Share this article on:

Efficacy of an Algorithm-Guided Treatment Compared With Treatment as Usual: A Randomized, Controlled Study of Inpatients With Depression

Bauer, Michael MD, PhD*; Pfennig, Andrea MD, MSc*; Linden, Michael MD, PhD; Smolka, Michael N. MD*; Neu, Peter MD; Adli, Mazda MD§

Journal of Clinical Psychopharmacology: August 2009 - Volume 29 - Issue 4 - p 327-333
doi: 10.1097/JCP.0b013e3181ac4839
Original Contributions

Objective: Medication algorithms have been proposed as effective means to offer optimal treatment and improved outcome for patients with severe mental illness. This single-center prospective study compared the efficacy and effects on treatment prescriptions of an algorithm-guided treatment regimen with treatment as usual (TAU) in depressed inpatients.

Methods: Depressed inpatient participants were randomized to an algorithm-guided standardized stepwise drug treatment regimen (SSTR, n = 74) or TAU (n = 74). The SSTR regimen included sleep deprivation, antidepressant monotherapy, lithium augmentation, monoamine oxidase inhibitor therapy, or electroconvulsive therapy guided by scores on the clinician-rated Bech-Rafaelsen Melancholia Scale. The primary outcome was time to remission (defined as a Bech-Rafaelsen Melancholia Scale score of ≤7). Secondary outcomes were remission rates, number of changes in treatment strategies (types), and the number of different prescribed medications over the treatment period.

Results: Patients receiving SSTR had a significantly shorter time to remission (7.0 ± 0.9 weeks vs 12.3 ± 1.8 weeks for TAU). Compared with that in remitters in SSTR, the number of strategy changes was significantly higher in TAU remitters (3.0 ± 2.7 and 1.0 ± 1.5) and had more psychotropic medications (fix agents: 3.0 ± 1.5 and 1.9 ± 1.1; optional agents: 1.5 ± 1.0 and 0.9 ± 0.7). Although more patients dropped out of the SSTR group (33 of SSTR, 12 of TAU), the probability of remission tended to be higher in SSTR.

Conclusions: Algorithm-guided treatment produces better outcomes and less frequent medication changes than TAU. A systematic, stepwise, measurement-based approach to the treatment of depressed inpatients is warranted.

From the *Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Technische Universität Dresden; †Rehabilitation Center Seehof, Teltow; ‡Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Campus Benjamin Franklin; and §Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Campus Mitte, Berlin, Germany.

Received October 9, 2008; accepted after revision April 13, 2009.

The German Algorithm Project, Phase 2, was supported by unrestricted research grants from Lily Deutschland GmbH, Janssen-Cilag, and Wyeth Pharmaceuticals.

Reprints: Michael Bauer, MD, PhD, Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstr 74, D-01307 Dresden, Germany (e-mail:

Depression is a prevalent disorder that imposes a high burden on individuals and society. In addition to the intensive use of the health care system and substantial costs, major depressive disorder (MDD) is associated with more functional impairment than most chronic medical illnesses.1

Despite considerable increase in the number of treatment strategies for the past 20 years, treatment-resistant depression remains a significant problem in clinical practice.2-4 Up to 40% of patients do not respond to the first course of drug treatment chosen, and approximately half of those do not subsequently respond to a different course of treatment.5,6 Remission, which is the primary goal of treatment, is achieved in even fewer patients (usually approximately 30%).7-9

Inadequate and unsystematic treatment plans may be among the major contributors to unfavorable treatment outcomes.5 In clinical practice, apparent "treatment resistance" frequently results from inadequate dosages, too brief durations of treatment, or insufficient use of the available therapeutic repertoire. Only a minority of "treatment-resistant" patients have absolute resistance (ie, do not respond to an adequate dose and duration of treatment).10 Rigorous treatment management may enhance outcomes.9 On the other hand, the probability of response to an antidepressant declines by a factor of approximately 15% to 20% for each adequately delivered but failed drug treatment.11

Systematic treatment algorithms have been developed to decrease inappropriate variance and to increase the use of appropriate treatment strategies to enhance patient outcomes.12-15 Algorithms seem to provide an effective means to optimize clinical outcomes.13,16 A standardized stepwise drug treatment regimen (SSTR) is one example of such a systematic treatment approach. Standardized stepwise drug treatment regimens are empirically derived protocols based on sequential application of a variety of single therapeutic steps.15

