Electroencephalography (EEG) Signal Processing (EEG-SP)

This study is currently recruiting participants.
Verified November 2011 by St. Joseph's Healthcare Hamilton
Sponsor:
Information provided by (Responsible Party):
Gary Hasey, St. Joseph's Healthcare Hamilton
ClinicalTrials.gov Identifier:
NCT01369290
First received: September 18, 2010
Last updated: November 28, 2011
Last verified: November 2011

September 18, 2010
November 28, 2011
October 2009
October 2012   (final data collection date for primary outcome measure)
Machine learning [ Time Frame: 6 weeks with medication, or 12 weeks with CBT ] [ Designated as safety issue: No ]
The accuracy of the trained predictive model based on machine learning methodology is the primary outcome we are interested in studying. The primary outcome measure, i.e. model performance accuracy, is tested using the jack-knifed "leave N out" nested cross validation method with response being determined using the MDRS scale.
Machine learning [ Time Frame: 6 weeks with medication, or 12 weeks with CBT ] [ Designated as safety issue: No ]
The accuracy of the trained predictive model based on machine learning methodology is the primary outcome we are interested in studying. The primary outcome measure, i.e. model performance accuracy, is tested using the jack-knifed leave one out nested cross validation method.
Complete list of historical versions of study NCT01369290 on ClinicalTrials.gov Archive Site
Machine learning [ Time Frame: 6 weeks with medication, 12 weeks with CBT ] [ Designated as safety issue: No ]
The accuracy of the trained predictive model based on machine learning methodology is the primary outcome we are interested in studying. The primary outcome measure, i.e. model performance accuracy, is tested using the jack-knifed "leave N out" nested cross validation method with response being determined using the Beck II scale.
Machine learning [ Time Frame: 6 weeks with medication, 12 weeks with CBT ] [ Designated as safety issue: No ]
The MADRS is the main response indicator. Changes in the MADRS scores from pre to post treatment will be a secondary outcome indicator.
Not Provided
Not Provided
 
Electroencephalography (EEG) Signal Processing
EEG Signal Processing as a Predictor of Antidepressant Response

Current methods of choosing treatment for major depressive disorder (MDD) are inefficient. The Strategic Treatment to Achieve Remission of Depression (STAR*D) Trial revealed that only about 1/3 of patients treated with antidepressant drugs will go into remission with the first medication chosen. We hypothesize that pattern recognition software using Machine Learning methods can accurately predict response to a variety of antidepressant medications (ADM) or cognitive behavior therapy (CBT) after training using pre-treatment demographic, clinical, laboratory or electroencephalographic (EEG) data. These algorithms might assist the clinician to chose, for any given patient, an antidepressant treatment option with greater probability of favourable response than is achievable using current best practise methods.

Objective of this study:

To improve antidepressant treatment efficacy by determining,in advance, a given subject's probability of response to a range of antidepressant treatments. The study is intended to to further train and test, in a larger sample of depressed subjects, a digital system that has been shown to be an accurate predictor of antidepressant response in pilot studies. The accuracy of the trained predictive model based on machine learning methodology is the primary outcome we are interested in studying.

Subjects:

males and females age 18-70 years of age.

Inclusion Criteria:

Meet DSM IV criteria for MDD on Structured Clinical Interview for DSM IV (SCID) capable of providing informed consent

Exclusion Criteria:

Psychosis; acute suicidal intent or plan; alcohol or drug dependence within 3 months; previous treatment with 3 or more of the following:

  • adequate CBT
  • adequate trials of the study antidepressant medications [adequacy definitions: ≥ 4 weeks of i) venlafaxine ≥150 mg/day, ii) bupropion ≥150 mg/day iii) escitalopram ≥ 10 mg/day iv) duloxetine ≥ 30 mg/day v) ≥ 8 CBT sessions over ≥ 8 weeks
  • unstable medical illness
  • ECT within 6 months
  • pregnancy or sexually active female not using contraception.

Study Design:

Pre-treatment data collection:

After 10 days of psychotropic medication washout demographic, syndromatic, illness severity , biochemical/hematological and electroencephalographic data will be collected from which a list of potential response predictor variables will later be extracted.

The data collected include the following areas

  • Depression Severity: evaluated using the Montgomery Asberg Depression Rating Scale (MADRS) and the Beck II Depression Rating Scale.
  • Anxiety Severity: measured using the Spielberger Stait-Trait Anxiety Index.
  • Diagnosis and Syndromatic Features: documented using the Structured Clinical Interview for DSM IV (SCID).
  • Personality Attributes: determined using the Minnestota Multi-phasic Personality Inventory (MMPI) and the NEO-Personality Inventory.
  • Social Support: measured using the Perceived Social Support from Friends and Family rating scale (PSS).
  • Previous Antidepressant Medication Treatment (range and adequacy): determined using a modified and updated version of the Michigan Adequacy of Treatment Scale.
  • Hematological/Biochemical Testing: complete blood count, hepatic transaminases, thyroid stimulating hormone level, serum creatinine, serum calcium, serum magnesium, fasting blood glucose and serum B12.

