Predicting methylphenidate response in attention deficit hyperactivity disorder: a preliminary study

Blair A. Johnston (Lead / Corresponding author), David Coghill, Keith Matthews, J. Douglas Steele

    Research output: Contribution to journalArticle

    20 Citations (Scopus)

    Abstract

    Methylphenidate (MPH) is established as the main pharmacological treatment for patients with attention deficit hyperactivity disorder (ADHD). Whilst MPH is generally a highly effective treatment, not all patients respond, and some experience adverse reactions. Currently, there is no reliable method to predict how patients will respond, other than by exposure to a trial of medication. In this preliminary study, we sought to investigate whether an accurate predictor of clinical response to methylphenidate could be developed for individual patients, using sociodemographic, clinical and neuropsychological measures. Of the 43 boys with ADHD included in this proof-of-concept study, 30 were classed as responders and 13 as non-responders to MPH, with no significant differences in age nor verbal intelligence quotient (IQ) between the groups. Here we report the application of a multivariate analysis approach to the prediction of clinical response to MPH, which achieved an accuracy of 77% (p = 0.005). The most important variables to the classifier were performance on a 'go/no go' task and comorbid conduct disorder. This preliminary study suggested that further investigation is merited. Achieving a highly significant accuracy of 77% for the prediction of MPH response is an encouraging step towards finding a reliable and clinically useful method that could minimise the number of children needlessly being exposed to MPH.
    Original languageEnglish
    Pages (from-to)24-30
    Number of pages7
    JournalJournal of Psychopharmacology
    Volume29
    Issue number1
    DOIs
    Publication statusPublished - Jan 2015

    Fingerprint

    Methylphenidate
    Attention Deficit Disorder with Hyperactivity
    Conduct Disorder
    Intelligence
    Multivariate Analysis
    Pharmacology
    Therapeutics

    Keywords

    • ADHD
    • attention deficit hyperactivity disorder
    • children
    • conduct disorder
    • drug activity
    • drug sensitivity
    • methylphenidate
    • pattern recognition
    • predictive methods
    • therapeutic drugs

    Cite this

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    abstract = "Methylphenidate (MPH) is established as the main pharmacological treatment for patients with attention deficit hyperactivity disorder (ADHD). Whilst MPH is generally a highly effective treatment, not all patients respond, and some experience adverse reactions. Currently, there is no reliable method to predict how patients will respond, other than by exposure to a trial of medication. In this preliminary study, we sought to investigate whether an accurate predictor of clinical response to methylphenidate could be developed for individual patients, using sociodemographic, clinical and neuropsychological measures. Of the 43 boys with ADHD included in this proof-of-concept study, 30 were classed as responders and 13 as non-responders to MPH, with no significant differences in age nor verbal intelligence quotient (IQ) between the groups. Here we report the application of a multivariate analysis approach to the prediction of clinical response to MPH, which achieved an accuracy of 77{\%} (p = 0.005). The most important variables to the classifier were performance on a 'go/no go' task and comorbid conduct disorder. This preliminary study suggested that further investigation is merited. Achieving a highly significant accuracy of 77{\%} for the prediction of MPH response is an encouraging step towards finding a reliable and clinically useful method that could minimise the number of children needlessly being exposed to MPH.",
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    Predicting methylphenidate response in attention deficit hyperactivity disorder : a preliminary study. / Johnston, Blair A. (Lead / Corresponding author); Coghill, David; Matthews, Keith; Steele, J. Douglas.

    In: Journal of Psychopharmacology, Vol. 29, No. 1, 01.2015, p. 24-30.

    Research output: Contribution to journalArticle

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    AU - Coghill, David

    AU - Matthews, Keith

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