The German Algorithm Project (GAP) was designed to evaluate the feasibility and efficacy of antidepressive treatment algorithms in clinical practice. This multistep project included 3 phases: GAP 1: an observational 2-year pilot study to evaluate effectiveness, feasibility, and acceptance among algorithm users17; GAP 2: a randomized, controlled, single-center study to evaluate treatment efficacy and treatment process compared with treatment as usual (TAU); and GAP 3: a nationwide, randomized, controlled study to evaluate efficacy of 2 different treatment algorithms compared with TAU (in the "Research Network on Depression" supported by the German Federal Ministry for Education and Research).18 The GAP 1 demonstrated favorable overall clinical effectiveness of algorithm-guided treatment of depression (total response rate, 72%) and a moderate acceptance by algorithm-naive physicians (patient inclusion rate, 48%).15,17 The main results of the second phase (GAP 2) are presented here.

Back to Top | Article Outline



This randomized, prospective, single-center study was conducted at the Department of Psychiatry, Freie Universität Berlin, Germany. Patients with a depressive syndrome consecutively hospitalized as inpatients between June 1, 1997, and May 31, 2000, were screened for study eligibility by clinical interview. Patients with an International Statistical Classification of Diseases, 10th Revision (ICD-10),19 diagnosis of a major depressive episode with or without psychotic features, dysthymia, longer depressive reaction, and bipolar depression were enrolled. Diagnoses were confirmed with the Composite International Diagnostic Interview, a fully structured diagnostic interview for the assessment of mental disorders, which provides current diagnoses according to the accepted ICD-10 definitions.20

Exclusion criteria included organic mental disorders, schizoaffective disorders, alcohol or substance dependence, substance-related affective disorders, ongoing prophylactic medication with a mood stabilizer (lithium, carbamazepine, or valproate) that could not be discontinued (decision made by treating physician). Further exclusion criteria were outpatient therapy with antidepressants used in the SSTR monotherapy step (step 3: amitriptyline, paroxetine, or venlafaxine; Fig. 1), which had been started 7 to 21 days before hospital admission, a specific indication for a treatment approach not included in the SSTR protocol (eg, history of a successful treatment response to a particular antidepressant or urgent clinical requirement of electroconvulsive treatment [ECT]), severe general medical illnesses prohibiting standard antidepressant medication proposed in the SSTR, pregnancy or breast-feeding, and involuntary court-ordered hospitalization. Patients were excluded when the total Bech-Rafaelsen Melancholia Scale (BRMS)21 score fell below 11 within the first 3 days of hospitalization (step 1), indicating spontaneous remission.



The study protocol was approved by the local ethics committee. After complete description of the study to the subjects, written informed consent was obtained.

Back to Top | Article Outline



The SSTR was developed by a consensus group of senior psychiatrists at the Department of Psychiatry, Freie Universität Berlin, Germany, based on a synthesis of current scientific knowledge on the treatment of depressive disorders.15 Experience drawn from GAP 1 study and novel therapeutic agents were integrated into the second version of the SSTR for use in the present study.

The primary feature of the SSTR is its stepwise, algorithm-guided, medical decision making based on the routine evaluation of clinical outcomes with the BRMS21 at 2-week intervals (Fig. 1). The BRMS includes 11 items, each rated from 0 to 4. Established thresholds are 6 to 14 for mild, 15 to 25 for moderate, and 26 to 44 for severe depression. Validity studies yielded high positive correlations between the BRMS and the 21-item Hamilton Rating Scale for Depression22 (correlation coefficient r = 0.86).23

