THE PRIORITIZE STUDY: A Pragmatic, Randomized Study of Oral Regimens for Hepatitis C: Transforming Decision-Making for Patients, Providers, and Stakeholders
Phase: PHASE4
Conditions: Chronic Hepatitis C
Sponsor: University of Florida

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PRIORITIZE 
THE PRIORITIZE STUDY:  A Pragmatic, Randomized Study of Oral Regimens for Hepatitis C: 
Transforming Decision-Making for Patients, Providers, and Stakeholders.  
 
 
Version 5.0 
 
 
 
 
 
 
David R. Nelson, M.D. (Principal Investigator) 
Professor of Medicine 
Assistant Vice President for Research 
Director, Clinical and Translational Science Institute 
University of Florida  
 
Michael W. Fried, M.D. (Co-Principal Investigator) 
Professor of Medicine 
Director, UNC Liver Center 
University of North Carolina at Chapel Hill 
 
Mark Sulkowski, MD (co-Principal Investigator) 
Professor of Medicine 
Medical Director, Viral Hepatitis Center 
Johns Hopkins University School of Medicine 
 
Anna S. Lok, MD (co-Principal Investigator) 
Alice Lohrman Andrews Research Professor in Hepatology 
Director of Clinical Hepatology 
Associate Chair for Clinical Research 
University of Michigan 
 
Donna Evon, PhD. (co-Principal Investigator)  
Associate Professor of Medicine 
University of North Carolina at Chapel Hill 
 
NCT02786537

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TABLE OF CONTENTS 
1. PROTOCOL VERSION 5.0/PROTOCOL AMENDMENT/RATIONALE AND SUMMARY OF CHANGES ........4 
1.1 UPDATE IN SAMPLE SIZE ..................................................................................................................... 4 
1.2 SAFETY ANALYSIS/STOPPING RULE .................................................................................................... 5 
1.3 VA CONSORTIUM ................................................................................................................................ 5 
2. BACKGROUND AND INTRODUCTION ...............................................................................................5 
2.1 EXTENT OF HCV .................................................................................................................................. 6 
2.2 IMPACT OF HCV AND CURE ................................................................................................................ 6 
2.3 GAPS IN EVIDENCE ................................................................................................................................... 7 
3.  PURPOSE AND SIGNIFICANCE ....................................................................................................... 11 
4.  STUDY DESIGN ............................................................................................................................ 12 
4.1 STUDY INFRASTRUCTURES AND CENTERS ........................................................................................ 15 
5.  SUBJECT POPULATION ................................................................................................................. 15 
5.1 INCLUSION CRITERIA ......................................................................................................................... 15 
5.2 EXCLUSION CRITERIA ........................................................................................................................ 15 
6. HCV-TREATMENT PRODUCTS ........................................................................................................ 15 
6.1 INVESTIGATIONAL NEW DRUG (IND) EXEMPTION ........................................................................... 15 
6.2 PROVISION OF HCV DRUG ................................................................................................................. 16 
6.3 RATIONALE PROVISION OF HCV DRUG ............................................................................................. 16 
6.4 CENTRALIZED STUDY DISPENSING SPECIALTY PHARMACY- PARTICIPANTS OUTSIDE THE 
VETERANS HEALTH ADMINISTRATION .............................................................................................. 17 
6.5 HCV THERAPY PRESCRIPTION COST FOR PATIENTS WHO ARE RANDOMIZED TO HARVONI®........ 18 
6.6 HCV THERAPY PRESCRIPTIONS FOR PATIENTS WHO CANNOT HAVE COMMERCIAL PRODUCT 
DISPENSED THROUGH THE CENTRALIZED SPECIALTY PHARMACY ................................................... 19 
6.7 HCV THERAPY PRESCRIPTIONS FOR SCREEN FAILURE AND RANDOMIZATION FAILURES............... 19 
7. STUDY PROCEDURES .................................................................................................................... 19 
7.1 INFORMED CONSENT ......................................................................................................................... 19 
7.2 SCHEDULE OF OBSERVATIONS AND SCHEDULE OF PRO ASSESSMENTS- ......................................... 20 
7.3 BASELINE NS5 RESISTANCE ASSOCIATED POLYMORPHISM (RAP) TESTING ................................... 21 
7.4 CLINICAL DATA- BASELINE, ON TREATMENT, POST-TREATMENT, AND LONG- TERM FOLLOW-UP22 
7.4.A BASELINE DEMOGRAPHIC INFORMATION ....................................................................................... 22 
7.4.B BASELINE CLINICAL DATA ............................................................................................................. 22 
7.4.C BASELINE LABORATORY DATA ...................................................................................................... 23 
7.4.D ON-TREATMENT CLINICAL DATA .................................................................................................. 23 
7.4.E POST TREATMENT CLINICAL AND LABORATORY DATA ................................................................ 24 
7.4.F VIROLOGIC FAILURE RESISTANCE ASSOCIATED POLYMORPHISM (RAP) TESTING....................... 24 
7.4.G CLINICAL DATA ABSTRACTED POST HCV TREATMENT AND DURING YR 3 .................................. 25 
7.5 PATIENT REPORTED OUTCOMES DATA- BASELINE, ON TREATMENT, AND POST-TREATMENT, AND 
LONG-TERM FOLLOW-UP ................................................................................................................... 25 
7.5.A FUTURE BIOMEDICAL RESEARCH .................................................................................................. 26 
7.6 PROGRESSION OF LIVER DISEASE, MORBIDITY AND MORTALITY DATA .......................................... 27 
7.7 PROCEDURES FOR SUBMITTING CLINICAL RECORDS FOR STUDY OBSERVATIONS .......................... 29 
8.  ADVERSE EVENTS ........................................................................................................................ 30 
8.1 ADVERSE EVENT INTENSITY/SEVERITY ............................................................................................ 30 

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8.2 ADVERSE EVENT RELATIONSHIP TO HCV TREATMENT ................................................................... 30 
8.3 ABNORMAL LABORATORY EVALUATIONS ........................................................................................ 30 
8.4 SERIOUS ADVERSE EVENTS, EXPECTEDNESS, AND CAUSALITY OF AN ADVERSE DRUG REACTION 30 
8.4.1 SERIOUS ADVERSE EVENT DEFINITION .......................................................................................... 31 
8.4.2 EXPECTEDNESS AND CAUSALITY ................................................................................................... 31 
8.4.3 EXPEDITED ADVERSE EVENT REPORTING......................................................................................... 31 
8.4.3.1 EXPEDITED ADVERSE EVENT REPORTING REQUIREMENTS ........................................................ 31 
FDA VOLUNTARY MEDWATCH FORM: .................................................................................................. 31 
9.  PREMATURE DISCONTINUATION.................................................................................................. 32 
10. VIROLOGICAL RESPONSE DEFINITIONS ........................................................................................ 32 
11. PARTICIPANT WITHDRAWAL FROM PRIORITIZE ........................................................................... 32 
12. STOPPING RULES/DATA AND SAFETY MONITORING PLAN ........................................................... 33 
13. STATISTICAL ANALYSIS STRATEGY ............................................................................................... 33 
13.1 OVERVIEW ....................................................................................................................................... 33 
13.2 GENERAL STRATEGY AND HETEROGENEITY OF TREATMENT EFFECTS (HTE) .............................. 34 
13.3 STRATEGY FOR AIM 1 – SVR12....................................................................................................... 35 
13.4 STRATEGY FOR AIM 2 – DRUG SIDE EFFECTS ................................................................................. 35 
13.5 STRATEGY FOR AIM 3 – ADHERENCE AND PERSISTENCE ................................................................ 35 
13.6 STRATEGY FOR AIM 4 – CHANGE IN SYSTEMIC SYMPTOMS ........................................................... 36 
13.7 STRATEGY FOR AIM 5 – PROGRESSION OF LIVER DISEASE ............................................................. 36 
13.8 STRATEGY FOR AIM 6 – PERSISTENCE OF VIRAL CURE OR RE-INFECTION ..................................... 36 
13.9 STRATEGY FOR AIM 7 – FUNCTIONAL STATUS ............................................................................... 36 
13.10 STRATEGY FOR A NEW AIM – IMPACTS OF MANDATED PRIOR AUTHORIZATION ........................ 36 
13.11 USE OF CAUSAL INFERENCE METHODS ......................................................................................... 37 
13.12 METHODS FOR COPING WITH MISSING DATA ............................................................................... 37 
13.13 SAMPLE SIZE RATIONALE .............................................................................................................. 37 
14.  DATA MANAGEMENT ................................................................................................................ 49 
14.1 OVERVIEW .......................................................................................................................................... 49 
14.2 CENTRALIZED CHART DATA ABSTRACTION ................................................................................... 49 
14.3 REDCAP ELECTRONIC DATA IMPORTER (RED-I)........................................................................... 49 
14.4 SUBMITTING RECORDS FOR ABSTRACTION ..................................................................................... 49 
14.5 THE DATA COORDINATING CENTER (DCC) & DATA MANAGEMENT SYSTEM .............................. 50 
14.5.1 DATA QUALITY ASSURANCE ........................................................................................................ 50 
14.5.2 STANDARDS COMPLIANCE OF DATA MANAGEMENT SYSTEM ..................................................... 51 
14.5.3 CONTINUOUS DATA QUALITY MONITORING................................................................................ 51 
14.6 TRAINING & CERTIFICATION OF CHART DATA ABSTRACTION SPECIALISTS (CDAS).................... 51 
14.7 MONITORING ACTIVITIES ................................................................................................................ 52 
15. HUMAN PARTICIPANT ISSUES ..................................................................................................... 52 
15.1 POTENTIAL BENEFITS/DISCOMFORTS AND RISKS/SUBJECT CONFIDENTIALITY .................................................. 53 
15.2 HIPAA PRIVACY RULE ELEMENTS OF PHI ................................................................................................ 53 
16. DATA DISSEMINATION................................................................................................................ 55 
17. REFERENCES ............................................................................................................................... 56 
 

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1. Protocol Version 5.0/Protocol Amendment/Rationale and Summary of 
Changes  
 
The purpose of this amendment is to: 
 
o Reduce overall sample size to at least 1700 participants consented to achieve at least 1228 
participants who begin therapy.  
o Remove interim safety analysis/stopping rule 
o Remove VA consortium 
 
1.1 Update in Sample Size 
In summary, the update of the target sample size is entirely a consequence of the marked changes 
of cirrhotic participants being treated, restrictions related to Harvoni PA, and the discontinuation 
of regimen V. This amendment has been reviewed and approved by the Steering Committee. We 
believe that the changes are less than minimal risk and will increase the perceived benefit for study 
participants and other stakeholders.  PRIORITIZE will answer critical questions regarding: 1) Rates 
of patients living with chronic hepatitis C who are being cured and durability of their cure, 2) side 
effects of the commonly prescribed drug regimens and other short and long-term treatment harms, 
and 3) patient-centered clinical benefits (changes in patient-reported HCV symptoms) and 
short/long-term liver disease progression or regression. 
 
Since the initial design of this clinical trial in 2014, there have been dramatic shifts in the HCV 
treatment landscape in the US with respect to the type of patient who is presenting for treatment 
and the types of HCV direct acting antiviral (DAA) regimens available.  Our original assumption 
that a high rate of cirrhotics would be treated was based on the available treatment data at the 
time.   In 2013-2014, more than 50% of patients undergoing HCV treatment had evidence of 
cirrhosis.  With rapid uptake of HCV treatment in this cirrhotic patient population, the prevalence 
of cirrhosis among untreated persons with HCV has decreased substantially to only 15 to 20%.  
This shift in the characteristics presenting for HCV treatment in the US is reflected in both the 
PRIORITIZE demographics to date (16% cirrhosis in over 1200 patients enrolled) and the HCV-
TARGET observational registry (15% cirrhosis).  Another dramatic shift in characteristics of 
patients presenting for HCV treatment is the increasing prevalence of Black Americans (42% of 
current enrollment) and persons who have never been treated (treatment-naïve 87% to date). 
Thus, compared to 2014, the typical patient presenting to health care providers for HCV treatment 
is more likely to be Black, have mild liver fibrosis, and have no prior HCV treatment.  As such, 
the enrolled PRIORITIZE patient population differs from the initial expectations of the study 
team. This shift in patient demographics has affected our sample size.  
 
From an enrollment metric standpoint, the study tracked behind projected milestones at a time in 
the study at which we had anticipated increasing enrollment.  After extensive discussion with our 
site principal investigators and their study teams, the decreased pace of enrollment was attributed 
to the FDA approval of Mavyret™ (AbbVie Glecaprevir/Pibrentasvir or G/P).  G/P was approved 
on August 4, 2017 for the treatment of persons with chronic HCV infection including all patients 
who are eligible for the PRIORITIZE study.  Importantly, the wholesale acquisition cost (WAC) 

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of this regimen is markedly less (1/3rd) than that of other HCV drug regimens like Harvoni®.   
Further, most patients who do not have cirrhosis (the majority of the US population presenting for 
treatment) are eligible to be treated with Mavyret™ for 8 weeks (WAC $26,400 per course).  From 
the time Mavyret™ was approved many payors, particularly Medicaid plans, changed their drug 
formularies to make Mavyret™ the preferred regimen. In addition, Mavyret was anticipated to 
replace regimen V, which would be withdrawn from the US market. 
Based on these considerations, the PRIORITIZE Steering Committee discontinued new patients 
from being randomized to regimen V and proposed to end active enrollment of new participants in 
the PRIORITIZE study once an estimated 1228 patients combined between the regimens studied 
were dosed. 
 
 
1.2 Safety Analysis/Stopping Rule 
The original intent of the interim safety analysis was to screen for any safety signals that might 
warrant discontinuation of assigning enrollees to one of the treatment regimens.  The interim safety 
analysis was removed from the protocol because that original purpose was rendered obsolete when 
it became clear that, by meeting the recruitment targets and milestones, enrollment would be 
completed before the results of the interim safety analysis could become available.  The other 
alternative, pausing recruitment to allow time for the interim safety analysis, would have prevented 
recruitment from reaching its desired target.  Lastly, each of the drugs being tested is a FDA-
approved drug regimen that is being used per label in indicated populations (during study design 
drug Z had not been approved and label indication had not been fully known). 
 
