PRIME Care (PRecision Medicine In MEntal Health Care)
Phase: NA
Conditions: Major Depression
Sponsor: VA Office of Research and Development

 
 
 
 
 
 
 
 
 
PRIME Care (PRecision medicine In MEntal health Care) 
 
Funding Agency: VA Office of Research and Development 
 
Principal Investigator: David Oslin, MD 
 
Version Number 18 
 
October 22, 2021 
 
 
 

  
PRIME Care – Protocol Version 18  10/22/21 Page 2 of 45 
 
 
 
Abstract 
 
Background:  In the last several years, commercial pharmacogenetic (PGx) testing for the 
selection of psychotropic medications has become widespread as a means of implementing 
“precision medicine”, with some insurers electing to cover the cost of testing.  These 
developments have put increasing pressure on the Veterans Health Administration to implement 
a mental health focused PGxs program, especially for treating depression, but without sufficient 
scientific study to support the utility of its clinical application.   
 
Objectives:  This project is designed to evaluate the utility of PGx testing in treating Major 
Depressive Disorder. 
 
Methods:  The project is a multi-site randomized clinical trial in which 2000 patient/provider 
dyads will be randomly assigned to receive the results of the PGx battery right after 
randomization (i.e., the intervention group) or after 6 months of treatment as usual (i.e., the 
delayed results group).  The study will test the following primary hypotheses: 
 
1. Veterans with major depressive disorder (MDD) whose care is guided by the results of 
the PGx battery (the intervention group) will have a higher rate of remission of depression than 
those in the delayed results group.  
2. Provider/patient dyads in the intervention group will use fewer medications that have 
potential gene-drug based on commercial PGx tests results than dyads in than the delayed 
results group.  
  
The patient inclusion and exclusion criteria are designed to target a population of patients 
with a major depression diagnosis who are starting or switching antidepressants.    
 
Anticipated Impact on Veteran’s Healthcare:  Despite the high prevalence of depression 
and its adverse impact on healthcare costs and life functioning, its treatment is often 
inadequate.  As shown in several studies, to achieve remission from depression, patients and 
providers must be persistent and try multiple treatments until they find one that is both tolerable 
and effective.  However, with each round of treatment, there is greater attrition from care.  
Replication of the results of the few PGx implementation studies that have been conducted to 
date suggest that PGx could enhance the treatment of MDD and provide an impetus for early 
diagnosis and treatment initiation, resulting in more rapid and higher rates of remission.   
 
 
 

  
PRIME Care – Protocol Version 18  10/22/21 Page 3 of 45 
 
Contents 
1.0 
Study Personnel ................................................................................................................ 4 
2.0 
Introduction ....................................................................................................................... 6 
3.0 
Objectives ......................................................................................................................... 7 
4.0 
Background ....................................................................................................................... 7 
5.0 
Study Procedures .............................................................................................................11 
5.1 Study Design ............................................................................................................12 
5.2 Recruitment Methods ................................................................................................13 
5.3 Informed Consent Procedures ..................................................................................17 
5.4 Inclusion/Exclusion Criteria .......................................................................................18 
5.5 Study Evaluations .....................................................................................................18 
5.6 Data Analysis ............................................................................................................29 
5.7 Withdrawal of Subjects ..............................................................................................36 
6.0 
Data safety and monitoring ...............................................................................................37 
7.0 
Privacy and Confidentiality ...............................................................................................37 
8.0 
Communication Plan ........................................................................................................38 
9.0    Risk/Benefit: .....................................................................................................................39 
10.0  Resources and personnel ................................................................................................40 
11.0  References .......................................................................................................................41 
 
 
 

  
PRIME Care – Protocol Version 18  10/22/21 Page 4 of 45 
 
Protocol Title:  PRIME Care (PRecision medicine In MEntal health Care) 
 
1.0 Study Personnel 
 
Principal Investigator 
• 
David Oslin, MD 
Chief of Behavioral Health and VISN 4 MIRECC Director,  
CPL Michael J. Crescenz VAMC  
Professor of Psychiatry, University of Pennsylvania Perelman School of Medicine 
 
Conflict of Interest: 
The investigators have no relationships that would be considered a conflict of interest for 
this project.   
 
Executive Committee (EC) for the trial, all of whom will serve as investigators or site 
principal investigators. 
This committee will regularly conduct an ongoing, internal critique of program activities, 
providing an opportunity to exchange information on the activities across the project.  The EC is 
an interdisciplinary group with representation from genomic medicine, informatics, clinical 
research, laboratory medicine, pharmacy, ethics, and primary care.  Monthly virtual meetings of 
the EC will be chaired by Drs. Oslin and Thase. Site PIs will be encouraged to participate in EC 
proceedings and scientific discovery. EC meetings will focus on the coordination of study activity 
such as recruitment and personnel issues.  Members of the EC are listed below. 
 
• 
CPL Michael J. Crescenz VAMC University of Pennsylvania 
Henry R. Kranzler, MD 
Role in Project: Investigator 
Co-Associate Director of Research, VISN 4 MIRECC, 
Professor of Psychiatry, University of Pennsylvania Perelman School of Medicine 
 
Kevin Lynch, PhD 
Role in Project: Investigator 
Assoc. Professor of Biostatistics in Psychiatry 
University of Pennsylvania Perelman School of Medicine 
 
Michael E. Thase, MD 
Role in Project: Investigator 
Professor of Psychiatry  
CPL Michael J. Crescenz VAMC  
Professor, University of Pennsylvania Perelman School of Medicine 
 
• 
VA Pittsburgh Healthcare System 
Sara Chapman, MS, OTR/L 
Role in Project: Investigator 
Associate Director of Education VISN 4 MIRECC, 
 
• 
VA Salt Lake City Health Care System 
Scott Duvall, PhD 
Role in Project: Investigator 
Director, VA Informatics and Computing Infrastructure (VINCI) 

  
PRIME Care – Protocol Version 18  10/22/21 Page 5 of 45 
 
• 
VA Connecticut 
Joel Gelernter, MD 
Role in Project: Investigator 
Foundations Fund Professor of Psychiatry 
Yale University School of Medicine  
 
• 
VA Central Office 
Lisa Lehmann, MD, PhD, MSc.  
Role in Project: Investigator 
Executive Director, National Center for Ethics in Health Care 
Associate Professor of Medicine and Medical Ethics, Harvard Medical School 
 
• 
Central Arkansas Veterans Healthcare System 
Jeffrey Pyne, MD 
Role in Project: Investigator 
Associate Director for Research, South Central MIRECC 
Director Rural Access and Engagement CREATE 
Professor, Psychiatric Research Institute, University of Arkansas for Medical 
Sciences 
 
• 
Annjanette Stone, MS 
Role in Project: Investigator 
Laboratory Manager, Pharmacogenomics Analysis Laboratory 
University of Arkansas for Medical Sciences 
 
• 
VA Palo Alto Cooperative Studies Program Coordinating Center 
Mei-Chiung Shih, PhD 
Role in Project: Investigator 
Stanford University 
 
• 
VA Western New York Healthcare System at Buffalo 
Laura O. Wray, PhD, MPH 
Role in Project: Investigator 
Executive Director, VA Center for Integrated Healthcare 
Associate Professor, School of Medicine and Biomedical Sciences, University at 
Buffalo 
 
 
Study management 
Study management will be overseen by Drs. Oslin and the EC.  The Crescenz VA Medical 
Center will be the coordinating center for this study.  Both a regulatory and an operations 
coordinator will be housed at the coordinating site; they will report to the senior research 
coordinator and be responsible to coordinate with local sites on everyday study activities.  The 
monthly site coordinator meeting will be run by the coordinating site research staff to discuss 
study progress, coordinate research efforts, communicate changes in the protocol or 
procedures, and discuss regulatory items.  To kick off the project at each site, the Crescenz VA 
Medical Center hosted a 2-day trainings for site PIs and coordinators.    
A monthly EC call will monitor the various activities of the trial and coordination with team 
members.  Local site PIs will be invited to participate in the EC calls as needed. 
 

  
PRIME Care – Protocol Version 18  10/22/21 Page 6 of 45 
 
The Coordinating site staff will be responsible to: 
• 
ensure that all required local site approvals are obtained;  
• 
keep all engaged sites informed of changes to the protocol, informed consent form, 
and HIPAA authorization 
• 
inform local sites of any serious adverse events (SAEs), unanticipated problems, or 
interim results that may impact the conduct of the study 
• 
notify all local facility directors and local site investigators (LSI) when a multi-site 
study reaches the point that it no longer requires engagement of the local facility 
(e.g., all subsequent follow-up of subjects will be performed by the staff at the 
Philadelphia coordinating site). 
 
 
2.0 Introduction 
 
Genomic testing has the potential to improve patient outcomes and reduce patient care 
costs through personalizing medication selection. Commercial pharmacogenetic (PGx) testing 
for psychotropic and other medications has become widely available and is advertised as 
providing the means to implement “precision medicine.”  As a consequence, some insurers 
[e.g., the Centers for Medicare and Medicaid Services (CMS)] have elected to cover the cost of 
PGx testing.  While there is evidence for this approach in other areas of medicine, clinical 
application to psychiatry has proceeded without sufficient scientific study.  Nonetheless, the 
commercialization of genomic testing has led to increased pressure on the Veterans Health 
Administration (VHA) to implement a mental health focused PGx testing program, especially for 
treating depression.   
 
While there is evidence that genetic variation affects the metabolism of psychotropic 
medications and, genetic testing to identify known variants has been commercialized, the 
clinical utility of these findings has yet to be established.  Moreover, implementing such tests in 
routine care is complex, requiring a systematic approach to ensure efficiency, effectiveness, and 
an appropriate understanding of its clinical implications.  To bridge the implementation gap, this 
project will consist of a randomized clinical trial (RCT) to evaluate the utility of PGx testing in 
treating Major Depressive Disorder (MDD).  The program project will be known as the PRIME 
Care study.  Focusing on PGxs in mental illness represents a distinct opportunity for the VA to 
contribute to the advancement of precision medicine in the United States, complementing the 
work of other federal agencies working to advance the personalized treatment of cancer, 
cardiovascular disease, and other medical disorders. MDD is one of the most common 
conditions associated with military service and combat exposure. Moreover, MDD increases 
suicide risk and worsens the course of common medical conditions, making it a leading cause of 
functional impairment and mortality.  Thus, validating a PGx test to personalize MDD treatment 
could contribute substantially to improving the healthcare of Veterans.   
 
The multi-site RCT, involving up to 25 sites, will examine whether and how patients and 
providers use genetic test results at the time an antidepressant medication is initiated to treat 
MDD and whether use of the test results improves patient outcomes.  The PGx test consists of 
a battery of genetic markers that principally identify genetic variation affecting the metabolism of 
psychotropic medications.  The project will also examine patients’ and providers’ experience of 
the PGx testing; establish processes to educate patients and providers, and explore ethical and 
economic issues related to genetic testing.  Thus, the program will empirically evaluate the utility 
of genetic testing for Veterans who are being treated for MDD and will facilitate the development 
of standards for PGx testing within the VA healthcare system (VHA).  Lastly, the RCT will yield a 

  
PRIME Care – Protocol Version 18  10/22/21 Page 7 of 45 
 
rich data source for the discovery of new PGx testing methods and the exploration of 
approaches that combine genetic testing with other treatment response modifiers (e.g., other 
medications, obesity, tobacco or alcohol use).   
 
3.0 Objectives 
 
The design of this randomized clinical trial, which will be registered on clinicaltrials.gov, is a 
two-arm, 24-week, parallel-groups comparison of patient/provider dyads that will be randomly 
assigned to receive the results of the PGx test at the time the planned treatment is initiated 
(intervention group) or to have the results returned after 24 weeks of treatment as usual 
(delayed results group).   The study will be conducted in up to 25 participating VA Medical 
Centers.  In the intervention group, patient/provider dyads will be encouraged but not obligated 
to follow the recommendations resulting from the PGx battery to inform shared decision making. 
The primary aims and secondary aims of the trial are to evaluate the utility of PGx testing in the 
treatment of MDD and to understand how providers and patients use the information for shared 
treatment decision making, respectively.  The study will test the following hypotheses: 
 
1. Veterans with MDD whose care is guided by the results of the PGx battery (the 
intervention group) will have a higher rate of remission of depression than the delayed results 
group. (Primary Hypothesis) 
2. Provider/patient dyads in the intervention group will use fewer medications that have 
potential gene-drug interactions based on commercial PGx test results than dyads in the 
delayed results group. (Primary Hypothesis) 
3. Veterans in the intervention group will have better secondary outcomes than the delayed 
results group, including depressive symptom severity, side effect rate, treatment adherence 
rate, number of outpatient visits, and functional improvement. (Secondary Hypothesis) 
4. Three months after receiving the PGx battery results, the delayed results group will show 
time-dependent changes in antidepressant prescribing and reductions in depressive symptoms 
that are similar in direction and magnitude to those seen in the intervention group. (Secondary 
Hypothesis) 
 
In addition to the primary and secondary aims of the project, we have included a 
number of exploratory aims such as examining other outcome markers, understanding 
provider and patient educational needs for PGx testing, understanding the ethical 
implications for providing PGx testing, understanding the biological relationship of serum 
concentrations of medication to PGx testing, and examining other genetic markers that 
may predict treatment using Genome Wide Association Study (GWAS) methods. In 
addition, we hope to better understand the interaction between sleep and activity and 
antidepressant use by offering an optional actigraphy component at selected sites.  
 
 
4.0 Background 
 
Major depressive disorder – impact and treatment.  We chose to focus on MDD because it is 
one of the most common conditions associated with military service. The high rate of MDD in 
military personnel is due, in part, to exposure to traumatic experiences, including witnessing 
combat and separation from family during deployment or military training [1].  For example, 
based on data collected in 2011 from a de-identified cross-sectional survey of active duty 
soldiers, the Army Study to Assess Risk and Resilience in Service members (Army STARRS) 
reported that the 30-day prevalence of MDD was 4.8%, compared to less than 1% among a 
civilian comparison group [2]. A meta-analysis of 25 epidemiological studies estimated the 

  
PRIME Care – Protocol Version 18  10/22/21 Page 8 of 45 
 
prevalence of current DSM-IV MDD to be 12.0% among currently deployed U.S. military 
personnel, 13.1% among previously deployed personnel, and 5.7% among individuals who were 
never deployed [3]. Among Veterans seeking care in the VHA, an estimated 21% of post-9/11 
Veterans suffer from MDD, a rate similar to that of PTSD [4]. Moreover, MDD results in poor 
overall quality of life, decreased productivity, and increased mortality, accounting for about two-
thirds of all cases of suicide [5].  Worldwide, MDD is the fourth leading cause of disease burden 
and is among the top five causes of morbidity [6-8].  Depression contributes to increased 
healthcare costs by increasing the risk for and adversely affecting the outcomes of a variety of 
conditions, including heart disease, which is the major cause of mortality in the United States [9-
16].     
 
The recently updated VA/DOD depression treatment guidelines recommend that either 
antidepressants or psychotherapy be used as a first-line treatment for mild-to-moderate 
depression and that a combination of these treatments be used for more severe, chronic, or 
recurrent depression [17].  However, beyond recognizing that several classes of newer 
generation antidepressants are more commonly used as first-line medications, there is no 
guidance as to which particular antidepressant should be prescribed or what might guide the 
change from one medication to another in the absence of a clinical response.  In essence, the 
selection of antidepressants is a trial and error process based on clinical judgment and the 
occurrence and severity of side effects.  Although antidepressants are approved by the Food 
and Drug Administration (FDA) to treat disorders other than MDD, they are most widely used to 
treat depression and thus are a natural focus for this project.  A 2009-2012 survey of medication 
use showed that 9.0% of Americans of all ages used an antidepressant in the last 30 days, 
making them the second most commonly prescribed class of medications behind lipid lowering 
agents (12.4%) and ahead of analgesics (8.8%) [18].  Moreover, the rate of antidepressant use 
increases with age (15% of those over 65 took an antidepressant in the last month), which is 
highly relevant to an aging Veteran population. Within the VHA population, 59% of Veterans 
with depression (n>300,000) are actively prescribed an antidepressant (VINCI data – see 
appendix 1).   
 
Despite their widespread use, antidepressants produce a relatively low remission rate in 
clinical practice. One of the largest community trials conducted for MDD, the Sequenced 
Treatment Alternatives to Relieve Depression (STAR*D) trial, demonstrated that only about one-
third of patients achieved remission with the first treatment, and that the odds of remission 
decreased further for each successive treatment trial [19].  To achieve remission from 
depression, patients and providers must try multiple treatments until they find one that is both 
tolerable and effective [20].  A major factor limiting a medication’s effectiveness is the patient’s 
willingness to persist in care and, if necessary, try several different courses of 
pharmacotherapy. Indeed, the STAR*D trial showed that with each subsequent trial of an 
antidepressant there was an increase in patient dropout from treatment, further reducing the 
likelihood of effective treatment [19, 21].  These findings underscore the potential value of 
personalized or precision treatment, in which the first choice of a medication may yield the 
highest success rate and the greatest reduction in morbidity and mortality.  
 