The SSTR included 10 sequential treatment steps (Fig. 1). In step 1 (first 3 days after admission), previous unsuccessful medication(s) was tapered. In step 2, patients underwent 1 or 2 courses of total or partial sleep deprivation to improve depression, to identify spontaneous remitters, and to complete psychiatric and medical assessments. In step 3, a 2-week antidepressant monotherapy was started, with a tricyclic antidepressant (amitriptyline or nortriptyline, 150 mg/d), a selective serotonin reuptake inhibitor (paroxetine, 40 mg/d), or a selective serotonin-norepinephrine reuptake inhibitor (venlafaxine, 225 mg/d). Titration was performed according to a standardized protocol, and target doses were achieved within 1 week. Selecting among these medications was left to the treating physician. During the SSTR procedures, concomitant psychotropic medication was not allowed except for hypnotic agents (chloral hydrate, up to 1000 mg/d) and/or antipsychotic agents (haloperidol, up to 10 mg/d; or olanzapine, up to 15 mg/d) only for depressed patients with psychotic symptoms (delusions and/or hallucinations). The subsequent steps (Fig. 1) included dose escalation of the initial antidepressant (step 4: amitriptyline or nortriptyline, 300 mg/d; paroxetine, 80 mg/d; and venlafaxine, 375 mg/d), augmentation with lithium carbonate for 4 weeks (step 5: starting dose of lithium carbonate 450 mg/d, increase on day 2 to 900 mg/d; subsequent dose adjustment to achieve lithium blood levels of 0.5-0.8 mM), discontinuation of all psychotropic medication except for lithium for 2 weeks (step 6), subsequent treatment with the irreversible monoamine oxidase inhibitor (MAOI) tranylcypromine (step 7: 20 mg/d for 2 weeks; step 8: 40 mg/d) in combination with lithium, discontinuation of MAOI treatment for 5 days while assessment of standard exclusion criteria for ECT was performed (step 9), and a subsequent course of ECT for another 2 to 4 weeks (step 10: 3 ECT sessions/wk, in case of cognitive adverse events and elderly patients 2 ECT sessions/wk).

The clinical outcome was categorized as nonresponse (change in BRMS, <6), partial response (change in BRMS of ≥6 but total score of >7), or remission (BRMS, ≤7). At critical decision points, categorization resulted in specific therapeutic action. Nonresponse after completion of the current step led to the next step; partial response led to an extension of the current step for another 2 weeks. No step, however, could be extended more than once. In cases of persistent partial responses at the next critical decision point, a switch to the next treatment step was mandatory. Remitted patients remained at the current step and were reevaluated after 1 week. If remission was confirmed, the patient exited the study and could be discharged. If remission could not be confirmed, the SSTR continued with a 2-week prolongation of the current step.

The treating physician's acceptance of the SSTR was assessed indirectly by evaluating rates of inclusion and exclusion of patients and documented reasons for exclusion and dropout. Adverse drug events and a physician's noncompliance (protocol violation and premature discharge) were predefined sources of possible algorithm deviation; only for the SSTR group did they constitute reasons for dropout that were nevertheless included in the analysis.

Treatment of patients randomized to the control group (TAU) was not protocol guided. Rather, physicians were free to apply whatever treatment they thought appropriate. Clinical evaluations of these patients were performed at the same time intervals as for SSTR patients but were not presented to the treating physicians.

Clinical ratings were performed by members of the research team at the end of each step between 10 am and 12 am. All raters completed a video-training on how to use the BRMS. An interrater reliability test yielded a high intraclass correlation coefficient (0.87).

For all study participants, supportive general psychiatric management including unstructured psychoeducation, psychological counseling as well as occupational therapy and physiotherapy were provided continuously throughout the study according to current hospital practice. However, no specific depression-targeted psychotherapy (ie, cognitive-behavioral therapy) was administered.

Back to Top | Article Outline

Outcome Measures

The primary outcome measure was time to remission (BRMS, ≤7). Secondary outcomes were rate of remission, number of strategy changes (each new prescription and each discontinuation were considered a strategy change, ie, 2 strategy changes were counted if a drug was stopped, and another one was started), number of psychotropic agents (fix, ie, any psychotropic agent ordered on a regular basis), optional psychotropic agents (ie, any psychotropic agent to be taken as needed), and number of different psychotropic drug classes used.

Back to Top | Article Outline

Power Calculation

The estimated sample size needed to detect a moderate effect on the primary outcome measure with a power of 80% and an alpha error of 5% was 64 patients per group. The moderate effect was defined as a difference in time to remission between the groups of 4 weeks. To account for possible dropouts, the aim was to include approximately 20% more patients.

