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

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Personalized medicine claims of individual response differences are often misleading due to random variation. True differences require comparing intervention and comparator arms

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Area of Science:

  • Physiology
  • Biostatistics
  • Personalized Medicine

Background:

  • Personalized medicine aims to tailor interventions based on individual responses.
  • Common analyses often overstate individual differences in response.
  • Within-subject random variation can obscure true interindividual differences.

Purpose of the Study:

  • To scrutinize common methods for quantifying individual response differences in personalized medicine.
  • To highlight the impact of random variation and regression to the mean.
  • To present appropriate designs and analyses for quantifying true interindividual variation.

Main Methods:

  • Analysis of common plots and statistical approaches for individual response.
  • Use of a simulated dataset of blood pressure measurements.
  • Comparison of standard deviation (SD) of changes between intervention and comparator arms.

Main Results:

  • Popular plots can exaggerate individual differences due to random variation and regression to the mean.
  • True individual response differences are only quantifiable by comparing SDs of changes between arms.
  • Clinically unimportant individual differences are often reported as significant.

Conclusions:

  • Many current personalized medicine analyses are flawed by not accounting for random variation.
  • Comparing SDs between intervention and comparator arms is crucial for valid quantification of interindividual differences.
  • Further exploration of moderators/mediators is only warranted if true differences are clinically relevant.