Innovations In Clinical Neuroscience

CNS Summit 2016

A peer-reviewed, evidence-based journal for clinicians in the field of neuroscience

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[ V O L U M E 1 4 , N U M B E R 1 – 2 , J A N U A R Y – F E B R U A R Y 2 0 1 7 , S U P P L E M E N T ] Innovations in CLINICAL NEUROSCIENCE S15 An electronic (eCOA)-prompted Yale Global Tic Severity Scale (YGTSS) with blinded internal scoring P resenters: Busner J 1 , Farber R 2 , O'Brien C 2 , Liang G 2 , Scahill L 3 , Coffey B 4 Affiliations: 1 Penn State College of Medicine, Department of Psychiatry, Hershey, Pennsylvania, and Bracket G lobal, Wayne, Pennsylvania; 2 N eurocrine Biosciences, Inc., San Diego, California; 3 Emory University, Atlanta, Georgia; 4 Icahn School of Medicine at Mount Sinai School, New York, New York Objective: The YGTSS is a gold- standard tic severity assessment in Tourette's syndrome (TS) studies. To improve ratings quality, we developed an eCOA-prompted YGTSS that provided rating guidance, captured rater scores, and generated rater-blinded algorithm-derived scores as quality checks. Design: An eCOA-prompted YGTSS was developed with TS experts. The eCOA YGTSS ensured correct navigation through the scale and assisted raters by displaying earlier endorsed tics when needed for motor and phonic severity ratings. The scale included algorithms for a second set of rater-blinded "tandem" scores. The scale is being piloted in two ongoing, placebo-controlled, multisite TS trials, one pediatric and one adult, with rater scores serving as efficacy data. Results: There were 99 visits by 20 raters that were completed at the time of the analysis. Correlations between rater and computer scores were high for each of the 10 YGTSS severity scores (range: 0.74–0.91, all p values <0.0001); for the Total Tic Score (TTS) (primary efficacy measure), the correlation was 0.95 (p<0.0001). The mean rater versus computer TTS scores were almost identical (28.8 and 28.5, respectively, NS). The findings did not differ between pediatric and adult subjects. Conclusion: Our internal scoring algorithms correlated significantly with all rater-selected motor, phonic, and TTS scores, with the latter nearly identical. The work provides preliminary validation of our algorithms and supports the feasibility of the approach. In a risk-based monitoring model, less trained raters whose scores deviate significantly from those of the internal algorithm might be selected for additional scrutiny and intervention. Disclosures/funding: Dr. Busner is an employee of Bracket Global, Wayne, Pennsylvania. Drs. Farber, O'Brien, and L iang are employees of Neurocrine Biosciences, Inc., San Diego, California. Dr. Scahill is a consultant to Roche, Bracket, Neuren Pharmaceuticals, MedAdvante, Coronado Biosciences, Inc., a nd Supernus Pharmaceuticals, Inc.; has received research support from the United States National Institute of Mental Health (NIMH) and Department of Defense; and has received royalties from Oxford and Guilford. Dr. Coffey has received honoraria from American Academy of Child and Adolescent Psychiatry; has received research support from Neurocrine, NIMH, Shire, and Catalyst Pharmaceuticals Inc.; serves on the advisory board, received Center of Excellence Funding, and is on the speakers bureau of Tourette Association of America; serves on the advisory board and receives research support from Auspex Pharmaceuticals; and serves on the advisory board of Genco Sciences. The electronic self-report of the C-SSRS (eC-SSRS) places little burden on patients initially and even less with repeated administrations Presenters: Yamamoto R 1 , Durand E 1 , Lima V 1 , Christopher D 1 , Yershova K 2 , Dallabrida S 1 Affiliations: 1 ERT Corp., New York, Neew York 2 ; Columbia University/New York State Psychiatric Institute, New York, New York Objective: A key factor to consider for instruments that measure suicidal ideation and behavior (SIB) is the duration of patient completion time. The Columbia Suicide Severity Rating Scale (C-SSRS) (interviewer completed) and electronic C- SSRS (eC-SSRS) (self-report) are sourced by the United States Food and Drug Administration (FDA) in the SIB Industry Guidance as recommended assessments. This study examined patient completion time for the tablet-based eC-SSRS over time. Design: Over 2,000 subjects with substance abuse disorder completed the tablet-based eC-SSRS assessment at each clinic visit in a trial. Data from the eC- SSRS since last contact version were analyzed. Results: Completion times for patients who scored negative for SIB using the tablet version of the e-C-SSRS were 1 .15±1.33min at Visit 1, 0.84±0.89min at Visit 7, and 0.73±0.79min at Visit 12. There was a significant decrease in the time it took patients to complete the e- CSSRS across Visits 1 through 12 General L inear Model (mixed) (F=5809.25, p<0.0001). ANOVA repeated measures on all 12 visits (F=7.7, p<0.0001) showed that the time to complete the eC-SSRS decreased across visits. A t-test between Visit 1 and Visit 12 (p<0.0001, t=4.8) indicated that it took significantly less time for subjects to complete the eC-SSRS on Visit 12 versus Visit 1. Conclusion: These data showed that there was little burden on subjects to complete the tablet eC-SSRS, and this burden decreased with repeated administrations. This is a particularly important consideration in lengthy studies with many repeat collections of an SIB assessment. Disclosures/funding: Drs. Yamamoto, Durand, and Dallabrida and Ms. Lima and Mr. Christopher are employees of ERT Corp., New York, New York. Dr. Yershova is an employee of Columbia University/New York State Psychiatric Institute, New York, New York. Evaluating the use of an artificial intelligence platform on mobile devices to measure adherence in subjects with an acute exacerbation of schizophrenia Presenters: Shafner L 1 , McCue M 2 , Rubin A 2 , Dong X 2 , Hanson E 2 , Mahableshwarkar A 2 , Hanina A 1 , Macek T 2 Affiliations: 1 AiCure, New York, New York; 2 Takeda Development Center Americas, Inc., Deerfield, Illinois Objective: The need to minimize medication nonadherence is particularly important in central nervous system (CNS) clinical trials. An artificial intelligence (AI) platform was assessed in measuring and increasing medication adherence in subjects with schizophrenia in a Phase 2, randomized, double-blind study. Design: Subjects in the TAK-063 study who were stable after three or more weeks of inpatient treatment and were discharged were followed up as outpatients for the remainder of the six-week period. Subjects

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