Back to Top | Article Outline

Statistical Analysis

Differences in baseline characteristics between the SSTR and TAU were assessed using a χ2 test for categorical variables and a Student t test for continuous variables. Data are expressed as means (SD) and medians, where appropriate. With an alpha error of 5%, statistical significance for all analyses was assumed with P < 0.05 (2-tailed). P < 0.1 was considered a trend. Survival analysis was conducted to be able to use all patient data including right-censored cases due to dropout. It was assumed that treatment response did not differ between patients remaining in the study until remission and dropout. Median survival times were calculated using Kaplan-Meier statistics. Differences in probability (hazard) of remission between groups were analyzed using log-rank test and Cox regression modeling. Mean BRMS scores during treatment were compared between groups. Missing values were calculated using the last observation carried forward method. Analyses were based on the intent-to-treat population where the baseline measure was the final value for subjects that had no postbaseline measurement. Additionally, for sensitivity analysis, scenarios with all dropouts as nonremitters by the end of study (worst case) and with study completers only (best case) were modeled in a survival analysis. All statistical procedures were performed with the SPSS 10.0 (SPSS Inc, Chicago, Ill) package for Windows.

Back to Top | Article Outline


Of the 346 consecutive patients screened, 174 did not meet the inclusion criteria, and 12 declined study participation. One hundred sixty patients were enrolled, of which, 12 were excluded within the first 3 days after admission (change in diagnosis [n = 11]; drop in BRMS score, ≤10 [n = 1]). A total of 148 eligible patients were randomized to the SSTR algorithm (n = 74) versus TAU (n = 74) using computer-generated block randomization (10 per block).

There were no statistically significant differences in sociodemographic and clinical features between groups (Table 1).



There were no substantial differences in the type of medication or treatment strategy between groups. Tricyclic and tetracyclic antidepressants were administered in 48.6% of the TAU and in 40.5% of the SSTR group, selective antidepressants (selective serotonin reuptake inhibitor and serotonin-norepinephrine reuptake inhibitor) in 62.2% (TAU) versus 55.4% (SSTR), and MAOI in 16.2% (TAU) versus 13.5% (SSTR). Dose escalation to maximal dosages of antidepressants was used less frequently in the TAU than in the SSTR group (27.0% vs 47.3%). Antipsychotics were given to an equal proportion of TAU (37.8%) and SSTR (36.5%) patients. Lithium augmentation was performed in 39.2% of TAU and 44.6% of SSTR patients. Electroconvulsive treatment was applied in 5.4% (TAU) versus 8.1% (SSTR). Benzodiazepines were prescribed in 11% of TAU patients, whereas their use was not permitted in the SSTR group.

Survival analysis showed a significant difference in median time to remission between the groups (7.0 ± 0.9 for SSTR, 12.3 ± 1.8 weeks for TAU) (log-rank test, χ2 MC = 8.64, P = 0.003). Cox regression analysis revealed a hazards ratio of 2.02 (95% confidence interval, 1.25-3.28), indicating a 2-fold probability of remission in a given time interval in the SSTR group (Wald = 8.156; P = 0.004; Fig. 2). There was no statistical difference in mean BRMS scores between the groups at any time during the study. However, BRMS scores were numerically lower in the SSTR group at all time points; at weeks 8, 10, and 12, this difference reached P values below 0.1.



Of the 74 patients randomized to the SSTR group, 40 (54%) achieved remission compared with only 29 (39%) in TAU (χ2 = 3.3, P = 0.07).

In the remitters for each group, both baseline and exit depression severity were not different. The duration of treatment until remission was achieved tended to be shorter in SSTR (40 ± 26 days) than in TAU (51 ± 26 days) (P = 0.097). Remitters in TAU had a 3-fold higher number of strategy changes than did SSTR remitters (P = 0.001). The number of psychotropic agents and optional psychotropic agents applied in the SSTR remitters was significantly lower than that in TAU remitters; there was a trend for fewer different drug classes used in the SSTR compared with the TAU group. There was no difference between the groups in the dosage of antidepressants (Table 2).



