Prediction of recurrence in recurrent depression: a 5.5-year prospective study

OBJECTIVE: Depression is a disease with high recurrence rates. Identifying predictors of recurrence and their relative importance in patients with recurrent depression is important for a better understanding of the course of this disease. This type of knowledge can be used to optimize and tailor preventive strategies of recurrence. In this study, we examined predictors of recurrence over a 5.5-year follow-up period and quantified to which extent these predictors explained observed variation in recurrence.

METHOD: Data from 172 remitted recurrently depressed patients over a 5.5-year follow-up period were used. Recurrence was assessed with the Structured Clinical Interview for DSM-IV. Illness-, stress-, and coping-related factors were examined as predictors of recurrence. Multiple Cox regression analysis was used, and explained variation was assessed to quantify the relative importance of the predictors. Patients were recruited between February 2000 and September 2000.

RESULTS: Number of previous episodes and residual symptoms explained each 15% of the variation in recurrence, indicating a medium effect size. The final multivariate prediction model included: a higher number of previous episodes, more residual symptoms, and lower levels of positive refocusing (explained variation 29%, indicating a strong effect size).

CONCLUSION: In our multivariate prediction model, the number of previous episodes, residual symptoms, and a specific coping style were predictors of recurrence over a 5.5-year follow-up period in remitted recurrently depressed patients. Preventive therapies should focus on these factors. Although a substantial part of variation in recurrence (29%) was explained by these predictors, most of it remains unexplained. Consequently, recurrence remains a difficult to predict and only partially understood phenomenon.

TRIAL REGISTRATION: International Standard Randomized Controlled Trial Register Identifier: ISRCTN68246470.