   
1.3 VA Consortium 
 After extensive discussions and delays, the VA consortium elected not to participate. 
 
1.4 Impact of Amendment on Design and Randomization 
 
The shift in demographics and influence of market forces on enrollment has important implications 
for current study design. First, we were (in 2014) anticipating a cirrhosis cohort of 625 patients per 
arm, which is now unrealistic and not reflective of current and future treatment populations. 
Second, we will have a much greater % of Blacks and treatment naive in our cohort, which is 
advantageous since these were important subgroups pre-specified in our data analysis plan. Thus, 
although we will lose precision and power for inferences regarding the cirrhotic sub-population, 
we will maintain or gain precision and power for inferences about the sub-populations that are 
increasing in prevalence.   
 
2. BACKGROUND and INTRODUCTION 
 
HCV is a devastating disease that impacts millions of Americans and contributes to impaired quality of 
life, morbidity, and premature death. HCV is curable with antiviral therapy, but only a minority of 
patients have been diagnosed and, of those, only a fraction have been offered treatment due to the difficult 
side effects of interferon-containing regimens. In 2014, the first all-oral HCV regimens were approved, 
marking a dramatic shift in treatment efficacy and tolerability. As we enter a new era of well-tolerated 

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therapies with high cure rates, we have a unique opportunity to begin to eradicate this chronic infection. 
However, as these all-oral therapies are introduced into practice, significant gaps in current evidence and 
high cost of treatment are impacting treatment choices and access to these medications.  To narrow the 
evidence gaps, we propose a randomized, pragmatic clinical trial to compare the effectiveness of all-oral 
therapies to better understand the real-world efficacy and outcomes that matter most to patients and 
stakeholders.  
 
2.1 Extent of HCV 
It is estimated between 2% and 3% of the global population is infected with HCV, corresponding to 
approximately 130 to 170 million individuals.1,2,3,4 In the United States (US), 3 to 4 million people are 
estimated to be infected, but no US survey has included institutionalized, incarcerated, or homeless 
individuals – populations with a high rate of HCV infection. Table 1 shows estimated rates in these 
populations.   The prevalence of HCV in the US also shows marked 
gender, racial, and socioeconomic disparities. The 
US Preventive Services Task Force now recommends 
that Americans born between 1945 and 1965 (baby 
boomer birth cohort) undergo one-time screening for 
HCV infection to help identify individuals unaware 
of their chronic infection.6 Thus, it is estimated that a 
large number of chronically infected adults will be 
identified in the next few years. Coupled with the 
advent of safer and more effective HCV treatments, 
this will lead to an influx of patients seeking anti-
viral therapy, most of whom do not represent the 
“traditional” patients (healthy, Caucasian, male, 
minimal co-morbidities) studied in phase III clinical 
trials. For example, a high prevalence of HCV 
infection, 14%, is found in male non-Hispanic Black 
between the ages of 40-50, compared to 6% of male 
non-Hispanic whites in the same age group. The 
PRIORITIZE trial will enroll a more representative 
US population of HCV-infected people. 
 
2.2 Impact of HCV and Cure  
In the US, chronic HCV is the most common cause of liver disease and is responsible for at least 15,000 
deaths annually and will continue to increase over the next few decades.7,8 Despite what is thought to be a 
slow progression to cirrhosis, HCV-related mortality due to liver failure and liver cancer has increased 
substantially since 1995, especially in persons age 45 and older with the greatest increase in males and 
non-Hispanic blacks.9 It has now become an important cause of premature mortality due to the relatively 
young age of those dying from HCV-related causes.10 In addition to liver disease burden, chronic HCV 
impacts wellbeing and health-related quality of life with the most profound impairments in physical 
activity, energy, and vitality.11 The main goal of HCV treatment is to eradicate HCV from the liver and 
blood thereby preventing progressive liver disease as well as the potential for transmission. Treatment 
effectiveness is measured by the sustained viral response rate (SVR), defined by the proportion of patients 
with undetectable HCV RNA in the blood 12 weeks after completing a course of treatment (SVR12).12 
SVR, analogous to cure of HCV infection, is associated with reduced risk of liver cancer, histologic 
Table 1: HCV Prevalence Rates5 
 
US population 
2% 
Baby Boomer generation (born 
1945-1965) 
3.25%  
Injection drug use > 10yrs 
90% 
Injection drug use < 10yrs 
66% 
Homeless persons 
19 to 
69% 
Prisoners 
29% 
Individuals with mental illness 
20% 
Black American men (age 40-50 
yrs) 
14% 

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reversal of liver fibrosis, decreased comorbidities, and reduced risk of liver-related death.13 A recent 
study of 21,000 U.S Veterans found that SVR was associated with a substantial decrease in all-cause 
mortality, even in those without evidence of cirrhosis suggesting an impact on non-liver related 
comorbidities (heart disease, diabetes, non-liver related cancers) presumably due to the impact of 
eliminating a chronic inflammatory disease.14 In addition, SVR is associated with improvement in patient-
reported quality of life (QOL) and fatigue, one of the most commonly reported systemic HCV-associated 
symptoms.15 However, no data exist on improvements in other commonly reported systemic symptoms 
(e.g., sleep disturbance, achiness, irritability).16 The improvement with SVR in morbidity, quality of life, 
fatigue and mortality presents a strong argument to provide treatment of all patients infected with HCV, 
regardless of degree of liver fibrosis. However, most of this data has been generated with interferon-
containing regimens, and the lack of comparable data with direct-acting antivirals related to persistence of 
SVR, impact on patient-reported outcomes (PROs), and long-term treatment benefits and harms remain 
important gaps for all stakeholders that will be addressed in PRIORITIZE. 
 
2.3 Gaps in Evidence 
Important patient groups underrepresented in HCV clinical trials include Black Americans, older adults 
(> age 65), persons with active drug and alcohol use or mental illness, and patients with multiple co-
morbidities. The generalizability of results to these populations is therefore unknown. In a recent phase III 
trial evaluating HARVONI® (ION-4)17, the SVR for Black American participants was 10% lower than 
for other participants (89% vs. 99%) raising new concerns about this high-prevalence group.  All phase III 
studies included patients ages 18-70 (very few above > 65) and, as such, the results may not be 
generalizable to older age groups. Also relevant is the exclusion from clinical trials of patients with 
histories of drug or alcohol abuse or mental health disturbances due to concern about safety and 
adherence to the protocol. Over half of patients infected with HCV suffer from drug and alcohol abuse 
and/or mental health disturbances.18,19 Now that treatment regimens are interferon-free and better 
tolerated, these patients will be seeking treatment, yet the harms and benefits of these therapies for them 
remain completely unknown. Data regarding the effectiveness of new treatments in these and other 
patient groups is critical to inform the use of these regimens in clinical practice, particularly given the 
high financial cost of the regimens and the need to efficiently allocate resources. Important questions 
must be addressed to allow patients and clinicians to make the best treatment decisions: What is the SVR 
rate in a population of diverse patients and does SVR equal cure? What are the side effects for these 
regimens in sicker populations or those with comorbid psychiatric and substance use disorders? How do 
lower adherence rates impact SVR?   
When the first two oral protease inhibitors (boceprevir and telaprevir) were introduced into clinical 
practice, the risk of severe adverse events approximately tripled over that seen in Phase III trials.20,21 As 
noted in Table 2, real-world cure rates from usual care are often substantially lower than predicted by 
Phase III studies, especially in treatment-experienced patients with cirrhosis. 22,23,24  
 
Table 2. Comparison of Sustained Viral Response in Phase III Studies and in Usual Care Settings 
Treatment regimen 
Phase III studies (SVR) 
Usual Care (SVR) 
PEG-IFN + RBV + Protease Inhibitor 
70-75% 
43-60% 
PEG-IFN + RBV + Sofosbuvir 
90% 
80%25 
Sofosbuvir + RBV 
90% 
69%26 
Sofosbuvir + Simeprevir + RBV 
94% 
88%27 
PEG-IFN= pegylated interferon, RBV=ribavirin, SVR= sustained viral response rate 

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Dr. Jodi Segal and colleagues performed a systematic review of the oral regimens during the planning 
stage of this application.28    None of the Phase III trials had active comparator groups; instead, these 
regimens were compared to historical control groups and compared within the trials to regimens modified 
by the addition or absence of ribavirin. A summary of SVR12 and confidence intervals from these Phase 
III trials is shown below. We illustrate here, simply, the wide and overlapping confidence intervals across 
regimens. 
 
 
Several federally funded agencies and institutes have recognized the issues associated with these critical 
evidence gaps in HCV.   In late 2014, the Patient-Centered Outcomes Research Institute (PCORI) 
convened a large stakeholder engagement meeting that included representatives from the pharmaceutical 
industry, patient advocacy groups, payers, patients and providers and concluded “data are particularly 
needed on longer-term effectiveness of new therapies, on the comparative effectiveness of these therapies, 
and on a set of treatment outcomes relevant to patients, including symptoms of infection, drug side effects, 
treatment adherence, and quality of life”.  The Agency for Healthcare Research and Quality identified as 
top-tier research needs effectiveness designs to understand real-world effects of antiviral regimens in a 
broader spectrum of patients, such as those with co-morbid conditions and cirrhosis. 29 The Center for 
Evidence-based Policy at Oregon Health & Science University also identified many evidence gaps in the 
current studies that support treatment guidelines for HCV and concluded: “Policymakers can ask the NIH 
to fund and the FDA to demand truly comparative studies on this [Sofosbuvir] and other newer drugs for 
hepatitis C. Current trials do not answer the question of which therapy is best for which patient at which 
point in time during the disease course. Studies of these drugs should include populations that 
approximate the characteristics of publicly insured patients including race, stage of disease, prior 
treatment history, and comorbid medical and behavioral conditions.”30 As highlighted in the 2015 report 
from the Institute for Clinical and Economic Review (ICER),31 “for the patient population with cirrhosis, 
the confidence intervals are wide for all four of the new DAA combinations. Pragmatic randomized trials 
in real-world settings will be essential for evaluating the comparative effectiveness of the combination 
DAA therapies and to see if the SVR achieved in clinical trials and long-term cure rates are replicated in 
usual care settings.”  Furthermore, since these data come from single arm studies, in which everyone 
enrolled in a trial receives the experimental therapy, selection bias may explain some of the observed 
differences among the SVR point estimates.  Lastly, there also exist significant gaps in our understanding 

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of baseline viral resistance and how it impacts treatment outcomes.  While almost every new therapy has 
known naturally occurring resistance, the clinical significance is poorly understood. Many of the current 
guidelines and drug labels include consideration for resistance testing prior to using oral therapies, but 
only one regimen recently approved from Merck has clear guidance on how to adjust therapy based on the 
presence or absence of resistant viral variants.32, 33, 34 
 
Significance 
The absence of comparative effectiveness data has led to restricted access to treatment as well as to payer-
mandated use of specific regimens based on negotiated pricing. Patients with mild liver disease and those 
with recent alcohol or drug use are often excluded from treatment plans. The HCV marketplace has 
evolved in a manner that may hamper a simple, randomized, controlled pragmatic trial utilizing 
commercial drug supply.  The limitations to treating patients in the real world are based on two ill-
conceived principles: 1) Restrictions to the formulary for which drugs will be accessible under specific 
insurance plans and 2) Restrictions about which patients can be treated based upon the severity of liver 
disease or other more arbitrary factors such as history of substance abuse.  Despite objections by many, 
including the AASLD/IDSA Guidelines Panel and The President’s Advisory Council on HIV/AIDS, these 
have been imposed, without scientific rationale, solely to minimize cost to payers.  Indeed, the 
preponderance of current evidence suggests that almost all patients with hepatitis C would benefit from 
treatment, with minimal harms and regardless of severity of liver disease.  Furthermore, in clinical 
practice there appears to be treatments that would be better than others for certain subpopulations with 
comorbidities, yet by happenstance of socioeconomic status or geography, these medications are beyond 
the reach for many persons infected with hepatitis C. Thus, the choice of treatment and regimen has been 
removed from key stakeholders (patients and physicians). Also, important patient groups have been 
underrepresented in HCV clinical trials, including Black Americans, older adults, and persons with active 
substance use or mental illness, especially those with advanced liver disease.  Through active engagement 
with HCV patient advocacy organizations and HCV patient partners, we learned that the top-ranked 
priorities to inform decisions about HCV treatment include: likelihood of being cured, out-of-pocket costs 
of therapy, drug side effects and other short and long-term treatment harms and benefits. Our pragmatic 
clinical trial is specifically designed to address these important study outcomes identified by multiple 
stakeholders. Importantly, the study will provide data on underrepresented populations (Black Americans, 
individuals with multiple comorbidities, low-income groups, older adults age > 65, individuals with 
substance use and mental health disorders) and subgroups (genotype 1a vs 1b) so the results of this study 
will be applicable to most clinical settings. We selected this subgroup because patients with cirrhosis have 
been under-represented in clinical trials (typically <15% of trial population) but comprise up to 50% of 
those who will be considering antiviral therapy. Moreover, those with cirrhosis are potentially more 
susceptible to short and long-term harms from the medications and have shown the largest difference in 
SVR when comparing real-world observational data with phase III trial results.35 Recent post-approval 
safety concerns for both regimen H (cardiotoxicity with Amiodarone) and V (hepatotoxicity in advanced 
cirrhosis), highlight the critical need for safety data in larger, more diverse populations. Thus, our study 
will provide valuable information for all patients considering HCV treatment including this vulnerable 
subgroup (cirrhosis). This proposed study of new oral regimens is very responsive to this PFA and will 
answer critical questions regarding: 1) rates of patients being cured and durability of cure, 2) drug side 
effects and other short and long-term treatment harms, and 3) patient-centered clinical benefits (changes 
in patient-reported HCV symptoms) and short and long-term liver disease progression or regression.  
The PRIORITIZE investigators have had extensive discussions with pharmaceutical manufacturers, 
payers, and pharmacy benefits managers to develop mechanisms that would ensure randomized access to 
medications.  Unfortunately, most pharmaceutical sponsors and payers have little interest or incentive to 
develop evidence to refute the current restrictions. Market leaders are content with the status quo that 

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guarantees them garish profits and payers continue to control their costs, largely unchallenged by a 
disenfranchised patient population, which has been denied a voice in this discussion. Payers and 
pharmacy benefits managers have significant financial disincentives to randomize across all regimens, 
due to contractual discounts most have received to exclusively use one regimen over others.  Similarly, 
despite enthusiastic and significant financial support for our observational cohort study (HCV-TARGET), 
pharmaceutical companies have been reluctant to support a randomized, controlled trial that could 
influence future policy and guideline decisions, and potentially threaten their market share/profits. Given 
these implications, Gilead did not agree to supply free study drug.  Fortunately, AbbVie and Merck 
continue to support this trial, and the current design takes advantage of “free drug” to achieve our goal of 
a randomized, controlled trial.  The decision of some pharmaceutical companies not to provide access to 
drugs for the trial underscores the importance of independent organizations in the effort to conduct 
comparative effectiveness studies. Indeed, we believe it is incumbent upon investigators and patient-
centered research funding sources, therefore, to develop sound evidence to support or refute the current 
status of HCV treatment in order to optimize care for patients with chronic hepatitis C.   
 