Using genetics to improve treatment response. Precision medicine is only possible when we 
rely on science, rather than trial and error, to guide the choice of treatment(s). However, 
treatment matching is complex and influenced by the pathophysiology of the disease, the 
pharmacokinetic properties of the medication, and the mechanism(s) of action of the 
medication, all of which may differ among individuals.  In the last decade, there have been 
substantial efforts to match patient characteristics to treatment, particularly by identifying genetic 
variation that moderates the treatment response either pharmacokinetically or 
pharmacodynamically.  Although non-genetic biomarkers or other characteristics can be used to 

  
PRIME Care – Protocol Version 18  10/22/21 Page 9 of 45 
 
match patients to specific treatments, genetic variation has been the most common focus of the 
burgeoning field of precision medicine.  
 
Two common approaches have been used to implement precision medicine.  The first 
focuses on disease variability, i.e., the fact that most disorders are heterogeneous and, as a 
consequence, different treatments are required for different subtypes of the disorder.  The 
second approach focuses on the pharmacokinetics of specific medications. This approach has 
been used by a variety of companies to identify genetic variation affecting the metabolism of 
many commonly prescribed medications, including psychotropics.  These companies have 
applied findings from some of the 140 FDA-approved medications whose labels contain PGx 
information, most of which affects metabolism (i.e., the drugs’ pharmacokinetics).  These 
companies classify individuals as slow, normal, rapid, or ultra-rapid metabolizers of specific 
groups of drugs based on the genetic variation detected in those individuals.  Thus, PGx testing 
rests on the concept that a patient who is a slow metabolizer of a medication will have a very 
high level of the medication and a greater likelihood of side effects than a normal metabolizer.  
Further, a rapid or ultra-rapid metabolizer will need a higher dose of the medication than a 
normal metabolizer to ensure an effective dosage of the medication.  Despite the intuitive nature 
of this approach, its implementation and impact on clinical outcomes are mostly untested. 
 
Current evidence base for the PGxs of psychotropic medications.  The Evidence Based 
Synthesis Program released a report on the use of PGx testing for antidepressants, concluding 
that more research was needed before routine testing could be incorporated effectively into 
clinical practice [22].  The just-released VA/DOD Clinical Practice Guidelines for Major 
Depression reached the same conclusion [17].  Despite substantial evidence that genetic 
variation is highly predictive of differences in the metabolism of antidepressants, there is only 
marginal evidence that these differences impact clinical outcomes [23, 24].  Variation in the 
genes encoding the hepatic CYP450 enzymes accounts for most of the variation in the 
metabolism of antidepressants [23], with variation in CYP2D6 and CYP2C19 genes affecting the 
metabolism of many of these drugs. The FDA encourages pharmaceutical companies to include 
PGx information in drug labels, which together with genetic information can be used to 
characterize patients as ultra-rapid, rapid, or slow metabolizers of the medications.  There is 
also growing interest in the use of genetic variants that yield pharmacodynamic differences 
among drugs.  Potential moderators of treatment response include variation in genes encoding 
serotonin receptors (e.g., 5-HT1A and 5-HTR2A, encoded by HTR1A and HTR2A), the 
serotonin transporter (SLC6A4), the dopamine transporter (SLC6A3) and inflammatory 
responses to antidepressant drugs (e.g., changes in the concentration of interleukin-1β) [25].  
Thus, commercial PGx tests often combine pharmacokinetic and pharmacodynamic marker 
information in the algorithms that they use to make antidepressant treatment recommendations. 
 
Three small (n’s of 51-148 patients), randomized trials compared PGx-guided treatment with 
usual care [26-28].  Only one of the three trials showed an advantage for the guided treatment 
approach, i.e., a higher rate of remission and fewer sick days in treatment than unguided 
treatment [27].  As shown on clinicaltrials.gov, two large trials with the Assurex product are 
currently underway, and Assurex is collaborating with the Centre for Addiction and Mental 
Health (CAMH) in Toronto on a large open-label joint PGx study.  Finally, one industry-
sponsored trial (Pathways) (n=300), initiated in 2016, is being conducted in the VAHS.  The VA 
study focuses on treatment refractory depression and bipolar disorder and is recruiting 3-4 
subjects per month. 
 
Pooled results of several studies, mostly sponsored by Assurex, provide modest support for 
PGx testing to guide antidepressant treatment, though findings must be interpreted with caution 

  
PRIME Care – Protocol Version 18  10/22/21 Page 10 of 45 
 
because of the small samples and the open-label design.  These studies suggest that guided 
treatment may result in lower health care utilization and lower pharmacy costs than unguided 
treatment (these outcomes will be evaluated in the current RCT in secondary analyses).  The 
pooled findings suggest that the use of guided treatment can result in patients experiencing 
higher rates of remission from depression [29-31].  Open-label evidence also suggests that 
Assurex’s proprietary algorithm for combining genetic marker data is superior to the individual 
use of genetic marker data [32].   Thus, the sum of the evidence shows that the combinatorial 
use of multiple markers may be of benefit even when the variance accounted for by some 
markers is small.  Assurex has sought to leverage this finding by including putative 
pharmcodynamic markers, such as variants in serotonin receptor genes, which have much less 
consistent evidence to support their use individually.  The identification of novel markers and 
alternative approaches to weighting the markers is an exploratory focus, which is linked to the 
current RCT. This additional source of hypothesis testing will seek to develop a more 
informative test that takes into account not only genetic markers, but other health care 
behaviors (e.g., smoking and the use of other medications that can affect antidepressant 
pharmacokinetics). In this manner, the PRIME Care study will yield critical information about 
how best to leverage PGx results to improve treatment efficacy, independent of the results from 
the RCT evaluating the standard delivery of PGx testing.   
 
Presentation of results.  The process of presenting genomic results to the patient and 
provider has not been well studied, though the evidence synthesis identified it as an important 
area on which to focus given its obvious clinical relevance.  We include an evaluation of this 
process.  Each company in the psychotropic medication genomics marketplace has taken a 
different approach to interpreting the genetic markers in their panels. Some companies (e.g., 
Genomind) present the “raw” results and the medication labeling information, leaving the 
provider to interpret these findings.  Other companies (e.g., Pathways and Assurex [see 
appendix for an example report]) provide raw data along with color coding of medications 
(green, yellow, or red) to highlight the implications of the PGx results for selecting the optimal 
medication(s) for a given individual (see Appendix 2 for a sample report).  Although providing 
both the raw data and a color code for medication selection gives the provider more direction, its 
benefit is untested.  
 
Two additional areas that the evidence synthesis highlighted as needing further research 
are ethical considerations related to the return of results (e.g., how a patient’s genetic variation 
in metabolism should impact potential titration of other medications that he or she is being 
prescribed) and educational issues such as the training needed for providers to effectively 
collaborate with their patients in the use of PGx testing for psychotropic medications.   
 
Regulatory Concerns.  The Institute of Medicine recently released a report on standardizing 
the use of biomarkers in healthcare [33], which raised several points that are relevant to PGx 
testing.  Although regulation is needed to ensure that PGx testing is accurate and clinically 
relevant, regulations are not likely to be implemented soon by the FDA.  In the absence of such 
regulation, the number of new PGx companies has grown rapidly, underscoring the need for 
oversight and accreditation of PGx laboratories to ensure high standards in testing. There 
currently is no clear guidance on how to interpret test results, nor is there a mechanism to 
communicate changes in the algorithm.  Inevitably, the information about PGx testing will 
continue to grow, and the interpretation of the results will evolve, requiring that knowledge be 
translated to providers in an ongoing manner.  Finally, among other recommendations is the 
need to address the practical issues of how results should be made available to providers in the 
electronic health record (EHR), the use of which is pervasive in medicine and well established in 
VHA. The Executive Committee and the Scientific Advisory Board for the current RCT will 

  
PRIME Care – Protocol Version 18  10/22/21 Page 11 of 45 
 
monitor these issues and weigh in on policy decisions that the VHA is considering for the 
implementation of PGx testing. 
 
Insomnia and Depression: While each is disabling in its own right, insomnia is also highly 
comorbid with depression, a disorder affecting approximately 5-13% of Veterans. Research also 
suggests that roughly 67% of individuals with major depression also meet criteria for clinical 
insomnia [34]. The co-occurrence of insomnia and depression confers greater functional 
impairment, treatment resistance, likelihood of relapse, and suicidal risk [2,3] than either 
disorder alone[34, 35]. Indeed, a recent meta-analysis showed a 2- to 3-times greater risk of 
suicidal ideation, attempts, and death following attempts among depressed individuals when 
sleep disturbances were present compared to those without sleep disturbance [36]. Further, 
research on Veterans in particular has demonstrated significant relationships between sleep 
disturbance and suicide, indicating that the presence of sleep disturbance predicted shorter time 
to suicide completion than absence of sleep disturbance, controlling for mental health 
conditions, substance use, age, and region [37]. Later average sleep start time via actigraphy 
was significantly related to increased suicidality; after adjusting for depression and insomnia 
severity it was marginally significant. As such, there is a critical need to better understand the 
relationships between depression and sleep. We have the opportunity to add both sleep and 
daytime activity data to the project for some participants by using ActiGraphs to collect this data. 
These data would help us examine further the relationship between treatment, depression and 
activity. These data would be used in secondary analyses as an objective measure of response 
to depression treatment. Some studies have shown that actigraphy can be a useful means of 
studying activity levels and sleep patterns in patients with depression, but that additional work in 
this area is needed. 
 
Significance.  Despite the availability of dozens of antidepressants and psychotherapeutic 
approaches, the treatment of depression is often inadequate.  As shown in several studies, to 
achieve remission from depression, patients and providers must try multiple treatments until 
they find one that is both tolerable and effective [20].  However, there is attrition with each round 
of treatment, which is additive.  Thus, the promise of tailoring treatments to patients based on 
genetic variation could speed treatment response and reduce dependence on trial and error, 
thereby reducing attrition and improving satisfaction with treatment.  
 
Validation of the results from the limited PGx implementation studies that have been 
conducted to date could usher in a new era in the treatment of MDD and provide an impetus for 
evidence-informed treatment, expanding access to effective treatments for the disorder. 
Alternatively, if the proposed study does not validate the available preliminary findings, it will 
provide a strong rationale to modify or limit testing as currently conducted and implemented, 
which carries a cost and healthcare burden. Even if the results of the RCT do not support the 
use of PGx testing at this time, the achievement of the other aims will provide substantial insight 
for the future (improved) implementation of PGx testing in psychiatry based on our discovery 
efforts, which will yield new information to help optimize PGx panels for a variety of disorders. 
Finally, almost no information is available on the impact of population genetic differences on the 
utility of the commercially available PGx tests.  Though the present RCT will not be powered 
statistically to detect population by medication group differences, we will provide a preliminary 
description of differences in PGx effects on medication response as a function of the major 
population (European and African ancestry) groups. We will also be collecting some preliminary 
data on sleep and daytime activity for some of our participants and begin examining further the 
relationship between treatment, depression and activity in relation to the PGx results.  
 
5.0 Study Procedures 

  
PRIME Care – Protocol Version 18  10/22/21 Page 12 of 45 
 
 
5.1 Study Design 
The study is a two-arm, 24-week, parallel-groups comparison of patient/provider dyads 
(n=2000), which will be randomly assigned to receive the results of the PGx battery at the time 
of randomization (i.e., the intervention group) or receive the results after 6 months of treatment 
as usual (i.e., the delayed results group).  The genetic test results are designed to assist the 
patient/provider dyad in making a shared decision as to the appropriate antidepressant.  There 
are many additional factors that can influence that decision and the provider/patient dyads are 
not obligated to follow the recommendations in the genetic test report but rather are encouraged 
to use the results to inform shared decision making.   
 
The study intervention.  The intervention for this study is the delivery of genetic test results 
that reflect pharmacokinetic and pharmacodynamic effects of specified genetic markers.  The 
choice and dose of the antidepressant to be prescribed to each patient is left to the provider and 
patient, though we will recommend to the provider that he or she carefully consider the genetic 
test results prior to selecting a medication and dose.  For the trial, we will use the commercially 
available GeneSight™ psychotropic panel from Assurex Health.  This product, which combines 
genetic markers related to pharmacokinetics and pharmacodynamics, has the greatest market 
penetration of any genetic tests for MDD treatment.   
 
The results of the test will be available on a secure website hosted by Assurex Health and 
accessible by study staff and prescribing provider participants.  Reports will be labeled with the 
participant’s sample acquisition ID number, study site, provider name, participant’s date of birth 
and initials, and date of collection.  Reports will be accessed by the coordinating center and/or 
site study coordinators and sent directly to the prescriber via encrypted email or printed and 
hand delivered based on provider preference. The provider may also access the test 
themselves. The results will also be uploaded into CPRS via VISTA imaging.  The results will be 
presented in the report in two ways.  First, there will be a cover sheet grouping antidepressants 
into three color-coded categories (green, yellow, or red), which help to interpret the test results.  
Medications in green (“Go”) have no relevant genetic interaction.  Medications in red (“Stop”) 
should be used with caution, as the patient may have either pharmacokinetic or 
pharmacodynamic variants that are relevant to the medication.  Those in yellow (“Caution”) may 
be at some risk of genetic interaction, but implications are not as straightforward as those in red.  
In addition to the interpretive results, the provider is also given the individual genetic marker 
information (see appendix for a sample report). Note that the genetic results will be returned to 
the delayed-results arm six months after randomization and completion of the 24-week 
assessment.  
 
 
Patient Education.  Patients will have access to a number of educational materials 
available for providers to assist in partnering with patients in the decision process.  At the time 
of randomization, an instruction sheet will be provided to the patient that reminds them of the 
arm they were assigned.  In the intervention arm, this instruction sheet includes a reminder to 
call their provider if they haven’t heard back within 10 business days so that medication can be 
started.  Educational resources also include brochures about the test result, and access to 
Assurex’s website which is publicly available.  A short whiteboard video will also be developed 
and available on the study website available to the public that explains the genetic test.  In 
addition, patients have access to Assurex’s call center (toll free) which will review results with 
patients at their request. This is voluntary and only initiated by the Veteran.  The call number is 
printed on the test result along with the subject’s sample acquisition ID number that allows the 
company’s call center to identify the Veteran.  This optional service is a standard part of 
Assurex’s product. 

  
PRIME Care – Protocol Version 18  10/22/21 Page 13 of 45 
 
 
There are no study medications prescribed as part of this study.  The antidepressants used 
will be limited to those prescribed by an authorized VA provider and only informed by the 
genetic results in the intervention arm.  The genetic testing is not regulated under an 
Investigational New Drug (IND) or Investigational Device Exemption (IDE) process.  
 
 
Provider Education.  Providers will have access to a number of educational materials.  
These include a prerecorded “grand rounds” presentation, the slide deck for the “grand rounds” 
presentation that can be used locally by the local site investigator, brochures about the test 
result, and a quick reference guide for study providers. They will also have access to several 
videos around the test itself, including how to use it and how to talk to their patients about it. 
These videos will be provided to the CIRB. Occasional brief newsletters will also be provided to 
participating providers. These newsletters will highlight study related topics of interest to this 
group such as recent publications about pharmacogenetics, update on project progress, and 
provide helpful tips related to handling pharmacogenetics results.  These individual newsletters 
will not be submitted to the CIRB. In addition, providers will have access to Assurex’s website 
which is publicly available as well as to Assurex’s call center which will provide an overview of 
any test.  This optional service is a standard part of Assurex’s product; to access, the provider 
calls and the Assurex staff will review the results and assist in interpretation.   
 
Actigraphy Optional Add-On Study. Participants at selected sites will have access upon 
randomization to an optional component of the study to gather daytime and nighttime activity 
using an ActiGraph. Participating in this component of the study is optional and Veterans will 
complete an addendum to the PRIME Care study consent for this part of the project.  
 
5.2 Recruitment Methods 
Site Selection. Based on past experience, we anticipate recruitment of only 2 
patient/provider dyads/month at each site in the first 6 months, with recruitment gradually 
increasing after that, reaching a maximal level of 3-4 patient/provider dyads/month during the 
last 2 years of the study. We have targeted sites that have high numbers of patients already 
being treated with antidepressants, sites with larger Primary Care Mental Health Integration 
programs, and sites that were successful in recruiting in past depression treatment studies. The 
plan for recruiting dyads is shown in Table 1. 
 
Table 1. Study timeline. 
 
 
 

  
PRIME Care – Protocol Version 18  10/22/21 Page 14 of 45 
 
Provider recruitment. The prescribing clinician (MD, DO, PA, PharmD, or CRNP) will be a 
participant in the study and will give one-time written informed consent prior to their participation 
and referral of subjects.  Sites will be encouraged to consent all providers who are interested 
and have the potential to refer eligible patients.  Each site will use different methods to recruit 
providers including the use of a recruitment flyer, presentations at staff meetings, an educational 
offering to introduce the study, or personal contact (emails or in person discussions). This is an 
important design consideration, as a typical multi-site study includes one or two providers per 
site. Thus, we are maximizing the external validity of the study’s results by including providers 
who have no or limited stake in the outcomes (Hypothesis #2).  As described below, we will also 
rely on feedback from various providers to understand the impact of the presentation of results 
and the requirements for educating providers and patients.  In sum, though a smaller number of 
providers per site would reduce variability in implementing the results of the genetic test, it 
would also limit our understanding of the impact of widespread use of genetic testing and the 
range of providers’ attitudes toward the utility of the PGx.  
 
