Design paperSequenced treatment alternatives to relieve depression (STAR*D): rationale and design
Section snippets
Introduction and background
Major depressive disorder (MDD) is a common, typically recurrent, often chronic, and very disabling disorder, costing the United States over $44 billion/year in direct and indirect costs [1]. MDD has a lifetime prevalence of 4.9ā17.9% [2], [3]. Women are twice as likely to suffer MDD as men. MDD occurs more frequently among young adults and among those with general medical conditions (GMCs) [4]. Depressed adults have nearly twice the annual health care costs of those without depression [5].
MDD
Aims and treatment paradigm
Sequenced Treatment Alternatives to Relieve Depression (STAR*D) aims to define prospectively which of several treatments are most effective for participants with MDD who experience an unsatisfactory clinical outcome following an initial and, if necessary, subsequent treatment(s). Eligible participants who consent to STAR*D are enrolled into the first level of STAR*D (level 1), which uses the selective serotonin reuptake inhibitor (SSRI) citalopram (CIT). Participants with an adequate clinical
Major endpoints
The primary outcome is depressive symptom severity, measured by the 17-item Hamilton Rating Scale for Depression (HRSD17) obtained at the end of each treatment level (levels 1ā4) by independent, telephone-based interviewers with no knowledge of treatment assignment [34], [35]. Treatment remission, for research purposes, is defined as an HRSD17 total score <8 upon exit from a treatment level. The 30-item Inventory of Depressive SymptomatologyāClinician-Rated (IDS-C30), obtained by the same
Selection of protocol treatments
The specific treatments at each level were selected to balance safety while evaluating common practices and pharmacological reasoning. A detailed rationale for the treatments chosen at each level are reviewed elsewhere [39].
To illustrate, CIT was chosen to represent the SSRI class at level 1 since, as several SSRIs will shortly become generic, health care systems are likely to encourage use of an SSRI as a first agent. Thus, defining the ānext bestā step following an ineffective SSRI has high
Organizational structure
The STAR*D infrastructure includes the NCC (Dallas), the data coordinating center (DCC) (Pittsburgh), and 14 regional centers (RCs), each of which oversees two to four primary and specialty care clinical sites (CSs). Each RC provides support, quality control, and coordination for the recruitment, retention, and safety of study participants and oversees the acquisition of clinical information from the CSs. STAR*D provides opportunities for ancillary studies relevant to improving the treatment of
Screening and clinical data
Table 2 summarizes the data collected during the screening process. Data collection forms can be ordered at www.star-d.org.
At all clinic visits, information is obtained to guide clinicians implementing study treatments (Table 3). Symptomatic status is measured by the QIDS-C16 [40], [41], [42]. The QIDS-C16 is used to gauge response because previous experiences suggest that global ratings may be insensitive to detecting residual symptoms [49], [50]. The QIDS-C16 rates all nine criterion symptoms
Anticipated analytic approaches
Data analyses from levels 2 and 3 are complicated by the fact that participants may accept or decline specific treatment strategies or substrategies (e.g., medication switch), in a so-called āequipoise-stratified randomizedā design [68]. For level 2 analyses, data will be stratified by acceptability strata, and Mantel-Haenszel Ļ2 tests will be used to make pairwise comparisons among the treatment options within the medication switch substrategy and between-treatment options within the
Sample size, power, and effect size
Levels 2 through 4 of STAR*D are considered separate RCTs, addressing the question, āWhat should be done next considering that the prior treatment(s) failed?ā Therefore, we have made efforts to maintain an overall type I error rate of 0.05 within each level.
Utilization and cost data analyses
Differences in utilization of services will also be calculated for each health outcome comparison among patients randomly assigned to treatment options within the same acceptability strata. Classifying care by type (depression-related, other mental, general medical) and setting (outpatient, emergency room, hospital), between-group differences from the censored and bimodal distributions often encountered with utilization data are tested separately by first comparing use versus no-use (e.g.,
Data monitoring and safety reporting
The data and safety monitoring board (DSMB) (three psychiatrists, one medical ethicist, one patient advocate, one statistician, and one physician/patient advocate) meets every 3 months to monitor various aspects of the study, including participant recruitment, protocol compliance, and adverse events. Adverse events are recorded by study clinicians or CRCs at each clinic visit, based on spontaneous reports and on a participant-completed side effects checklist. Serious adverse events (those that
Current status
As of June 1, 2003, 2555 subjects had been enrolled into level 1 at 41 CSs from 14 RCs. Of these, 771 had entered level 2, 164 had entered level 3, and 42 had entered level 4.
Conclusions
STAR*D uses a randomized, controlled design to evaluate both the theoretical principles and clinical beliefs that currently guide the management of treatment-resistant depression in terms of symptoms, function, satisfaction, side-effect burden, and health care utilization and cost estimates. Given the dearth of controlled data, results should have substantial public health and scientific significance, since they are obtained in representative participant groups/settings, using clinical
Acknowledgements
This project has been funded in part with federal funds from the National Institute of Health, National Institute of Mental Health under Contract N01-MH-90003. Additional funds were provided by the Betty Jo Hay Distinguished Chair in Mental Health, Rosewood Corporation Chair in Biomedical Science and the Sara M. and Charles E. Seay Center for Basic and Applied Research in Psychiatry (A.J.R.), and by MH-30915 (Mental Health Intervention Research Center) (M.E.T., D.J.K.). The following
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See appendix for a complete listing and location of regional centers, regional center directors, and clinical sites.