There is an urgent clinical need to identify effective interventions to prevent suicidal behaviors among individuals at high suicide risk – such as patients who are experiencing suicidal ideation and patients who have recently attempted suicide. While there are several evidence-based psychosocial interventions for suicide prevention among high-risk patients, little is known about the potentially preventative role of psychotropic medications – largely because inclusion of suicidal individuals in randomized trials has traditionally entailed ethical difficulties and securing large enough sample sizes of such patients may not be feasible. Lack of evidence regarding use of commonly prescribed antidepressants among individuals at high suicide risk has particularly important clinical implications because most suicidal patients endure mental health conditions potentially treatable with antidepressants (e.g., major depressive disorder) and there is conflicting evidence as to whether antidepressant initiation temporarily increases risk of suicidal ideation and behaviors. In the absence of randomized trials, we can use high-quality observational data to evaluate the benefits and risks of clinical interventions – using expert knowledge coupled with advanced data science methods for causal inference to emulate a (hypothetical) pragmatic randomized trial. This approach, formally known as Target Trial Emulation, can be considered the gold-standard for guiding decision-making if/when randomized trials cannot be implemented. Using electronic health records including data on 150,000 individuals receiving mental healthcare from Madrid, Spain, we will apply cutting-edge causal inference methods to longitudinal data on diagnoses, prescriptions, clinical outcomes, disease and suicide risk severity, sociodemographic characteristics, and ecologic momentary assessments conducted in individuals screening positive in suicide risk stratification tools and suicide attempters. We will emulate a set of target trials examining the comparative effectiveness of pharmacological treatment strategies for individuals at suicide risk, including initiation vs. no initiation of antidepressants and head-to-head comparisons of commonly prescribed antidepressants. In this set of target trials, all patients will receive all other psychosocial treatment components included as treatment as usual in Madrid’s universal health system – i.e., early post-discharge follow-up visit scheduling, assertive outreach, or 24-hour crisis care. The outcomes of interest will be nonfatal suicide re-attempt, hospital admission, suicide death, and death by any external cause, as well as clinician-rated mental health functioning, all measured within 1-, 3-, 6-, and 12-months following discharge. This AFSP Early Career Researcher Innovation Grant would advance my early career as a physician-scientist by funding the first application of the Target Trial Emulation framework to address a critical unanswered research question with major implications for clinical decision-making. This grant will provide the support for me to develop and adapt cutting-edge causal inference methods for psychiatric research, generate readily applicable findings for clinical practice, and provide the basis for future grant proposals.