Temporal Sequence of Study Procedures. Patients will be identified by providers working in 
VA mental health programs and primary care settings. The prescribing provider will alert 
potential patients to the study and introduce interested patients to the Research Coordinator 
(RC) or other study staff at each site. The handoff from the provider to the study staff will be by 
secure electronic means, a phone call or in person.  Sites are encouraged to have a back-up 
telephone contact plan so that someone on the research staff is always available to providers 
for phone access.  This could be a backup RC or the LSI or a beeper or cell phone.  
Alternatively, if the patient wants to return for a later appointment for consent and 
randomization, this pathway should also be worked out locally so that no patient is left without 
contact or potentially doesn’t receive treatment because of the study procedures. If providers 
are unable to contact staff, they should not delay treatment and thus should forgo subject 
referral. The prescribing provider will complete a referral form which includes confirmation of 
some inclusion and exclusion criteria and the responses to treatment decisions.  Potential 
participants are those who are about to undergo antidepressant treatment for MDD or be 
switched from a current antidepressant to a new one. The study staff will describe the study to 
the patient and initiate the informed consent process. After consent, a brief baseline 
assessment will be conducted by the study staff to establish eligibility and to collect baseline 
data prior to randomization.  We will keep track of the number of study referrals and will collect 
the following research data for those who do not consent: name, SSN, age, sex, race, and 
ethnicity. Name and SSN are tracked for those who do not consent so that research 
coordinators can determine if a subject has already been referred to the project (re-referral), and 
whether outcomes from an earlier referral impact eligibility.  The design of the study will mimic 
routine clinical care, which will minimize the research burden and maximize the ecological 
validity of the trial.  While every attempt will be made to complete the baseline visit within 60 
minutes on the day of the clinical visit to allow randomization to occur rapidly and not delay 
prescribing, the patient will be given the option to return to the clinic on another day to give 
consent (e.g., to discuss potential participation with family) and complete the baseline 
assessment.   
 
Eligible Veterans will be randomized to one of two groups - the “immediate results” group or 
the “delayed results” group.  After completion of the baseline visit, the RC will contact the 
prescribing provider to inform him/her of the results of the randomization.  Results for subjects 
assigned to the intervention group are in most cases returned to the subject’s healthcare 
provider in 2-3 business days. Once the test results are available, the healthcare provider will 
prescribe an antidepressant medication.  The healthcare provider is encouraged to share the 
results of the genetic testing with the subject and to use the results in selecting the medication 

  
PRIME Care – Protocol Version 18  10/22/21 Page 15 of 45 
 
and target dose. Occasionally shipping delays or the need for further sample testing may delay 
the results for up to four additional business days. If delays are identified, and the report will not 
be available within the expected three business days, the local site will notify the provider that 
the report has been delayed and provide an updated timeframe. The provider has the option to 
wait until the report is available or to proceed with prescribing without the genetic results. 
Subjects assigned to the “delayed” results group (and their providers) will be notified after the 
baseline.  The provider and patient can then start the antidepressant of choice on the same day. 
Veterans excluded from study participation will continue to receive care from their referring 
provider.    
Recruitment.  We project that, after the 6-month start-up period, sites will randomize 3-4 
patient/provider dyads/month.  We will assist sites in developing a recruitment strategy that best 
fits their needs and adjust it as appropriate.  We will enhance recruitment using a variety of 
methods, including clinical referrals, IRB-approved advertisements, and targeted recruitment 
using VISTA.  Sites will be strongly encouraged to recruit as many prescribing providers as 
possible with an emphasis on including psychiatrists and primary care providers.  An 
informational brochure (Quick Guide for providers) containing inclusion/exclusion criteria will be 
made available to prescribing providers. Local sites will also be able to use VISTA to view 
patient panels of consented providers and conduct chart reviews to determine eligibility. Local 
sites will pull a list of patients per provider with upcoming visits (up to 6 weeks out).  Local sites 
will then conduct a brief chart review to check inclusion/exclusion criteria based on MH 
diagnoses and review current medications. If the patient is a good match for the project then the 
local site will alert the prescriber prior to the appointment, so that they can be considered for 
referral.  Communication about these patients will be sent to providers using encrypted email.  A 
paper copy can be given if requested by the provider; provider will be reminded to destroy the 
list using a locally approved method such as a secure document vault. If the provider is 
agreeable, local site staff may also approach these identified patients in the waiting room ahead 
of a scheduled visit to provide basic information about the study and a study brochure.  When 
handing out the brochure, study staff will let the patient know that their provider is participating 
in this study and if they are interested in finding out if the study is a good match for them, they 
should talk to their provider.  Study staff will not indicate that they have reviewed the patient’s 
chart and that they may be eligible. Brochures may also be placed in waiting areas. We will host 
a regular learning collaborative with the site RC to share ideas about recruitment and to provide 
site-by-site recruitment progress reports.   
 
Randomization. We will randomize patients to the intervention or delayed results arms, 
controlling for possible bias due to confounding by provider by using a within-provider 
randomization scheme within each site. Overall, this scheme will balance treatment conditions 
across known (e.g., primary care versus specialty care) and unknown (e.g., future adherent 
versus non-adherent status at randomization) provider characteristics. In addition, as we expect 
the depression severity of patients to be associated with primary versus specialty care status of 
the providers, stratification will also tend to balance depression severity across the intervention 
groups. The randomization will be based on a permuted blocks approach, with (slightly) varying 
block sizes to discourage “guessing” of upcoming allocations [38]. The research coordinator at 
each site will conduct the randomization, having been trained on the use of the system during 
the study initiation meeting. Within each site, the system will maintain a log of the participants 
randomized. Each site will also have a short list of random assignments, one list per consented 
provider, to be used in the event that there is a system failure at the time of randomization. The 
list of randomized allocations will be maintained separately from the tracking and research data, 
to ensure blinded assessments by the interviewers. 
 

  
PRIME Care – Protocol Version 18  10/22/21 Page 16 of 45 
 
 
Subject payments.  We will compensate subjects $20 for each of the first 4 telephone follow-up 
assessments (weeks 4, 8, 12, 18 follow-up assessments), $25 for the week 4 blood draw, and 
$50 for the week 24 telephone follow-up assessment. The treatment as usual group will also 
receive $25 for the week 36 telephone follow-up assessment. Participants opting to participate 
in using the wearable ActiGraph device will receive $25 if they wear the device for 85% of the 
days during the first four weeks. Subjects who do not attend the four week visit will still be 
compensated if they meet the wear requirements. After the first four weeks all subjects will 
be paid $5 for each additional week that they wear the device for 6 out of 7 days. If the 
subject uses the optional syncing process to sync their device through their smartphone 
they will receive ongoing payments paid out with other PRIME Care study payments. If they 
do not sync then the weekly payments from week 5-24 will be paid out in a lump sum at the 
end of study, prorated by number of completed weeks We will compensate subjects using 
direct deposit to the Veteran’s bank account (or their designee’s) or similar allowable and 
secure methods for sending these payments. Subjects are paid $50 to return the ActiGraph 
device at any time they decide to end participation. Note that depositing into the Veteran’s bank 
account is the preferred and only mechanism for paying Veteran benefits such as transportation 
reimbursement so most Veterans have a bank account. Until we are able to secure another 
mechanism for paying at a national level, Veterans can only participate if they are willing to use a 
bank account. 
 
Alternate Sequence of study procedures. When Veterans are unable to participate in a face to 
face visit, such as the COVID-19 pandemic preventing or otherwise limiting in person visits or a 
Veteran only available to participate by telehealth, we will have an alternate enrollment path 
available under a waiver of documentation of consent. Providers will submit referrals by 
encrypted email or Skype attaching the approved referral form or provide information over the 
phone for study staff to complete the referral form. The referral form contains patient name and 
last four; study staff will look up the phone number in CPRS. When referrals are received, study 
staff will call the Veteran to discuss the study and conduct oral consent. If the subject does not 
answer, a voicemail will be left using a script. The study staff will continue outreach to the 
subject, at minimum making three calls over the course of 5 business days after referral at 
differing times of day, no more than one call per day (5 calls maximum) when there has been no 
contact with the Veteran e.g. no return call from Veteran. If study staff are unable to contact the 
subject, they will contact the provider by encrypted email, Skype or phone at the end of 5 
business days, to see if the provider wants to return to care as usual or continue outreach to the 
patient.  If the subject is reached and consents, the baseline assessments will be completed. If 
eligible, a PGx cheek swab kit will be sent to the patient via UPS and the subject will be 
provided instructions on collecting the sample and returning by FedEx to Assurex. These 
instructions will also include directions to contact their primary care provider before returning the 
sample if they have felt any new physical symptoms of COVID-19, including loss of taste. We 
will also include in this package an Information Sheet with a summary of the study including 
consent elements and contact information. Study staff will check UPS tracking information daily 
to confirm that this package is received by the subject. Study staff will also schedule a call back 
time with the subject when the package is expected to arrive, to walk the subject through 
sample collection and shipping. We intend to make this process as easy as possible for the 
Veteran, assisting them with scheduling a FedEx pick-up at their home or providing them with 
the location of local FedEx drop boxes. Once the sample return is registered in the FedEx 
system, the Veteran will be randomized, and the provider and patient will be informed of the 
study arm. Participants will be compensated $25 for sample receipt. When visits are completed 
virtually, we will forgo collection of blood samples, as they are primarily used for secondary 

  
PRIME Care – Protocol Version 18  10/22/21 Page 17 of 45 
 
analyses. If the subject does not consent or is not eligible, the provider will be notified by 
encrypted email, Skype or by phone the same day, and alerted that they should return to 
standard care.  Under a separate written informed consent, we plan to collect a DNA sample 
(blood or saliva) either at the in person four-week visit, at a later separate visit just for DNA 
collection, or by mail for home collection (saliva sample only). If the DNA sample is collected at 
a separate in person visit or at home, the participant will receive $25 in compensation. 
 
5.3 Informed Consent Procedures 
Prescribing providers (referred to as prescribers or providers) will participate as subjects in the 
trial and will be required to provide informed consent, as we will be collecting data about their 
prescribing practices. There are no exclusion criteria for prescribers.  The site PI or research 
coordinator will begin recruitment of providers at the onset of the trial before recruitment begins.  
PI or research coordinator will obtain consent from prescribing providers; consent must be 
completed before referrals from a provider will be accepted.  Providers will not be asked to sign a 
HIPAA form, as no health information is being collected from them. Version 4.0 of the provider 
consent dated 1/14/19 includes some minor changes related to transcribing and analysis of 
individual interviews. Participation in individual interviews is an optional component of the study.  
Providers consented using earlier versions of the consent, and who are invited to participate in 
these interviews, will receive an email explaining these changes. The changes will also be 
reviewed verbally at the start of the telephone interview.  
 
Patients will be recruited through prescribers’ referrals from clinical treatment programs at 
the individual sites.  All advertising will require IRB approval.   We have requested a HIPAA 
waiver to use VISTA to identify potentially eligible patients (those with appointments in the future 
who have MDD and no exclusionary diagnoses).  These names can be distributed to consented 
prescribers to facilitate recruitment.   
 
 Once a Veteran has been referred to the study by their provider, there are two paths to 
consent (written consent or oral consent via a Waiver of Documentation of Consent).  As 
feasible, patients will meet with the local research staff at each site to review the consent form 
and answer questions.  Following resolution of any questions, patients who demonstrate an 
understanding of the nature of the study and consent will be asked to sign the study consent 
form and the HIPAA form. Subjects at selected sites will also be provided information on the 
option to participate in actigraphy for the collection of sleep and activity data. If the subject is 
interested, the local research staff will review the consent addendum for this optional activity 
and answer questions. The patient will be asked to sign this consent addendum if they are 
interested in participating in the actigraphy. A signed copy of all forms will be given to each 
patient.  
 
When a face to face visit is not possible with the Veteran, an alternate oral consent process 
will be used under a Waiver of Documentation of Consent and HIPAA Waiver. All of the same 
elements of consent are covered, and the process includes documentation of who completed 
the consent and the date and time that oral consent was obtained. A consent Information Sheet 
will be sent to participants who complete the oral consent process. For those consented under 
the waiver of documentation of consent, a separate written informed consent form will be used 
for collection of DNA blood or saliva samples.  
 
All local site principal investigators and research coordinators will maintain up-to-date 
required human subjects training certificates, including Good Clinical Practice, Privacy and 
HIPAA Focused Training, VA Privacy and Information Security Awareness and Rules of 

  
PRIME Care – Protocol Version 18  10/22/21 Page 18 of 45 
 
Behavior, and Research Compliance.  The coordinating center will provide training and virtual 
supervision of site staff on all study procedures, including obtaining, documenting, and 
assurance of consent. 
 
 
5.4 Inclusion/Exclusion Criteria 
 
A total of 2000 men and women will be randomized.  To reach this number, up to 250 
subjects per site or a total of about 3000 subjects will be consented and screened.   
 
Veteran subjects 
Patient Inclusion Criteria. a) age 18 to 80 years, inclusive; b) PHQ-9 score ≥ 10 and a 
presumptive diagnosis of MDD per the prescriber; c) at least one prior treatment exposure for 
MDD (psychotherapy or antidepressant); d) intent to start treatment of the MDD with an 
antidepressant (simple dose increases will not be considered inclusionary), and e) willingness to 
provide signed, informed consent to participate in the study.  
 
Patient Exclusion Criteria. a) current serious co-occurring psychiatric illness (i.e., 
schizophrenia, bipolar disorder, psychotic major depression, borderline or antisocial personality 
disorder, eating disorder; b) active alcohol or other drug use disorder; c) current use of an 
antipsychotic medication, methadone, buprenorphine, or naltrexone (depot or oral);  d) 
augmentation therapy (e.g., use of two or more antidepressants at the time of randomization), 
(trazodone at a dosage ≤ 150 mg/day will not be considered augmentation and thus allowed); e) 
patients requiring urgent care or inpatient hospitalization at the time of consent; or f) currently 
incarcerated. 
 
Prescribers 
There is no limit on the number of prescribers that can be enrolled at each site.  Sites will be 
encouraged to consent any prescriber who is interested in participating in the study. 
 
Inclusion Criteria: Capacity to prescribe 
Exclusion Criteria: None 
 
5.5 Study Evaluations 
 Visit 1 (Baseline assessment).  This visit will most often occur directly after informed 
consent has been obtained (described above).  The baseline assessments and prescribing 
provider referral form will serve to establish the patient’s eligibility.  Patient-reported outcome 
measures (PROMs) will be collected using tablet devices/paper/or interview and entered into 
the Behavioral Health Lab (BHL) software based on availability of a tablet device. Responses 
will be populated directly to CPRS/VISTA using the VA-approved BHL software.  For eligible 
patients, a cheek swab will be taken for the commercial genetic test and several blood samples 
will be taken as described below.  The patient themselves or the research coordinator will 
collect the cheek swab, based on patient preference.  Blood will be collected as part of the 
discovery and secondary aims as described below. Patients who consent to the optional 
actigraphy component (see below) will be assigned an ActiGraph device and shown how to use 
it, including optional syncing.  Providers will record the medication that they plan to prescribe for 
the patient prior to randomization and rate their expectancy for treatment outcomes.  After data 
collection and the establishment of eligibility, the patient will be randomized to the intervention 
group or the delayed results group.  Patient/provider dyads assigned to the delayed results arm 
will initiate therapy with the antidepressant that the patient and provider agreed upon prior to 
randomization.  Patients in the intervention group will have their cheek swab sample shipped for 

  
PRIME Care – Protocol Version 18  10/22/21 Page 19 of 45 
 
testing, with the results, in most cases, returned to the site in 2-3 business days. Prescribing will 
then proceed; prescribers will be encouraged to use the genetic test results in selecting a 
medication. Occasionally shipping delays or the need for further sample testing may delay the 
results for up to four additional business days. If delays are identified, and the report will not be 
available within the expected three business days, the local site will notify the provider that the 
report has been delayed and provide an updated timeframe. The provider has the option to wait 
until the report is available or to proceed with prescribing without the genetic results. 
Visit 1 alternate. When a face to face visit is not possible, we will use an alternate virtual 
process for visit 1. If the subject is reached and consents to the study, the baseline 
assessments will be completed. If eligible, a PGx cheek swab kit will be sent to the patient via 
UPS and the subject will be provided instructions on collecting the sample and returning by 
FedEx to Assurex. These instructions will also include directions to contact their primary care 
provider before returning the sample if they have felt any new physical symptoms of COVID-19, 
including loss of taste. We will also include in this package an Information Sheet with a 
summary of the study including consent elements and contact information. Study staff will check 
UPS tracking information daily to confirm that this package is received by the subject. Study 
staff will also schedule a call back time with the subject when the package is expected to arrive, 
to walk the subject through sample collection and shipping. We intend to make this process as 
easy as possible for the Veteran, assisting them with scheduling a FedEx pick-up at their home 
or providing them with the location of local FedEx drop boxes Once the sample return is 
registered in the FedEx system, the Veteran will be randomized, and the provider and patient 
will be informed of the study arm. To encourage return of samples, participants will be 
compensated $25 for sample receipt. If the sample is not registered in the FedEx system within 
10 business days of referral, the provider will be notified by the study staff so that they can 
determine whether to return to usual care or to continue. Blood draws are not included in this 
virtual visit. 
 