Back to Top | Article Outline

Dropout Rates

More patients dropped out of the study in SSTR than in TAU (33 [45%] vs 12 [16%], χ2 = 14.08, P < 0.001). However, adverse drug events (18%) and protocol violations due to physicians' noncompliance (39%) that only applied to SSTR patients explained largely this difference between groups. Reasons for dropout that occurred in both groups were premature self-discharge (SSTR 15% vs TAU 58% of dropouts in the group), discharge before remission (SSTR 6% vs TAU 0%), withdrawal of consent (SSTR 15% vs TAU 17%), and miscellaneous events (SSTR 6% vs TAU 25%). The SSTR patients who dropped out showed no differences in sociodemographic and clinical variables except for age compared with those who remained in the study (42.0 ± 14.7 vs 51.4 ± 12.5 years; t = 2.655, P = 0.01).

Back to Top | Article Outline

Sensitivity Analysis

Analysis with all dropouts being counted as nonremitters (worst case scenario) and with study completers only (best case scenario) revealed hazards ratios of 1.59 (SE, 1.28; P = 0.059) and 2.64 (SE, 1.28; P < 0.0001). Thus, even with all dropouts being considered nonremitters, the probability of remission tended to favor SSTR.

Back to Top | Article Outline


This is, to our knowledge, the first randomized, controlled, prospective trial of hospitalized depressed patients to compare the outcomes of an algorithm-guided treatment (SSTR) with TAU. The study population had substantial symptom severity, chronicity, and significant coexisting psychiatric and general medical conditions.

The SSTR intervention was associated with a significantly faster symptom remission and higher remission rates than TAU. The magnitude of the difference between SSTR and TAU was robust (median time to remission, 7.0 vs 12.3 weeks; twice the probability of remission). There were also significant differences in other secondary outcome assessments, for example, fewer strategy changes, less use of psychotropic medication, and optional psychotropic agents in SSTR than TAU. More patients dropped out in SSTR, but even if all dropouts were considered to be nonremitters, the probability of remission tended to be higher with SSTR than with TAU. Because type of medication and treatment strategies used were not significantly different in the study groups, we suggest that the difference in efficacy mainly results from the timing of the use of pharmacological and nonpharmacological treatment strategies, fewer strategy changes, and more use of dose escalation in SSTR.

The superiority of algorithm-guided treatment is consistent with other recent reports. The Texas Medication Algorithm Project (TMAP13,24) compared prespecified medication algorithms combined with clinical support and a prespecified patient and family educational package for algorithm-guided treatment against TAU in public sector outpatients with MDD.24 Algorithm-guided treatment was associated with significantly greater symptom reduction over 1 year than with usual care. However, the interpretation of the TMAP study is limited by the fact that patients were not randomized. In TMAP, a care coordinator was part of the algorithm intervention, which could have accounted for part of the difference in improvement between the intervention and TAU. In the present study, no care coordinator was used, although such an addition could further enhance outcomes in SSTR.

In the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study, a measurement-based care approach including stepwise treatment procedures was assessed in a large outpatient sample with nonpsychotic MDD.25,26 Remission rates were 36.8% in step 1, 30.6% in step 2, 13.7% in step 3, and 13.0% in step 4. The remission rates in the first 2 steps resembled those reported in uncomplicated outpatients enrolled in 8-week registration trials, although more than 80% of patients had a chronic or recurrent course of illness. The authors of STAR*D suggested that the systematic use of easily implemented measurement-based care procedures could help achieve robust response and remission rates even in severe courses of disease.

Both TMAP and STAR*D included an outpatient population. In contrast, the study by Birkenhager et al27 and our study included inpatients only. The 4-step treatment algorithm of Birkenhager et al27 was quite similar to the one used in our study, and the reported remission rate of 50% is close to the 54% we found in the SSTR treatment arm.

