:  J Nutr       Date:  2019-07-01       Impact factor: 4.798

2.  A Method to Stop Analyzing Random Error and Start Analyzing Differential Responders to Exercise.

Authors:  Scott J Dankel; Jeremy P Loenneke
Journal:  Sports Med       Date:  2020-02       Impact factor: 11.136

3.  Time-course changes associated with PA lumbar mobilizations on lumbar and hamstring range of motion: a randomized controlled crossover trial.

Authors:  Paul Chesterton; William Evans; Nick Livadas; Shaun J McLaren
Journal:  J Man Manip Ther       Date:  2018-11-13

Review 4.  The Importance of Resistance Exercise Training to Combat Neuromuscular Aging.

Authors:  Kaleen M Lavin; Brandon M Roberts; Christopher S Fry; Tatiana Moro; Blake B Rasmussen; Marcas M Bamman
Journal:  Physiology (Bethesda)       Date:  2019-03-01

5.  Exercise-Induced Changes in Muscle Size do not Contribute to Exercise-Induced Changes in Muscle Strength.

Authors:  Jeremy P Loenneke; Samuel L Buckner; Scott J Dankel; Takashi Abe
Journal:  Sports Med       Date:  2019-07       Impact factor: 11.136

Review 6.  Energetics and Biomechanics of Running Footwear with Increased Longitudinal Bending Stiffness: A Narrative Review.

Authors:  Justin A Ortega; Laura A Healey; Wannes Swinnen; Wouter Hoogkamer
Journal:  Sports Med       Date:  2021-04-08       Impact factor: 11.136

Review 7.  Antioxidants in Personalized Nutrition and Exercise.

Authors:  Nikos V Margaritelis; Vassilis Paschalis; Anastasios A Theodorou; Antonios Kyparos; Michalis G Nikolaidis
Journal:  Adv Nutr       Date:  2018-11-01       Impact factor: 8.701

8.  Exercise dose and individual response of healthy adults: is it time to re-evaluate exercise responsiveness and training recommendations?

Authors:  Raffaele Mazzolari
Journal:  J Physiol       Date:  2018-08       Impact factor: 5.182

9.  Impairment of body mass reduction-associated activation of brown/beige adipose tissue in patients with type 2 diabetes mellitus.

Authors:  S Rodovalho; B Rachid; J C De-Lima-Junior; S van de Sande-Lee; J Morari; H M Carvalho; B J Amorim; A J Tincani; E Chaim; J C Pareja; M J Saad; F Folli; C D Ramos; B Geloneze; L A Velloso
Journal:  Int J Obes (Lond)       Date:  2017-07-03       Impact factor: 5.095

10.  Correlations Do Not Show Cause and Effect: Not Even for Changes in Muscle Size and Strength.

Authors:  Scott J Dankel; Samuel L Buckner; Matthew B Jessee; J Grant Mouser; Kevin T Mattocks; Takashi Abe; Jeremy P Loenneke
Journal:  Sports Med       Date:  2018-01       Impact factor: 11.136

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