Locating Biomarkers in OCD Through Behavioral Tasks
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|ClinicalTrials.gov Identifier: NCT03313622|
Recruitment Status : Not yet recruiting
First Posted : October 18, 2017
Last Update Posted : January 15, 2019
|First Submitted Date||October 13, 2017|
|First Posted Date||October 18, 2017|
|Last Update Posted Date||January 15, 2019|
|Estimated Study Start Date||November 2019|
|Estimated Primary Completion Date||March 2020 (Final data collection date for primary outcome measure)|
|Current Primary Outcome Measures
|Original Primary Outcome Measures||Same as current|
|Change History||Complete list of historical versions of study NCT03313622 on ClinicalTrials.gov Archive Site|
|Current Secondary Outcome Measures||Not Provided|
|Original Secondary Outcome Measures||Not Provided|
|Current Other Pre-specified Outcome Measures||Not Provided|
|Original Other Pre-specified Outcome Measures||Not Provided|
|Brief Title||Locating Biomarkers in OCD Through Behavioral Tasks|
|Official Title||Locating Biomarkers of Medically Intractable Obsessive Compulsive Disorder (OCD) Through the Use of Behavioral Tasks|
Subjects that have a diagnosis of OCD will participate in a clinical interview and cognitive tasks, during which they will be exposed to their individual OC stressors or will be asked to make decisions related to information value and quantity while measuring neural activity and filming facial reactions. This will assist investigators to look for biomarkers of that change. This study offers a unique opportunity to develop biomarkers for key domains of OCD, and other neuropsychiatric disorders, that are grounded in brain neurocircuitry at the individual-patient level.
Subjects will participate in a clinical interview (Day 1), and then tasks+EEG (Day 2). Day 1 will be 4 hours or less, and Day 2 will be 2.5 hours or less.
This is a research study in which BCM is collaborating with Brown University/Butler Hospital and University of Pittsburgh. BCM and Butler Hospital will be enrolling sites. Brown University and University of Pittsburgh will be analyzing the assessment, EEG and facial recognition data.
Subjects will participate in a clinical interview (Day 1), and cognitive tasks with EEG (Day 2).
Neural data (through EEG) will be collected from OCD subjects when their symptoms are provoked, so we can look for biomarkers of that change. The subjects will be monitored through EEG and video recording for facial recognition. After initial video and EEG setup subjects will complete the Beads task followed by the Provocation task.
Demographics Questionnaire. Assesses psychiatric and medical treatment history.
SCID-5: Structured Clinical Interview for the DSM 5 (SCID): The SCID will be used to determine comorbid diagnoses at baseline.
Yale-Brown Obsessive-Compulsive Scale (Y-BOCS): The YBOCS is a 10-item inventory that assesses severity of OCD symptoms
Y-BOCS Symptom Checklist: The YBOCS symptom checklist assesses OCD symptom subtypes.
Trait Core Dimensions Questionnaire (TCDQ): The TCDQ measures prevalence of harm avoidant or incompleteness traits related to OCD.
Beck Anxiety Inventory (BAI). The BAI is a 21-question self-report inventory that is used for measuring the severity of anxiety. The questions used in this measure ask about common symptoms of anxiety that the participant has had during the past week.
Beck Depression Inventory (BDI): The BDI is a 21-question self-report inventory designed to measure depression severity.
Participants will be asked to make a series of categorical decisions that involve combining information about the value and probability of potential rewards. Subjects will sit in front of a computer monitor and place their hand over a box with orange and blue button that they will be asked to press based on their idea of which one will be the majority in a jar full of orange and blue beads. This task is designed to dissociate information value and quantity as the guesses are made based on information shown to the subject. Combining asymmetric rewards beads task with neuroimaging could dissociate neural signals related to information value from those related to information quantity. That is the goal here as we track neural activity through EEG measurements and facial recognition through video acquisition. This task should take 15-20 minutes to complete, not including EEG setup.