The studies comparing algorithm-guided treatment with TAU suggest that the highly structured procedure of treatment and the operationalized assessment of response and side effects at critical decision points resulting in clear-cut therapeutic recommendations are effective components that account for better treatment outcomes. For a review of the efficacy of standardized treatment algorithms and a discussion on the rationale of algorithm development, their risks and limitations, and important elements in their implementation in clinical practice, see study by Adli et al.16

The present study includes the following limitations: (a) patients, clinicians, and outcome assessors were not blind to treatment assignment, which could have biased the results in favor of the SSTR group. However, patients' self-reports (on the von Zerssen Depression scale28) corroborated clinician ratings of the benefits of the SSTR intervention (data not shown). Physicians were aware of the intervention algorithm when treating patients randomized to the TAU arm of the study. Looking into the decisions they made regarding treatment choices, no major differences in drug classes and combination strategies were observed. Because the patients in both SSTR and TAU were treated by the same group of physicians, a tendency toward minimizing treatment differences between the groups cannot be ruled out but are regarded as a conservative bias. Considering this, it is even more remarkable that we still found a significant difference in efficacy. (b) This study was not placebo-controlled because we did not consider that ethical. The control condition TAU can be expected to show a higher efficacy than placebo treatment. (c) There was a high dropout rate, especially in the SSTR group, which mainly resulted from noncompliance of the treating physician to the protocol and occurrence of adverse events with predefined antidepressive medication. Possible explanations for physician's noncompliance include reluctance to follow preset guidelines and impatience, usually resulting in premature drug switches as seen in the control group (Table 2). Adverse events did occur in both groups but led to dropout only in the SSTR study group because, in the TAU group, physicians could simply switch to another treatment option. There may still be room for improvement within the applied stepwise treatment algorithm that could result in lower dropout rates, for example, by offering parallel alternatives in the algorithm steps, more flexibility in the duration of treatment steps, and by thoroughly educating physicians about the algorithm. Sensitivity analysis showed that even when assigning all dropouts in the SSTR group to be nonremitters, there still was a statistical trend with a 60% higher chance of remission within a specified time interval for SSTR patients (hazards ratio, 1.59; see "Results" section). (d) There were 17 depressed patients with a history of bipolar disorder in the study. Today, guidelines usually recommend a combination treatment with an antidepressant and a mood stabilizer for bipolar depression. However, at the time the SSTR was developed, there was no clear consensus about a differential treatment of depressive episodes in unipolar and bipolar affective disorder. We decided to keep the few bipolar patients in the analysis because this was how the study was designed originally. The fact that the number of bipolar patients was numerically higher in the TAU group could have influenced the efficacy of treatment or the number of dropouts. An additional analysis of time to remission omitting patients with bipolar disorders did not substantially influence the results; the hazards ratio for remission even increased to 2.3 in favor for the SSTR group (P = 0.002). Similar considerations about differential effectiveness of treatment could apply to patients with psychotic depression; however, the proportion of psychotic patients was approximately equal in the study groups. (e) The presented study was a single center trial, resulting in a limited number of patients assessed. Because only inpatients from a university hospital were included, the presented data may not apply to outpatients and patients in other nonacademic inpatient settings. In the TMAP study, the superiority of a stepwise treatment algorithm including care-based management has been demonstrated in outpatients.

Despite these limitations, study results may have direct implications for inpatient treatment of depressed patients. The results suggest that an algorithm-based intervention program for hospitalized patients with MDD enhances patient outcome and reduces costs because of the shorter duration of inpatient treatment. The duration of the treatment steps in the SSTR was chosen rather short and aimed at short inpatient treatment times. Increasingly, research data29,30 suggest that antidepressant response can be detected relatively early in the treatment process (within the first 2-4 weeks) and justifies our "rapid" algorithm procedures.

We are aware of the fact that many physicians and experts would likely use a different algorithm and steps in the treatment of their patients. Compared with the STAR*D protocol,l8,31 we gave the lithium augmentation strategy a much more prominent position because of the high evidence from placebo-controlled trials.32 The dosage of the irreversible MAOI was restricted to a maximum of 40 mg/d within the SSTR protocol. With dosages up to 80 mg/d, an even higher efficacy could have been possible.33-35

Back to Top | Article Outline


An algorithm-guided stepwise intervention for depressed inpatients seems to be more effective than TAU. Remission from depression was achieved faster with the SSTR intervention than with TAU. The third phase of the GAP conducted at both academic and nonacademic hospitals will further evaluate the efficacy of the SSTR algorithm.