 
 
Visits 2-6 (Weeks 4, 8, 12, 18, and 24).  During treatment, patients will be assessed by 
centralized assessment center personnel (at the Crescenz VAMC), with all follow-up 
assessments conducted by telephone.  The outcomes assessors will be blinded to the study 
arm.  At each telephone visit, patients’ depressive symptoms, medication adherence, and side 
effects will be assessed. For those participating in the ActiGraph component, we will also ask 

  
PRIME Care – Protocol Version 18  10/22/21 Page 20 of 45 
 
about their use of the ActiGraph and any problems they have encountered with the device. 
Support will be provided as needed. At 36 weeks, we will repeat a final assessment in the 
delayed results group to test Hypothesis #4 (i.e., that they will ultimately show changes in 
antidepressant prescribing and reductions in depressive symptoms that are similar in direction 
and magnitude to those seen in the group that received genetic test results at the outset of the 
trial). We chose to administer the assessments by telephone centrally because centralized 
assessment helps to maintain the masking of the treatment condition; enhances consistency in 
the assessments; allows the use of standardized methods to reach patients, thereby reducing 
the amount of missing data; and reduces cost.  Our group has considerable experience in 
administering self-assessment instruments by telephone [39, 40].  Outreach efforts will include 
varying call attempts at different times of the day with one attempt in the evening or on a 
Saturday, sending a letter, and reaching out to the participant’s respective VA site to see 
whether there is new/additional contact information.  Our practice is to call twice, send a letter 
and then follow with a third call unless instructed differently by the Veteran. We will continue to 
call up to five times. 
 
At visit 2 we will also collect three different blood samples for the serum antidepressant 
level, mRNA assay, and serotonin assay. The local research coordinator will contact the 
subjects to arrange for the blood draw and will report back to the coordinating site when this is 
accomplished.  The blood draw and visit 2 interview will be coordinated to ideally occur within 7 
days of each other.  We expect some participants to miss visits and/or drop out of the follow-up 
calls. If not collected at baseline for any reason or the sample was not viable, DNA is also 
collected at this visit if written informed consent has been obtained. If subject was consented for 
the project under the waiver of written consent, they will be asked to sign a separate written 
informed consent prior to the DNA blood draw or saliva sample collection.  Missing data will not 
be considered a protocol deviation. 
 
Visit 2 alternate.  If the visit 2 cannot be completed in a face to face visit, the four-week 
assessments will be completed virtually. In these cases, the four-week blood draw will not be 
collected.   
 
DNA alternate.  If the 4-week visit is conducted by phone, we may send the subject by 
carrier a separate written DNA collection consent form, a HIPAA form, and two saliva collection 
kits. Study staff will walk through the written consent over the phone and consent documents 
will be returned with the completed kits in a prepaid return package.  If the kits are returned, but 
no consent forms are returned, then the samples will be destroyed.  Alternatively, when 
possible, we may complete the consent process with the subject using the DocuSign system 
and send the saliva kits out by mail after the subject has consented and signed electronically. 
Note, DocuSign requires use of the subject’s email address (covered in HIPAA waiver). The 
subject can also choose to do a later separate in person visit to sign consent and collect the 
DNA sample.  
 
 
Assessments.  We include measures from different sources (see Table 2 below), including 
provider measures, patient assessments, interview data, and EHR data.   
5.5.a Provider measures. 
a) Prescriber characteristics and assessment of pharmacogenetic test knowledge.  For 
every consenting provider, we will gather basic demographics:  age, sex, race, 
ethnicity, specialty (internist, CRNP, psychiatrist, etc.), years of practice, and the 
fraction of the work week that the individual dedicates to clinical care (at the start of 
participation).  This assessment also assesses knowledge about pharmacogenetics. 

  
PRIME Care – Protocol Version 18  10/22/21 Page 21 of 45 
 
The opinion and knowledge questionnaire may be repeated during the latter part of 
the trial. We added this to the consent but will do a protocol modification with the 
specifics prior to implementing the follow-up survey. 
b) Provider profiling.  For consented providers, we will identify patients engaged in care 
with that provider in order to examine distribution of patient diagnoses, changes in 
care (utilization) and changes in prescribing patterns across the course of the study. 
To accomplish this, we will extract prescribing and patient utilization data from VINCI 
for all patients for which the provider has engaged in care during the study period or 
in the one year pre- and post the study. We will assess the quantity and distribution 
of provider antidepressant prescribing as a characteristic of their practice. We will 
use this information to assess how often during the study providers deviate from their 
prior prescribing pattern. Such deviations could indicate that the provider is 
attempting to adjust his or her prescribing based on results from patients randomized 
to the intervention, and this will be used to gauge the internal validity of the study. 
We will also be able to examine referral patterns in relation to the available pool of 
patients seen by an individual provider. This characterization of providers will be 
important to understand outcomes for Aim 2 of the trial. In addition, characterizing 
provider practices will facilitate recruitment by identifying which consented providers 
have higher numbers of potentially eligible patients. The provider names will be given 
to local sites for focused local outreach efforts, which includes one on one 
communication with providers and chart review of consented providers scheduled 
visits (protocol, page 15, Recruitment) to remind providers about patient eligibility 
and potential patients. 
c) Referral form – there are two components on the referral form. 
a. Treatment decision.  At the time of recruitment, the provider will be asked to 
record the antidepressant that he or she would prescribe if no genetic test 
information were available.  This will be used to measure whether the 
provider/patient dyads in the intervention group will use fewer medications 
that have potential gene-drug interactions based on commercial PGx test 
results than dyads in the delayed results group (Hypothesis #2).  The 
provider will also rate the likelihood that the antidepressant will be effective 
for the patient, the patient’s anticipated degree of adherence, and how helpful 
the provider believes the PGx results will be in informing care for the patient. 
b. Confirmation of inclusion and intent to prescribe.  The referral form requests 
that the provider confirm the lack of serious psychiatric illness, the need for 
urgent treatment, and the intent to prescribe monotherapy.   If we later find by 
administrative data that an exclusionary diagnosis has been used on a 
patient, this will not be considered a protocol deviation as chart extraction is 
not the method of confirming the exclusionary diagnoses. 
d) Provider Focus groups. We will ask a subset of the sites to participate in virtual focus 
group interviews.  We will conduct up to ten 45 minute-long (15-minute presentation, 
30-minute discussion) focus groups with at least 3-5 primary care providers and/or 3-
5 psychiatrists (and other specialty mental health providers) in each group.  The 
focus groups will include a brief presentation on PGxs, including an Assurex sample 
report of results, and discussion about current knowledge and perceptions of PGx 
testing.  They will provide feedback on how PGx results should be returned to 
providers and patients, and input on overcoming implementation barriers.  All groups 
will be held virtually via Lync On-Line Meetings so that slides can be presented.  The 
site PIs will encourage participation and their research coordinators will coordinate 
the meeting arrangements. Providers will provide written informed consent prior to 
participation. One consent form will serve for all components of provider 

  
PRIME Care – Protocol Version 18  10/22/21 Page 22 of 45 
 
participation. The focus groups will also be recorded and professionally transcribed 
for detailed review.  Study staff will also take notes. 
e) Individual interviews with providers who are participating in the RCT will be used to 
identify barriers and facilitators to individual uptake and use of PGx test 
recommendations.  We will sample across sites based on the provider’s rate of 
referral and their specialty area (primary care or psychiatry). Each individual 
interview will take 30-45 minutes and be recorded and professionally transcribed.   
 
5.5.b Subject data 
a) Patient measures 
i. 
Depressive symptoms – The Patient Health Questionnaire (PHQ-9), a widely 
used, 9-item, self-report measure of depressive symptoms with a total score of 0-
27, will be completed at each visit and will serve as the principal outcome 
measure for the trial [41].  The instrument rates the severity of depressive 
symptoms, can assist in identifying treatment goals, can be used to facilitate 
making a diagnosis of MDD, and can guide the choice of treatment.  The results 
of the baseline PHQ-9 assessment will be provided to the clinical team and 
placed in the EHR.   
ii. 
PTSD symptoms – The PTSD Checklist for DSM-5 (PCL-5), a 20-item self-report 
measure, assesses the presence and severity of PTSD symptoms [42].  Items on 
the PCL-5 correspond to the DSM-5 criteria for PTSD.  The PCL-5 can be used 
to quantify and monitor PTSD symptoms over time, screen individuals for the 
disorder, and assist in making a provisional diagnosis of PTSD.  The measure 
will be administered at baseline both to describe the sample and in a secondary 
moderator analysis of patients with MDD to differentiate them by the presence or 
absence of PTSD symptoms.  The measure will be repeated at all follow up 
assessments. The results of the baseline PCL assessment will be placed in the 
EHR.   
iii. 
Anxiety symptoms – The Generalized Anxiety Disorder – 7 (GAD-7) scale is a 
validated measure of anxiety symptoms that will be used as a secondary 
outcome measure and a potential moderator of treatment, as anxiety is known to 
decrease the response to treatment of MDD [43].  The measure will be 
administered at baseline and all follow-up assessments. The results of the 
baseline GAD-7 assessment will be placed in the EHR.   
iv. 
Functional assessment – The Veterans RAND 12-item Health Survey (VR-12) is 
a widely used measure of quality of life [44].  The VR-12 subscales measure 
physical and mental functioning.  The scale is a publicly available version of the 
MOS SF-12 instrument [45, 46].   The measure will be administered at baseline 
and all follow-up assessments. The results of the baseline VR-12 assessment 
will be placed in the EHR.   
v. 
Alcohol use – The Timeline Follow-back (TLFB) [47] will be used to estimate past 
7-day drinking at baseline and at each follow-up visit.  The TLFB uses a 
retrospective calendar method to measure daily alcohol use.  We chose a 7-day 
TLFB window because it is easily ascertained and provides a snapshot of recent 
drinking that reflects average alcohol consumption.  The TLFB is the most widely 
used outcome measure in alcohol studies [48].  The results of the baseline TLFB 
assessment will be placed in the EHR.   
vi. 
Illicit drug use – The NIDA-Modified ASSIST was adapted from the Alcohol, 
Smoking and Substance Involvement Screening Test (ASSIST). It was 
developed, validated, and published by the World Health Organization (WHO) as 
a screening tool for substance use [49].  This self-report questionnaire will be 

  
PRIME Care – Protocol Version 18  10/22/21 Page 23 of 45 
 
completed at baseline to describe the patient population. The results of the 
baseline ASSIST assessment will be placed in the EHR.   
vii. 
Treatment satisfaction – We will use two questions that ask about the quality of 
care received and the ability to receive the services desired.  The questions are 
adapted from the 28-item version of the Mental Health Statistics Improvement 
Program (MHSIP) Consumer Survey [50].  We have used these two questions for 
10 years in our Primary Care Mental Health Integration (PCMHI) program.  
Because raters assessing satisfaction with study participation at each follow-up 
visit are blinded to treatment assignment, we will be unable to ask specifically 
about the PGx testing using the MHSIP. The measure will be done at each 
follow-up assessment. 
viii. 
Receiving results – at four weeks the local research coordinator will ask if 
patients in the intervention group were given a copy of the results.  We will ask 
the control group at week 36. 
ix. 
Current smoking – At each visit, we will record the average number of cigarettes 
smoked daily over the past week.  The results of the baseline smoking 
assessment will be placed in the EHR.   
x. 
Demographics – Patient will self-report basic demographic information:  sex, 
race, branch of military, works status, marital status, and ethnicity.  We will also 
record the patient’s birthdate, address and phone number as part of a tracking 
data base but these data will not be part of the analytic data set. 
xi. 
Antidepressant adherence – This is a self-report assessment of the patient’s 
adherence to medications during the prior week.  The measure will be 
administered at all follow-up assessments. 
xii. 
Structured adverse effects questionnaire – The Assessment of Side Effects is a 
semi-structured interview designed to assess and track the course and severity 
of adverse effects including headache, nausea or vomiting, diarrhea, 
constipation, and sexual dysfunction.  The measure will be done at each follow-
up assessment.  Designations of mild, moderate, and severe will be used to 
grade the severity of any adverse effects. The measure will be administered at all 
follow-up assessments. 
xiii. 
Treatment history – By self-report, we will obtain the lifetime information about 
treatment exposures including psychotherapy, and self-reported effectiveness of 
the most helpful treatment.  This will provide information on the chronicity of 
depression and a proxy measure of treatment resistance.  It will be obtained at 
baseline. 
xiv. 
Lifetime psychiatric diagnoses – The MINI International Neuropsychiatric 
Interview (MINI) [51] will be used to screen for lifetime mania and psychotic 
symptoms, panic disorder, antisocial personality disorder, and drug and alcohol 
dependence.  It will be administered at week 4 by the local research 
coordinator/staff. If missed at the 4 week interview, the questions will be asked 
virtually. 
xv. 
Nutritional assessment – by self-report we will record selected nutraceuticals and 
foods use that have been associated with depression and/or medication 
metabolism.  This is not a standardized assessment but rather developed for this 
study.  The responses will be used by the discovery core to combine with genetic 
data to refine analyses related to outcomes and new genetic markers. 
xvi. 
Treatment received outside the VA – This instrument will be used to collect 
information on all non-VA health services received, including ER, inpatient, and 
outpatient care.   The measure will be administered at baseline and all follow-up 
assessments. 

  
PRIME Care – Protocol Version 18  10/22/21 Page 24 of 45 
 
xvii. 
Early termination information – This information will be used to identify the 
reasons for early termination (e.g., dissatisfaction, death, left VA care). 
xviii. 
Suicide Assessment – The Columbia Suicide Severity Rating Scale (C-SSRS) 
will be used to screen for risk of suicide. This assessment will be included at the 
baseline visit for all subjects and in all scheduled follow up phone calls from the 
central call center. The results of the C-SSRS completed at baseline will be 
placed in the EHR.  
xix. 
Social Support – A short Social Support assessment will be used, as social 
support has been demonstrated to be related to suicidal ideation. This 
assessment will be included at the baseline visit for all subjects and in all 
scheduled follow up phone calls from the central call center. The results of the 
baseline Social Support assessment will be placed in the EHR 
 
b) Biological samples - All blood samples will be collected by the local site and shipped 
to the coordinating site for storage.   
i) Baseline samples:  At baseline the blood samples include: 2 – 8.5 ml tubes 
for a Genome wide association study (GWAS); 2 - 2.5 ml tubes for mRNA 
analysis; 1 – 10ml tube for C-reactive protein, and 1 -4ml tube for serotonin 
analysis.    
ii) 1 month post randomization samples:   this includes 1-10 ml tube for serum 
drug level; 2 - 2.5 ml tubes for mRNA analysis and 1 -4ml tube for serotonin 
analysis.     
iii) Thus at baseline we collect 36ml and at one month post randomization we 
collect 19 ml. 
ii. 
Cheek swab (at the baseline visit only) to be sent to Assurex for PGx testing. 
Testing kits supplied by Assurex. The oral swab will be shipped directly to 
Assurex under a CRADA agreement for processing and analysis.  Shipping 
labels will be supplied by Assurex.  Each sample will be labeled with the sample 
acquisition number, subject initials and date of birth, site ID, provider name, 
randomization outcome, and date of collection. For sample verification purposes, 
the sample acquisition number, along with the birthdate and subject initials will 
also be sent to Assurex by the coordinating center, using a VA approved 
encrypted email method (RMS).Once results are verified, Assurex will destroy 
the sample.  In the rare event that the sample is not able to be processed and 
provide a result, we will attempt to recollect the sample from the subject. 
iii. 
Whole blood sample or saliva sample for the GWAS sample. The blood sample 
will be collected in Paxgene DNA tubes that draw 8.5 ml (two tubes or a total of 
17 ml).  An alternate method of saliva collection will be available for collection of 
the GWAS sample. This saliva sample will be collected in DNA Genotek Oragene 
OGR-600 kits or the equivalent. The blood or saliva samples will be shipped at 
room temperature to the Crescenz VA Medical center for storage.  At the time of 
the GWAS, one sample will be shipped to the West Haven VA for processing and 
GWAS, after which it will be destroyed.  The other sample will be banked for 
potential future use. The samples will be labeled with the study ID number and 
date of draw. In the rare event that the sample is not able to be processed and 
provide a result, we will attempt to recollect the sample from the subject.  
iv. 
Serum drug assay.  Serum will be used to measure serum levels of selected 
antidepressants as an intermediate phenotype for the PGx results.  A single red 
top serum tube (10 ml) will be collected at 1 month after randomization.  The 
sample will be processed locally by centrifuging and then drawing off the serum.  
Serum will be placed in cryotubes, frozen and shipped to the Crescenz VA 

