Publications by authors named "B G Szigeti"

Expectancy Effects in Psychedelic Trials.

Biol Psychiatry Cogn Neurosci Neuroimaging

May 2024

Clinical trials of psychedelic compounds like psilocybin, lysergic acid diethylamide (LSD), and N,N-dimethyltrptamine (DMT) have forced a reconsideration of how nondrug factors, such as participant expectations, are measured and controlled in mental health research. As doses of these profoundly psychoactive substances increase, so does the difficulty in concealing the treatment condition in the classic double-blind, placebo-controlled trial design. As widespread public enthusiasm for the promise of psychedelic therapy grows, so do questions regarding whether and how much trial results are biased by positive expectancy.

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Background: To investigate the association between pre-trial expectancy, suggestibility, and response to treatment in a trial of escitalopram and investigational drug, COMP360, psilocybin, in the treatment of major depressive disorder (ClinicalTrials.gov registration: NCT03429075).

Methods: We used data ( = 55) from our recent double-blind, parallel-group, randomized head-to-head comparison trial of escitalopram and investigational drug, COMP360, psilocybin.

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Article Synopsis
  • This study investigates the expression of tight junction proteins called claudins (CLDNs) in rare lung cancers, specifically pulmonary salivary gland tumors like adenoid cystic carcinomas (ACCs) and mucoepidermoid carcinomas (MECs).
  • A total of 35 tumor samples were analyzed using immunohistochemical staining to evaluate the presence of various CLDN proteins, revealing significant expression patterns, especially for CLDN2, -7, and -18.
  • The findings suggest that the overexpression of certain CLDNs in ACC and MEC may offer new avenues for targeted therapies in these less common types of lung cancer.
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In medical trials, 'blinding' ensures the equal distribution of expectancy effects between treatment arms in theory; however, blinding often fails in practice. We use computational modelling to show how weak blinding, combined with positive treatment expectancy, can lead to an uneven distribution of expectancy effects. We call this 'activated expectancy bias' (AEB) and show that AEB can inflate estimates of treatment effects and create false positive findings.

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