Impact on clinical practice: In 2011, we established a large, real world, observational treatment registry 
called HCV-TARGET to follow patients prescribed HCV therapy at multiple centers in the U.S., Canada, 
and Europe.  Although HCV-TARGET continues to produce high-quality observational cohort data to 
rapidly inform clinical guidelines and enhance treatment safety and efficacy, we strongly believe that a 
well-designed randomized controlled trial is critical to impact practice and policy at the level needed to 
improve patient-centered outcomes for all HCV patient populations. These data will be instrumental for 
patients, physicians, payers and policy makers to make sound and rational treatment decisions. 
Comparative data from this study can inform clinical, policy and insurance guidelines so that cost is not 
used as the sole criterion to evaluate the interventions. Most importantly, the data can help patients and 
physicians make more informed treatment decisions. Through HCV-TARGET’s existing partnership with 
the FDA, the FDA can use the data to monitor and act on differences in safety from what was reported 
during phase III trials or expand label indications. HCV-TARGET data has already been instrumental in 
identifying new safety signals (cardiovascular risk in patients taking Sofosbuvir), drug-drug interactions 
(proton pump inhibitors and Ledipasvir), and expanding drug labels (expansion of Simeprevir label to 
include all oral combination with Sofosbuvir). Our stakeholder organizations also will use their 
established relationships to share the study findings with state and federal representatives that influence 
public policy and coverage decisions. Further descriptions for dissemination of study results are detailed 
in the Dissemination and Implementation section. 
Patient-centeredness: PCORI was established from the Affordable Care Act Legislation to address gaps 
in health care evidence that are important to patients, their families, and their providers.  In response to 
the PCORI HCV Stakeholder meeting detailed earlier, a major HCV-specific funding initiative (PFA) was 
used to support this study.  Core principles in PCORI funding are the inclusion of patient stakeholders 
(including their families, advocacy groups and 
providers) in the development, implementation, 
and dissemination of PCORI funded research.  
To that end, this study was developed over 1.2 
yrs through active engagement with HCV 
patient advocacy organizations, HCV patient 
partners, and HCV providers among other HCV 
stakeholders.  First, our investigative team 
conducted 45 interviews to discuss HCV 
treatment with patients infected with HCV who 
represent a diverse population (age range 35-72 
with a mean age of 55, 58% male, 56% 
treatment naïve, 36% with cirrhosis, 20% Black American, 24% uninsured). Participants were asked to 
TABLE 3 
Priority 
Rank 
HCV PEG Ranking of  
Reported Informational Needs  
1st 
Chance of cure 
2nd 
Total out of pocket cost of treatment 
3rd 
Treatment side effects 
4th 
Harm to my liver 
5th 
Harm to my other medical conditions  
6th 
Interference with functional status & QOL 
7th 
Long-term survival if cured 
8th 
Benefits to my other medical conditions 
9th 
Risk or harm if I do not do treatment 
10th 
Benefits to my functional status & QOL 

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free-list all information they needed to make an informed decision about starting HCV treatment or 
choosing between hypothetical regimens. These interviews helped us understand what kind of 
information was critical to patient decision-making. Next, we asked our 9-member HCV Patient 
Engagement Group (HCV-PEG) to prioritize these informational needs, all considered harms or benefits 
to the patients (see Table 3). These HCV-PEG priority rankings directly informed the selection of patient-
centered outcomes we intend to evaluate in this trial.  We learned that the top-ranked priorities to 
inform decisions about HCV treatment include: likelihood of being cured, out-of-pocket costs of 
therapy, drug side effects and other short and long-term treatment harms and benefits. This trial is 
specifically designed to address these important study outcomes identified by multiple stakeholders.  
Importantly, the study will provide data on underrepresented populations (Black Americans, individuals 
with multiple comorbidities, low-income groups, older adults age > 65, individuals with substance use 
and mental health disorders) and subgroups (genotype 1a vs 1b) so the results of this study will be 
applicable to most clinical settings. We selected this subgroup because patients with cirrhosis have been 
under-represented in clinical trials (typically <15% of trial population) but comprise up to 50% of those 
who will be considering antiviral therapy. Moreover, those with cirrhosis are potentially more susceptible 
to short and long-term harms from the medications and have shown the largest difference in SVR when 
comparing real-world observational data with phase III trial results.36 Recent post-approval safety 
concerns for both regimen H (cardiotoxicity with Amiodarone) and V (hepatotoxicity in advanced, 
decompensated cirrhosis), highlight the critical need for safety data in larger, more diverse populations. 
Thus, our study will provide valuable information for all patients considering HCV treatment, including 
the cirrhotic subgroup.  
This proposed study will answer critical questions important to patients with HCV regarding: 1) rates of 
patients being cured and durability of cure, 2) drug side effects and other short and long-term treatment 
harms, and 3) patient-centered clinical benefits (changes in patient-reported HCV symptoms) and short 
and long-term liver disease progression or regression. 
3.  PURPOSE AND SIGNIFICANCE 
 
Phase 1 
The original purpose of this study was to learn whether oral regimens for treating HCV worked equally 
well under real-world conditions when delivered to a broad spectrum of patients.  The proposed study 
utilized a randomized pragmatic clinical trial design to compare the effectiveness of standard of care 
medications for HCV Genotype 1 (HARVONI®-Regimen H, Viekira Pak/Viekira XR™- Regimen V, and 
ZepatierTM- Regimen Z). The study collected and analyzed comprehensive data to address the multi-
faceted outcomes and measures that HCV patients and stakeholders identified as being most important 
when making HCV treatment decisions.  
 
Phase 2 (As of January 2017 Amendment and May 2018) 
The purpose of this study is to learn whether oral regimens for treating HCV work equally well under 
real-world conditions when delivered to a broad spectrum of patients.  The amended study will utilize a 
randomized pragmatic clinical trial design to compare the effectiveness of standard of care medications 
for HCV Genotype 1 (HARVONI®-Regimen H and ZepatierTM- Regimen Z). The study will collect and 
analyze comprehensive data to address the multi-faceted outcomes and measures that HCV patients and 
stakeholders identified as being most important when making HCV treatment decisions.  In consideration 
that there are no changes to safety or efficacy of ViekiraTM, participants randomized to ViekiraTM in Phase 
1 of this study will remain on ViekiraTM and continue to be followed. 
 

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4.  STUDY DESIGN 
The proposed study will compare the effectiveness of approved, HCV Genotype 1 treatment regimens to 
learn whether they work equally well under real-world conditions.  Using methods developed in HCV-
TARGET to collect clinical data on safety and effectiveness, patients receiving HCV therapy in 
community and academic clinics will be offered the opportunity to consent to be randomly assigned to 
Regimen H, V, (Phase 1) or Z, and then observed for outcomes. Once randomized, all medical care, 
laboratory testing, and any disease or side effect management will be assumed by usual care conditions, in 
keeping with pragmatic design principles. The collection of patient reported outcomes (PRO) surveys is 
atypical in standard clinical care; therefore, to preserve the usual clinical conditions and pragmatic design 
principles, the PRIORITIZE PRO surveys will be administered through the use of technology /devices 
outside of clinical interactions (web-based and phone based surveys). We received extensive patient and 
stakeholder input in designing this trial to yield results that will be useful to patients, clinicians, payers, 
and policy makers when making decisions about treatment. These study aims directly target the majority 
of informational needs and evidence gaps identified by HCV patients, clinicians, multiple stakeholders, 
the Agency for Healthcare Research and Quality CER systematic review, and PCORI’s Working Group 
on HCV. 
 
Phase 1 
We originally proposed a pragmatic, open-label, randomized study of approximately 3750 participants 
that will allow evaluation of HARVONI®, Viekira Pak/Viekira XR™ and ZepatierTM. The proposed study 
design assumed HARVONI® (H) would only be available via commercial payer while Viekira 
Pak/Viekira XR™ (V) and Zepatier™ (Z) would be provided by the manufacturers. AbbVie and Merck 
agreed to provide free drug and to set up drug delivery protocols with our centralized pharmacy.  
Additionally, Merck provided free NS5a (Resistance Associated Polymorphisms) RAP testing for all 
patients participating in the study. The results of the RAP testing for genotype 1a participants randomized 
to ZEPATIERTM were used clinically to determine treatment regimen; with those without RAPs (approx. 
90%) were provided 12 weeks of Z, while those with RAPs were provided 16 wks + RBV (per FDA label 
recommendations). NS5A RAP testing for patients on other regimens were used for research purposes 
only. 
 
Phase 2 (Amendment as of January 2017 and May 2018) 
The second phase of this study will follow the amended protocol and will continue as a pragmatic, open-
label, randomized study of n= 1700 (estimated) consented participants that will allow evaluation of at 
least 1228 patients who begin treatment with HARVONI® and ZepatierTM.  The N assumes 
enrollment/randomization of 154 subjects to ViekiraTM in Phase 1 (146 began treatment), at least 707 
subjects randomized to Harvoni® with at least 375 starting therapy, and up to 730 subjects randomized 
to ZepatierTM to achieve at least 707 starting therapy.  The proposed study design assumes HARVONI® 
(H) will only be available via commercial payer while Zepatier™ (Z) will be provided by the 
manufacturer. Merck has agreed to provide free drug and has set up drug delivery protocols with our 
centralized pharmacy.  Additionally, Merck will provide free NS5 (Resistance Associated 
Polymorphisms) RAP testing for all patients participating in the study. The results of the RAP testing for 
genotype 1a participants randomized to ZEPATIERTM will be used clinically to determine treatment 
regimen; those without RAPs (approx. 90%) will be provided 12 weeks of Z, while those with RAPs will 
be offered 16 wks + RBV (per FDA label recommendations). NS5 RAP testing for patients on other 
regimens will be used for research purposes only. 
 
Sample Size Rationale 
For the primary analyses comparing regimens H and Z, the ITT analysis will be modified to use causal 
inference methods to address potential selection biases induced by the Harvoni arm of the study   --due to 

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Harvoni’s arduous prior authorization hurdles such as requirement for negative urine toxicology tests and 
denial of persons with minimal fibrosis.  In total, we anticipate that about N = 1700 participants will be 
consented and enrolled, with at least 1228 being both successfully randomized and successfully starting 
treatment as follows:  1228 = (707 to Z) + (375 to H) + (146 to V).   Due to the discontinuation of 
assignments to regimen V, only 154 enrollees were assigned to regimen V.  Of those, only 146 started V 
regimen treatment.  While equal numbers of participants are assigned by randomization to H and Z, the 
sample size expectations take into account the higher rate of failure to start treatment that is inherent for 
those assigned to regimen H (see Section 13. Statistical Analysis Strategy).   
 
 
The Primary Aims are to characterize and compare regimens H, V (Phase 1), and Z on the following 
patient-centered outcomes: 
   1) treatment effectiveness (i.e., sustained viral response 12 weeks post-treatment, “SVR12”)      
   2) drug side effects. (both patient reported and medical record abstracted) 
   3) efficacy of ZEPATIERTM with RBV for 16 weeks when used in G1A patients with baseline RAPs 
The Secondary Aims are to characterize and compare regimens H, V (Phase 1), and Z on the following 
outcomes:  
   3) treatment adherence and persistence;  
   4) amelioration of systemic HCV-associated symptoms post-treatment;  
   5) post-treatment progression and regression of liver disease  
   6) persistence of viral cure for 3 years post- treatment; and  
   7) functional status on treatment and after treatment. 
8) impact of baseline NS5A RAPs on treatment outcomes 
     
The Expected Results   
   1) In clinical practice populations, the regimens will have similar cure rates and durability of cure. 
 2) The frequency and severity of drug side effects may be higher for regimens that are more likely to 
require concomitant use of ribavirin, V (Phase 1) more than H or Z   
   3) Medication non-adherence may be greater for regimens that have higher pill burden and more 
frequent side effects from DAA alone or from requirement for concomitant use of ribavirin, V more 
than H or Z 
   4) After achieving SVR, improvements will be evident in measures of clinical outcomes (incident 
cancer, liver decompensation, and/or diabetes) and systemic HCV symptoms. 
   5) After achieving SVR, improvements will be evident in measures of liver disease (fibrosis and 
progression to cirrhosis). 
   6) After achieving SVR, the incidence of new or latent HCV infection will be extremely rare. 
   7) After achieving SVR, improvements will be evident in functional status. 
   8) SVR in genotype 1a patients with RAPs will be similar regardless of previous treatment experience 
and or cirrhosis status 
Appropriateness of a Pragmatic Design for this Study 
The proposed study will compare the effectiveness of 3 approved HCV treatment regimens to learn 
whether they work equally well under real-world conditions.  Using methods developed in to collect 
clinical data on safety and effectiveness, patients receiving HCV therapy in community and academic 
clinics will be offered the opportunity to consent to be randomly assigned to Regimen H, V (Phase 1), or 
Z and then observed for outcomes. Once randomized, all medical care, laboratory testing, and any disease 
or side effect management will be assumed by usual care conditions, in keeping with pragmatic design 
principles.   A pragmatic-explanatory continuum indicatory summary (PRECIS) exercise was undertaken; 
we found our proposed study to be highly pragmatic.   

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PRECIS Summary: A. The participants will receive the 
standard clinical care that is delivered in their respective 
center for the treatment of HCV; the clinical 
management, visit schedule, and safety and efficacy 
lab evaluation schedule is not defined by the protocol.  
B. All data related to that standard clinical care will be 
abstracted from submitted medical records (clinic notes, 
telephone notes, safety and efficacy labs) by a specially 
trained group of chart data abstractors. C. The collection 
of patient reported outcomes (PRO) surveys is atypical in 
standard clinical care; therefore, to preserve the usual 
clinical conditions, PRO surveys will be administered 
through the use of technology / devices outside of 
clinical interactions (web-based and phone based 
surveys). The Yellow wheel plots indicate design options 
that move away from the Pragmatic pole toward the 
explanatory design pole. 
 
