Outlier-response pattern checks to improve measurement with the Positive and Negative Syndrome Scale (PANSS)

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Abstract

We derived outlier-response pattern checks to flag possible careless PANSS (Positive and Negative Syndrome Scale) administrations based on analysis of 122,000 administrations from 29 registration trials of antipsychotics from NEWMEDS data repository. Flags identify outlier administrations based on frequency of endorsing a given response value, use of even or odd values, consecutive use of same value, variability of values, responses per specific item, and values on multiple items. Outlier flags were compared to published expert derived scoring inconsistency flags and tested in Monte Carlo simulated data, with known inconsistency, and appear to be useful at identifying administrations that require review.

Original languageEnglish
Article number114114
JournalPsychiatry Research
Volume303
DOIs
StatePublished - Sep 2021

Bibliographical note

Publisher Copyright:
© 2021 Elsevier B.V.

Funding

Jonathan Rabinowitz has received research grant(s) support and/or travel support and/or speaker fees and/or consultant fees from Janssen (J&J), Eli Lilly, Pfizer, Lundbeck, Roche, Abraham Pharmaceuticals, Pierre Fabre, Intra-cellular Therapies, Minerva, Takeda and Amgen.

Funders
Abraham Pharmaceuticals
Amgen
Eli Lilly and Company
Pfizer
Roche
Takeda Pharmaceutical Company
Les Laboratories Pierre Fabre
H. Lundbeck A/S

    Keywords

    • Data surveillance
    • PANNS flags
    • Reliability
    • Risk-based monitoring

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