Clinical trial NCT02546024: Predictors of Treatment Response in Late-onset Major Depressive Disorder
Official title: Predictors of Treatment Response in Late-onset Major Depressive Disorder
Study type: OBSERVATIONAL
Overall status: SUSPENDED
Conditions: Depressive Disorder, Major
Keywords: Major depressive disorder
late-onset
treatment response
predictors
moderators
Lead sponsor: King's College London
Sponsor class: OTHER
Collaborators: name: South London and Maudsley NHS Foundation Trust
First posted: 2015-09-10
Enrollment: 40
Sex: ALL
Minimum age (years): 60
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: 40 participants with major depressive disorder will be recruited from Community Mental Health Services, Home Treatment Service, and Inpatient services of the Mental Health of Older Adults and Dementia Clinical Academic Group in the South London and Maudsley NHS Foundation Mental Health Thrust.

Brief summary: Depression is a common disorder, especially in old age, where it is associated with significant morbidity and mortality.

This study will investigate whether there are features of individual patients with major depression that may predict positive treatment response. The study will invite 40 patients who have been diagnosed with major depressive disorder with onset after the age of 60 years to participate. Participants will be recruited from the Mental Health of Older Adults services at the South London and Maudsley NHS Mental Health Foundation Trust. Participants will receive usual treatment as set out in standard Care Pathways, used by the clinical care team. As part of the study, they will undergo a short battery of neuropsychological tests and a standard MRI brain imaging protocol. The neuropsychological tests and assessment of depression severity will be carried out twice (at Baseline and Week 12). Data will be analysed to investigate whether there are features specific to those patients who show a good response to antidepressant treatment after 12 weeks. Identification of such predictors may help to stratify treatment approaches in the future and lead to the early identification of individual patients who may require alternative treatment approaches to standard antidepressants.

Detailed description: Aim and objectives:

Predictors of treatment response may help to improve treatment approaches in late-onset major depression patients. The study will identify features of patients with major depression that may predict good and poor treatment response. It will use demographic, clinical, neuropsychological and brain MRI data to investigate the potential value of these as predictors of response to standard treatment over 12 weeks. For example, impairment of executive functioning on cognitive testing may predict patients whose depression does not respond to 12 weeks of treatment. MRI may reveal specific characteristics that predict good response to treatment.

Methodology Subject inclusion and exclusion criteria Inclusion: Patients with major depressive disorder, diagnosed for the first time after the age of 60 years, with a Mini Mental State Examination score \>24/30.

Exclusion: Participants with a history of other major psychiatric illness or intellectual disability will be excluded. Those who have unstable medical conditions, including a history of neurological disease (stroke, epilepsy, recent delirium, neurodegenerative disease or dementia) will also be excluded.

Recruitment:

Patients with late-onset major depressive disorder will be identified by members of care teams of the Mental Health of Older Adults Services of the South London and Maudsley NHS Foundation Trust. A poster and information leaflet about the study will be also provided to the services to facilitate recruitment. The researcher will also use the trust Consent for Contact (c4c)' mechanism to assist the recruitment process. Potential participants who contact the researcher or give their permission to be contacted will be sent a written brief information sheet and invited to respond via an expression of interest letter and a stamped and addressed envelope. If they are interested, a consent for screening and medical record review will be sought. And following screening for the absence of significant cognitive impairment with the Mini-Mental State Examination by the researcher if this has not already been performed, they will be provided with a full information sheet and be invited to consent to participate in the study at their home or the IOPPN depending on participants' preference.

Screening assessment

The initial screening assessment will be done at potential participants' residences. A brief history of psychiatric and medical conditions will be taken. Participants will be interviewed with the following assessments:

* Mini-Mental State Examination (MMSE) is a 30 point assessment for general cognitive function, with exemption if they have been completed in clinical work within 1 month of the assessment.
* MRI safety questionnaire

If potential participants are eligible for inclusion into the study and remain interested, written information will be left with them and an appointment will be made for further discussion and gaining informed consent. If they are not eligible for the study on the basis of screening, or decide not to proceed at this stage, all data collected will be destroyed.

Consent visit and baseline assessment:

Subjects will have been encouraged to read all information sheets carefully and will have the opportunity to ask further questions at this stage. Their capacity to consent will be assessed by the researcher and they will then be asked to provide verbal and written consent to be involved in the study.