Antidepressant Treatment:

The antidepressant treatment will be administered in Phase I. Subjects who show less than a 50% response to the treatment at the end of Phase I will receive a different treatment in Phase II. There will be a 10 day period between phases I and II during which the antidepressant medication (if used in Phase I) is tapered and discontinued .

Treatment choice is made naturalistically i.e. patient preference is taken into account, but patients cannot receive a treatment if they have previously failed to respond to an adequate trial of that treatment. Subjects judged insufficiently "psychologically minded" are not offered CBT. If the patient has no preference regarding treatment, the choice of treatment is determined randomly.

Treatment options:

i) escitalopram for 6 weeks ii) venlafaxine for 6 weeks iii) bupropion for 6 weeks iv) duloxetine for 6 weeks v) cognitive behaviour therapy (CBT) for 12 weeks. Antidepressant medication dosing will follow established medical procedures and published dose guidelines. CBT is administered in manualized format by highly trained therapists.

Data Analysis:

After treatment, subjects will be classified as responders or non-reponders using the % change in the MADRS score from pre-treatment to post treatment. Subjects will be considered to be responders if the post treatment MADRS score has dropped by 50% or more from the baseline score. The machine learning algorithms will be trained using features extracted from the pre-treatment demographic, syndromatic, illness severity , biochemical/hematological and electroencephalographic data and Phase I treatment response as the classification variable. The algorithm will first be tested using nested cross-validation "leave N out" techniques using only Phase I data.

Overfitting of the predictive algorithm is not entirely excluded as a possibility, even using nested cross validation methods. For this reason the resulting algorithm will be further tested in Phase II subjects using the predictive features extracted from pre-treatment data but, in this instance, using treatment response data from Phase II treatment. The pre-treatment demographic, syndromatic, illness severity , biochemical/hematological and electroencephalographic data data for Phase II subjects will only have been employed to train the algorithm for the treatment they received during Phase I and not for the treatment received during Phase II. Under these circumstances retesting of the algorithm using Phase II treatment outcome constitutes testing in an entirely independent sample.

Observational
Observational Model: Case-Only
Time Perspective: Prospective
Not Provided
Not Provided
Probability Sample

Outpatients with Major Depressive Disorder from the Greater Hamilton Area

Major Depressive Disorder
  • Drug: Venlafaxine
    75 to 375 mg/day for 6 weeks. If no response at 6 weeks, reassignment to one of the other treatment groups for a further 6 to 12 weeks in phase II.
    Other Name: Effexor
  • Drug: bupropion
    150 to 300 mg daily for 6 weeks. If no response at 6 weeks, reassignment to one of the other treatment groups for a further 6 to 12 weeks in phase II.
    Other Name: Wellbutrin
  • Drug: escitalopram
    10 to 30 mg daily for 6 weeks. If no response at 6 weeks, reassignment to one of the other treatment groups for a further 6 to 12 weeks in phase II.
    Other Name: Cipralex
  • Other: Psychotherapy
    Once weekly CBT psychotherapy session for 12 weeks. If no response at 12 weeks, reassignment to one of the other treatment groups for a further 6 weeks in phase II.
    Other Name: CBT
  • Drug: Duloxetine
    30 to 60 mg daily for 6 weeks. If no response at 6 weeks, reassignment to one of the other treatment groups for a further 6 to 12 weeks in phase II.
    Other Name: Cymbalta
  • Drug 1
    Venlafaxine
    Intervention: Drug: Venlafaxine
  • Drug 2
    Bupropion
    Intervention: Drug: bupropion
  • Drug 3
    Escitalopram
    Intervention: Drug: escitalopram
  • Drug 4
    Duloxetine
    Intervention: Drug: Duloxetine
  • Psychotherapy
    Cognitive behaviour therapy
    Intervention: Other: Psychotherapy
Not Provided

*   Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
 
Recruiting
150
October 2013
October 2012   (final data collection date for primary outcome measure)

Inclusion Criteria:

  • Clients with Major Depression
  • Males and Females ages 18 - 70

Exclusion Criteria:

  • Clients who have known neurological problems
  • Clients with a history of severe head injury
  • Clients with strong thoughts of suicide
  • Clients who have had ECT or Cognitive Behavior Therapy within 6 months
  • Females who are sexually active and are not on adequate birth control
Both
18 Years to 70 Years
No
Contact: Rose Marie Mueller, RN 905-522-1155 ext 36629 rmueller@stjoes.ca
Canada
 
NCT01369290
ESP-3152, EEG Signal Processing
No
Gary Hasey, St. Joseph's Healthcare Hamilton
St. Joseph's Healthcare Hamilton
Not Provided
Principal Investigator: Gary M Hasey, MD St. Joseph's Healthcare and McMaster University, Hamilton
St. Joseph's Healthcare Hamilton
November 2011

ICMJE     Data element required by the International Committee of Medical Journal Editors and the World Health Organization ICTRP