Study design: For a broad population of individuals seeking treatment for HCV genotype 1, we propose a 
multi-center, three-arm, randomized pragmatic clinical trial to compare Regimen H (n  up to 730 
randomized to achieve at least 375 dosed) Ledipasvir / Sofosbuvir (HARVONI®, Gilead Sciences) vs 
Regimen V (up to 170) Paritaprevir/ritonavir/ Ombitasvir + Dasabuvir +/- ribavirin (Viekira Pak/Viekira 
XR™, AbbVie) (Phase I) vs Regimen Z (n > up to 730 randomized to achieve at least 707 dosed) 
Elbasvir/Grazoprevir (ZEPATIERTMMerck & Co). Using the HCV-TARGET infrastructure for data 
collection with the addition of patient surveys for collection of patient-reported outcomes and a validated 
model for impact on liver disease progression, the study is open-label for both participants and providers. 
Study population and proposed inclusion and exclusion criteria: All patients infected with HCV genotype 
1 being considered for HCV therapy will be invited to consent to have their HCV treatment and outcomes 
observed.   Among the patients who consent to be observed, most will meet inclusion criteria to 
participate in The Randomized Cohort:  a) in the provider’s opinion, the patient can begin treatment with 
regimen H, V(Phase I), or Z without significant risk or harm and b) the patient is willing to consent to 
have their HCV treatment assigned randomly. We anticipate some participants (up to 21%) may not 
receive treatment with their randomized regimen. These 5%-10% include participants who decide to 
choose a different regimen after being randomized and participants who cannot gain access to the 
commercially available regimen (HARVONI®) when assigned. Randomization will be stratified by 
cirrhosis status (based on biopsy or markers of cirrhosis) and by subtype 1a or 1b.  Stratification by 
cirrhosis is important in assessing SVR and clinical outcomes and fibrosis progression/regression while 
stratification by subtype is important as this impacts the need for RBV, adherence and tolerance.  
Genotype 1a participants randomized to ZEPATIERTM will have their baseline NS5a RAP sample tested 
prior to dispensing drug.  If a baseline RAP at amino acid positions 28, 30, 31, and/or 93 is identified, 
those genotype 1a patients will be offered ZEPATIERTM for 16 wks + RBV, consistent with the FDA label 
recommendation. 
 
Our approach will build on the HCV-TARGET infrastructure for data collection with the addition of 
patient surveys for collection of patient-reported outcomes and a validated model for impact on liver 
disease progression. PRIORITIZE will be implemented using the fully functional HCV-TARGET 
infrastructure and committed clinical sites. HCV-TARGET is rooted in the collaborative network 
developed through the National Institutes of Health’s Clinical and Translational Science Award program. 
The registry follows patients treated for chronic HCV to rapidly inform strategies for better management 
of populations underrepresented in clinical trials and to identify and remediate educational gaps relative to 
PrimaryAnalysis
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exper se
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Par cipant
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Prac
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Adherence
Outcomes
Follow-up
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Flexibilityof
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HCVPragma cPRECIS:ThePRIORITIZEStudy

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Page 15 
treatment guidelines and adverse event management.  HCV-TARGET has grown into an extensive 
partnership between 42 academic and 14 community centers (in 31 states, Puerto Rico, Canada and 
Europe), the pharmaceutical industry, HCV community advocates and the FDA. HCV-TARGET 
developed standardized, centralized chart data abstraction methods along with detailed data monitoring to 
increase the efficiency and quality of an observational registry while also minimizing costs typically 
associated with performing post-marketing clinical research.  
 
4.1 Study Infrastructures and Centers 
The PRIORITIZE study will be led by co-PIs at three universities: David R. Nelson, M.D., at the 
University of Florida (UF- Clinical Coordinating Center); Michael Fried, M.D. & Donna Evon, Ph.D. at 
the University of North Carolina (UNC- Data Coordinating Center); and Mark Sulkowski, M.D., at Johns 
Hopkins University. Additional experts at each of the three universities as well as the University of 
Michigan (fibrosis progression modeling) will contribute to the project. In addition, the PRIORITIZE 
study will utilize the operational infrastructure of the existing HCV-TARGET Research Network.  UF 
serves as the Clinical Coordinating Center (CCC) and UNC serves as the Data Coordinating Center 
(DCC) for HCV-TARGET; they will perform the same roles for PRIORITIZE.  
PRIORITIZE will be implemented using the fully functional HCV-TARGET infrastructure and up to 45 
committed clinical HCV-TARGET sites.  HCV-TARGET developed standardized, centralized chart data 
abstraction methods along with detailed data monitoring to increase the efficiency and quality of an 
observational registry while also minimizing costs typically associated with performing post-marketing 
clinical research.   The HCV-TARGET sites were selected for their historical enrollment patterns, 
contributions to the network and based on the HCV drug prescription market analysis that was used to 
identify centers with high approval percentage for HARVONI® prescription.   
5.  SUBJECT POPULATION 
5.1 Inclusion criteria 
• 
HCV Genotype 1a or 1b, Adult patients (age 18 or older) who are being prescribed HCV 
treatment outside of a clinical trial and, in the provider’s opinion, can begin treatment with 
regimen H, V (Phase 1), or Z 
5.2 Exclusion criteria 
• 
Inability to provide written informed consent  
• 
HARVONI® is not a covered drug on benefits formulary 
• 
Current or historical evidence of hepatic decompensation (variceal bleeding, hepatic 
encephalopathy, or ascites).  In the event potential participant is post-transplant, no 
evidence of hepatic decompensation since transplantation 
• 
Child Pugh (CTP) B or C Cirrhosis (documented CTP calculation is required) 
• 
Pregnant or breastfeeding women 
 
6. HCV-TREATMENT PRODUCTS 
6.1 Investigational New Drug (IND) Exemption 
Given that the study drug regimens used in PRIORITIZE are marketed drugs at the time included in the 
randomization schedule and in accordance with 21 CFR 312.2(b)(1), PRIORITIZE will be IND 
exempted.  While this exemption from the standard methods of providing clinical trial data to the FDA is 

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Page 16 
expected, a less traditional but perhaps more efficient communication of the details of the clinical trial 
between the FDA and PRIORITIZE will be employed.  Via a memorandum of understanding, the 
research team has partnered with FDA to share data on how newly approved therapies for hepatitis C are 
used and managed in routine practice.  Through this unique partnership, research members will be able to 
evaluate how marketed drugs are used and managed in routine practice.  Through this distinctive 
partnership, PRIORITIZE will continue to disseminate important safety, efficacy, and general 
characteristics of the HCV patient population to the FDA and drug manufacturers from the PRIORITIZE 
trial. 
 
6.2 Provision of HCV drug 
In late July 2016, the FDA approved a once daily dosing formulation of Paritaprevir/ritonavir/ Ombitasvir 
+ Dasabuvir, Viekira XR.  Viekira XRTM was approved by the FDA for use in the HCV Genotype 1 
population.  Patients participating in PRIORITIZE Phase I will have either Viekira PakTM or Viekira 
XRTM made available for treatment to arm V of the study.  While subjects will no longer be randomized 
to ViekiraTM during Phase 2 of this study, participants randomized to Viekira in Phase 1 of this study will 
be maintained on the ViekiraTM dosing formulation to which they were initially dispensed.  
 
Commercially labeled HCV product for Viekira Pak/Viekira XRTM(Phase 1) and ZepatierTM +/-RBV will 
be provided free of charge to PRIORITIZE study participants randomized in non-VA sites to those 
regimens by AbbVie and Merck. Participants randomized to HARVONI® will have their respective HCV 
treatment prescription processed and filled through standard payer processes.  
 
6.3 Rationale Provision of HCV drug 
PRIORITIZE is a pragmatic study with HCV-treatment duration, addition of ribavirin to the treatment 
regimen and treatment/side effect management all decided at the discretion of the local provider 
according to the site standard of care and is not defined by this protocol. Given the pragmatic design of 
this study, ideally the randomized HCV drug would be acquired from the usual and customary clinically 
prescribed therapy sources. However, current market HCV prescribing practices in most payer systems 
have been limited by payer exclusive product contracting.  A detailed market simulation was performed in 
August 2015 to evaluate HARVONI® and Viekira PakTM prescription rejection rates of 43 current HCV-
TARGET sites including the 35 centers proposed to participate in the PRIORITIZE study.  Based on that 
analysis, there is a rejection variance depending on health care center.  The overall median rejection rate 
for HARVONI® prescription was 11% with a range of 0-26% (excluding a single outlier that had a 46% 
rejection rate) while the median rejection rate for Viekira PakTM prescriptions was 68% (range 32-91%).  
Parity between the two regimens (ability to prescribe both H and V) was evident only 10% of the time 
(range 0%- 32%). This simulation supports wide availability of HARVONI® by prescription, high 
rejection rates of prescribed Viekira PakTM and very limited ability to prescribe both drugs among HCV-
TARGET centers.  In addition, the very recent approval of ZepatierTM and lengthy contractual procedures 
for restructuring pharmacy contracts suggest that ZepatierTM will have limited uptake over the next year. 
These data demonstrate the challenging environment for a randomization design that utilizes real world 
access to each regimen and has informed our approach to develop the best possible study design.  
 
With wide availability of HARVONI® by prescription and provision of free drug from AbbVie and 
Merck to treat patients in PRIORITIZE, the cohort for enrollment into this study will be limited to 
patients whose insurance formulary has HARVONI® as a covered drug (approximately 90% of all insured 
HCV patients), except patients in the Veterans Health Affairs Administration. This will include most 
commercial payers (Aetna, Anthem, BlueCross, Cigna, Humana, and United healthcare), most PBMs 

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Page 17 
(BioPlus, CVS Caremark, EnvisionRx, Kroger Specialty Pharmacy (formerly known as TLCRx), PBM 
Prime Therapeutics), and Medicare Part D.  
 
 
Phase 2 
• 
ViekiraTM (one of the three standard of care treatments for HCV that is being studied) will be 
replaced in the market by the approval of AbbVie's next generation compound during the planned 
enrollment phase for PRIORITIZE. This has and will continue to negatively impact enrollment 
and make future data on the results for the ViekiraTM arm not relevant.  
• 
Background: Glecaprevir (ABT-493)/pibrentasvir (ABT-530) (G/P) is an all-oral, once-daily, 
ribavirin-free investigational hepatitis C virus regimen from AbbVie. Recently released phase 3 
trial data show excellent response in genotype 1 patients. Overall, 99% of non-cirrhotic patients 
reached SVR12 after 8 weeks of treatment (n = 348); 96% in those with compensated cirrhosis 
with 12 weeks of therapy. It has received “breakthrough” designation by the FDA and is expected 
to be approved in the US in summer 2017. As a result of the anticipated approval, the once daily, 
ribavirin-free G/P regimen will replace ViekiraTM in the United States and ViekiraTM will 
eventually be removed from the US market.   
• 
Given that there are no changes in the safety or efficacy of Viekira Pak/XRTM, each patient who 
has been randomized to Viekira (n=154 randomized with n=146 dosed), will complete their 
assigned regimen and remain in the study for long-term follow-up.  No further patients will be 
assigned to ViekiraTM. Further recruitment and balanced randomization to Harvoni® and 
ZepatierTM will ensure that up to 1,460 patients are randomized to those two regimens.  At the end 
of the study, the primary analyses characterizing and comparing Harvoni® and ZepatierTM will be 
based on at least 1082 patients starting treatment (375-H, 707-Z).   Of secondary importance, the 
primary analyses (descriptive) concerning Viekira will be based on the first 510 patients (up to 
170).     
 
 
6.4 Centralized Study Dispensing Specialty Pharmacy- Participants outside 
the Veterans Health Administration 
Phase 1 
A full service, experienced specialty pharmacy (Kroger) will be used as a centralized pharmacy to 
manage the HCV treatment prescriptions for participants outside of the Veterans Health Administration.  
After signing consent, patient-specific prescriptions for HARVONI®, Viekira Pak(V)/Viekira XRTM 
(Phase 1) and ZepatierTM will be submitted to the centralized specialty dispensing pharmacy to initiate an 
insurance benefit investigation. If the benefits investigation identifies HARVONI® as a covered drug on 
the respective patient formulary, the patient will be RANDOMIZED to receive either HARVONI® by 
prescription or Viekira Pak/Viekira XRTM (Phase 1) or ZepatierTM via the free drug provided by 
AbbVie/Merck (see Centralized Pharmacy Study Enrollment Process).  If the benefits investigation 
identifies any non-HARVONI® regimen as preferred, the patient will be counted as a SCREEN 
FAILURE and will not be randomized.  This patient may be offered the opportunity to be followed for 
outcomes in the observational HCV-TARGET study that runs in parallel to PRIORITIZE as an 
observational cohort. 

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Phase 2 
A full service, experienced specialty 
pharmacy (Kroger) will be used as a 
centralized pharmacy to manage the 
HCV treatment prescriptions for 
participants outside of the Veterans 
Health Administration.  After signing 
consent, patient-specific prescriptions 
for HARVONI® and ZepatierTM will be 
submitted to University of Florida and 
Kroger, the centralized specialty 
dispensing pharmacy.  Initial benefit 
assessment can be performed by the 
institution or the Kroger Specialty Pharmacy. Participants will be RANDOMIZED to receive either 
HARVONI® by prescription or ZepatierTM via the free drug provided by Merck.  If the benefits 
investigation identifies any non-HARVONI® regimen as preferred, the patient will be counted as a 
Randomization Failure and will not receive HCV treatment through this protocol.  This patient may be 
offered the opportunity to be followed for outcomes in the observational HCV-TARGET study that runs 
in parallel to PRIORITIZE as an observational cohort. 
 
Aside from free drug provided by AbbVie (Phase 1) and Merck, PRIORITIZE participants will have 
access to the full slate of services provided by specialty pharmacy to mimic as closely as possible the real-
world experience of HCV-treatment.  The centralized study pharmacy will work directly with 
PRIORITIZE patients to dispense drug and maintain drug refills, provide access to on-staff clinical 
pharmacists, and on treatment support consistent with standard specialty pharmacy practices.  
Additionally, patients randomized to receive HARVONI® which will be dispensed via the usual and 
customary clinically prescribed therapy sources, the centralized specialty pharmacy will provide to the 
sites and patients their resources to maximize third party reimbursement, coordination of prior 
authorizations and appeals, expertise in formulary overrides, and support to access drug co-payment 
cards.  Patients randomized to ZEPATIERTM will have their baseline NS5a RAP sample tested prior to 
dispensing drug.  If a baseline RAP at amino acid positions 28, 30, 31, and/or 93 is identified, those 
patients will be offered ZEPATIERTM for 16 wks + RBV, consistent with the FDA label recommendation. 
 