  
PRIME Care – Protocol Version 18  10/22/21 Page 25 of 45 
 
Medical Center for storage and inventory control.  When appropriate numbers of 
samples have been collected, they will be shipped to the Arkansas Children’s 
hospital for processing.  All shipments will follow standard procedures for tracking 
and security.  Each sample will be labeled with the subject study ID, and date of 
collection. Along with the samples a manifest with the subject ID and the 
subject’s psychotropic medication(s) and date of draw will be provided, so the 
correct assay can be used on the sample. Samples will be tested in the lab of Dr. 
Stepan B. Melnyk at the Arkansas Children’s Hospital (ACH), which is an 
academic affiliate of the Central Arkansas Veterans Healthcare System. Dr. 
Melnyk’s laboratory will store the specimens until samples are analyzed and 
results reviewed. Once this process is complete the samples will be destroyed. 
Results will be returned using a VA approved encrypted email method (RMS). 
v. 
Real-time quantitation of mRNA analyses will be performed in Central Arkansas 
Veterans Healthcare System [52]. Specifically, blood will be collected in 
PaxGene tubes (2-2.5ml) at baseline and at 1 month and mRNA will be isolated 
using PaxGene Blood RNA kits (Qiagen). The quality and quantity of the mRNA 
will be assessed using NanoDrop UV/VIS &/or Picogreen Fluorescence followed 
by RIN Scores generated on an Agilent 2100 Bioanalyzer.  Quantitative PCR will 
be performed with a TaqMan 7900 System. When appropriate numbers of 
samples have been collected, they will be shipped to the Central Arkansas 
Veterans Healthcare System for processing.  All shipments will follow standard 
procedures for tracking and security.  Each sample will be labeled with the 
subject study ID, and date of collection. 
vi. 
Blood for serotonin assay.  Whole blood will be assayed for serotonin as an index 
of serotonin reuptake inhibition bioeffect.  The assay used also provides results 
for tryptophan levels.  A single 1 ml sample of blood will be collected in a plastic 
4 ml EDTA serum tube at randomization and at 1 month after randomization. The 
tubes will be shipped on the day of collection to the Crescenz VA Medical Center 
for storage and inventory control.  When appropriate numbers of samples have 
been collected, they will be shipped to the West Haven VAMC for serotonin 
assays.  All shipments will follow standard procedures for tracking and security.  
Each sample will be labeled with the patient study ID, and date of collection. 
vii. 
C-Reactive protein – a marker of inflammation which correlates to severity of 
depression and will be used as a baseline marker of severity.  A single red top 
serum tube (10ml) will be collected at baseline. The sample will be processed 
locally by centrifuging and then drawing off the serum.  Serum will be placed in 
cryotubes, frozen and shipped to the Crescenz VA Medical Center for storage 
and inventory control.  C-reactive protein, an acute-phase reactive protein, will be 
measured as mg/L liter of blood from the same sample using a high-sensitivity 
immunoturbidimetry assay.  The analysis of the samples will be done through the 
Crescenz VA Medical Center Clinical Laboratory. Each sample will be labeled 
with the subject study ID, and date of collection. 
viii. 
Metabolites and alcohol use.  Remaining back up serum cyrosamples, after 
serum assay is complete, will be used to identify blood markers (metabolites) that 
are associated with heavy alcohol use.  Samples will be delivered to Dr. Zachary 
Schug at the Wistar Institute at the University of Pennsylvania under a local data 
transfer agreement.  Each sample is labeled with the subject study ID, and date 
of collection. Dr. Schug’s laboratory will analyze the samples. Once this process 
is complete the samples will be destroyed or returned to the VA. Analysis and 
storage of the data from these samples will be only on VA servers.  
 

  
PRIME Care – Protocol Version 18  10/22/21 Page 26 of 45 
 
c) Optional Actigraphy: Participants at selected sites will have access upon 
randomization to an optional component of the study to gather daytime and nighttime 
activity. Participating in this component of the study is optional and Veterans will 
complete an addendum to the consent for this part of the project. For participating 
subjects, the local research staff will provide an ActiGraph wearable device 
(ActiGraph LLC) and charging station. The device is worn on the wrist, like a wrist 
watch and does show the time. The subject will be shown how to wear, and how to 
charge and sync the device using their smartphone. Syncing is optional but allows us 
to monitor more closely use and problem solve with patients who are having 
difficulty. Participants will be asked to wear the device at all times including sleeping 
but not while in water (swimming, etc.). Participants will be asked to bring the device 
to their four week in person visit to be synced by the coordinator using actisync 
software. Participants will not have access to their own data but can use the device 
as a watch.   
i. 
We will obtain the devices from ActiGraph LLC using a statement of work 
between the Philadelphia Research and Education Foundation (our local 
research non-profit - PREF) and ActiGraph LLC. 
ii. 
The device provides the following data points: amount of activity, estimated time 
in bed, estimated time out of bed, steps taken, energy expenditure, amount of 
sleep, awakenings, and sleep efficiency 
d) Electronic health record (VINCI). Data on healthcare utilization will be obtained 
through VINCI for:  
i. 
Three time periods: 12 months prior to study entry, the duration of the study, and 
12 months after the study period.  These data will focus on mental health and 
substance abuse services received by Veterans randomized in the trial, as well 
as data for Veterans not enrolled in the trial who otherwise met 
inclusion/exclusion criteria during the same time frame.   
i) Medication use – For the main trial, we will examine medication switches and 
adherence to the recommendations resulting from the genetic test.  These 
data will also be used to account for other medications that could affect the 
metabolism of antidepressants.   
ii) Services utilization – We will extract data related to the utilization of health 
care services to conduct the economic analysis and as a secondary measure 
of treatment outcome (Hypothesis #3). 
e) Patient Tracking. 
i. 
Subject tracking logs – To facilitate tracking and participation, we will store in a 
separate data table the patient name, SSN, birthdate, address and phone 
number.  This table will not be included in any analytic data sets.  This tracking 
will be stored on the secure MIRECC server 
(\\oitphihsmsvm200.v04.med.va.gov\Research). This is necessary for tracking 
and to return PGx test results.   
ii. 
Centralized tracking – The centralized call center (Crescenz VA Medical Center) 
will receive information for each randomized patient, including identifiable patient 
information (name, SSN, address, phone number, date of birth).  The call center 
will use REDCap and the BHL software to track follow-up assessments.  The 
software allows patient tracking, records all call attempts, and prompts 
centralized staff when the next assessment is scheduled.  All follow-up 
assessments will be entered into either REDCap or the BHL software.  Both the 
BHL and REDCap are approved for VA use. 
5.5.c Assurex data from call center. 

  
PRIME Care – Protocol Version 18  10/22/21 Page 27 of 45 
 
a) Provider call information.  For providers who call for assistance in interpreting test 
results, Assurex will keep track of the name of the provider, the general nature of the 
questions and the sample acquisition number of the test results reviewed. 
b) Patient call information.  For patients who call for assistance in interpreting test 
results, Assurex will keep track of the sample acquisition number of the patient and 
the general nature of the questions asked by the patient. 
 
Table 2: Patient assessments 
 *Delayed results group only 
 
Storage of data.  Research material will include information obtained from consented 
patients and prescribers.  The clinical trial will use two main data collection systems for 
prospectively collected data: BHL software and REDCap.  Both of these data collection portals 
have safeguards for data entry (e.g., no out of range or otherwise invalid responses will be 
Instrument 
Patient 
Time 
Uploaded 
to CPRS 
Baseline 
Follow-up 
assessments 
Week 36* 
PHQ-9 
2 min 
X 
X 
X 
X 
C-SSRS 
1 min 
X 
X 
X 
X 
Social Support 
1 min 
X 
X 
X 
X 
PCL-5 
5 min 
X 
X 
X 
X 
GAD-7 
2 min 
X 
X 
X 
X 
VR-12 
5 min 
X 
X 
X 
X 
TLFB (alcohol) 
2 min 
X 
X 
X 
X 
Modified ASSIST 
2 min 
X 
X 
 
 
Satisfaction 
1 min 
 
 
X 
X 
Demographics 
1 min 
X 
X 
 
 
Treatment history (self-
assessment) 
2 min 
 
X 
 
 
Adherence 
1 min 
 
 
X 
X 
Side effects 
1 min 
 
 
X 
X 
Screens for psychosis, 
panic disorder, antisocial 
personality disorder, mania 
and diagnosis for drug and 
alcohol use disorders 
15 min 
 
 
week 4 only 
 
Nutritional questionnaire 
3 min 
 
 
week 4 only 
 
Receiving results 
1 min 
 
 
week 4 
intervention 
arm only 
X control 
arm 
Smoking status 
1 min 
 
X 
X 
X 
Care outside the VA 
1 min 
 
X 
X 
X 
Biological samples (Saliva, 
whole blood, and serum) 
5 min 
 
X 
week 4 only 
 
Early termination 
 
 
 
As applicable 
As 
applicable 
VA health care utilization 
EHR 
 
X 
X 
X 
Concurrent medication use 
EHR 
 
X 
X 
X 
Actigraphy 
Wearable 
6 months 
 
X 
(Continuous) 
 

  
PRIME Care – Protocol Version 18  10/22/21 Page 28 of 45 
 
accepted) and form validation (e.g., logically impossible responses to different questions will not 
be accepted). Audit logs will record any modification to the original entry. All data collection, 
transfer, and storage of any identified data will be performed on the VA Intranet and thus access 
to the system is user based and requires maintenance of all relevant employee trainings. The 
system will be compliant with the guidelines described in the VA Handbooks 1200, 1605, 6300, 
6500, and 6502, and with the VA IT Directive 06-2.   
 
A brief description of each source and storage site is provided below: 
a) BHL software. The participant’s self-reported responses to all questionnaires used in the 
clinical trial, which will cover the domains of Depression (PHQ-9), PTSD symptoms (PCL-5), 
Functional Assessment (RAND 12-item Health Survey – VR-12), Alcohol Use (TLFB), Illicit and 
Addictive Drug Use (NIDA-Modified ASSIST), and Treatment Satisfaction (two items on quality 
of care and ability to obtain the services desired) and Participant Tracking Information, will be 
collected using the Behavioral Health Lab (BHL) software system.  The BHL software is a VA 
approved and network wide installed software package that allows patients and clinicians to 
collect and use patient reported outcomes and allows providers to track patients in care and to 
graphically display assessment reports by patient or for groups of patients.  The software has 
been in use for more than 10 years in the VA and has the capacity to allow direct entry of self-
assessments using a tablet, which then links to VISTA/CPRS.  For the purposes of the trial, we 
will use this system of data collection for the patient reported outcomes at baseline at each site 
and allow the assessments to populate the local clinical record.  We will also use the software to 
track patients and store the assessment data from the follow-up interviews 
(\\oitphihsmsvm200.v04.med.va.gov\Research \BHL Software). The BHL software includes 
personal, identifiable data such as names and social security numbers as a mechanism to 
interface with VISTA/CPRS and to allow convergence of data across the data collection 
methods.  
b) REDCap (Research Electronic Data Capture) is a web-based application for managing 
data acquisition during clinical research.  REDCap is supported by the VA Information Resource 
Center and is maintained within the VA firewall so that it is only accessible on the VA intranet.  
REDCap will be used in this trial to supplement the BHL software and will include the Veteran 
response data, and provider surveys.   
c) CDW:  In addition to prospectively collected data, we will require administrative data 
from the corporate data warehouse (CDW) for both prescribers and patients.  The CDW is a 
representation of the electronic health record. The VA Informatics and Computing Infrastructure 
(VINCI) is a major informatics initiative of the Department of Veterans Affairs that provides a 
secure, central analytic platform for conducting research and supporting clinical operations 
activities.  The VA provides services to Veterans at over 1,400 points of care. The electronic 
health record system used at each point of care is known as the Veterans Information System 
Technology Architecture (VistA). VistA provides a longitudinal view for patients receiving care 
nationwide and includes diagnoses, procedures, medications, labs, physiologic measurements, 
and text notes and reports.  Data are aggregated from individual VistA systems to the VA 
Corporate Data Warehouse, where they are modeled and prepared for use.  We will use VINCI 
to access pharmacy and medical care utilization records for the 12 months prior to study entry, 
the duration of the study, and the 12 months after the study period.  These data will focus  on 
the mental health and substance abuse services delivered to patients and the prescribing 
practices of prescribers.   
d) Assurex outcomes will be received regularly using a VA approved encrypted email 
method (RMS) or data will be uploaded to a secure Microsoft Teams SharePoint folder 
managed by Assurex. The data will be uploaded to and stored on secure MIRECC server 
space. Likewise, biological sample results, and any other source of data will also be stored on 
secure VA server space with assigned access as need to perform study duties. 

  
PRIME Care – Protocol Version 18  10/22/21 Page 29 of 45 
 
e) ActiGraph data.  Data are transmitted from the device to ActiGraph LLC’s web based 
platform (CentrePoint Data Hub). Participants have the option of syncing the device to this 
platform during the 6-month period using their smartphone. Research coordinators will sync 
data using ActiSync software at the in person four week visit. When synced, data is deleted off 
the device. There is no transmission of personalized identifiable data or locations. The devices 
do not collect or store GPS signals. The wearable is identified by a unique device number and 
we will only register subjects in the data hub using site name and an assigned subject identifier. 
ActiGraph LLC will not have access to any PII. Data will be transmitted to the VA either as a 
download from the CentrePoint data hub, portal or using a VA approved encrypted email 
method (RMS). An application software system provides a secure Web API (CentrePoint API) 
for retrieval of subject data via HTTPS. ActiGraph LLC will not use the data for any other 
purposes than our specific research project, and data is to be destroyed at the end of the study.  
f) Transcription Audio Files and transcripts. We will use VA approved audio recording 
devices. Either the VA Salt Lake City (VASLC) transcription service or the VA approved vendor, 
Productions Transcripts Inc., will transcribe the audio files. The VASLC has a Professional 
Transcription Service available to VA sites and monitored by their own IRB. The PRIME Care 
audio recordings to be transcribed will be labeled by the provider's unique code and saved 
behind the VA Firewall in PRIME Care’s secure shared project folder on the VISN 4 MIRECC 
server \\oitphihsmsvm200.v04.med.va.gov\Research). If VASLC transcription staff are used they 
will be given access to a limited access sub-folder.  Approved study staff will place a copy of the 
audio files in this folder for an approved VASLC transcriptionist to access for the purposes of 
transcription. If Productions Transcripts Inc. staff are used, the audio files will be submitted by a 
study team member using a login/password to https://client.productiontranscripts.com/ and 
stored on secure servers located at PhonixNAP, 3402 E. University Dr., Phoenix, AZ 85034. 
The transcriptionist will transcribe each interview verbatim and, depending on the vendor, either 
save the completed transcript in the sub-folder, or make available for download through the 
secure website. As completed transcripts become available, final versions will be stored on the 
VISN 4 MIRECC server (\\oitphihsmsvm200.v04.med.va.gov\Research) in a folder accessible 
by study staff only.  Final transcripts are coded and will only be identified by the provider ID; any 
identifying information will be removed before analysis. For data analysis, temporary copies of 
the transcripts will be used on local servers at the Buffalo and Boston VAMCs as well as the 
University of Buffalo.  Analytic staff at these three sites may print temporary hardcopy 
transcripts for qualitative analysis. When not in use these hard copy transcripts will be kept in 
locked file cabinets and at the end of the study will be securely discarded.  
 
5.6 Data Analysis 
Prior to data analysis, it will be necessary to create appropriate databases by 
combining data from BHL, CDW, and REDCap, de-identified to remove all personal or 
identifying information (i.e., all fields with PHI or identifiers will be removed), and kept in 
separate password-protected files on the VISN 4 Mental Illness, Research, Education 
and Clinical Center (MIRECC) server space within the VA firewall.   We will merge this 
file with the randomization assignment database (Palo Alto Cooperative Studies 
database).  Only this resultant data file will be used in subsequent data management 
and analyses, and only the Principal Investigator and research staff will have access to 
the data.  No data will be allowed outside of the VA intranet unless by agreement to 
make public a de-identified analytic data set.   
 
Data Analyses.  Prior to analyses, we will compare groups on a set of characteristics to 
check that the randomization procedure yielded approximately balanced groups. Our primary 
analyses will adjust for the design variables of site and provider, using fixed and random effects, 
respectively. If some characteristics show marked imbalance, we will perform sensitivity 

  
PRIME Care – Protocol Version 18  10/22/21 Page 30 of 45 
 
analyses adjusting for them, and compare and report both sets of results. The expected 
distributions of our responses fall within the generalized linear models family, and we anticipate 
that parametric models will provide adequate fit in all cases. In all analyses, we will use 
standard model-checking procedures to assess the validity of our models, based on residual 
analyses. We will examine numerical measures of fit and graphical tests of various departures 
from the model based on residuals. In the event that these models provide a questionable or 
inadequate fit, the sample is large enough to allow sensitivity analyses via non-parametric 
analogues of the primary models.  
 
