Can the Risk of Severe Depression-Related Outcomes be Reduced by Tailoring the Antidepressant Therapy to Patient Characteristics?

Selective serotonin reuptake inhibitors (SSRIs) are the first-line treatment for patients with unipolar depression, yet there is little guidance on which SSRI provides the most benefit to a patient, based on her/his personal characteristics. In this work, we explore whether an individualized treatment strategy can be used by healthcare providers to adapt their prescription pattern to reduce the risk of a severe depression-related outcome (SDO) when choosing between citalopram and fluoxetine, two commonly prescribed SSRIs. Our population-based cohort study used data from the Clinical Practice Research Datalink, the Hospital Episode Statistics repository, and the Office for National Statistics database in the United Kingdom to create a cohort of individuals diagnosed with depression who were prescribed citalopram or fluoxetine between 04/1998 and 12/2017. Patients were followed from treatment initiation until occurrence of the SDO outcome, treatment discontinuation or end of study. To find an optimal treatment strategy, we used dynamic weighted survival modelling considering patient features such as age, sex, body mass index, previous psychiatric diagnoses, and medications. Our findings suggest that using patient characteristics to tailor the antidepressant drug therapy is associated with an increase of 4 days in the median time to SDO (95% confidence interval: 2, 10 days).