Links To And Excerpts From “What Are the Implications of the STAR*D Trial for Primary Care? A Review and Synthesis”

For a much more negative evaluation of the STAR*D trial, please review Guidelines for the pharmacological acute treatment of major depression: conflicts with current evidence as demonstrated with the German S3-guidelines [PubMed Abstract] [Full-Text HTML] [Full-Text PDF]. BMC Psychiatry. 2019 Sep 2;19(1):265.

The above article has been cited by 9 articles in PubMed. PubMed lists 72 similar articles. PubMed lists 17 similar articles published in the last five years.

In this post, I link to and excerpt from What Are the Implications of the STAR*D Trial for Primary Care? A Review and Synthesis [PubMed Abstract] [Full-Text HTML] [Full-Text PDF]. Prim Care Companion J Clin Psychiatry. 2008;10(2):91-6.

PubMed lists 83 similar articles. PubMed lists 30 similar articles in the last five years.

The above resource has been cited by 22 articles.

All that follows is from the above resource.


Background: Although results of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial have been widely disseminated to mental health care providers, hitherto, primary care providers, who diagnose and manage most individuals with depressive syndromes, have had minimal exposure to the study’s key findings.

Objective: We aim to provide translational implications of the STAR*D trial for primary care practitioners as well as for future research vistas.

Data Sources: A PubMed search was carried out with key search terms STAR*D and treatment-resistant depression found in articles published from 2001 through 2007.

Study Selection: Articles reporting on the STAR*D outcomes at each sequence of treatment were the primary sources for review.

Data Extraction: Results from the primary outcome measures at each sequential treatment were extracted and reviewed. Articles reporting variables affecting the probability of achieving remission were also selected.

Results: The STAR*D trial is the largest effectiveness study evaluating next-step therapies in real-world patients with major depressive disorder. The ecological validity of the study results are burnished by several methodological factors, including the enrollment of both publicly and privately insured patients, the recruitment of patients in primary and specialty care settings, the broad inclusion criteria, the use of pharmacologic and psychosocial (i.e., cognitive-behavioral therapy) treatment options, the use of measurement-based care, and the randomized clinical equipoise design. Taken together, remission rates of approximately 50% to 55% were reported after 2 sequential treatment interventions. A substantial percentage of individuals achieving remission do so after 6 weeks of treatment. The probabilities of achieving remission with third- and fourth-step therapy were considerably lower, i.e., ≤ 25%. The probabilities of relapse during continuation therapy increased as a function of number of treatment trials required to achieve remission. There is no evidence that individuals failing to achieve remission with a selective serotonin reuptake inhibitor (SSRI) have a greater probability of remitting with a separate class antidepressant versus an alternative SSRI.

Conclusion: A window of therapeutic opportunity appears to exist insofar as acute remission rates in major depressive disorder are greatest with the first 2 sequential treatments. Taken together, measurement-based care affords the greatest probability that an individual will achieve remission. Despite optimal continuation treatment, relapse rates remain significant, underscoring the chronicity of depressive disorders.


The composite of depression in primary care is similar to specialty care settings with reports of an overrepresentation of somatic symptoms in individuals utilizing primary care services. Subgroup analyses evaluating individuals recruited from specialty and primary care sectors participating in the STAR*D trial revealed minimal differences in symptom severity, course of illness variables, and/or patterns of comorbidity. . . . Moreover, symptomatic outcome, presented as a continuous or categorical (i.e., remission/response) outcome variable, was not different in the specialty and primary care STAR*D patients.

The encompassing aim of the STAR*D trial was to address the pragmatic and fundamental question: What is the treatment of next choice in individuals failing to achieve remission with index antidepressant therapy? Toward that aim, the STAR*D trial evaluated disparate pharmacologic treatment options as well as cognitive-behavioral therapy (CBT) administered as augmentation/combination or switching strategies (Figure 1). The primary outcome measure in the STAR*D trial was remission, operationalized as a total 17-item Hamilton Rating Scale for Depression score of ≤ 7. Subjects who failed to achieve remission after a 12 to 14 week index trial with the selective serotonin reuptake inhibitor (SSRI) citalopram were given the opportunity to proceed to the next step of treatment. Individuals who achieved remission after index therapy were offered enrollment into a 12-month follow-up observation period to evaluate for relapse of illness.

Fig1 when server ready.

In keeping with the view that decision support (e.g., evidence-based guidelines, clinimetrics) is a critical component of chronic disease management capable of enhancing patient outcome, all participating centers adopted measurement-based care.

Measurement-based care refers to the routine use of rating scales, systematic monitoring of treatment adverse events, guideline-informed antidepressant dosing, and other decision support to guide treatment.


