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Choosing the right antidepressant for depressive disorder




Choosing the right antidepressant for depressive disorder

What is the aim of the study and why is it important?

Depression is a very common major health problem, 350 million people in the world are affected. The costs for major depression are largely due to significant problems in treatment. There are several effective treatments for depression including drug treatment and talking therapies, but clinical guidelines often recommend antidepressant medications as the first method of treatment for adults with moderate to severe depression. Antidepressants are very commonly used (in England alone, 64.7m prescriptions of antidepressants were dispensed in 2016). Many patients, however, are given antidepressants, which, for them, do not work or cause side-effects that can not be tolerated. This happens because antidepressants are prescribed without a clear understanding of which drug is the most appropriate medication for each patient, so people often stop the antidepressant early because they are prescribed a drug which might work for the “average person” but has not been tailored to them individually.

Clinical trials provide the best evidence “in theory”, but to understand whether these results are similar to we see in daily clinical practice, we need information collected by GPs in primary care.

The aim of this study is to create a web-based treatment algorithm, which will match a specific antidepressant to each individual patient. The tool will be used as part of the shared decision making process between patients and clinicians. We hope that for patients this will decrease the likihood of them stopping the medication due to side effects that cannot be tolerated. We also hope that this will increase the chance of them being prescribed the antidepressants that works best from them as an indiviudal.

How is the research being done?

Prescribing the Right Antidepressant for Depression in Adults (PRADA) is a research project being undertaken by academics, researchers, clinicians and people with lived experience of depression at the Department of Psychiatry, University of Oxford. As part of this project we aim to use the information from the QResearch database, the largest primary care database in the UK, to assess clinical information, especially about the side effects of antidepressants. In this study we will include only acutely unwell adults with depression treated with antidepressants. We will exclude individuals with a severe mental health illness, such as schizophrenia or bipolar disorder. We will describe the characteristics of both the groups of individuals included and excluded from our study.

We will use clinical and demographic information for each patient with depression (e.g. sex, age, the initial severity score of their depression and treatment duration) which will help to predict how the patient responds and which patients respond better to which drug. At the end we will use clinical and demographic information associated with each antidepressant as a source of information to instruct a computerised tool to rank the different antidepressants and personalise treatment in depression. We will then test this computerised tool in a study across the UK. Involving patients and the public in our research is extremely important and we will do this using the Patients and Public Involvement (PPI) through the Oxford Health Biomedical Research Centre (BRC) patient and research group.

Chief Investigator

Professor Andrea Cipriani

Lead Applicant Organisation Name



Location of research

University of Oxford

Date on which research approved


Project reference ID


Generic ethics approval reference


Are all data accessed are in anonymised form?


Brief summary of the dataset to be released (including any sensitive data)

Anonymised subset of GP data from the QResearch database. Data sets to be shared include:
1. QResearch GP data for patients aged 18-100 with a first recorded diagnosis of depression between 1998 and 2018; associated diagnoses and symptoms including diagnoses of depression; symptoms; clinical outcomes and baseline co-morbidities; prescription data antidepressants; antipsychotic drugs; lithium
2. ONS date of death and cause of death
3. ICD9 and ICD10 depression codes

Implications and Impact

This study will: a) Provide clinical and demographic information that can predict the effectiveness and side effects of antidepressants; b) Develop a computerised tool which will be used in everyday clinical settings within the NHS (e.g. GP practices); c) Improve the shared decision-making process between patients and clinicians and pave the way for the implementation of a personalised approach in everyday mental health care.

Funding Source

National Institute for Health Research (NIHR)

Public Benefit Statement

Research Team

Professor Andrea Cipriana, Dr Franco De Crescenzo, Dr Anneka Tomlinson, Professor Julia Hippisley-Cox


Access Type

Trusted Research Environment (TRE)

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