 
 
 
6.5 HCV Therapy Prescription Cost for Patients who are randomized to 
HARVONI® 
Patients randomized to HARVONI® will potentially have drug co-pays while those randomized to 
Viekira Pak/Viekira XRTM (Phase 1) or ZEPATIERTM-will not have a co-pay. Kroger Specialty Pharmacy 
has indicated HARVONI® therapy co-pays can range from $5-$1000, depending on insurance benefit. 
The centralized study pharmacy is providing resources to help and guide patients to obtain access to 
HARVONI® co-pay assistance cards, which reduces the co-pay to $5 and should minimize this impact.  
Although there is a co-pay disparity between the two randomized groups, because we are selecting a 
cohort of patients with HARVONI® preferred on formulary, these patients are receiving the treatment by 

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Page 19 
prescription they would have otherwise received as part of standard of care and thus also have the same 
co-pay burden they would have as part of standard of care.  We have consulted with our UF legal 
department and IRB, who concluded that the design and randomization is in compliance with the 
Common Rule.  
 
 
6.6 HCV Therapy Prescriptions for Patients who cannot have Commercial 
Product dispensed through the Centralized Specialty Pharmacy 
It is recognized that the centralized specialty pharmacy may not be able to fill all commercially acquired 
prescriptions for patients randomized to the HARVONI® arm of the study.  The centralized specialty 
pharmacy will provide the insurance benefits verification information to the study site as well as forward 
to the respective payer-approved pharmacy to complete the commercial HARVONI® product dispensing 
for HCV treatment.  That patient will continue to be followed in PRIORITIZE for all outcomes. 
 
 
6.7 HCV Therapy Prescriptions for Screen Failure and Randomization 
Failures 
The centralized specialty pharmacy will communicate back to the study site the status of patients 
submitted for the insurance benefits investigation.  For study participants who screen fail or do not begin 
treatment with their respectively randomized regimen (randomization failure), it will be at the discretion 
of the study site to determine how to proceed with treating that patient. All efforts will be made to follow 
randomization failures in PRIORITIZE.  In the event participants begin treatment with a medication other 
than H or Z, these participants may be enrolled in HCV-TARGET database to capture the treatment 
course and outcomes.  
 
7. STUDY PROCEDURES 
7.1 Informed Consent 
The protocol and informed consent documents will receive approval by the local site IRB prior to 
initiation of the study at each site.  Consent for participation in PRIORITIZE will include permission 1) to 
submit historical medical records related to patient demographics, medical/co-morbid condition history, 
prior HCV therapy and evaluation of liver disease, 2) to submit prospective medical records related to 
HCV treatment response, safety, side effects, side effect management and safety/efficacy outcomes of 
antiviral therapy; 3) for collection of patient reported symptoms and outcomes via surveys administered 
via paper, online or by telephone outside of the standard clinical interaction; 4) to be followed for HCV 
systemic symptoms, co-morbid conditions, hepatic fibrosis progression/regression and mortality for up to 
3 years after treatment outcome is determined; and 5) to share contact information to complete study 
surveys and social security number information to receive payment for survey completion.  Subject 
contact information will be used for long- term follow-up by telephone or email for any participants who 
do not return to their local site for health care follow-up up to 3 years after HCV treatment 6) to have 
blood drawn for baseline NS5a RAP testing 7) to share limited datasets with PRIORITIZE research 
partners.  Eligible participants being prescribed HCV treatment may be offered the opportunity to consent 
to participate in PRIORITIZE.   
 
Written informed consent must be obtained before patient information is submitted for randomization. 
 

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Where approved by local IRBs, the investigator or qualified designee will explain the Future Biomedical 
Research to the subject.  Subjects are not required to participate in the Future Biomedical Research.  
Subjects who decline to participate will not be discontinued from the main study and will have blood 
destroyed.    Investigator or designee will answer all subjects’ questions and obtain written informed 
consent before performing any procedure related to the Future Biomedical Research sub-trial.  Consent 
for Future Biomedical Research may be included in the main informed consent or a separate informed 
consent as per local IRB regulations or requirements. 
 
7.2 Schedule of Observations and Schedule of PRO Assessments- 
The schedule of observations is a guide for the HCV treatment data that is collected in PRIORITIZE and 
is provided in Table 4.   HCV treatment is not dictated by the protocol.  Dosing, treatment/side effect 
management, and duration will be at the discretion of the site/provider according to the site standard of 
care. Efficacy and safety outcomes observations (clinically documented drug side effects, clinical labs) as 
well as long term follow-up measures (disease progression/regression, mortality, co-morbid 
conditions) as part of the participants’ standard clinical follow up and will be submitted and analyzed 
where available.  Participants should be managed for HCV treatment and follow-up according to their 
respective local standard of care. 
 
TABLE 4: SCHEDULE OF OBSERVATIONS *No window historically for baseline records submitted for Abstraction (Most recent records should be provided) 
Assessments 
Screening & 
Randomization 
Baseline 
ON TREATMENT 
OBSERVATIONS through 
Follow-up 
SVR/viral 
outcome 
3 yrs after 
treatment 
baselineb 
Informed Consent 
X 
 
 
 
 
Randomization  
X 
 
 
 
 
Demographics  
 
X 
 
 
 
Medical History/Co-morbid 
conditions 
 
X 
 
 
 
Fibrosis Staging- all methods 
applicable 
 
X 
 
 
 
Prior HCV Treatment Response, if 
applicable 
 
X 
 
 
 
IL-28B genotype 
 
X 
 
 
 
HCV Genotype (most recent 
genotyping) 
 
X 
 
 
 
CBCD/Coags 
 
X 
Submit ALL CBCD results/reports collected 
during treatment through viral outcome. 
 
Serum Chemistries 
 
X 
Submit ALL chemistries to monitor patient 
health and safety during treatment through 
viral outcome. 
 
HCV RNA  
 
X 
Submit ALL HCVRNA results collected during 
treatment and Follow-up until SVR outcome is 
determined 
X 
 
 
Blood draw for HCV Resistance 
Associated Polymorphisms (RAP) 
testing 
Xa 
 
Xc 
 
Blood for Future Biomedical 
Research 
X 
 
 
 
 
HCV Medications  
 
X 
Submit ALL clinic/telephone notes during 
treatment through viral outcome.  Medication 
data to be abstracted from notes. 
 
ConMeds 
 
X 
Submit ALL clinic/telephone notes recorded 
during treatment through viral outcome.  - 
conmed data to be abstracted from notes 
 
Adverse Events/Drug Side Effects 
 
 
 
Submit ALL clinic/telephone notes recorded 
during treatment through viral outcome.  - 
adverse event/drug side effect data to be 
abstracted from notes 
 

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Year of Transplant (if transplanted) 
 
X 
 
 
 
Progression of Liver 
Disease/Morbidity/Mortalityc 
 
BMI, labs, imaging (US/CT/MRI), liver stiffness measurement by Fibroscan, 
and histology to be submitted where done clinically according to data 
submission milestones.  Data will be used to run disease progression modeling 
(Section 6.6) 
a – RAP testing will be performed on all Genotype 1a participants randomized to ZEPATIERTM  prior to treatment initiation 
b- Yr 3- all hepatology records and labs from viral outcome to 3 yrs post baseline to evaluate disease 
progression/regression, alive/dead  
c- Participants with virologic failure may be asked to submit a sample for analysis of treatment emergent RAPs.   
 
 
TABLE 5: PATIENT REPORTED OUTCOMES SCHEDULE OF ASSESSMENTS 
Study Outcome 
Measure 
Baseline 
Week 4 
EOT 
1 yr after 
treatment 
3 yrs after 
treatment 
Systemic HCV Symptoms 
PROMIS Fatigue, Cognitive 
Impairment, Sleep Disturbance, 
Nausea, Diarrhea, and abdominal 
pain 
X 
 
 
X 
X 
Patient Reported Drug Side 
effects 
PROMIS Fatigue & Nausea; Headache 
Impact Test (HIT) 
X 
X 
X 
 
 
Functioning 
HCV-PRO 
X 
X 
X 
X 
X 
Adherence / Persistence  
3 Item Voils Survey, persistence rate 
 
X 
X 
 
 
Disease progression/mortality 
Patient medical record & telephone 
call  
X 
 
 
X 
X 
 
Data related to standard clinical care, HCV treatment, drug side effects/adverse events, disease 
progression/regression, long term durability of SVR, co-morbid conditions and mortality will be 
abstracted from submitted medical records (clinic notes, telephone notes, safety and efficacy labs- see 
SCHEDULE OF OBSERVATIONS) by a specially trained group of chart data abstractors at the 
University of Florida.  The collection of patient reported outcomes (PRO) surveys is atypical in standard 
clinical care; therefore, to preserve the usual clinical conditions, PRO survey will be administered through 
the use of technology / devices outside of clinical interactions (web-based and phone based surveys).  
7.3 Baseline NS5 Resistance Associated Polymorphism (RAP) Testing 
ALL participants, regardless of assigned treatment regimen, will undergo baseline NS5a resistance 
associated polymorphism testing free of charge via a central commercial laboratory vendor.  The results 
of RAP testing can be used clinically to determine treatment duration and the addition of ribavirin to the 
regimen in support of the ZEPATIERTM US FDA label.  Participants randomized to ZEPATIERTM will 
have their baseline NS5a RAP sample tested PRIOR to dispensing drug.  If a baseline RAP at amino acid 
positions 28, 30, 31, and/or 93 is identified, those participants will be provided with 16 wks of 
ZEPATIERTM + RBV, consistent with the FDA label recommendation for resistance guided therapy.  
There are no label specific RAP testing recommendations for HARVONI® or Viekira Pak/Viekira XRTM 
(Phase I), thus participants randomized to HARVONI® or Viekira Pak/Viekira XRTM (Phase I), will be 
treated according to the prescribed local standard of care.   
 
The baseline RAP testing sample will be collected PRIOR to dosing with HARVONI®, VIEKIRA 
PAK/VIEKIRA XRTM (Phase I), or ZEPATIERTM.  Participants will not be charged for sample collection 
or NS5a RAP testing. 
 

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7.4 Clinical Data- Baseline, On Treatment, Post-Treatment, and Long- Term 
Follow-up  
Several clinical and laboratory evaluations are routinely performed in the management of HCV treatment 
and as part of standard clinical long-term patient follow-up. Medical records will be submitted to collect 
patient pretreatment variables (baseline characteristics), on treatment experience (for safety and efficacy) 
and the post-treatment experience (for safety and efficacy, disease progression/regression, co-morbid 
conditions, and mortality). 
  7.4.a Baseline demographic information  
• Year of birth  
• Gender 
• Race 
• Ethnicity (Hispanic or non-Hispanic) 
• Weight 
• Height (BMI will be calculated in database from provided Wt./Ht.) 
• Insurance Type 
 
 7.4.b Baseline Clinical Data 
Pre-treatment medical records, where available, containing the following information should be 
submitted to support centralized chart data abstraction. 
 
• 
Prior treatment status will be ascertained as either naïve to therapy or treatment-
experienced. Among treatment-experienced participants, prior response will be recorded 
in addition to therapies received that may be noted in the submitted medical records.   
• 
Absence/Presence of cirrhosis and supporting diagnostic data. Site will submit any 
available information in the medical record obtained as part of standard of care (e.g., for 
diagnosis or follow-up) to evaluate hepatic fibrosis including: 
a. most recent liver biopsy pathology report (fibrosis stage and staging method)  
b. fibroscan/liver elastography report 
c. serum fibrosis marker test results 
d. most recent abdominal imaging (ultrasound, CT, or MRI)  
e. or any test results to support calculation of fibrosis (i.e. FIB-4, APRI). 
• 
Measures of portal hypertension 
– 
EGD report 
– 
Abdominal imaging (can also be used for fibrosis staging) 
• 
Year of kidney and/or liver transplant (if applicable) 
• 
Concomitant medications  
• 
Key medical history/co-morbidities  
–     Psychiatric disease  
– 
Diabetes mellitus 
–     Cardiovascular or cardiac disease/conditions  
–     Lipid disorders 
                                –     Neurological disorders 
– 
Pulmonary diseases/conditions  
– 
Substances that contribute to co-morbid conditions (current or historical 
smoking, alcohol and substance abuse) 
– 
Coagulation disorders 

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– 
Prior/Current Malignancies including Hepatocellular carcinoma 
– 
Chronic skin disease, including dermatologic extrahepatic   
manifestation of CHC  
– 
HIV or HBV coinfection 
– 
Other forms of liver disease (i. e. hemochromatosis, NASH) 
– 
Pre-existing complications of liver disease if present or being treated at 
baseline (ascites, encephalopathy, esophageal varices). 
 
7.4.c Baseline Laboratory Data  
Where a result is available, the site will submit medical records that were collected as part of the 
site standard practice for participants undergoing HCV treatment.  Results must have been 
collected on or before the HCV treatment start date to be considered baseline. Submit laboratory 
results collected closest to the treatment start date.   
• 
HCV RNA level.  This BASELINE value will be used to calculate change in HCV RNA 
during therapy.  
• 
HCV RNA genotype and subtype  
• 
HCV Resistance Mutation Testing (NS3/4, NS5a, NS5b) 
• 
IL28B genotype (any historical result, if available) 
• 
Complete blood cell count including platelets 
• 
Measures of hepatic disease and function  
• 
Measures of renal disease and function 
• 
Measures of metabolic risk factors (i.e. fasting glucose, Hgb A1c) 
• 
Prothrombin time/INR  
• 
Results of Baseline Resistance Associated Polymorphisms (RAP) testing (if applicable) 
 
 
7.4.d On-Treatment Clinical Data 
On-treatment visits will coincide with local standard of care visits for participants in 
PRIORITIZE.  Sites will submit medical records to document HCV treatment safety and efficacy.  
To support comprehensive centralized chart data abstraction of HCV treatment safety and 
efficacy, ALL on-treatment clinic notes and nursing/staff telephone notes will be submitted. 
• 
HCV Treatment Data 
HCV-Therapy Regimen 
1. All anti-HCV therapies used (product names for each anti-HCV product used in 
the treatment regimen) 
2. Doses (starting doses of all products) 
3. Dose changes (any adjustments during treatment) 
4. Reasons for dose adjustments/premature discontinuation 
5. Treatment end date 
6. Duration of treatment 
• Adverse Events /Interval Complications of Liver Disease 
ALL adverse experiences recorded in the medical record during treatment for HCV will 
be abstracted. Records documenting newly diagnosed hepatocellular carcinoma, ascites 
(radiologically verified), esophageal varices, and/or hepatic encephalopathy should also 
be submitted.  
 
