Accounting for behavior in treatment effects

New applications for blind trials

Sylvain Chassang, Erik Snowberg, Ben Seymour, Cayley Bowles

    Research output: Contribution to journalArticle

    Abstract

    The double-blind randomized controlled trial (DBRCT) is the gold standard of medical research. We show that DBRCTs fail to fully account for the efficacy of treatment if there are interactions between treatment and behavior, for example, if a treatment is more effective when patients change their exercise or diet. Since behavioral or placebo effects depend on patients' beliefs that they are receiving treatment, clinical trials with a single probability of treatment are poorly suited to estimate the additional treatment benefit that arises from such interactions. Here, we propose methods to identify interaction effects, and use those methods in a meta-analysis of data from blinded anti-depressant trials in which participant-level data was available. Out of six eligible studies, which included three for the selective serotonin re-uptake inhibitor paroxetine, and three for the tricyclic imipramine, three studies had a high (>65%) probability of treatment. We found strong evidence that treatment probability affected the behavior of trial participants, specifically the decision to drop out of a trial. In the case of paroxetine, but not imipramine, there was an interaction between treatment and behavioral changes that enhanced the effectiveness of the drug. These data show that standard blind trials can fail to account for the full value added when there are interactions between a treatment and behavior. We therefore suggest that a new trial design, two-bytwo blind trials, will better account for treatment efficacy when interaction effects may be important.

    Original languageEnglish (US)
    Article numbere0127227
    JournalPLoS One
    Volume10
    Issue number6
    DOIs
    StatePublished - Jun 10 2015

    Fingerprint

    Paroxetine
    Imipramine
    biomedical research
    value added
    Nutrition
    meta-analysis
    serotonin
    gold
    placebos
    clinical trials
    Serotonin
    exercise
    Therapeutics
    drugs
    methodology
    diet
    Pharmaceutical Preparations
    Placebo Effect
    Serotonin Uptake Inhibitors
    Meta-Analysis

    ASJC Scopus subject areas

    • Agricultural and Biological Sciences(all)
    • Biochemistry, Genetics and Molecular Biology(all)
    • Medicine(all)

    Cite this

    Accounting for behavior in treatment effects : New applications for blind trials. / Chassang, Sylvain; Snowberg, Erik; Seymour, Ben; Bowles, Cayley.

    In: PLoS One, Vol. 10, No. 6, e0127227, 10.06.2015.

    Research output: Contribution to journalArticle

    Chassang, Sylvain ; Snowberg, Erik ; Seymour, Ben ; Bowles, Cayley. / Accounting for behavior in treatment effects : New applications for blind trials. In: PLoS One. 2015 ; Vol. 10, No. 6.
    @article{52969e4845514e17b8dbb79a4928c692,
    title = "Accounting for behavior in treatment effects: New applications for blind trials",
    abstract = "The double-blind randomized controlled trial (DBRCT) is the gold standard of medical research. We show that DBRCTs fail to fully account for the efficacy of treatment if there are interactions between treatment and behavior, for example, if a treatment is more effective when patients change their exercise or diet. Since behavioral or placebo effects depend on patients' beliefs that they are receiving treatment, clinical trials with a single probability of treatment are poorly suited to estimate the additional treatment benefit that arises from such interactions. Here, we propose methods to identify interaction effects, and use those methods in a meta-analysis of data from blinded anti-depressant trials in which participant-level data was available. Out of six eligible studies, which included three for the selective serotonin re-uptake inhibitor paroxetine, and three for the tricyclic imipramine, three studies had a high (>65{\%}) probability of treatment. We found strong evidence that treatment probability affected the behavior of trial participants, specifically the decision to drop out of a trial. In the case of paroxetine, but not imipramine, there was an interaction between treatment and behavioral changes that enhanced the effectiveness of the drug. These data show that standard blind trials can fail to account for the full value added when there are interactions between a treatment and behavior. We therefore suggest that a new trial design, two-bytwo blind trials, will better account for treatment efficacy when interaction effects may be important.",
    author = "Sylvain Chassang and Erik Snowberg and Ben Seymour and Cayley Bowles",
    year = "2015",
    month = "6",
    day = "10",
    doi = "10.1371/journal.pone.0127227",
    language = "English (US)",
    volume = "10",
    journal = "PLoS One",
    issn = "1932-6203",
    publisher = "Public Library of Science",
    number = "6",

    }

    TY - JOUR

    T1 - Accounting for behavior in treatment effects

    T2 - New applications for blind trials

    AU - Chassang, Sylvain

    AU - Snowberg, Erik

    AU - Seymour, Ben

    AU - Bowles, Cayley

    PY - 2015/6/10

    Y1 - 2015/6/10

    N2 - The double-blind randomized controlled trial (DBRCT) is the gold standard of medical research. We show that DBRCTs fail to fully account for the efficacy of treatment if there are interactions between treatment and behavior, for example, if a treatment is more effective when patients change their exercise or diet. Since behavioral or placebo effects depend on patients' beliefs that they are receiving treatment, clinical trials with a single probability of treatment are poorly suited to estimate the additional treatment benefit that arises from such interactions. Here, we propose methods to identify interaction effects, and use those methods in a meta-analysis of data from blinded anti-depressant trials in which participant-level data was available. Out of six eligible studies, which included three for the selective serotonin re-uptake inhibitor paroxetine, and three for the tricyclic imipramine, three studies had a high (>65%) probability of treatment. We found strong evidence that treatment probability affected the behavior of trial participants, specifically the decision to drop out of a trial. In the case of paroxetine, but not imipramine, there was an interaction between treatment and behavioral changes that enhanced the effectiveness of the drug. These data show that standard blind trials can fail to account for the full value added when there are interactions between a treatment and behavior. We therefore suggest that a new trial design, two-bytwo blind trials, will better account for treatment efficacy when interaction effects may be important.

    AB - The double-blind randomized controlled trial (DBRCT) is the gold standard of medical research. We show that DBRCTs fail to fully account for the efficacy of treatment if there are interactions between treatment and behavior, for example, if a treatment is more effective when patients change their exercise or diet. Since behavioral or placebo effects depend on patients' beliefs that they are receiving treatment, clinical trials with a single probability of treatment are poorly suited to estimate the additional treatment benefit that arises from such interactions. Here, we propose methods to identify interaction effects, and use those methods in a meta-analysis of data from blinded anti-depressant trials in which participant-level data was available. Out of six eligible studies, which included three for the selective serotonin re-uptake inhibitor paroxetine, and three for the tricyclic imipramine, three studies had a high (>65%) probability of treatment. We found strong evidence that treatment probability affected the behavior of trial participants, specifically the decision to drop out of a trial. In the case of paroxetine, but not imipramine, there was an interaction between treatment and behavioral changes that enhanced the effectiveness of the drug. These data show that standard blind trials can fail to account for the full value added when there are interactions between a treatment and behavior. We therefore suggest that a new trial design, two-bytwo blind trials, will better account for treatment efficacy when interaction effects may be important.

    UR - http://www.scopus.com/inward/record.url?scp=84936818619&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84936818619&partnerID=8YFLogxK

    U2 - 10.1371/journal.pone.0127227

    DO - 10.1371/journal.pone.0127227

    M3 - Article

    VL - 10

    JO - PLoS One

    JF - PLoS One

    SN - 1932-6203

    IS - 6

    M1 - e0127227

    ER -