Provocation of OC symptoms (PROVOC):
PROVOC will be used to evoke manageable levels of OCD related distress. Three tasks will be developed collaboratively with the participant and independent evaluator that involve the participant being exposed in vivo to triggers that are considered by him/her impossible to confront without ritualizing. Each of the 3 tasks will be broken up into 7 steps, which provoke increasing levels of distress when encountered. Each step will be uniform in duration (i.e., one minute exposure) with the potential of 7 one-minute tasks with ~30 seconds break between steps, to provide brief rest for the patient and introduction of the next task. Participants will systematically confront triggers without ritualizing starting with easier items, and will continue until they feel their distress or need to ritualize is intolerable. This task will involve researchers and subjects deciding upon a few different triggering items (bloody (fake) napkin, used tissue, etc) that will be moved closer and closer to the subject as they wear the EEG measuring system. Each step should take one minute or less, and the subject will always have the option of stopping if the task becomes too distressing. There will also be a similar process involving objects that should not cause any distress to be used as a control. Consistent with prior research, 5 scores are calculated including percentage of steps completed, subjective units of distress (SUDS) across steps, avoidance, ritual engagement, and composite provocation score, which will be associated with changes in biosignature from brain recordings. We will pilot the provocation protocol, and start addressing problems that come up (e.g. EEG movement artifacts). Sessions will be videotaped with AFAR system concurrent to recording of LFPs from VS and scalp EEG.
High-density EEG System:
The g.BCIsys64USB EEG system, manufactured by g.tec GmBH, uses wide-range DC-coupled amplifier technology with 24-bit sampling, which results in an input voltage resolution of < 30 nV. Very efficient analog-to-digital converters (2.5 MHz per channel) result in very high signal to noise ratio, critical for recording subtle changes in EEG measures. The system combines four bio-amplifiers (16-channels each) that can either be stacked to provide a higher density (32/48/64 channels) system, or can simultaneously be used on different study participants. The EEG system makes use of 'active' electrode technology that employs an additional ultra-low noise pre-amplifier located inside each electrode to maximize the signal-to-noise ratio. The active electrodes work in a frequency range from 0 - 10 kHz (DC) or 0.1 - 10 kHz (AC). The EEG system is also equipped with innovative data acquisition and data analysis software that allows sophisticated signal processing and data analysis capabilities. The system includes a 3D scalp digitizer that maps the scalp in the stereotactic space for EEG source localization. Other capabilities of the system include eye-tracking and acquisition of physiological data (SpO2, pulse and skin conductance).
Automated Facial Affect Recognition (AFAR) will be used to measure facial expression of positive and negative valence. AFAR is a computer-vision based approach that can objectively measure the occurrence, intensity, laterality, and timing of facial action units, head pose, and gaze at video frame rate (30 to 60 frames per second). Participants will be videotaped. Action units are anatomically based actions that individually or in combination can describe nearly all-possible facial expressions. AFAR has strong concurrent validity with manual measurement of facial action units, holistic expressions, depression severity, and psychological distress; and with ground truth measures of head pose and gaze. Previous research has identified action units associated with positive (e.g., enjoyment) and negative (e.g., fear, anger, disgust, and anxiety) emotion; and used them to represent scales for positive and negative valence and pain. Because gaze and head orientation also are strongly related to emotion and valence, we include them in positive and negative valence scales. Videotaped data will be shared with the University of Pittsburgh.
Local data and safety monitoring will be conducted by the PI who will meet regularly with the study team to review new information from clinical ratings, assessments, and medical records for each subject. Study-related adverse events or threats to subject confidentiality will be monitored, and any needed safety changes will be addressed. Assessment of adverse events, including grading of severity and attribution to research, will be conducted at each visit and noted on the rating coversheet. The PI will report all unanticipated problems within 5 working days from becoming aware of the event. The PI will evaluate all adverse events and determine whether the event affects the Risk/Benefit ratio of the study, and whether modifications to the protocol or consent form are required.
|Study Design||Observational Model: Case-Only
Time Perspective: Prospective
|Target Follow-Up Duration||Not Provided|
|Sampling Method||Non-Probability Sample|
|Study Population||Potential subjects are patients diagnosed with OCD meeting the inclusion/exclusion criteria above.|
|Study Groups/Cohorts||OCD group
Day 1: Questionnaires/Assessments
Day 2: Tasks
|Publications *||Not Provided|
* Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
|Recruitment Status||Not yet recruiting|
|Original Estimated Enrollment||Same as current|
|Estimated Study Completion Date||March 2020|
|Estimated Primary Completion Date||March 2020 (Final data collection date for primary outcome measure)|
|Ages||18 Years to 65 Years (Adult, Older Adult)|
|Accepts Healthy Volunteers||No|
|Listed Location Countries||United States|
|Removed Location Countries|
|Other Study ID Numbers||H42237|
|Has Data Monitoring Committee||No|
|U.S. FDA-regulated Product||
|IPD Sharing Statement||
|Responsible Party||Wayne Goodman MD, Baylor College of Medicine|
|Study Sponsor||Baylor College of Medicine|
|PRS Account||Baylor College of Medicine|
|Verification Date||January 2019|