Background: The goal of the Berlin Algorithm Project is to establish a standardized stepwise drug treatment regimen (SSTR) for the treatment of inpatients with depressive disorders. We are reporting on the first of 3 subsequent study phases evaluating effectiveness and feasibility of the SSTR in a naturalistic clinical setting.
Method: Patients with depressive disorders (International Classification of Diseases, Ninth Revision criteria) admitted to an academic medical center for inpatient treatment were enrolled in the SSTR protocol that comprised an algorithm-guided sequential treatment process (including pharmacologic washout period, sleep deprivation, antidepressant monotherapy, lithium augmentation, monoamine oxidase inhibitor treatment, and electroconvulsive therapy) dependent on the scores of a standardized assessment of treatment outcome, the Bech Rafaelsen Melancholia Scale (BRMS).
Results: Of 248 patients with depression, 119 (48%) were enrolled in the SSTR protocol. One hundred twenty-nine patients (52%) were not included, mostly due to individualized treatment procedures. An intent-to-treat (ITT) analysis showed that 38% of enrolled patients achieved remission (BRMS score < or = 5), 34% achieved "classic" response (deltaBRMS score > or = 50%), 15% achieved "low" response (deltaBRMS score 26% to 49%), and 13% did not respond. The overall response rate (remitters and classic responders) of SSTR treatment was 72% of the ITT sample. Twenty-one patients (18%) dropped out from the SSTR as nonresponders and 19 patients (16%) dropped out as low responders due to protocol deviations.
Conclusion: The acceptance of the antidepressive treatment algorithm among physicians not specifically trained was moderate, resulting in a relatively low enrollment rate. However, once patients were enrolled into the study, adherence to the algorithm-based rules resulted in a low dropout rate. Most importantly, algorithm-guided antidepressive treatment showed a favorable response in those depressed patients who were treated according to the SSTR protocol.