5.6.a Patient response to treatment (Hypothesis #1). The primary outcome measures will be 
a set of binary indicators of remission (PHQ-9 score < 5) across the intervention phase time 
points (weeks 4, 8, 12, 18 and 24). We will use a mixed effects logistic regression model to test 
the hypothesis that patients whose treatment is informed by the PGx results are more likely to 
be in remission than those receiving usual care. The model will have a binary indicator from the 
intervention group as the main explanatory variable, together with variables for time and group 
by time effects. The model will also include a fixed effect for site. The covariance structure of the 
model will take the hierarchical structure of the design into account, to accommodate nesting of 
repeated measures within patients, and nesting of patients within providers. Including a random 
intercept for provider, and correlated residuals within patient, should account for the nesting, but 
we will use information criteria to compare the fit of different covariance structures to ensure 
adequate fit. As there is particular interest in the remission rate of patients at the end of 
treatment, we will report a model-based comparison between the groups at the endpoint of the 
intervention phase.  
 
To examine the effects of patient-level and provider-level characteristics, we will include 
these variables and their interactions with intervention group in the logistic regression model. 
For example, we will examine the effects of sex, race and ethnicity, baseline depression 
severity, the number of prior treatment episodes, and the effects of primary care versus 
specialty care, etc. We will also test for heterogeneity of the intervention effect across sites (i.e., 
site by treatment interactions). Analyses to assess the influence of missing data, and of 
adherence at the provider and patient level, are described below. Our reports will include clear 
descriptions of the statistical methods used and the clinical interpretations of the parameters 
used to test the hypotheses, with estimates, standard errors, confidence intervals and p-values 
associated with the parameters.  
 
5.6.b. Patient and provider use of PGx results (Hypothesis #2). For each provider-patient 
dyad in the trial, we will use the results of the genetic test to classify each medication prescribed 
by the provider to that patient as green, yellow, or red, thus creating an ordinal measure for 
each time the provider prescribes a medication. Our primary response for Hypothesis #2 will be 
the correspondence between the study-period prescription for the provider-patient dyad across 
the randomized groups. We will compare the groups on the probability of receiving medications 
of the three types (red, yellow, green) using mixed effects ordinal regression model, including 
random intercepts for providers. 
 
5.6.c. Secondary Responses (Hypothesis #3).  We will use generalized linear regression 
models to evaluate secondary outcomes, using the same covariates as above: a binary 
indicator for intervention group, and variables for site, provider, and depression severity. 
Regression models will include random effects to accommodate correlations due to repeated 
measures and nesting of patients within providers.  
 

  
PRIME Care – Protocol Version 18  10/22/21 Page 31 of 45 
 
Secondary analyses will include an examination of the longitudinal trajectories of PHQ-9 
summaries of depression severity across the intervention phase. These models will use the 
overall PHQ-9 score as a response, yielding a set of continuous (possibly skewed) repeated 
measures. These responses will be analyzed using mixed-effects linear models (or mixed-
effects gamma models, depending on the degree of skewness). We will compare the groups on 
functional improvement, using the mental health component of the VR-12 score, with analogous 
generalized linear mixed effects models appropriate to the response distribution.  
 
We will compare the groups on the rates of side effects that are moderate or severe. Indeed, 
side effects may be more plausibly related to serum antidepressant levels and thus PGx results 
than depressive symptoms. The data will include ordinal ratings of headache, nausea or 
vomiting, diarrhea, constipation, and sexual dysfunction at weeks 4, 8, 12, 18, and 24. We will 
use a mixed effects ordinal logistic regression model to test whether there are differences in the 
probabilities of moderate or severe side effects between the two intervention groups.  We will 
compare the two groups on the number of outpatient visits per patient using a regression model 
for count outcomes, with a random intercept for provider to accommodate nesting pf patients 
within providers. We expect that a negative binomial, possibly with zero-inflation, will provide the 
best fit to the response distribution. We will also consider the delay in treatment in the 
intervention group as a potential adverse outcome if it leads to more patients not receiving 
treatment.  
 
Actigraphy will be used in secondary analyses, as an objective measure of response to 
depression treatment. While there will not be a true baseline period of assessment 
(pretreatment) we will utilize the first 2 weeks of study participation as a marker of baseline 
activity. This is consistent with depression treatment typically taking 4-6 weeks to see objective 
improvements. We will then examine change in daytime activity (exercise and energy 
expenditure) as well as nighttime sleep (efficiency, awakenings) as markers of improvement.  
We will examine the relationship between these markers and self-reported symptoms and 
contrast improvement across the two arms. We will also be able to examine the degree to which 
sleep and activity are moderators of depression response. Finally, there are a number of other 
potential questions that could be examined. The availability of genetic data would also permit 
analyses examining associations between genomic variants and objectively-assessed sleep and 
activity phenotypes 
 
5.6.c. Economic evaluation. There are a variety of methods and perspectives that can be 
used in health economic evaluations.  For this proposal, we will use three methods (budget 
impact analysis (BIA), cost-effectiveness analysis (CEA), and Markov modeling) and one 
perspective (VA) for the economic evaluation of the clinical trial.  BIA has become essential for 
developing the business case for healthcare interventions generally and health technology 
interventions in particular.  CEA combines cost and patient outcomes into a single outcome.  
Markov models can use the clinical trial data to run the BIA or CEA beyond the 24-week 
duration of the PGx trial. 
 
The economic evaluations described above will be conducted from the payer's perspective 
(VA) for the main analyses. VA costs will be assessed using Decision Support Systems (DSS) 
National Data Extracts, which use an activity-based cost allocation method; includes fixed 
direct, variable direct, and fixed indirect costs; and is the official cost managerial accounting 
system for the entire Department of VA.  Cost estimates from the VA Health Economics 
Resource Center (HERC) will be used in a sensitivity analysis.  Access to DSS and HERC data 
will be requested through VA Corporate data warehouse (CDW/VINCI) and National Data 
Systems (NDS). Outpatient costs for the main analysis will be organized in the following groups 

  
PRIME Care – Protocol Version 18  10/22/21 Page 32 of 45 
 
by primary stop code field: primary care, mental health specialty care, ancillary, physical health 
specialty, and other (i.e., costs that fall into none of the other categories). Outpatient VA 
medication costs will be assessed using VA DSS data. The cost of each prescription will be 
based on the drug product costs and the supplies needed to dispense the prescription 
according to dispensing location (centralized mail order pharmacy vs. pharmacy window).  PGx 
intervention costs will include the cost of the PGX test and additional provider time to utilize the 
PGx data.  Other costs for setting up the communication of PGx data to providers will be 
considered sunk costs and not included in the economic evaluation.  In secondary analyses, 
inpatient cost and non-VA healthcare utilization costs will be added to the main analysis cost.  
Non-VA healthcare utilization will be collected via patient self-report and average Medicare 
payment rates applied.   
 
Budget Impact Analysis.  The BIA will be conducted in accordance with the guidelines from 
the International Society for Pharmacoeconomics and Outcomes Research (ISPOR). The BIA 
covariates will be the same as those used in the primary analysis plus one-year pre-intervention 
healthcare utilization costs to control for baseline cost differences. Because total costs are likely 
to be non-normally distributed, we will use generalized linear models (GLMs) to estimate the 
effect of the intervention on total costs. To calculate the incremental treatment effect on costs, 
we will compute two predicted costs for each participant based on the coefficients from the GLM 
regressions and the covariate values for each patient. The first cost prediction will be for costs 
as if the subject had been randomized to the PGx arm of the study, and the second cost 
prediction will be for costs as if the participant had been randomized to usual care. The 
difference between these two cost predictions represents the incremental cost effect of the 
intervention for a particular participant because all covariate effects will be identical for the two 
estimates in a given patient.  We will then average the difference between these two predicted 
values for each Veteran across all Veterans in the sample to generate an over marginal effect 
and 95% confidence interval.  To estimate the budget impact, we will estimate the total 6-month 
cost that would be incurred by VA to deliver PGx tests to all VA patients who would be eligible 
for the PGx trial using the inclusion and exclusion rates.  This number will be multiplied by the 
marginal cost difference calculated above.  Sensitivity analyses will include using HERC cost 
data and cost range for PGx testing. 
 
Cost-Effectiveness Analyses (CEA). The CEA will be conducted in accordance with the 
guidelines from the US Panel on Cost-Effectiveness in Health and Medicine.  The CEA result 
will be a ratio with marginal cost in the numerator and marginal effectiveness in the 
denominator.  The marginal cost component of the CEA will use the methods described for the 
BIA above.  The effectiveness component of the ratio will be calculated using disease-specific 
(i.e., depression) and generic (i.e., quality-adjusted life year or QALY) outcomes.  The disease-
specific outcomes will be measured by calculating depression-free days from the PHQ-9 scores.  
Depression-free days will be calculated by using a formula now used for multiple depression 
severity measures where a PHQ-9 score <5 is considered depression free (score=1) and a 
score of 15 or more is considered fully symptomatic (score=0).  Scores in between will be 
assigned a linear proportional value.  Generic QALYs will be calculated using the Veterans 
RAND 12-item Health Survey (VR-12) standard gamble to QALY conversion formula.  Total 
depression free days and QALYs will be calculated using area under the curve methods.  GLM 
methods similar to those described above for costs will be used to calculate marginal 
effectiveness.  Typical standard error estimation methods do not apply to incremental cost-
effectiveness ratios for two reasons. First, the possibility of having zero or near zero 
denominators is non-negligible. Second, expenditure and effectiveness estimates are rarely 
independent.  Therefore, we will use 1000 replications of a nonparametric bootstrap with 
replacement model to generate an empirical joint distribution of marginal (or incremental) costs 

  
PRIME Care – Protocol Version 18  10/22/21 Page 33 of 45 
 
and QALYs.  We will then construct acceptability curves representing the probability of falling 
below incremental cost-effectiveness ratio thresholds ranging from 0 to $100 per depression 
free days and 0 to $100,000 per QALY.   
 
A Markov model will be constructed to evaluate the cost-effectiveness of the use of PGx 
tests beyond 6 months. The cycle length for the model will be 30 days with a time horizon of 
one-year. The baseline model population consists of Veterans initiating antidepressant 
treatment for depression.  The respective ages for the baseline model population will be derived 
from Veterans initiating treatment for MDD in the national VA database so that findings can be 
generalized to all Veterans. The model structure will be adapted from the study by Perlis et al. 
[53], which performed cost-effectiveness analyses using a Markov model incorporating 
probabilities from the multicenter STAR*D effectiveness study of depression. For this study, 
probabilities from the current trial will be used. Patients will enter the model with a current 
episode of depression. The first decision node will be whether or not PGx test data are available 
to the prescribing clinician.  Under each study arm, we will develop a state-transition model of 
probabilities in which an individual patient could occupy a distinct health state, depressed (on 
treatment consistent with PGx test or on treatment not consistent with PGx test or off treatment), 
well (on treatment consistent with PGx test or on treatment not consistent with PGx test or off 
treatment), or death. Probabilities of remission, discontinuation, and recurrence will be drawn 
directly from the trial and extrapolated to one year. For remitted patients (“well”), the mortality 
rate will be equal to the age-gender-adjusted all-cause mortality rate from the U.S. Census. For 
depressed patients, we will add the rate of suicide among depressed patients to the age-
gender-adjusted all-cause mortality rates of the remitted patients. Costs and utility values will be 
calculated as described in the section for BIA and CEA studies. For the base case analysis, we 
will simulate a hypothetical cohort of 10,000 patients using first-order Monte-Carlo simulation. 
The simulated cohort will have mean demographic characteristics consistent with MDD patients 
initiating treatment in the VA population nationally.  We will perform both 1-way sensitivity 
analysis on the influential model input parameters (e.g., time horizon, remission, 
discontinuation, recurrent rates, drug cost, and cost of genomic test) and second order Monte-
Carlo simulation by generating 100 cohorts of 10,000 patients to account for potential patient 
heterogeneity. Since the time-horizon is 1 year, no discounting will be applied. 
5.6.d. Change in prescribing in delayed results group post-intervention (Hypothesis #4). At 
the conclusion of the six-month intervention phase of the trial, the genetic test results will be 
returned to the providers (and patients) in the treatment as usual group.  We expect to see a 
rise in use of medication categorized as green medications after the results are returned.  Thus, 
within the delayed results group, we will use a mixed effects ordinal response model to estimate 
and test a time dependent change in the probability of receiving medications of the three types 
(red, yellow, green) after the intervention. In addition, we will perform a bivariate analysis, 
combining the ordinal model with a linear model for the PHQ-9 score, to examine whether 
change in prescribing practice (i.e. increased prescribing of green-type medications) is related 
to change (i.e. an expected decline) in PHQ-9 scores.   
 
5.6.e.  Biological confirmation of effect of testing. As reviewed above, the literature on 
genetic variation affecting the pharmacodynamics of antidepressant treatment is sparse, and 
the available tests depend nearly completely on the variation associated with antidepressant 
pharmacokinetics, where individual variants have much greater effects. As part of the clinical 
trial we have included the collection of additional biological samples with several exploratory 
aims.   First we will obtain genomewide association study (GWAS) data for the 2000 participants 
with MDD in the PRIME Care study.  This will allow us to: 

  
PRIME Care – Protocol Version 18  10/22/21 Page 34 of 45 
 
1a. Conduct a GWAS on medication response traits (daily antidepressant dose in people 
whose depression remits with treatment, as in the main trial: PHQ-9 score <5). We will 
also explore via GWAS the most common side effects observed during antidepressant 
treatment. 
1b. Evaluate the relationship of Psychiatric Genomics Consortium (PGC)-derived depression 
polygenic risk score (PRS) to medication response. 
1c. Develop an algorithm that takes into account not only the genetic markers in the Assurex 
marker panel but also those identified through GWAS (1a above) as predicting daily 
antidepressant dosage and other relevant health care behaviors (e.g., smoking, use of 
other medications) that can affect antidepressant pharmacokinetics).  
We will also use GWAS and the Assurex testing results to examine intermediate phenotypes 
related to serum concentrations of medications and treatment response to: 
2a. Compare GWAS and Assurex testing results against serum drug level, which could 
identify novel response predictors. Assuming that serum drug level mediates treatment 
response (an underlying assumption of all of the PGx commercial tests), this will help to 
identify better predictors than those currently in use. Levels will be drawn once 
medication dosage is stable (4 weeks from randomization). 
2b. Conduct a GWAS against baseline platelet serotonin (5HT) and percentage change in 
serotonin level (delta5HT, an index of serotonin reuptake inhibitor bioeffect) to identify 
potential mediators of response.  
Finally, we will compare the utility of levels of C-reactive protein (CRP), a commonly available 
marker of systemic inflammation, with absolute levels of mRNA for macrophage migration 
inhibitory factor (MIF) and interleukin 1-β (IL-1-β) as predictors of antidepressant treatment 
response in the PRIME Care sample.  
 
Remaining back up samples after these analyses are complete, might be used for additional 
exploratory aims, rather than discarded, to further the science around health and mental health 
outcomes in this patient population.   
• 
Use remaining back up cryo serum samples to identify blood markers (metabolites) that 
are associated with heavy alcohol use. We will use high-dimensional multivariate 
analyses and machine learning approaches to determine how heavy drinking impacts 
systemic metabolism. 
 
5.6.f.  Contextual assessment of PGx testing and impact on future implementation. An 
important aspect of this trial will be to learn about delivering PGx testing in clinical practice.  We 
will imply the Consolidated Framework for Implementation Research (CFIR) to structure a 
formative evaluation of the implementation of PGx testing [54, 55].  This aim will include the 
quantitate knowledge assessment as well as the focus and individual qualitative assessment of 
providers.  Specifically, we will focus on an exploration of the current state of knowledge and 
perceptions of PGx testing, and findings will be used to develop provider and patient materials 
that can support the uptake and implementation of PGx testing.  We will focus on how provider 
and patient beliefs and expectations of pharmacotherapy and PGx tests affect their use of the 
results (moderating the effects of Hypothesis #2). We anticipate that we will have sufficient 
diversity of sites represented to use qualitative methods to explore contextual factors within the 
CFIR domains of Inner and Outer Settings that will be important in preparing for a national roll-
out of PGx testing.  We are particularly interested in the Inner Setting context of team care 
(PCMHI in PACT and BHIP in specialty Mental Health [MH] settings) as it relates to the ability of 
individual providers to make this change in their practice. 
 
To accomplish these aims, we will recruit a subset of sites to participate in virtual 
(telephone/Lync-based) focus group interviews.  We will conduct up to ten 45-minute-long (15 
minute presentation, 30 minute discussion) focus groups with 3-5 prescribers each, grouped by 

  
PRIME Care – Protocol Version 18  10/22/21 Page 35 of 45 
 
provider type (PCPs and psychiatrists (and other specialty mental health providers)).  
Membership will mirror the intended eligibility for provider participants in the trial.  While these 
groups are smaller than typical focus groups, we believe that our highly educated participants 
will provide rich feedback and increase the feasibility of both provider and patient recruitment by 
helping us to understand the common perceptions of PGx testing.  These focus groups will 
receive a brief presentation on PGx’ s, including a sample report of Assurex results, and will 
then discuss current knowledge and perceptions of PGx testing.  They will provide input that will 
facilitate the RCT (e.g., How can we help prescribers recruit for the trial? What information is 
needed to understand and use PGx results?), and feedback on how PGx results should be 
returned to providers and patients.  The use of focus groups at this stage is important to enable 
group discussion to flesh out perceptions and stimulate ideas about how PGx testing can be 
implemented. All groups will be held virtually via Lync On-Line Meetings so that slides can be 
presented.   
 
