Using scoring algorithms to identify serious scoring violations among placebo responders and non-responders in clinical trials using the Pos

January 25, 2019 Dr. Mark Opler, PhD, MPH | Chief Research Officer

The objective was to use a priori scoring algorithm designed to assess violations and non-violations on PANSS items, to compare PANSS ratings for subjects who were responders and non-responders to placebo treatment during participation in a clinical trial.

About the Author

Dr. Mark Opler serves as Chief Research Officer, directing scientific research and development at MedAvante-ProPhase. Dr. Opler was the founder of ProPhase and served as its CEO and Chief Scientific Officer among other positions. He holds the titles of Adjunct Assistant Professor of Psychiatry at New York University and Assistant Professor of Clinical Neuroscience at Columbia University’s College of Physicians and Surgeons. His academic research focuses on the etiology, phenomenology, and treatment of serious and persistent mental disorders. He is also leading the development of the new upcoming edition of the PANSS Manual©.
Follow on Linkedin More Content by Dr. Mark Opler, PhD, MPH | Chief Research Officer

Previous Flipbook

Using PANSS Score Profiles to Predict Early Termination in a Study on Acute Exacerbation of Schizophrenia

Blinded analyses were aimed to determine how different atypical Positive and Negative Syndrome Scale (PANSS...

Next Flipbook

Validation of Goal Attainment Scaling for Depression: Initial Findings From an Open-Label Study in Patients Switching to Vortioxetine

Using scoring algorithms to identify serious scoring violations among placebo responders and non-responders in clinical trials using the Pos

About the Author

Previous Flipbook

Next Flipbook

Most Recent Flipbooks

Blinded analyses were aimed to determine how different atypical Positive and Negative Syndrome Scale (PANSS) score profiles (identified using algorithms) were able to predict early termination.

The goal of this study was to identify a CDR quality metric, based upon internal patterns of domain scores that could be used to identify atypical patterns that might be indicative of scoring errors.

This study investigated the impact of lag time on error rates for commonly used Alzheimer’s disease COAs, as well as the degree to which administration attenuated error rates associated with lag time.

The goal of the present study was to examine the potential utility of the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) in prodromal AD trials.