The following baseline assessment and neuropsychological tests will be performed at participants' homes or the IOPPN depending on participants' preference and last about one and a half hour:

1. Demographic data including sex, age, marital and living status, number of education years completed, and occupation.
2. Clinical data including current prescribed medical treatment, current depressive episode onset and treatment type, dosage and duration received.
3. Cumulative Illness Rating Scale for Geriatrics (CIR-G) is a scoring questionnaire for assessing underlying medical disease.
4. Hospital Anxiety Depression Scale (HADS), a self-rating scale and Hamilton Depression Rating Scale (HAM-D 21 items), an interview-based rating scale are used for depressive severity assessment.
5. WHODAS 2.0 is a questionnaire assessing general functioning and disability.
6. Neuropsychological tests

   * Trail making test - a pen and paper based test for processing speed.
   * Digit span and Spatial Span tests - tests for working memory.
   * Verbal fluency, category fluency and design fluency - tests for fluency that ask participants to generate words or pictures in the rules given.
   * Colour-Word Interference test - a paper-based reading test for inhibition.

A letter will be sent to participants' GPs to inform them of their participation. The GP may be asked to confirm or provide information in case of the participant has questionable medical history that might contraindicate an MRI procedure.

MRI scan procedure:

Participants will undergo an MRI scan at the CNS based at the IOPPN within 4 weeks of baseline assessment. A taxi will be provided for participants to travel to the IOPPN. At the CNS, participants will be encouraged to ask any questions and the MRI safety questionnaire will be repeated to ensure there are no contraindications. Noise protection will be provided to the participants and a mock scan will be offered to familiarize them with the real MRI scanner if they would like this. Participants will then undergo a structural and functional MRI scan, the latter includes asking them to close their eyes for a period of time. The MRI scan will last about 1 hour. After the MRI scan, transport by taxi will be provided to return participants to their home.

Final assessment At Week 11, the researcher will contact the participants and make an appointment for the final assessment at Week 12 at their home or the IOPPN depending on participants' preference. The final assessment will last about one hour. Participants will undergo the same assessment as in baseline assessment and the Mini-Mental State Examination.

Note that throughout and following the study, participants will receive standard care, following the Trust Care Pathway.

Eligibility criteria: Inclusion Criteria:

* The participant is 60 or more years old at the point of first contact with psychiatric specialist services for depression.
* Satisfies diagnostic criteria for current major depressive disorder according to DSM-IV TR (American Psychiatric Association, 2000)
* Mini-Mental State Examination (MMSE) score of 25 or greater.

Exclusion Criteria:

* Previously diagnosed with other major psychiatric illness (schizophrenia, bipolar disorder, benzodiazepine/ substance dependence or personality disorder) or registered intellectual disability.
* Severe or unstable medical condition e.g. severe infection, myocardial infarction, renal failure or metastatic cancer. Including those who have stroke, epilepsy, delirium within 3 months, neurodegenerative disease or dementia.
* History of traumatic brain injury with more than 10 minutes of loss of conscious period.
* Metal implants that would be a contraindication for MRI.

Primary outcomes:
measure: Resting Functional brain MRI
timeFrame: Week 4 after enrollment
Secondary outcomes:
measure: Neuropsychological test battery
timeFrame: at entry and endpoint (Week12)
measure: Structural brain MRI
timeFrame: Week 4 after enrollment
measure: Functional assessment
timeFrame: at entry and endpoint (Week12)
Other outcomes:
Locations:
Study officials:
affiliation: King's College London
name: Chavit Tunvirachaisakul
role: PRINCIPAL_INVESTIGATOR
References:
citation: Alexopoulos GS, Hoptman MJ, Kanellopoulos D, Murphy CF, Lim KO, Gunning FM. Functional connectivity in the cognitive control network and the default mode network in late-life depression. J Affect Disord. 2012 Jun;139(1):56-65. doi: 10.1016/j.jad.2011.12.002. Epub 2012 Mar 15.
citation: Patel MJ, Andreescu C, Price JC, Edelman KL, Reynolds CF 3rd, Aizenstein HJ. Machine learning approaches for integrating clinical and imaging features in late-life depression classification and response prediction. Int J Geriatr Psychiatry. 2015 Oct;30(10):1056-67. doi: 10.1002/gps.4262. Epub 2015 Feb 17.