This project aims to improve the health care provided to people with major depressive disorder (MDD), a disease which is a top cause of disability worldwide. One of the main obstacles to a more effective health care in these patients is represented by clinical heterogeneity, which has not completely elucidated biological correlates. Using a large sample of people with MDD already recruited (n=29,400), the investigators develop a clustering algorithm based on genetic-environmental and brain imaging predictors aimed at identifying homogeneous MDD subgroups. The researchers will then link these subgroups with relevant health outcomes, such as disease recurrency and severity, well-being and functioning, risk of psychiatric and medical comorbidities (e.g. cardiovascular disorders). Replication in independent samples already recruited(n=1380) will prove the validity of the subgroups and expand their clinical characterization. The investigators will develop a classification tool to link the individual's characteristics to the relevant health outcomes and provide corresponding clinical recommendations. The prognostic support tool will be applied to newly recruited samples, feasibility and usefulness according to clinicians's opinion will be assessed (n=120, ongoing recruitment).
Study Type
OBSERVATIONAL
Enrollment
30,900
Benedetta Vai
Milan, Italy
RECRUITINGThe depressive status
Assessment of the severity of disease using the Self-report Inventory Of Depressive Symptoms (IDS-SR) (Rush et al., 1996) with minimum-maximum values 0-116, higher scores mean a worse outcome, regarding the last week.
Time frame: Assessment at the time of recruitment
The self-report depressive symptomatology
Assessment of the depressive characteristics, using the Beck Depression Inventory (BDI) (Beck et al., 1961) with minimum-maximum values 0-39, higher scores mean a worse outcome, regarding the last 2 weeks.
Time frame: Assessment at the time of recruitment
The clinical evaluation of depressive symptomatology
Assessment of the presence of depressive status, Hamilton Depression Rating Scale (HDRS) (Hamilton, 1967) with minimum-maximum values 0-69, higher scores mean a worse outcome, regarding the current state.
Time frame: Assessment at the time of recruitment
The rate of cardiovascular and/or cardiometabolic diseases
Assessment of the presence/absence of lifetime and current cardiometabolic and/or cardiovascular diseases (e.g. diabetes, arterial hypertension, pulmonary arterial hypertension) based on extracted data from medical records and chart.
Time frame: Assessment at the time of recruitment
The quality of functioning and well-being
Assessment of current and lifetime quality of life and well-being using the WHO Quality of Life-BREF (WHOQOL-BREF) (World Health Organization, 1996): the minimum and maximum values are 0-118, higher scores mean a better outcome, regarding the last 2 weeks.
Time frame: Assessment at the time of recruitment
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