• Liver Transplant 

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Participants may require liver transplantation during HCV treatment or follow-up either 
as part of pre-treatment listing or due to HCV treatment complications.  Records showing 
the date of transplant and reason for transplant will be submitted 
 
• Concomitant medications  
ALL concomitant medications (over the counter and prescription) recorded in the 
medical record during the treatment for HCV or follow-up may be abstracted. 
 
• Laboratory data collection during treatment 
To support comprehensive centralized chart data abstraction of HCV treatment safety and 
efficacy, ALL labs collected during HCV treatment to monitor safety and efficacy will be 
submitted.  These include but are not limited to 
• 
Complete blood cell count including platelets 
• 
Measures of hepatic disease and function  
• 
Measures of renal disease and function 
• 
Measures of other organ disease and function 
• 
Prothrombin time/INR  
• 
HCV RNA levels 
 
 
7.4.e Post Treatment Clinical and Laboratory Data 
Post treatment visits will coincide with local standard of care visits for participants in 
PRIORITIZE.  Sites will submit medical records to document HCV post treatment safety and 
efficacy.  To support comprehensive centralized chart data abstraction of HCV post treatment 
safety and efficacy, all clinic notes, telephone notes and lab results done to monitor the 
participants HCV treatment and outcome should be submitted through viral outcome.  If a 
patient does not physically return for a visit to the treating clinic in the immediate post-treatment 
period, a nursing/telephone note or equivalent source record should be submitted to document 
this. Additional medical records documenting hepatic decompensation (new/worsening ascites, 
encephalopathy, esophageal variceal bleeding) OR other events of special interest may be 
requested from the site to fully characterize HCV treatment safety outcomes.   
• 
Complete blood cell count including platelets 
• 
Measures of hepatic disease and function  
• 
Measures of renal disease and function 
• 
Measures of other organ disease and function 
• 
Prothrombin time/INR  
• 
HCV RNA levels 
 
7.4.f Virologic Failure Resistance Associated Polymorphism (RAP) Testing 
Any participant who exhibits virologic failure, regardless of assigned treatment regimen, may be 
asked to undergo resistance associated polymorphism testing for treatment emergent RAPs free 
of charge via a central commercial laboratory vendor.  Virologic failure RAP testing samples 
must be collected within 30 days of known viral failure noted as part of standard clinical care 
(non-response, viral breakthrough, or relapse).  In the event significant RAPs are identified in a 
failure test sample, blood collected at screening for NS5a testing may undergo additional RAP 
testing.  Participants will not be charged for sample collection or RAP testing. 
 

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7.4.g Clinical Data Abstracted post HCV treatment and during Yr 3 
Participants who return to the clinical site for annual follow-up after HCV treatment is completed 
will be followed for long-term health outcomes for up to 3 years after virologic outcome is 
determined.  A prospective annual clinical note, any clinical evaluations (CT, ultrasound, EGD, 
MRI) and annual labs to observe persistence of HCV therapy response (HCV-RNA) & HCV co-
morbid conditions (hematology, coags & serum chemistries) should be submitted.  Co-morbid 
conditions, concomitant medications and health-related lab data will be collected from the 
submitted records and utilized to evaluate long term outcomes and disease progression.  
Participants who achieve SVR will be compared to participants who do not achieve SVR for the 
persistence of baseline co-morbidities and emergence of new co-morbidities post treatment.  
Participants who do not return to their local site for health care follow-up up to 3 years after HCV 
treatment baseline will be contacted by telephone to ascertain living status.   
 
 
• 
Fibroscan, CT, ultrasound, MRI or other imaging at least once annually post viral 
outcome through approximately 3 years post treatment will be submitted 
according to the data milestone submission schedule  
• 
Hepatology clinic notes at least once annually post viral outcome to through 3 
years post treatment will be submitted according to the data milestone 
submission schedule. Complete blood cell count including platelets – at least 
once annually viral outcome through approximately 3 years post treatment will 
be submitted according to the data milestone submission schedule  
• 
Measures of hepatic disease and function evaluation– at least once annually post 
viral outcome through approximately 3 years post treatment will be submitted 
according to the data milestone submission schedule 
• 
Measures of renal disease and function – at least once annually post viral 
outcome through approximately 3 years post treatment will be submitted 
according to the data milestone submission schedule.  Measures of other organ 
disease and function– done post treatment through 3 years post treatment will be 
submitted according to the data milestone submission schedule  
• 
Prothrombin time/INR – at least once annually post viral outcome through 
approximately 3 years post treatment will be submitted according to the data 
milestone submission schedule.  Additional lab reports documenting 
hepatic/organ insufficiency or failure OR other events of special interest may be 
requested from the site to fully characterize HCV treatment safety. 
• 
Persistence of HCV RNA Virologic Outcome– HCVRNA collection completed 
after viral outcome is determined through 3 years post treatment will be 
submitted according to the data milestone submission schedule 
 
7.5 Patient Reported Outcomes Data- Baseline, On Treatment, and Post-
Treatment, and Long-Term Follow-up  
The PRIORITIZE Study was developed to address outcomes of interest to patients and their caregivers. A 
9-member HCV Patient Engagement Group (HCV-PEG) is acting as collaborators to this research and 
assisted in prioritizing HCV patients’ informational needs ensuring harms or benefits to the patients are 
considered.  Based on that input, the following patient reported outcomes surveys will be administered 
according to the Patient Reported Outcomes Schedule of Assessments (Table 5) 

PRIORITIZE                                                                                                       Version 5.0      9.18.2018 
 
 
 
 
 
Page 26 
• 
HCV-PRO: The HCV-PRO is a newly developed survey designed to assess functional status of 
patients with HCV and measures physical, emotional and social functioning, productivity, 
intimacy, and perception of quality of life.   
• 
PROMIS MEASURES- The HCV-PEG and researchers felt it would be useful to robustly and 
precisely measure six side effects reported by >10% of people in Phase III trials of the newly 
approved HCV therapies as well as common HCV systemic symptoms. The following five 
Patient-Reported Outcomes Measurement Information System® (PROMIS®) forms to obtain 
valid and precise measurement of specific, highly salient HCV systemic symptoms and/or 
treatment side effects: Fatigue, Cognitive Impairment, Sleep Disturbance, Diarrhea, Nausea, and 
Abdominal Pain. Each side effect/symptom is measured with a very brief form containing only 4-
8 items from the larger item bank that were the best performing items in content validity and 
reliability.  Change in PROMIS and HIT side effect scores from baseline to highest score during 
treatment will be evaluated.   
• 
Headache Impact Test (HIT): Headaches were a common side effect noted in trials for both 
HARVONI® and Viekira PakTM(Phase I).   
• 
Voils’ Medication Adherence Survey that consists of 3 items assessing the extent of adherence to 
medications using a 5-point Likert scale ranging from “none of the time” to “every time”.37,38 
These 3 items assess how often participants missed doses, skipped doses, or did not take doses 
over the past 7 days, and are combined into a single score shown to be reliable (a = 0.84).   
 
Study participants will have the option of completing patient-reported surveys in person using standard 
paper versions (where necessary), via a web-based REDCap Patient Portal (link with instructions will be 
emailed to patient) or via phone interview. Patients completing web-based surveys respond via a secure 
URL from a home-based computer, and they decide whether they want to receive a call or email reminder 
prompting them to log into the URL and complete the survey.  Data collected via REDCap Portals are 
transmitted to the HCV-TARGET Data Coordinating Center.  Alternatively, if patients prefer, staff from 
our Survey Center (English and Spanish-speaking) will contact the patient at a previously approved phone 
number and convenient time to deliver the surveys via phone.  Beyond convenience, phone interviews are 
critical to allow those with low literacy skills or without computer or access to participate in the study.  
All surveys (paper, electronic and telephone) will be offered in Spanish to sites with Spanish speaking 
populations. The PROMIS measures are already available in Spanish.  We will undergo the proper 
techniques to translate the HCV-PRO, and Voils Medication Adherence into Spanish.  
 
The telephone based surveys will be administered by The University of Florida Survey Research which 
has a state-of-the-art survey research program with a 93-station computerized lab operating seven days a 
week.  Staff members conduct research on a variety of survey-related topics and conducts customized 
surveys and projects for UF research units and clinical trials.  The center has the resources and training to 
complete the telephone surveys for this study with high attention to professionalism and sensitivities to 
patients needs during the survey process as well as in accordance with protections for privacy and 
protected health information. 
 
7.5.a Future Biomedical Research 
Samples collected for Future Biomedical Research are to be stored in appropriately consented participants. 
In the event the subject does not consent to participate in Future Biomedical Research, any sample 
remaining after the collection for baseline RAP testing will be destroyed. 

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Page 27 
It is now well recognized that information obtained from studying and testing clinical specimens offers 
unique opportunities to enhance our understanding of how individuals respond to drugs, enhance our 
understanding of human disease and ultimately improve public health through development of novel 
treatments targeted to populations with the greatest need. The future research blood sample collected in 
the current trial may be used to study various causes for how participants may respond to a drug.  The 
sample will initially be stored at the study central laboratory after collection. 
Samples will be initially collected at sites’ clinical/research laboratory or commercially available draw 
stations associated with the study central laboratory throughout the country and tested for baseline NS5a 
RAPs.  The future research samples will remain at the study central laboratory until shipped for long-term 
storage at the University of Florida IRB approved Biorepository ‘HCV-TARGET Biorepository 
Specimen Bank’ for up to 15 years after the end of the study (database closure) at which time they will be 
destroyed.  The sampling procedures, storage conditions and shipment instructions for participating sites 
will be provided in the supplemental laboratory manual. 
 
Exploratory biomarker and virologic marker/resistance studies can be used for research purposes to 
identify potential biomarkers predictive of response to HCV treatment (in terms of mode of action, 
efficacy, dose, safety and tolerability), disease progression, to determine how best to monitor and treat 
HCV, development of a new medical product, or to explore complications of HCV disease and treatment. 
These studies will help to better understand the pathogenesis and treatment outcome of HCV infection 
through evaluation of biomarkers and virologic markers/resistance to predict disease outcomes and, 
possibly, response to antiviral therapy. In addition, genetic analyses may be performed on collected blood.  
The resulting pharmacogenetic information may improve treatment outcomes by stratifying patients who 
are more likely to respond to specific drug therapies, susceptible to developing adverse side effects and/or 
prone to more severe disease states.  
 
Participants may withdraw their consent for Future Biomedical Research and have their specimens and all 
derivatives destroyed.   Participants may withdraw consent at any time by contacting the principal 
investigator at their local HCV treatment center (SITE).  The site investigator will contact the University 
of Florida using the designated mailbox (PRIORITIZE@medicine.ufl.edu), and a form will be provided 
by the University of Florida to obtain appropriate information to complete specimen withdrawal.  
Subsequently, the subject's specimens will be removed from the biorepository and be destroyed.  A letter 
will be sent from the University of Florida to the investigator confirming the destruction. It is the 
responsibility of the investigator to inform the subject of completion of destruction.  Any analyses in 
progress at the time of request for destruction or already performed prior to the request being received 
will continue to be used as part of the overall research trial data and results.   No new analyses would be 
generated after the request is received. 
 
In the event that the medical records for the main trial are no longer available (e.g., if the investigator is 
no longer required by regulatory authorities to retain the main trial records) or the specimens have been 
completely anonymized, there will no longer be a link between the subject’s personal information and 
their specimens.  In this situation, the request for specimen destruction cannot be processed. 
 
7.6 Progression of Liver Disease, Morbidity and Mortality Data 
Clinical data used to evaluate progression of liver disease, morbidity and mortality will be abstracted from 
the medical records submitted according to the Schedule of Observations (Table 4).  Comparison of 
regimens H, V and Z in terms of the risk of future clinical outcomes will rely on the application of 
machine learning algorithms to the patient’s longitudinal follow-up data.39 Using machine learning 
algorithms to predict outcomes (e.g., random forests with bagging) has been shown to outperform 
standard Cox regression approach because the machine learning approach can handle a large number of 

PRIORITIZE                                                                                                       Version 5.0      9.18.2018 
 
 
 
 
 
Page 28 
predictor variables while coping with incomplete data. Incorporating longitudinal data into prediction 
models allows the predicted risk to be updated over time as additional evaluations accrue.40 Predictions 
obtained before and after treatment can be used to characterize risk reduction and for a given treatment 
outcome. PRIORITIZE will use the following outcome measures: 1) Incident liver complications – 
hepatic decompensation (ascites, variceal bleeding, encephalopathy), cancer, liver-related death 2) 
Progression to cirrhosis – Increase in APRI to >2.0, Lok index to >0.5, or liver stiffness measurement to 
≥12.0; 3) All-cause mortality and liver-related mortality; 4) Incident extra-hepatic manifestations of 
hepatitis C such as –diabetes mellitus, cryoglobulinemia with organ involvement and 5) Fibrosis 
progression/regression – change in FIB-4, APRI, and liver stiffness measurement over time. We 
anticipate that fibrosis will regress over time in patients who achieve SVR and that a decrease in fibrosis 
score will be observed in many patients with SVR by the end of the study. Passive follow-up 3 years after 
treatment will also include linking claims data to each patient on health service use, clinical diagnoses and 
procedure codes and through query of the National Death Index Plus. Various non-invasive methods for 
assessment of liver fibrosis and cirrhosis in patients with chronic hepatitis C have been validated.   
 
We propose to apply both APRI and FIB-4 to all patients as these two indices comprise of routinely 
available labs that will be available longitudinally in hepatitis C patients. APRI and FIB-4 results will be 
used to determine baseline stage of liver disease and to determine progression or regression of liver 
disease after treatment. We will compare results based on APRI and FIB-4 and expect the conclusions 
regarding liver fibrosis progression and regression for each treatment arm will be similar. Both APRI and 
FIB-4 rely on two cutoff values, one for optimizing sensitivity and one for optimizing specificity (Tables 
4a and 4b).41,42 For example, low cutoff for assessing cirrhosis with APRI is <1.0 and high cutoff is >2.0. 
Summary sensitivity of APRI <1.0 in determining cirrhosis is 82% and summary specificity of APRI >2.0 
is 92% in determining cirrhosis. Up to 40% of patients fall into the indeterminate zone, i.e. APRI between 
1.0 and 2.0. Thus, it is recommended that more than one index based on blood tests or a sequential 
algorithm incorporating one index based on blood tests plus liver elastography be used to maximize the 
number of patients who can be classified. Although Fibroscan was approved by the US FDA in 2014, 
Fibroscan machines are not widely available outside major liver centers and even when available, liver 
elastography is not serially measured in most patients. We propose to apply both APRI and Fibroscan to 
assess baseline liver fibrosis in all patients in whom liver elastography is measured at baseline, and 
among this subset of patients who have follow up liver elastography measurement, we will again apply 
both APRI and Fibroscan to assess fibrosis progression or regression after treatment.  
 
