Real-world effect of antidepressants for depressive disorder in primary care: protocol of a population-based cohort study.

De Crescenzo, Franco; Garriga, Cesar; Tomlinson, Anneka; Coupland, Carol; Efthimiou, Orestis; Fazel, Seena; Hippisley-Cox, Julia; Cipriani, Andrea (2020). Real-world effect of antidepressants for depressive disorder in primary care: protocol of a population-based cohort study. Evidence-Based Mental Health, 23(3), pp. 122-126. BMJ Publishing Group 10.1136/ebmental-2020-300149

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INTRODUCTION

Clinical guidelines recommend antidepressants as the first line of treatment for adults with moderate-to-severe depression. Randomised trials provide the best evidence on the comparative effectiveness of antidepressants for depression, but are limited by a short follow-up and a highly selected population. We aim to conduct a cohort study on a large database to assess acceptability, efficacy, safety and tolerability of antidepressant monotherapy in people with depressive disorder in primary care.

METHODS AND ANALYSIS

This is a protocol for a cohort study using data from the QResearch primary care research database, which is the largest general practice research database in the UK. We will include patients registered for at least 1 year from 1 January 1998, diagnosed with a new episode of depression and on antidepressant and a comparison group not on antidepressant. The exposure of interest will be treatment with antidepressant medications. Our outcomes will be acceptability (treatment discontinuation due to any cause), efficacy (clinical response and remission); safety (adverse events (AEs) and all-cause mortality); and tolerability (dropouts due to any AE) measured at 2 months, 6 months and 1 year. For each outcome, we will estimate the absolute risks for all antidepressants, and relative effects between antidepressants using Cox's proportion hazards models. We will calculate HRs and 99.9% CIs for each outcome of interest.

DISCUSSION

The main limitation is the observational nature of our study, while the major strengths include the large representative population contained in QResearch and the possibly high generalisability.

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