The STAR*D trial provides an empirical basis for informing clinical decisions in the management of depression in primary care settings. The overarching question addressed by the STAR*D trial, (i.e., what is the most effective treatment of next choice?) is a common scenario in real-world clinical practice. Several algorithms for the selection and sequencing of antidepressant treatment, staging of treatment resistance in major depression, and hierarchies of evidence supporting treatment options have been published elsewhere (Tables 1 and and2).2). Guiding therapeutic principles include clarification of the principle diagnosis, identifying comorbidities or medications that possibly exacerbate depressive symptoms, ensuring adherence to treatment, and optimization of the index trial. Subsequent options include combining/augmenting with or switching to alternative medications or CBT.

fig2 when the server is ready.
Most depressed patients in the primary care setting who are labeled as treatment resistant are in fact “pseudoresistant” (i.e., they have not received sufficient guideline-concordant treatment). Before a strong pronouncement of treatment resistance is made, index trial optimization should be implemented by ensuring maximally recommended dosing for a sufficient period of time. Most available evidence-/consensus-based guidelines for the treatment of depression recommend index trial duration of approximately 4 to 6 weeks.
Results from the STAR*D trial indicate that longer index trials may be required for treated patients to realize the full therapeutic potential of the intervention. For example, of all participants who eventually remitted to index therapy, up to one half did so between weeks 6 and 12. Consequently, discontinuing antidepressant treatment prior to 6 weeks of therapy due to ineffectiveness may be premature in some cases.
The suggestion for a longer index trial needs to be considered in the context of patient acceptance of ongoing treatment despite the lack of a meaningful therapeutic benefit. An interesting implication of the observed late response to index therapy is the possibility that many individuals previously labeled as augmentation/combination responders may in fact be simply responding to the index trial.
Converging with clinical experience, STAR*D results indicate that the probability of achieving remission decreased in the STAR*D trial as a function of number of treatment interventions. Similarly, the probability of relapse was higher in individuals requiring multiple steps to achieve acute remission. For example, the overall remission rates for the medication options were 28%, 25%, 18%, and 10% at steps 1, 2, 3, and 4, respectively. Taken together, 53% and 81% of patients can be expected to achieve remission after 2 and 4 sequential pharmaco-therapies, respectively.
Given that higher relapse rates were observed among those who are treatment resistant, patients requiring multiple treatment interventions need to be carefully observed for recrudescence of depressive symptomatology.
Primary care providers may be less comfortable prescribing later-step treatments (e.g., tranylcypromine), inviting the need for specialist consultation, when available, after 2 or more failed adequate antidepressant trials.
It should be noted that the STAR*D trial did not evaluate the potential role of electro-convulsive therapy, which remains an effective treatment option for select patients suboptimally responding to pharmacotherapy and/or manual-based psychosocial intervention.
Remission is associated with a better prognosis even if multiple treatment interventions are required. For example, individuals achieving acute remission in the STAR*D trial evinced a longer time to relapse when compared to individuals not achieving remission (i.e., level 1 [4.4 months], level 2 [4.5 months], level 3 [3.9 months], and level 4 [2.5 months] versus level 1 [3.6 months], level 2 [3.2 months], level 3 [3.0 months], and level 4 [3.5 months]). A further analysis of the STAR*D data set revealed that female patients of reproductive age achieving remission were less likely to have a child with a mental disorder when compared to women whose depression was nonremitting.
An important clinical question pertains to the relative effectiveness of switching to an alternative monotherapy versus augmentation/combination with pharmacotherapy or CBT. Unfortunately, this question cannot be addressed by the STAR*D trial due to the clinical equipoise randomization design.
It is worth noting that overall symptomatic outcomes in the first and subsequent steps of the STAR*D trial may exceed outcomes typically encountered in routine clinical care. The use of measurement-based care, which includes measuring patient symptoms, using critical decision points for dose adjustments, and training clinicians, likely accounts for the improved outcome. Systematic measuring of symptoms allows a sharpened and more refined evaluation of illness severity, treatment response, and timing of interventions.
Several brief rating scales for depression have been published. The STAR*D trial utilized the QIDS-SR.* Copies of the QIDS-SR and other scales employed in STAR*D are available online. Several other published scales capable of quantifying and objectifying treatment outcomes in depression include, but are not limited to, the Patient Health Questionnaire and the 7-item Hamilton Rating Scale for Depression.

*Quick Inventory of Depressive Symptomatology (QIDS).
Rates depression symptoms via self-assessment, also known as QIDS-SR-16. From MDCalc.

(QIDS-SR) [Link is to the printable PDF]

To recapitulate, the STAR*D trial provides real-world generalizable results regarding the treatment of depressed individuals in primary care services in both public and private sectors. The representativeness of patients as well as the clinical equipoise design provides meaningful and accessible data regarding next-step treatment. Unanswered questions from the STAR*D trial and vistas for future research remain: Should combination treatment be initiated as first-line therapy for depression? What is the role for atypical antipsychotics in the symptomatic treatment of depression? and What is the optimal duration of maintenance treatment for individuals achieving remission? The answers to these and several other clinically relevant questions will be informed by ongoing studies.


This entry was posted in Depression, Guidelines. Bookmark the permalink.