Table 6a  Sensitivity and Specificity of APRI, FIB-4 and Fibroscan to Detect Liver Fibrosis Stage 
Metavir ≥F2 
 
Studies, n 
Patients, n 
Sensitivity, % 
95% CI 
Specificity, % 
95% CI 
APRI low 
47 
11696 
82 
77-86 
57 
49-65 
APRI high 
36 
9602 
39 
32-47 
92 
89-94 
FIB-4 low 
11 
2744 
89 
79-95 
42 
25-61 
FIB-4 high 
9 
2115 
59 
43-73 
74 
56-87 
Fibroscan 
37 
8346 
79 
74-84 
83 
77-88 
 
Table 6b Sensitivity and Specificity of APRI and Fibroscan to Detect Cirrhosis 
 
Studies, n 
Patients, n 
Sensitivity, % 
95% CI 
Specificity, % 
95% CI 
APRI low 
24 
7301 
77 
73-81 
78 
74-81 
APRI high 
19 
6930 
48 
41-56 
94 
91-95 
Fibroscan 
36 
7923 
89 
84-92 
91 
89-93 
 

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7.7 Procedures for Submitting Clinical Records for Study Observations 
Several clinical and laboratory evaluations are routinely performed in the management of HCV treatment.  
These evaluations and clinical management are recorded as part of a patient’s medical record.  All clinic 
notes, nursing/staff telephone notes, evaluations and lab results collected to monitor the HCV baseline 
condition and treatment safety and efficacy are sources of data for PRIORITIZE.  To collect HCV 
treatment and outcomes data, PRIORITIZE provides two pathways to submit safety and efficacy 
information from patient medical records recorded as part of standard clinical care.   
1. Centralized Chart Data Abstraction Service (CDAS):  Redacted medical records are uploaded into 
the study REDCap database for specially trained centralized teams of staff to manually abstract 
clinical, HCV treatment, safety and efficacy information as well as long term outcomes and 
disease progression into the study database (described in detail in Section 13.2).    
2.  REDCap Electronic Data Importer (RED-I): Redacted clinical data from the Electronic Medical 
Record (EMR) is electronically mapped and automatically uploaded into REDCap (described in 
detail in Section 13.3). 
 
 
 
ALL available safety and efficacy data in the patient’s redacted medical records will be recorded in the 
database, regardless of treatment regimen, dosing, or duration.   Before submitting records for manual 
abstraction or through the automated RED-I platform, all elements of PHI defined by HIPAA except dates 
of services are redacted from laboratory test results, procedures, clinic/telephone notes and records related 
to adverse event and serious adverse event reporting.  A study-coded identifier is added to the submitted 
records to help maintain subject confidentiality. HIPPA identifiers, the process of redacting records, and 
protection of patient confidentiality in PRIORITIZE is described in further detail in Sections 14.1 and 
HCV-TARGETDataAbstrac on
Pa entstreatedfor
HCVaspartof
rou neclinicalcare
Pa entclinicnotes,
telephonenotes&labs
redactedbySiteand
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Manual

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14.2. 
8.  ADVERSE EVENTS 
 
An adverse event (AE) is any untoward medical occurrence in a patient administered a pharmaceutical 
product and which does not necessarily have to have a causal relationship with the treatment.  Adverse 
events reported in and abstracted from the submitted patient medical records (clinic notes, telephone 
notes, and labs) will be collected.  Additionally, patient reported drug side effects will be collected 
through the study survey instruments.  The patient reported drug side effects will not be coded for severity 
except where the survey instrument includes severity estimates directly from the patient report. 
 
8.1 Adverse Event Intensity/Severity 
For the purposes of the observational nature of the study clinical activities, adverse events identified by 
the chart data abstractors will be defined and coded centrally based on the following definitions: 
– 
MILD: Adverse events and/or symptoms recorded in the medical record where no therapy was 
given to treat the event or where an over-the-counter medication/intervention ONLY was given 
to treat the event.   
– 
MODERATE: Adverse events and/or symptoms recorded in the medical record requiring 
prescription medication treatment or any anti-HCV drug dose reduction  
– 
SEVERE: Adverse events and/or symptoms requiring any anti-HCV drug discontinuation will be 
defined and coded as severe.  ANEMIA events requiring blood transfusion will be coded as 
severe. 
8.2 Adverse Event Relationship to HCV Treatment 
For the purposes of this study, adverse event causal relationships will be captured as indicated on 
submitted medical records. Due to temporal associations during HCV treatment, adverse event causal 
relationships will be coded as “related” unless the event is clearly noted as  “not related” to the HCV 
treatment regimen in the submitted records.   For serious adverse events where the relationship cannot be 
adequately ascertained and for participants who discontinued treatment early due to an adverse event, the 
site PI or designee will be asked to assign relationship. 
 
8.3 Abnormal Laboratory Evaluations 
Any abnormal safety laboratory test assessment, obtained as part of the patient’s standard of care, will be 
reported as an adverse event (AE) on the AE page of the eCRF ONLY if the laboratory abnormality meets 
one of the following criteria:  
 
• Is considered to meet criteria as Serious  
• Results in discontinuation from treatment (of any or all drugs)  
• Results in dose adjustment of any anti-HCV medication  
• Results in a requirement for new prescription medication 
 
When applicable, a diagnosis term should be used to document an abnormal lab value or cluster of values.   
 
8.4 Serious Adverse Events, Expectedness, and Causality of an Adverse Drug 
Reaction 

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8.4.1 Serious Adverse Event Definition 
A serious adverse event (experience) or reaction is any untoward medical 
occurrence that at any dose of any of the HCV treatment medications: 
 
• 
results in death, 
• 
is life-threatening, 
• 
requires inpatient hospitalization or prolongation of existing 
hospitalization, 
• 
results in persistent or significant disability/incapacity,  
• 
is medically important, or 
• 
is a congenital anomaly/birth defect. 
 
NOTE: The term "life-threatening" in the definition of "serious" refers to an event in 
which the patient was at risk of death at the time of the event; it does not refer to an 
event which hypothetically might have caused death if it were more severe. 
 
Seriousness (not severity) serves as a guide for defining regulatory reporting obligations. 
 
8.4.2 Expectedness and Causality 
An "unexpected" adverse event is one, the nature or severity of which is not consistent with information 
in the applicable product information or package insert.   
 
Causality assessment is required for clinical investigation cases; however, there is currently no standard 
international nomenclature. The expression "reasonable causal relationship" is meant to convey in general 
that there are facts (evidence) to support a relationship to a drug/drug regimen.  
 
8.4.3 Expedited Adverse Event Reporting  
Expedited adverse event reporting will apply to events that meet serious criteria while on treatment in 
PRIORITIZE. Any adverse event that meets the criteria for being serious, regardless of expectedness 
or causality, will be subject to expedited reporting as an adverse drug experience.  Additionally, 
information that might materially influence the benefit-risk assessment of an approved medicinal 
product or that would be sufficient to consider changes in medicinal product administration should 
also be reported. 
 
 8.4.3.1 Expedited Adverse Event Reporting Requirements 
Adverse drug experiences meeting expedited reporting criteria specified above will be reported by 
submitting the VOLUNTARY Form FDA 3500 (MedWatch) when an event abstracted by the data 
abstraction staff at the University of Florida from the submitted medical record is noted to meet serious 
criteria. The data abstraction staff will complete the VOLUNTARY Form FDA 3500 with the data 
available in the clinical record and provide to the site PI to review for accuracy and to complete causality 
assessment.  Every attempt will be made to submit these voluntary reports within 15 days of identification 
of the event.  The CCC will forward ALL VOLUNTARY MEDWATCH forms to the FDA 
regardless of SUSAR criteria.   
 
FDA Voluntary MedWatch Form:  

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https://www.fda.gov/safety/medwatch/howtoreport/downloadforms/default.htm 
9.  PREMATURE DISCONTINUATION 
For participants who prematurely terminate HCV therapy, data will be used from the submitted medical 
records to assign the primary reason for early termination of treatment. There may be instances where 
information in the medical record does not sufficiently detail the reason for discontinuation.  In those 
situations, the site PI will be asked to classify the reason for premature discontinuation and may use the 
following as a guide: 
• 
Adverse event (specify) 
• 
Virological failure (Meeting criteria for treatment futility as per drug label or local guidelines) 
• 
Virological breakthrough  
• 
Patient choice  
• 
Non-adherence  
• 
Administrative (Insurance changes) 
• 
Lost-to-follow-up 
• 
Other (specify) 
 
For participants who die during the course of their HCV treatment, it will be the responsibility of the site 
PI to assign a cause of death based upon available clinical information, hospital records, and/or death 
certificate. 
 
10. VIROLOGICAL RESPONSE DEFINITIONS 
Non-responder: HCVRNA does not become undetectable and treatment is prematurely discontinued. 
Non-responder may be further characterized by the absolute change (log10) in HCV RNA compared to 
baseline values  
 
Sustained virological response (SVR): HCV RNA undetectable at least 12 weeks after therapy was 
discontinued 
 
Relapser: HCV RNA was undetectable at the end of the course of treatment but became detectable at 
any time after discontinuing therapy 
 
Treatment intolerant: These participants discontinued therapy prematurely due to adverse event or 
patient choice prior to completion of therapy. Duration of therapy and reason for discontinuation of any or 
all anti-HCV medications will be recorded.  Post treatment virological response data will be provided 
where available in these participants to characterize SVR. 
 
 Virological breakthrough (VBT) during treatment 
VBT will be defined as an increase of HCV RNA > 1 log10 compared to nadir HCV RNA values during 
treatment. For participants with undetectable viral burden during treatment, an increase to > 100 IU/ml 
while still on treatment will define virological breakthrough. 
 
11.  PARTICIPANT WITHDRAWAL FROM PRIORITIZE  
If a participant chooses to withdraw from observation in PRIORITIZE, all data collected up to the point 
of withdrawal will remain in the study database, but no further data may be collected. A request to 

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withdraw must be documented by the clinical center personnel.  This is consistent with HIPAA guidelines 
and regulations.  
12. STOPPING RULES/DATA AND SAFETY MONITORING PLAN  
 
12.1 Data-Stream Monitoring 
 
PRIORITIZE will be implemented using the fully functional HCV-TARGET infrastructure which 
comprises standardized, centralized chart data abstraction methods along with detailed data monitoring to 
increase the efficiency and quality of the database.    
 
12.2 Interim Analysis of Safety Data 
 
No interim analyses will be performed. 
  
12.3 Stopping Rule  
 
A formal rule for stopping the study will not be used. 
 
13. STATISTICAL ANALYSIS STRATEGY  
                                                                                                                                      
13.1 Overview 
Best Practices: The statistical considerations and aim-specific analysis plans registered in this master 
protocol document were reviewed and updated in August 2017. To help ensure reproducible results, the a 
priori analysis plans specify detailed steps for the major estimators and inferential analyses along with 
guidelines for sensitivity analyses performed to assess the robustness of the major results to reasonable 
perturbations of the a priori assumptions, choices, and methods used. The plans also include a role for 
outcome-dependent exploratory analyses for hypothesis generation and necessary descriptive graphical 
and tabular methods used to characterize the participants, visualize the data and examine relationships 
among variables. Best practices for dealing with incomplete data will depend on the documented causes 
of missing, censored, and coarsened values. The main results will be obtained using appropriate model-
based methods.  To aid interpretation, simple means and proportions will also be tabulated. The outcomes 
of interest are binary (e.g. achievement of SVR), or interval-scale summary scores (e.g., PROMIS forms, 
HCV-PRO), or percent scores (e.g., adherence, persistence). Regardless of the scale of the outcome, the 
strategy for obtaining the main results is the same: for each regimen, and for the difference between 
regimens, point estimates of central tendency and variance will be obtained along with their 95% 
confidence intervals to indicate level of precision.  
Primary Analyses.  The main analyses will rely on intent-to-treat (ITT) estimation methods applied to 
those participants who started DAA drug therapy.  The main analyses can thus be considered modified 
ITT analyses because (1) the analysis is conditional on the treatment to which the patient was randomized 
(even if the patient actually received a different treatment) and (2) participants who did not start treatment 
are excluded.  Failure to start therapy after randomization is a particular kind of “drop out” and has many 
causes (e.g., death, change of employer/insurer, prior authorization (PA) filters, withdrawal of consent 
due to a burdensome PA application process).  The baseline characteristics of randomized patients who 
did not start DAA therapy will play an important role in our investigation of the causes of not starting 
DAA therapy and our investigation of potential selection biases due to not starting DAA therapy.    

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Sensitivity Analyses.  To guide our level of trust in the results from the main analyses, we will investigate 
the robustness of the study’s main results to reasonable perturbations of the statistical methods and 
assumptions used.  The domain of sensitivity analyses will include the following:  use of “as-treated” 
estimation, use of “per-protocol” estimation, use of instrumental variable methods, use of other causal 
inference methods, examination of the influence of any extreme or questionable data values, examination 
of the impact of inclusion/exclusion of interaction terms in regression models, diagnostics for model 
goodness-of-fit, and descriptive analysis of model residuals.   While there are always competing statistical 
methods and assumptions from which to choose, to help ensure reproducibility of research the main 
results should be obtained using a single choice of methods that is specified a priori; thus, uncertainty 
about the optimal choice of methods and assumptions is best handled by relegating competing approaches 
to an important role in the domain of sensitivity analyses.  In this study, the application of ITT estimation 
methods to the participants who started DAA therapy is expected to be the most reasonable and 
advantageous strategy.  All other methods and assumptions will play important roles in the domain of 
sensitivity analyses.  For example, we anticipate a low frequency (1% to 2%) of “regimen switching” 
protocol departures (i.e., the patient withdraws consent and is treated with a different drug); consequently, 
induced bias is small and the mean-square error of the ITT estimator is very small compared to the large 
mean-square error of an instrumental-variable (IV) estimator that attempts to correct for the infrequent 
“regimen switching”.  (The instrumental variable would be the indicator of the regimen assigned by 
randomization.)  Similarly, most of the mechanisms that cause drop-out prior to starting treatment are 
expected to be ignorable.  For the few that may be non-ignorable (e.g., PA filters for Harvoni such as 
urine toxicology tests and denials due to minimal fibrosis scores), use of IV methods and other causal 
inference methods are not expected to be advantageous but will play a role in the sensitivity analyses to 
guide trust in the main results.  
Available Data.  About 1700 participants are expected to be consented to allow for approximately 1600 
participants to randomized:  1600 = (725 to Z) + (724 to H) + (151 to V).    Of those, about 1228 
participants are expected to be randomized and successfully started on treatment: 1228 = (707 to Z) + 
(375 to H) + (146 to V).   Recruitment data suggests that about 25% of those assigned to H, and 2% of 
those assigned to Z will fail to start treatment.  Due to the discontinuation of assignments to regimen V 
(following the clinical practice shift away from regimen V, toward shorter therapies that pose less of a 
burden on patients), comparisons of regimen V to regimens H and Z will be based on data from the early 
participants who were enrolled while V was still available in the randomization process; that is, 146 
participates who started treatment per each of regimens V, H and Z.   In contrast, the primary analyses for 
comparing H and Z will be based on the data from all the subjects randomized to H or Z.    
 