Finally, individual interviews with providers in the RCT will be used to identify barriers and 
facilitators to individual uptake and use of PGx test recommendations.  We will sample across 
sites and providers based on the providers rate of referral and their specialty area (primary care 
or psychiatry) to interview up to 85 providers. Each individual interview will take 30-45 minutes 
and be recorded and professionally transcribed.  Atlas-ti software will be used to facilitate 
qualitative content analysis of interview transcripts. 
 
5.6.g. Dropout and Missing Data.  At the time of enrollment, we will stress to all patients the 
importance of follow-up assessments, independent of treatment adherence.  Despite every 
attempt to obtain outcome data for all patients, including those who drop out of treatment, we 
anticipate that there will be dropout from the study as well as intermittent missing data. To 
assess the sensitivity of our conclusions to missing data, we will use observed data such as 
baseline characteristics, intervention group, and responses obtained prior to dropout, to perform 
further sets of analyses. The mixed effects models described above can make use of all 
available responses, can accommodate the heterogeneity of response times caused by 
intermittent missing data, and will provide valid estimates and hypothesis tests under an 
assumption of “ignorable missingness,” meaning that the occurrence of dropout and missing 
data can be predicted based on observed data. We will use extensions of these models (inverse 
probability weighted selection models and pattern mixture models) to examine the plausibility of 
the ignorable missingness assumption [56]. We will perform these analyses under a range of 
different prediction models and assess the sensitivity of the results.  
 
5.6.h. Adherence. For Hypothesis #1, there are two levels of adherence to be considered. 
First, a provider/patient dyad in the intervention group may not use a recommended medication 
(this is the focus of Hypothesis #2 above) and, secondly, a patient may not actually take the 
medication as prescribed.  We will assess adherence at the provider/patient dyad level by 
comparing the prescriptions that are written to the recommendations of the PGx report. We will 
also ascertain self-reported adherence at each assessment and will supplement with 
prescription data.  Adherence to medication is well chronicled as an important concept in the 
effectiveness of treatment, yet no gold standard exists for the measurement of adherence [57, 
58].  Each method has advantages and limitations.  The advantage in this trial of using 
pharmacy records is the convenience of collection and the lack of interference with clinical 
practice, as this is not a standard trial with a high number of data collection time points. We will 
assess patients’ adherence to their prescribed medication via self-report at each assessment. 
 
To assess the sensitivity of the results of the analyses described above to non-adherence, 
the models described above for primary and secondary outcomes will be extended using 

  
PRIME Care – Protocol Version 18  10/22/21 Page 36 of 45 
 
instrumental variable approaches. Here, the instrumental variable is randomization that, under 
some conditions, will control for unmeasured bias (due to self-selection to adhere or not) when 
estimating the relative effects of the medications in those who adhere to their assigned 
medication. Results will use data from all patients who show various degrees of adherence as 
measured by the availability of medication or adherence to the PGx recommendation and will 
yield estimates of the intervention effects that would have been seen in a study with full 
adherence. For a single overall measure of adherence, we will use the methods of Nagelkerke 
et al. [59]; if there is sufficient within-patient variation across time in adherence, we will use the 
longitudinal methods of Small et al. [60]. Because adherence adjustments tend to be small and 
do not have a large influence on treatment comparisons, we view these as sensitivity analyses, 
whose main purpose is to check that estimates of effect from the primary models can be 
reported without explicit adjustments for adherence.  
 
5.6.i. Adequacy of sample size.  The single primary outcome is a set of repeated binary 
indicators of remission from depression. As we have a single outcome, we use a Type 1 error 
rate of 5%. Although we expect the intervention arm to be no less efficacious than the delayed 
results arm, we use a two-sided test. We also assume a 20% loss to dropout, distributed evenly 
over time, and across the two groups. The parameters that determine power are the base rate, 
which is the rate of treatment success expected in the delayed results arm, and the treatment 
effect.  The anticipated remission rate in usual care is based on results from STAR*D [19]. For 
the base rate, we consider rates of 20-25-30-35%, and for the treatment effect, we look at 
effects of 5-6-7%. The study design has patients nested within providers, so it is possible that 
there will be small correlations between the results for two patients of the same provider. 
Accounting for nesting within provider should also address the nesting within sites [61]. Our 
design will have approximately 200 providers, with an average of ten patients per provider. The 
design effect due to provider is then 1+9*r, where r is our assumed provider intra-class 
correlation. Our sample of size 2000 is then equivalent to an “independent patients” sample of 
2000/(1+9*r). We anticipate a low ICC, on the order of r<0.05. If we assume that r=0.05, then 
the design effect is 1.45, and the effective sample is 1379. For a base rate of 30%, and an 
assumed within-patient correlation of 0.4 or lower in a compound symmetry structure, then we 
have 82% power for a 5% treatment effect and 92% for the same effect in an ar(1) structure, 
with higher power for the same 5% effect with lower base rates. For r=0.01, where we have an 
effective sample size of 1835, we have power in excess of 90% for 5% effects, under either 
covariance structure.  Even with a conservative estimate of r=0.1, the design effect is 1.9, 
yielding more than 80% power for treatment effects of 6% or greater.  
 
5.6.j. Data management staffing.  Dr. Lynch and his staff will be responsible to coordinate 
the various data collection methods used in the clinical trial, and will provide support to the 
investigators, including site principal investigators to support additional exploratory hypotheses.  
In this section, we describe the methods that we will use to collect, store, and distribute data 
from the trial. 
 
5.6.k.  Security Awareness and Training. Security awareness starts with a request by an 
investigator to obtain access for his or her study personnel. To gain access to the BHL and 
REDCap systems, a user must first attend and pass the training/hands-on certification process. 
The training consists of a thorough introduction to the two systems and the policies governing 
their use.  
 
5.7 Withdrawal of Subjects 
Subjects and providers will be made aware that they may withdraw from this study at any 
time during the course of the research without penalty or loss of VA or other benefits to which 

  
PRIME Care – Protocol Version 18  10/22/21 Page 37 of 45 
 
they are entitled. Given that there are almost no known risks from assessing the PGx profile of a 
patient, and that the patient will receive usual care throughout his or her study participation, no 
further procedures for the orderly withdrawal or termination of participation is planned.  If a 
subject withdraws in the control group, the test results will still be returned at the 6 month time 
point.  Withdrawal of the provider has no impact on patient participation. 
6.0 Data safety and monitoring plan (DSMP) 
Data monitoring.  Throughout the trial, we will use an established protocol to manage 
patients who experience adverse clinical outcomes.  Specifically, during the follow-up outcome 
assessments, there will be a clinical staff member available at all times to call center staff, and 
patients in significant distress or who have suicidal thoughts (PHQ9 item 9 >1) will speak with a 
study clinician.  The call center clinician will then initiate appropriate care, which may involve 
initiating a rescue or working with the local investigator to facilitate care.  When clinically 
relevant, we will notify the local site team of the need for further follow-up of the patient.  
Patients who drop out of care and continue to be symptomatic will be encouraged to reconnect 
with their clinical team.  Patients who report non-adherence to medication or report that they 
never received their medication will also be encouraged to call their provider.  In addition, the 
local RC will review the chart to ensure that a prescription was written during the time between 
randomization and the 1 month blood draw or that a note was written indicating why a 
prescription wasn’t written.  If neither are found in the chart, the RC will email the provider 
altering them that the patient did not receive a prescription and query if this was intention or not.  
Results from the assessments will not be made available in CPRS/VISTA unless required for 
safety issues or those so indicated at baseline.   
 
Safety review.  The DSMP is intended to ensure the safety of research patients and the 
integrity of the study data.  Dr. David Oslin, M.D., the Principal Investigator of this program 
project and Dr. Thase, will be charged with the duty to receive from sites all submitted adverse 
events. The individual site investigators will be responsible to report any identified serious 
adverse events during the recruitment phase and until the 4 week assessment and the 
Crescenz VAMC site will be responsible to report any adverse events identified during the 
outcome calls.  Given that there are almost no known risks from assessing the PGx profile of a 
patient, it is anticipated that study-related adverse events will be low.  Given that the study 
population will include patients with serious mental illnesses, adverse events such as 
hospitalization will occur, but are expected as part of the natural disease course.  After 
assigning causality, the site investigator or the study P.I. or Co-Investigator will decide the 
course of action for the study patient.  The site PI, or for the outcome group, the study Principal 
Investigator (and, in his absence, Co-investigator) will differentiate serious from non-serious 
adverse events.  Upon discovery, all research-related deaths will be immediately and orally 
reported to the CIRB and the coordinating center followed by written notification within 5 working 
days after being made aware of the death.  All local serious unanticipated (unexpected) adverse 
events that are related to the research will be reported to the Central IRB and coordinating 
center (Crescenz VAMC) within 5 working days. Unanticipated problems that represent a risk to 
participants and/or others will be reported to the CIRB and the coordinating center within 5 
working days.  Protocol deviations that substantively affect subjects’ rights or safety, or 
potentially compromise facility human research protection will also be reported to the Central 
IRB and the coordinating center within 5 working days. An annual report summarizing all 
adverse events and unanticipated problems/protocol deviations that did not require immediate 
reporting will be prepared and reported to the Central IRB at the time of continuing review. All 
reporting requirements as detailed in the VA-CRB-SOP-114 will be followed.    
 
7.0 Privacy and Confidentiality 

  
PRIME Care – Protocol Version 18  10/22/21 Page 38 of 45 
 
All research project personnel will complete training in the protection of human research 
patients in accordance with the guidelines of the U.S. Department of Health and Human 
Services (DHHS) and the Office for Human Research Protection (OHRP).  The study staff (PI, 
clinical research coordinator, etc.) will keep all study medical records (including any codes to 
de-identified data) under lock and key in a secure location, as required by law.   Access to all 
electronic data and files (e.g., database, spreadsheet) containing identifiable patient information 
will be limited to approved users with a login.  Any computer hosting such files will have a 
password to prevent access by unauthorized users.  If data are to be exchanged with others, 
the data will be coded. If identification is necessary, then the data will be encrypted at strong 
encryption levels (≥128 bits for symmetric encryption (DES) and ≥1024 bits for asymmetric 
encryption (RSA) while en-route to the recipient.    
 
Aggregate data from cheek swab genetic testing will be returned to the Crescenz VAMC 
using a VA approved encrypted email method (RMS) or data will be uploaded to a secure 
Microsoft Teams SharePoint folder managed by Assurex. 
 
The analytic data set and blood specimens will be stored without direct identifiable 
information, but will be identifiable via a linking code. Blood will not be used for the purpose of 
establishing cell lines. Any hard copy records associated with the study will be kept in locked 
offices at the clinical site. Only staff members designated to handle or analyze study samples 
will have access to the samples and their storage.  Coded blood samples are stored in clinic-
specific refrigerators and freezers, which are located in secure rooms. 
 
Data used for safety monitoring will include serious adverse events, dropout rates and 
reasons for dropout, enrollment numbers, patient interviews, medication compliance, review of 
symptoms, review of clinical/diagnostic test results, protocol deviations, and blinded data. If it 
has been determined, for any reason, that there will be a suspension of this study, the PI will 
suspend enrollment of new patients but continue intervention/monitoring of previously enrolled 
patients if it is in the best interest of those patients.  
 
Blood or saliva and a cheek swab will be collected for DNA analysis. The information 
derived from the GWAS sample (i.e., the blood or saliva sample) will not be provided to the 
patient.  While the study is open, DNA samples will be coded with a number that provides a link 
to the patient’s identity (samples will be accessible only by the researchers and staff involved 
with this study).  Upon completion of the study, the sample for those subjects who consent will 
be kept in storage indefinitely. The lab procedures for storage include a passcode-protected 
locked room, and secure storage freezers.  All samples will be retained securely as per lab 
protocols. 
 
Individual ActiGraph activity tracker data will be returned to the Crescenz VAMC using a 
user id/password to download through the CentrePoint web portal or using a VA approved 
encrypted email method (RMS) and this data will be analyzed at the Crescenz VAMC. 
ActiGraph will store the data using an assigned subject identifier. ActiGraph LLC will destroy the 
data at the end of the study. No GPS data is collected or stored. ActiGraph will not have any PII.  
 
 
8.0 Communication Plan 
Data availability.  To facilitate manuscript writing and other dissemination activities, Dr. 
Lynch and his staff will create analytic data sets and place them in data share directories on the 
VA Intranet as approved by the CIRB.  The selection of instruments for these datasets will be 
based on discussions with the PI and data analysts for each particular manuscript.  In general, 

  
PRIME Care – Protocol Version 18  10/22/21 Page 39 of 45 
 
access to these datasets will be restricted to the Programmer/Analyst, Drs. Lynch and Shih, and 
the project investigators. Access for other users will be at the discretion of Dr. Oslin and the 
investigator group for the project.  All proposed manuscripts must be presented and approved 
by the Executive Committee prior to the initiation of analyses or access to data.  This also 
applies to the manuscripts that are planned at the outset of the study.  Failure to gain approval 
and proceeding to publication will result in the investigator being reported to the Office of 
Research and Development and will prompt communication with the editor of the journal to 
which an un-authorized manuscript is submitted. 
 
Public data set. As outlined in the Data Management and Access Plan (DMAP), de-identified 
data from this trial will be made publicly available after completion of the main outcome 
analyses. 
 
Communication of progress and results will be the responsibility of the Executive 
Committee.  We will target stakeholders including policymakers, legislators, healthcare 
providers, patients, and the scientific community. To accomplish this, we will (1) assist 
investigators in the preparation of scientific presentations and manuscripts for publication, (2) 
inform the public and policymakers of new findings through press releases and related 
mechanisms, and (3) facilitate dissemination to patients and healthcare providers through 
websites, direct to consumer marketing, and collaboration with VISN leadership, VA national 
leadership, and other centers. To facilitate dissemination, site principal investigators will be 
engaged in all scientific aspects of the project and will participate in manuscript development 
and dissemination. Dissemination is one of the responsibilities of centers of excellence such as 
the VISN 4 MIRECC. With its focus on measurement-based care and precision medicine, the 
VISN 4 MIRECC is well positioned to accomplish this goal. 
 
Publication and Presentation Plans: 
At this point, there are no planned presentations for the project. 
9.0 Risk/Benefit: 
Potential risks:  Overall, the risk to prescribers and patients is minimal. Potential risks to 
participants in this study include:   
 
Prescribers:  As employees, there could be a perceived risk that responses to the qualitative 
interviews would be available to supervisors or a sense of coercion to participate.  The data 
collected will not be made available to individual sites and only aggregate data will be published.  
This risk is considered minimal.  Members of our team have a great deal of experience in 
conducting these types of interviews.   
 
Veteran Patients: The psychological assessment includes questions of a sensitive nature in 
regards to the patients’ psychiatric symptoms.  Some patients may experience distress or 
discomfort when answering questions about these issues.  High levels of distress during these 
assessments are uncommon and staff will be trained to deal with such occurrences.  We have 
specific operating procedures that staff follows for high-risk patients, including those that report 
experiencing suicidal ideation.   
 
Genetic Testing:  The principal risk of genetic testing is breach of confidentiality, with 
sensitive information concerning the patient’s genetic risk for disease becoming known.  The 
informed consent forms will include all of the required elements of consent for genetic testing, 
including an explanation of the purposes of the DNA testing, a description of any benefits to the 

  
PRIME Care – Protocol Version 18  10/22/21 Page 40 of 45 
 
patient or others that may reasonably be expected from the DNA testing, and a statement 
describing the extent, if any, to which confidentiality of records/samples identifying the patient 
will be maintained. 
 
 
Anticipated Benefits to Patients and Society:  Potential benefits to patients include the 
acquisition of knowledge that could reduce the likelihood of exposing them to medications that 
are less appropriate for use in that patient because of their genetic features. Benefits to 
prescribers are the receipt of information about genetic variation, which could facilitate their 
selection of medication for patients in the intervention group.  Benefits to society include an 
improved understanding of PGx and other moderators of response to antidepressant 
medications that will enhance their clinical utility and the process of medications development 
for depression and related mental health conditions. 
 
Comparison of risks and anticipated benefits to patients and society:  The risks 
associated with the PGx testing are minimal.  Without confirming the value of PGx testing, 
benefits are minimal to, at most, moderate. The risk/benefit ratio thus appears favorable to the 
proposed intervention. 
 
10.0 Resources and personnel   
Below is a brief description of the study roles.  All will have access to sensitive health 
information with the exception of the executive committee.   
 