Back to Top | Article Outline


The authors thank Professor Emeritus H. Helmchen for advice on the SSTR protocol; Ursula Kiesslinger, M.A., for help with recruitment and rating of patients; and Catherine Aubel for editing the article.

Back to Top | Article Outline


Dr Bauer has received grant/research support from The Stanley Medical Research Institute, NARSAD, Eli Lilly and Company, and AstraZeneca. He is a consultant for AstraZeneca, Eli Lilly and Company, Servier Deutschland, Lundbeck, and Wyeth Pharmaceuticals. Dr Bauer has received speaker honoraria from AstraZeneca, Eli Lilly and Company, Lundbeck, GlaxoSmithKline, Pfizer, and Wyeth Pharmaceuticals. Dr Pfennig received a stipend/research support from GlaxoSmithKline and research support from AstraZeneca. Dr Adli has received grant/research support from Pharmacia, Pfizer, Eli Lilly and Company, Janssen-Cilag, and Wyeth Pharmaceuticals. He has received speaker honoraria from AstraZeneca, Eli Lilly and Company, GlaxoSmithKline, Pfizer, Sanofi-Aventis, and Wyeth Pharmaceuticals.

Back to Top | Article Outline


1. Wells KB, Stewart A, Hays RD, et al. The functioning and well-being of depressed patients. Results from the Medical Outcomes Study. JAMA. 1989;262:914-919.
2. Nolen WA, Haffmans J. Treatment of resistant depression. Review on the efficacy of various biological treatments, specifically in major depression resistant to cyclic antidepressants. Int Clin Psychopharmacol. 1989;4:217-228.
3. AHCPR (Agency for Health Care Policy and Research). Evidence Report on Treatment of Depression: Newer Pharmacotherapies. Washington, DC: San Antonio Evidence-Based Practice Center; 1999.
4. Keller MB. Issues in treatment-resistant depression. J Clin Psychiatry. 2005;66(suppl 8):5-12.
5. Bauer M, Whybrow PC, Angst J, et al. World Federation of Societies of Biological Psychiatry (WFSBP) Guidelines for Biological Treatment of Unipolar Depressive Disorders, Part 1: Acute and continuation treatment of major depressive disorder. World J Biol Psychiatry. 2002;3:5-43.
6. Bauer M, Whybrow PC, Angst J, et al. World Federation of Societies of Biological Psychiatry (WFSBP) Guidelines for Biological Treatment of Unipolar Depressive Disorders, Part 2: Maintenance treatment of major depressive disorder and treatment of chronic depressive disorders and subthreshold depressions. World J Biol Psychiatry. 2002;3:69-86.
7. Trivedi MH, Rush AJ, Wisniewski SR, et al. Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: implications for clinical practice. Am J Psychiatry. 2006;163:28-40.
8. Trivedi MH, Fava M, Wisniewski SR, et al. Medication augmentation after the failure of SSRIs for depression. N Engl J Med. 2006;354:1243-1252.
9. Thase ME, Rush AJ. Treatment-resistant depression. In: Bloom FE, Kupfer DJ, eds. Psychopharmacology: The Fourth Generation of Progress. New York, NY: Raven Press; 1995:1081-1097.
10. Berlim MT, Turecki G. Definition, assessment, and staging of treatment-resistant refractory major depression: a review of current concepts and methods. Can J Psychiatry. 2007;52:46-54.
11. Amsterdam JD, Maislin G, Potter L. Fluoxetine efficacy in treatment resistant depression. Prog Neuropsychopharmacol Biol Psychiatry. 1994;18:243-261.
12. Amsterdam JD, Hornig-Rohan M. Treatment algorithms in treatment-resistant depression. Psychiatr Clin North Am. 1996;19:371-386.
13. Gilbert DA, Altshuler KZ, Rago WV, et al. Texas Medication Algorithm Project: definitions, rationale, and methods to develop medication algorithms. J Clin Psychiatry. 1998;59:345-351.
14. Rush AJ, Crismon ML, Toprac MG, et al. Consensus guidelines in the treatment of major depressive disorder. J Clin Psychiatry. 1998;59(suppl 20):73-84.
