The impact of early remission on disease trajectory and patient outcomes in major depression disorder (MDD): A targeted literature review and microsimulation modeling approach based on the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study

Background: While literature has suggested that the duration of a major depressive episode (MDE) may affect both symptomatic and functional outcomes in major depressive disorder (MDD), study designs are limited in their ability to isolate a causal relationship.Methods: A targeted literature review was conducted using the MEDLINE database to assess whether there was an association between (1) shorter duration of an MDE, or (2) increased rapidity of symptom improvement, and MDD outcomes in adult patients. Given findings from the literature, we hypothesized that rapid symptom improvement could be associated with other longer-term clinical outcomes and used a previously-developed microsimulation model to test this hypothesis. The base case of the model replicated step-therapy treatment patterns, for 10,000 simulated patients, based on lines of therapy related to standard of care, observed remission rates, and observed time to relapse from the STAR*D study. In alternative scenario analyses, the step 1 remission rate was varied by +25 % and +50 % from the base case value to simulate the potential impact of improved earlier remission on disease trajectory and patient-level clinical outcomes.Results: The literature review (N = 35 studies) suggests a statistically significant relationship between the duration of MDE or early symptom improvement and MDD outcomes. The microsimulation model corroborated these findings and demonstrated that increasing the rate of remission in step 1 results in patients experiencing decreased number of treatment steps, faster time to remission, decreased rate of reaching treatment-resistant depression, and delayed time to relapse. Limitations: Rates of relapse in STAR*D were deemed unreliable due to the high-loss of follow-up; rates of relapse for the MDD DTM were instead derived using parametric extrapolation methods (i.e., exponential, Weibull, log-logistic, Gaussian, log-normal, logistic). Adherence to treatment was assumed to be 100 %; however, non-adherence is expected to result in lower cumulative remission rates.Conclusion: Findings from the literature, coupled with quantification through a novel microsimulation model, demonstrate the potential impact of increased remission on disease trajectory and patient outcomes in MDD. While additional analyses with the model may be warranted to explore the impact of novel interventions on population health, including long-term outcomes (i.e., 5-year follow-up, lifetime follow-up), efforts by clinicians to increase remission early in the disease trajectory may improve long-term outcomes.