Lead Site: 
Principal Investigator – Responsible for the overall conduct of the trial and fidelity to 
the design; oversees all aspects of the study; facilitates training of sites and 
communication among local sites; leads site and Executive Committee; responsible for 
reporting to the CIRB and the DSMB.   
Investigators – Collaborate with the PI and provide back-up of responsibilities when 
needed.   Develops study materials, including provider education.     
Executive Committee (EC) – Will conduct a regular, ongoing, internal critique of the 
RCT, providing an opportunity to exchange information on the activities across the 
project.  The EC is an interdisciplinary group with representation from genomic medicine, 
informatics, clinical research, laboratory medicine, pharmacy, ethics, and primary care.   
EC members are listed at beginning of this protocol.  
Senior Research Coordinator – Responsible for day-to-day aspects of the project, 
supervises the study coordinators and research assistants (RAs) and ensures protocol 
adherence and research design integrity.  Interfaces with data management team.   
Safety Monitor - Oversees all safety aspects of the trial, including being available to 
assist the research assistants during outcome monitoring when they encounter patients 
with significant distress or with suicidal ideation.  
Regulatory and Recruitment Coordinator – Responsible for all regulatory 
correspondence with the CIRB, maintaining regulatory records for the coordinating site, 
communicating with the local sites concerning all relevant correspondence, including 
modifications, continuing reviews, adverse events, etc.  Train local site personnel to 
maintain local regulatory materials.  Oversees all tracking of recruitment, working to 
keep sites on track with the recruitment goals and reporting to the PI and EC on their 
progress/status. 
Outcome Assessment Coordinator – Supervises the outcome assessment 
component being conducted at the coordinating site.  Oversees the RAs conducting the 
research follow-up telephone interviews.  Provides training to the RAs and is responsible 

  
PRIME Care – Protocol Version 18  10/22/21 Page 41 of 45 
 
for quality control.  Manages participant payments.  Ensures that standard operating 
procedures are followed.  
Research Assistants – Conduct the participant follow-up assessments via telephone.  
Coordinate logistics with the local sites.  Complete data entry and data cleaning.   
Senior Biostatistician – oversees all aspects of data collection and management.  
Oversees all data analyses.   
Statistician – Is responsible for data management, storage, access and analysis.  
Supervises data manager.  Facilitates data sharing with investigators and tracks all data 
use during later states of the trial.  Conducts the primary and secondary quantitative 
data analyses under supervision of the senior statistician.   
  Data Manager – Aggregates data from different sources and coordinates regular 
data extraction from VINCI and BHL.  Responsible for developing and implementing all 
survey in REDCap.  Assures data transfer is completed securely.  Responsible for 
assuring the return of genetic tests from Assurex.   
 
Local Sites: 
Local Site PI – Responsible for implementing the study at the local site, including 
subject recruitment and the supervision of the local site coordinator 
Local Site Coordinator – Responsible for recruitment, consenting participants, and 
completing baseline assessments at the local site.  Communicates with local 
prescribers, facilitates delivery of PGx results.  Facilitates collection of participant 
samples and their secure delivery to the sample repository.  Coordinates activities with 
the outcome assessment group and Regulatory Coordinator at the lead site in 
Philadelphia. 
 
      Other: 
Assurex – Commercial genetics laboratory providing genetic testing and results 
based on cheek swab sample from participants based on a Cooperative Research and 
Development Agreement (CRADA) between the Corporal Michael J. Crescenz VA 
Medical Center and ASSUREX HEALTH, INC., executed 10/10/2016. Samples received 
by Assurex will be labeled with the sample acquisition number, subject initials and date 
of birth, site ID, provider name, randomization outcome, and date of collection. 
ActiGraph LLC – Commercial company that provides Bluetooth Smart actigraphy 
monitors, in conjunction with a cloud-based Centre-Point Study Admin Portal software 
platform, delivering high quality, customized physical activity and sleep/wake measures 
while offering the data management and administrative support essential for complex, 
multi-site clinical research studies. A Statement of Work will cover a Master Services 
Agreement between the VA and ActiGraph LLC.  Data received by ActiGraph will be 
identified only by a subject identifier and date of collection. 
Janssen Research & Development, LLC, a pharmaceutical division of Johnson & 
Johnson – Commercial company that is providing funding though the Philadelphia 
Research and Education Foundation for the VA to add ActiGraphs to the PRIME Care 
Project. A CRADA is in place between Janssen Research & Development, LLC and the 
VA. Janssen Research & Development, LLC will only receive de-identified data from the 
project. 
 
 
11.0 References 

  
PRIME Care – Protocol Version 18  10/22/21 Page 42 of 45 
 
1. 
Hoge, C., J. Auchterlonie, and C. Milliken, Mental health problems, use of mental health 
services, and attrition from military service after returning from deployment to Iraq or 
Afghanistan. Journal of the American Medical Association, 2006. 295: p. 1023 - 1032. 
2. 
Kessler, R.C., et al., Thirty-day prevalence of DSM-IV mental disorders among 
nondeployed soldiers in the US Army: results from the Army Study to Assess Risk and 
Resilience in Servicemembers (Army STARRS). JAMA Psychiatry, 2014. 71(5): p. 504-
13. 
3. 
Gadermann, A.M., et al., Prevalence of DSM-IV major depression among U.S. military 
personnel: meta-analysis and simulation. Mil Med, 2012. 177(8 Suppl): p. 47-59. 
4. 
Vaughan, C.A., et al., Prevalence of mental health problems among Iraq and 
Afghanistan veterans who have and have not received VA services. Psychiatr Serv, 
2014. 65(6): p. 833-5. 
5. 
Smith, N.B., et al., Nature and determinants of suicidal ideation among U.S. veterans: 
Results from the national health and resilience in veterans study. J Affect Disord, 2016. 
197: p. 66-73. 
6. 
Murray, C. and A. Lopez, The global burden of disease: A comprehensive assessment 
of mortality and disability from diseases, injuries, and risk factors in 1990 and projected 
to 2020. The global burden of disease and injury series, ed. C. Murray and A. Lopez. 
Vol. 1. 1996, Boston: Harvard University Press. 
7. 
Baingana, F.K. and E.R. Bos, Changing Patterns of Disease and Mortality in Sub-
Saharan Africa: An Overview, in Disease and Mortality in Sub-Saharan Africa, D.T. 
Jamison, et al., Editors. 2006: Washington (DC). 
8. 
Organization, W.H., The Global Burden of Disease: 2004 Update. 2008, Geneva: WHO 
Press. 
9. 
Prince, M., et al., No health without mental health. Lancet, 2007. 370(9590): p. 859-77. 
10. 
Moussavi, S., et al., Depression, chronic diseases, and decrements in health: results 
from the World Health Surveys. Lancet, 2007. 370(9590): p. 851-8. 
11. 
Fagiolini, A. and A. Goracci, The effects of undertreated chronic medical illnesses in 
patients with severe mental disorders. J Clin Psychiatry, 2009. 70 Suppl 3: p. 22-9. 
12. 
Davydow, D.S., et al., The association of comorbid depression with intensive care unit 
admission in patients with diabetes: a prospective cohort study. Psychosomatics, 2011. 
52(2): p. 117-26. 
13. 
Rustad, J.K., D.L. Musselman, and C.B. Nemeroff, The relationship of depression and 
diabetes: pathophysiological and treatment implications. Psychoneuroendocrinology, 
2011. 36(9): p. 1276-86. 
14. 
Antelman, G., et al., Depressive symptoms increase risk of HIV disease progression and 
mortality among women in Tanzania. J Acquir Immune Defic Syndr, 2007. 44(4): p. 470-
7. 
15. 
Cook, J.A., et al., Depressive symptoms and AIDS-related mortality among a multisite 
cohort of HIV-positive women. Am J Public Health, 2004. 94(7): p. 1133-40. 
16. 
Smith, S.M., S. Allwright, and T. O'Dowd, Effectiveness of shared care across the 
interface between primary and specialty care in chronic disease management. Cochrane 
Database Syst Rev, 2007(3): p. CD004910. 
17. 
Management of Major Depressive Disorder Working Group, VA/DoD Clinical practice 
guideline for the management of major depressive disorder. 2016, Department of 
Veterans Affairs, Department of Defense: Washington, DC. 
18. 
Statistics;, N.C.f.H., Health, United States, 2015 With Special Feature on Racial and 
Ethnic Health Disparities. 2016: Hyattsville, Maryland. 
19. 
Trivedi, M.H., 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(1): p. 28-40. 

  
PRIME Care – Protocol Version 18  10/22/21 Page 43 of 45 
 
20. 
Warden, D., et al., The STAR*D Project results: a comprehensive review of findings. 
Curr Psychiatry Rep, 2007. 9(6): p. 449-59. 
21. 
Rush, A.J., et al., Selecting among second-step antidepressant medication 
monotherapies: predictive value of clinical, demographic, or first-step treatment features. 
Arch Gen Psychiatry, 2008. 65(8): p. 870-80. 
22. 
Peterson, K., et al., Evidence Brief: The Comparative Effectiveness, Harms, and Cost-
effectiveness of Pharmacogenomics-guided Antidepressant Treatment versus Usual 
Care for Major Depressive Disorder. 2016, Department of Veterans Affairs: Washington, 
DC. 
23. 
Fabbri, C., et al., Understanding the pharmacogenetics of selective serotonin reuptake 
inhibitors. Expert Opin Drug Metab Toxicol, 2014. 10(8): p. 1093-118. 
24. 
Dubovsky, S.L., The usefulness of genotyping cytochrome P450 enzymes in the 
treatment of depression. Expert Opin Drug Metab Toxicol, 2015. 11(3): p. 369-79. 
25. 
Porcelli, S., C. Fabbri, and A. Serretti, Meta-analysis of serotonin transporter gene 
promoter polymorphism (5-HTTLPR) association with antidepressant efficacy. Eur 
Neuropsychopharmacol, 2012. 22(4): p. 239-58. 
26. 
Winner, J.G., et al., A prospective, randomized, double-blind study assessing the clinical 
impact of integrated pharmacogenomic testing for major depressive disorder. Discov 
Med, 2013. 16(89): p. 219-27. 
27. 
Singh, A.B., Improved Antidepressant Remission in Major Depression via a 
Pharmacokinetic Pathway Polygene Pharmacogenetic Report. Clin Psychopharmacol 
Neurosci, 2015. 13(2): p. 150-6. 
28. 
Breitenstein, B., et al., The clinical application of ABCB1 genotyping in antidepressant 
treatment: a pilot study. CNS Spectr, 2014. 19(2): p. 165-75. 
29. 
Winner, J.G., et al., Combinatorial pharmacogenomic guidance for psychiatric 
medications reduces overall pharmacy costs in a 1 year prospective evaluation. Curr 
Med Res Opin, 2015. 31(9): p. 1633-43. 
30. 
Hall-Flavin, D.K., et al., Utility of integrated pharmacogenomic testing to support the 
treatment of major depressive disorder in a psychiatric outpatient setting. 
Pharmacogenet Genomics, 2013. 23(10): p. 535-48. 
31. 
Benitez, J., et al., The clinical validity and utility of combinatorial pharmacogenomics: 
Enhancing patient outcomes. Appl Transl Genom, 2015. 5: p. 47-9. 
32. 
Altar, C.A., et al., Clinical validity: Combinatorial pharmacogenomics predicts 
antidepressant responses and healthcare utilizations better than single gene 
phenotypes. Pharmacogenomics J, 2015. 15(5): p. 443-51. 
33. 
National Academies of Sciences, E., and Medicine,, Biomarker tests for molecularly 
targeted therapies: Key to unlocking precision medicine. 2016, The National Academies 
Press: Washington, DC. 
34. 
Franzen, P.L. and D.J. Buysse, Sleep disturbances and depression: risk relationships for 
subsequent depression and therapeutic implications. Dialogues Clin Neurosci, 2008. 
10(4): p. 473-81. 
35. 
Woznica, A.A., et al., The insomnia and suicide link: toward an enhanced understanding 
of this relationship. Sleep Med Rev, 2015. 22: p. 37-46. 
36. 
Pigeon, W.R., M. Pinquart, and K. Conner, Meta-analysis of sleep disturbance and 
suicidal thoughts and behaviors. J Clin Psychiatry, 2012. 73(9): p. e1160-7. 
37. 
Pigeon, W.R., et al., Sleep disturbance preceding suicide among veterans. Am J Public 
Health, 2012. 102 Suppl 1: p. S93-7. 
38. 
Pocock, S., Randomized Trials: a practical approach. 1983, New York: John Wiley and 
Sons. 

  
PRIME Care – Protocol Version 18  10/22/21 Page 44 of 45 
 
39. 
Oslin, D.W., et al., Screening, assessment, and management of depression in VA 
primary care clinics. The Behavioral Health Laboratory. J Gen Intern Med, 2006. 21(1): 
p. 46-50. 
40. 
Tew, J., J. Klaus, and D.W. Oslin, The Behavioral Health Laboratory: building a stronger 
foundation for the patient-centered medical home. Fam Syst Health, 2010. 28(2): p. 130-
45. 
41. 
Kroenke, K., R.L. Spitzer, and J.B. Williams, The PHQ-9: validity of a brief depression 
severity measure. Journal of General Internal Medicine., 2001. 16(9): p. 606-13. 
42. 
Wortmann, J.H., et al., Psychometric Analysis of the PTSD Checklist-5 (PCL-5) Among 
Treatment-Seeking Military Service Members. Psychol Assess, 2016. 
43. 
Lowe, B., et al., Validation and standardization of the Generalized Anxiety Disorder 
Screener (GAD-7) in the general population. Med Care, 2008. 46(3): p. 266-74. 
44. 
Selim, A.J., et al., Updated U.S. population standard for the Veterans RAND 12-item 
Health Survey (VR-12). Qual Life Res, 2009. 18(1): p. 43-52. 
45. 
McHorney, C.A. and J.E. Ware, Jr., Construction and validation of an alternate form 
general mental health scale for the Medical Outcomes Study Short-Form 36-Item Health 
Survey. Med Care, 1995. 33(1): p. 15-28. 
46. 
McHorney, C.A., et al., The MOS 36-item Short-Form Health Survey (SF-36): III. Tests 
of data quality, scaling assumptions, and reliability across diverse patient groups. Med 
Care, 1994. 32(1): p. 40-66. 
47. 
Sobell, L.C., et al., The reliability of the Alcohol Timeline Followback when administered 
by telephone and by computer. Drug Alcohol Depend, 1996. 42(1): p. 49-54. 
48. 
Allen, J. and M. Columbus, eds. Assessing Alcohol Problems: A Guide for Clinicians and 
Researchers (NIH Publication). 1995, NIH Publication no. 95-3745. 
49. 
Newcombe, D.A., R.E. Humeniuk, and R. Ali, Validation of the World Health 
Organization Alcohol, Smoking and Substance Involvement Screening Test (ASSIST): 
report of results from the Australian site. Drug Alcohol Rev, 2005. 24(3): p. 217-26. 
50. 
Teague, G.B., et al., The MHSIP mental health report card. A consumer-oriented 
approach to monitoring the quality of mental health plans. Mental Health Statistics 
Improvement Program. Evaluation Review, 1997. 21(3): p. 330-41. 
51. 
Sheehan, D.V., et al., The Mini-International Neuropsychiatric Interview (M.I.N.I.): the 
development and validation of a structured diagnostic psychiatric interview for DSM-IV 
and ICD-10. J Clin Psychiatry, 1998. 59 Suppl: p. 22-33. 
52. 
Cattaneo, A., et al., Absolute Measurements of Macrophage Migration Inhibitory Factor 
and Interleukin-1-beta mRNA Levels Accurately Predict Treatment Response in 
Depressed Patients. Int J Neuropsychopharmacol, 2016. 
53. 
Perlis, R.H., et al., When is pharmacogenetic testing for antidepressant response ready 
for the clinic? A cost-effectiveness analysis based on data from the STAR*D study. 
Neuropsychopharmacology, 2009. 34(10): p. 2227-36. 
54. 
Damschroder, L.J., et al., Fostering implementation of health services research findings 
into practice: a consolidated framework for advancing implementation science. 
Implement Sci, 2009. 4: p. 50. 
55. 
Kirk, M.A., et al., A systematic review of the use of the Consolidated Framework for 
Implementation Research. Implement Sci, 2016. 11(1): p. 72. 
56. 
Fitzmaurice, G., N. Laird, and J. Ware, Applied Longitudinal Analysis. Vol. 2nd Edition. 
2011, New York: John Wiley and Sons. 
57. 
Williams, A.B., et al., A proposal for quality standards for measuring medication 
adherence in research. AIDS Behav, 2013. 17(1): p. 284-97. 
58. 
Stirratt, M.J., et al., Self-report measures of medication adherence behavior: 
recommendations on optimal use. Transl Behav Med, 2015. 5(4): p. 470-82. 

  
PRIME Care – Protocol Version 18  10/22/21 Page 45 of 45 
 
59. 
Nagelkerke, N., et al., Estimating treatment effects in randomized clinical trials in the 
presence of non-compliance. Statistics in Medicine, 2000. 19: p. 1849 - 1864. 
60. 
Small, D., et al., Random effects logistic models for analyzing efficacy of a longitudinal 
randomized treatment with non-adherence. Statistics in Medicine, 2005. in press. 
61. 
Ten Have, T.R., A.R. Kunselman, and L. Tran, A comparison of mixed effects logistic 
regression models for binary response data with two nested levels of clustering. Stat 
Med, 1999. 18(8): p. 947-60.