15. Linden M, Helmchen H, Mackert A, et al. Structure and feasibility of a standardized stepwise drug treatment regimen (SSTR) for depressed inpatients. Pharmacopsychiatry. 1994;27(suppl 1):51-53.
16. Adli M, Bauer M, Rush AJ. Algorithms and collaborative-care systems for depression: are they effective and why? A systematic review. Biol Psychiatry. 2006;59:1029-1038.
17. Adli M, Berghofer A, Linden M, et al. Effectiveness and feasibility of a standardized stepwise drug treatment regimen algorithm for inpatients with depressive disorders: results of a 2-year observational algorithm study. J Clin Psychiatry. 2002;63:782-790.
18. Adli M, Rush AJ, Moller HJ, et al. Algorithms for optimizing the treatment of depression: making the right decision at the right time. Pharmacopsychiatry. 2003;36(suppl 3):S222-S229.
19. World Health Organization. International Classification of Diseases, 10th Revision. Geneva, Switzerland: WHO; 1996.
20. WHO. Composite International Diagnostic Interview - Version 1.1. Geneva, Switzerland: WHO; 1993.
21. Bech P, Rafaelsen OJ. The melancholia scale: development, consistency, validity and utility. In: Sartorius N, Ban TA, eds. Assessment of Depression. Berlin, Germany: Springer; 1986:259-269.
22. Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960;23:56-62.
23. Maier W, Philipp M, Heuser I, et al. Improving depression severity assessment-I. Reliability, internal validity and sensitivity to change of three observer depression scales. J Psychiatr Res. 1988;22:3-12.
24. Trivedi MH, Rush AJ, Crismon ML, et al. Clinical results for patients with major depressive disorder in the Texas Medication Algorithm Project. Arch Gen Psychiatry. 2004;61:669-680.
25. Trivedi MH, Rush AJ, Wisniewski SR, et al. Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: implications for clinical practice. Am J Psychiatry. 2006;163:28-40.
26. Rush AJ, Trivedi MH, Wisniewski SR, et al. Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR*D report. Am J Psychiatry. 2006;163:1905-1917.
27. Birkenhager TK, van den Broek WW, Moleman P, et al. Outcome of a 4-step treatment algorithm for depressed inpatients. J Clin Psychiatry. 2006;67:1266-1271.
28. Zerssen von D. Klinische Selbstbeurteilungsskalen aus dem Münchner Psychiatrischen Informations-System. a) Die Beschwerden-Liste. b) Die Depressivitätsskala. Weinheim, Germany: Beltz; 1976.
29. Stassen HH, Angst J, Delini-Stula A. Delayed onset of action of antidepressant drugs? Survey of results of Zurich meta-analyses. Pharmacopsychiatry. 1996;29:87-96.
30. Szegedi A, Müller MJ, Anghelescu I, et al. Early improvement under mirtazapine and paroxetine predicts later stable response and remission with high sensitivity in patients with major depression. J Clin Psychiatry. 2003;64:413-420.
31. Rush AJ, Trivedi MH, Wisniewski SR, et al. Bupropion-SR, sertraline, or venlafaxine-XR after failure of SSRIs for depression. N Engl J Med. 2006;354:1231-1242.
32. Crossley NA, Bauer M. Acceleration and augmentation of antidepressants with lithium for depressive disorders: two meta-analyses of randomized placebo-controlled trials. J Clin Psychiatry. 2007;68:935-940.
33. Birkenhager TK, van den Broek WW, Mulder PG, et al. Efficacy and tolerability of tranylcypromine versus phenelzine: a double-blind study in antidepressant-refractory depressed inpatients. J Clin Psychiatry. 2004;65:1505-1510.
34. Nolen WA, van den Broek WW, Birkenhager TK. Treatment with low doses of tranylcypromine resulted in a disappointing remission rate. Am J Psychiatry. 2007;164:524.
35. Adli M, Pilhatsch M, Bauer M, et al. Safety of high-intensity treatment with the irreversible monoamine oxidase inhibitor tranylcypromine in patients with treatment-resistant depression. Pharmacopsychiatry. 2008;41:252-257.

depression; algorithm; treatment as usual; outcome

© 2009 Lippincott Williams & Wilkins, Inc.