13.2 General Strategy and Heterogeneity of Treatment Effects (HTE)  
Primary subgroups of interest are patients with 1) cirrhosis, 2) genotype 1a, and 3) Black American 
patients. The main analyses for the primary outcomes (e.g., SVR12 or side effect scores) will rely on 
statistical models conditional on carefully-defined covariates representing cirrhosis, treatment naïve, 
genotype-1a, age-group, race, sex, treatment regimen received, along with the interactions of treatment 
regimen with cirrhosis status, genotype and race. For specified outcome variables, the baseline score will 
also be included. The fitted model will provide parameter estimates that will be used to obtain point 
estimates, confidence intervals (CI) and hypothesis tests to (a) characterize and compare the three 
treatment regimens within subgroup, and (b) assess HTE represented by the treatment-by-subgroup 
interaction terms. The within-subgroup comparisons of pairs of regimens (H, Z, V) will include treatment 
equivalence tests and superiority tests. Secondarily we will generate new hypotheses by conducting 
exploratory HTE subgroup analyses for which we do not have a strong hypothesis about the directionality 
of effects. Point- and interval-estimates of treatment effects and differences will be obtained for 

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subgroups defined by age (>65 years, and <65 years), sex, presence of mental illness, and recent or active 
alcohol or illicit drug use.  
For SVR12, we hypothesize that there is little or no HTE; in other words, we hypothesize that treatment-
by-subgroup interactions are negligible. This means that regimens H, Z and V have similar cure rates in 
the subgroups of patients defined by cirrhosis, genotype 1a, and race.  Within-subgroup differences in 
SVR between treatment arms are expected to be within the range of 0% to 6%. We also hypothesize that 
patients with cirrhosis, patients with genotype 1a, and Black American patients have lower SVR rates 
across the therapies (i.e., subgroup main-effects are substantial.) This expectation is based on previous 
uncontrolled trials and observational studies. For example, the review produced by ICER reported that 
among patients with cirrhosis, SVR was lower in patients treated with HARVONI® or Viekira PakTM, but 
only among the treatment naïve. The treatment-experienced patients with cirrhosis had similar response 
rates to treatment-experienced patients without cirrhosis, likely due to the longer treatment duration 
recommended for treatment-experienced patients with cirrhosis. The differences in response rate between 
the treatment arms {HARVONI® vs. Viekira PakTM (Phase I)} were small regardless of cirrhosis or past-
treatment status.   
For Drug Side Effects, we hypothesize treatment differences as well as HTE related to cirrhosis; e.g., 
regimen V (with ribavirin) will yield higher frequency and severity of drug side effects, especially in 
patients with severe cirrhosis. We further hypothesize that medication non-adherence will be greater for 
regimen V than regimen H or Z due to drug side effects and daily pill burden.   
13.3 Strategy for Aim 1 – SVR12 
We conjecture that the three regimens are similar in the general target population and in subgroups and 
that the difference between any two regimens, SVR = (P1-P2) is in the interval (0%, 6%]. Based on input 
from our stakeholders, the regimens will be considered clinically equivalent if the difference in the SVR 
(SVR) is < 5%. The primary null hypothesis (Ho) to be tested is that the regimens are not equivalent in the 
general target population; i.e., that |SVR| ≥ 5%. The alternative hypothesis (Ha) is that the regimens are 
equivalent; i.e., that |SVR| < 5%. Complementary to this test procedure, a “superiority” test of the null 
hypothesis that SVR = 0 will also be performed. It is easily possible to arrive at a conclusion such as 0% < 
SVR and |SVR| < 5%; i.e., we establish that one regimen is superior but it does not matter because the 
difference is not clinically important. To provide future patients with personalized information, i.e. “what 
is the SVR for a patient like me”, the model will be used to tabulate profile-specific point- and interval-
estimates of the probability of SVR12.  
13.4 Strategy for Aim 2 – Drug Side Effects  
Because patients have pre-existing symptoms at baseline that are similar to known drug side effects (e.g., 
fatigue), for each PROMIS score of interest we will condition on the baseline value of the PROMIS score 
as a covariate, and analyze change from baseline to the highest (worst) score during treatment. Additional 
supportive tabulations for each of the 32 side effects will be explored; e.g., the incidence of new side 
effects and the exacerbation of existing symptoms during treatment will be characterized in regard to raw 
frequency, severity and distress score. Linear model methods will be applied (see general strategy and 
HTE above). For each comparison of interest a multiple-comparisons procedure will provide an overall 
multivariate test (across PROMIS measures) and a set of component univariate tests. Drug side effects 
data will be collected from medical records to enrich patient’s survey data and provide a complete record 
of patient-reported, physician documented, and lab defined drug side effects. 
13.5 Strategy for Aim 3 – Adherence and Persistence 
Based on the patient-reported Voils’ Medication Adherence Survey, each participant’s level of adherence 
will be classified as high or low for purposes of the analysis of treatment effects. We anticipate that 50% 
to 95% of participants will achieve the high level of adherence, depending on regimen and patient 

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characteristics. Non-adherence is expected to be greatest for regimen B due to drug side effects and daily 
pill burden. Analysis will rely on logistic regression methods. Similarly, a generalized regression model 
for persistence will provide point and interval estimates and test procedures as described above (general 
strategy and HTE).  
13.6 Strategy for Aim 4 – Change in Systemic Symptoms  
Six PROMIS® scores recorded at baseline and at one and three years after treatment will be used to 
evaluate change from baseline. Linear model methods for response will be applied (see general strategy 
and HTE) and modified to account for baseline scores and response to treatment (SVR). The analysis will 
focus on point- and interval-estimates of the magnitude of treatment effects. For each comparison of 
interest a multiple-comparisons procedure will provide an overall multivariate test (for PROMIS 
measures) and a set of component univariate tests.   Sensitivity analyses will include use of modified and 
alternative assumptions and methods. For example, for any PROMIS score with heavily skewed and/or 
bimodal distributions we may examine the impact of using alternative modeling assumptions (e.g., a zero-
inflated log-normal model).  
 
13.7 Strategy for Aim 5 – Progression of Liver Disease  
In terms of the risk of long-term progression/regression of liver disease, characterization and comparison 
of the regimens will rely on the application of machine learning algorithms to the patient’s longitudinal 
follow-up data. Rather than relying on actual occurrence of long-term clinical outcomes, which is 
hindered by the relatively short time frame, we will apply validated prediction models to estimate the risk 
of clinical outcomes for each regimen in patients who achieved SVR versus those who did not.43 These 
longitudinal models will rely on baseline demographic variables and on 3 years of follow-up evaluations 
of BMI, labs (CBC, liver panel, INR, Cr), imaging (US/CT/MRI), liver stiffness measurement by 
Fibroscan, and histology. These prediction models for risk of liver outcomes will be re-fitted annually as 
follow-up data accrues. The regimens will be compared in terms of the changes in predicted risks of liver 
outcomes over time. For the primary outcome of fibrosis regression, we will compare treatment groups as 
follows: (1) % with fibrosis regression at up to 3 years post treatment baseline, (2) % with net fibrosis 
regression at up to 3 years post treatment baseline (% with fibrosis progression will be subtracted to 
obtain net improvement), and (3) % predicted to have fibrosis regression up to 3 years post treatment 
baseline. 
13.8 Strategy for Aim 6 – Persistence of Viral Cure or Re-infection  
Follow-up at 3 years will be used to characterize and compare the treatment regimens overall and in 
subgroups in terms of recurrence of infection in those participants who had achieved SVR. The analysis 
will focus on point- and interval-estimates of rates.  
13.9 Strategy for Aim 7 – Functional Status  
The HCV-PRO score recorded at baseline and at one and two years after treatment will be used to 
evaluate change from baseline. Linear model methods will be applied (see general strategy and HTE) and 
modified to account for baseline score and response to treatment (SVR). The analysis will focus on point- 
and interval-estimates of the magnitude of treatment effects together with treatment equivalence tests and 
superiority tests.  
13.10 Strategy for a New Aim – Impacts of Mandated Prior Authorization  
Data from the recruitment and randomization process will yield a secondary publication 
investigating the negative impact of payor-mandated prior authorizations on treatment start rates.  
Prior to any examination of data concerning the impact on clinical and PRO outcomes, a detailed 

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statistical analysis plan will be developed for this additional investigation.  The publication will 
emphasize that this additional investigation was not envisioned in the original a priori analysis 
plans.   
 
13.11 Use of Causal Inference Methods  
Causal inference methods will play important roles in (1) sensitivity analyses which use reasonable 
perturbation of methods and assumptions to guide trust in the main results, and in (2) any comparisons of 
the PRIORITIZE data to other databases such as that of the TARGET Study.   
Sensitivity Analyses. For example, sensitivity analyses using randomization as an instrumental variable 
will be useful in regard to guiding our level of trust in the results of tests of equivalence of regimens on 
SVR rates.  For SVR, instrumental variable methods will include two-stage logistic regression (2SLR), 
two-stage residual inclusion (2SRI), and bivariate-probit estimation.  In all of these, the randomized 
treatment assignment will be the instrumental variable.   More generally, the sensitivity analyses may 
include two-stage least squares (2SLS) IV methods and other causal inference methods such as inverse 
probability of treatment weighting (IPTW) based on propensity scores.  These methods are not expected 
to advantageously improve estimation and inference.        
Study Comparisons.  For any comparisons (if any) of the PRIORITIZE data to other databases (e.g., 
HCV-TARGET) a broad variety of causal inference methods would be used:  e.g.,  covariate-balancing 
propensity score methods, partitioning the covariate space for purposes of stratum-specific covariate 
matching, inverse probability weighting (IPW),  and doubly robust methods.44,45,46,47,48  These methods are 
more computationally intensive and require careful use of diagnostic methods (e.g., for covariate balance) 
and an extensive set of sensitivity analyses.  It should be noted that the required assumption of “no 
unmeasured confounders” would be unverifiable.  Although limited by the necessity of making additional 
assumptions and conjectures, efforts would be made to investigate the potential magnitude of residual 
bias that would exist if any unmeasured confounders exist.    Use of propensity-score methods would rely 
on an extensive set of covariates measured at baseline. For purposes of estimation of a propensity score 
model, missing covariate values will be addressed via multiple imputations and the resulting multiplicity 
of propensity scores would be averaged together as proposed by Mitra and Reiter.49   
13.12 Methods for Coping with Missing Data  
Generally, best practices for dealing appropriately with incomplete data, especially PROs, will depend on 
the documented causes of the missing, censored, or coarsened values. Every effort will be made to 
document the causes and to avoid incomplete data by capturing the PRO data and clinical data even when 
the participant terminates treatment earlier than scheduled. Depending on the mechanisms which cause 
loss-to-follow-up for outcomes such as the PROMIS Scores at 1 year, multiple imputation methods may 
be appropriate. Competing model-based methods will be examined for purposes of sensitivity analysis.  
13.13 Sample Size Rationale  
In total, we anticipate that about N = 1700 participants will be consented and enrolled, with at least 1228 
being both successfully randomized and successfully starting treatment as follows:  1228 = (707 to Z) + 
(375 to H) + (146 to V).   Due to the discontinuation of assignments to regimen V, only 154 enrollees 
were assigned to regimen V.  Of those, only 146 started V regimen treatment.  While equal numbers of 
participants are assigned by randomization to H and Z, the sample size expectations take into account the 
higher rate of failure to start treatment that is inherent for those assigned to regimen H.   
About 15% of participants in each treatment arm will be classified as cirrhotic.  The rationale for that 
original target was based in part on an assumption that 50% of the participants would have cirrhosis and 

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that outcomes would depend heavily on the presence or absence of cirrhosis.  The originally envisioned 
target sample size was 625 participants per cirrhosis subgroup per regimen (H, Z, V):   625  2  3  = 
3750 total.   It was assumed that cirrhotic and non-cirrhotic patients would have substantially different 
severity of disease and substantially different clinical experiences in terms of SVR and PROs.  In order to 
address the assumed existence of those strong “cirrhosis main effects”, it was assumed that a substantial 
sample size would be needed per stratum (cirrhotics, non-cirrhotics) per regimen (H, Z, V).       
Based on recent information, we anticipate that ~ 15% of the PRIORITIZE participates will be classified 
as cirrhotic and most of those cirrhotic participants will have be in milder stages of liver disease (e.g., 
MELD scores < 10). We therefore anticipate that the estimates and inferences for the overall combined 
target population will be the most important results.  Estimates and inferences for the cirrhotic 
sub-population (or the smaller sub-population of decompensated cirrhotic patients) will necessarily be 
based on samples sizes smaller than about 87 - 116 participants (or about 10 - 20 decompensated cirrhotic 
participants) in each of the H and Z treatment arms.   We anticipate that only about 23 of the 146 
participants receiving regimen V will be classified as cirrhotic.  
The current target sample sizes reflect the scarcity of cirrhotic patients and discontinuation of regimen V, 
as well as expectations about rate of recruitment, rates of successful randomization and treatment starts, 
and the length of time available to conduct the study.  While the target sample sizes have been updated, 
the statistical analysis plans have not been changed by the sample-size considerations.  Rather, some of 
the anticipated results have risen in importance: the estimates and inferences for the overall combined 
target population (especially for H and V) will be the most important results, while estimates and 
inferences about sub-populations defined by cirrhotic status necessarily will be less important than was 
anticipated in 2014 when PRIORITIZE was initially envisioned. 
The performance characteristics of the target sample sizes were evaluated in terms of the anticipated 
levels of power for the proposed hypothesis tests and anticipated levels of precision for important 
statistical estimators.    
General Assumptions Underlying the Sample Size Analysis.  
The main analysis will focus on point and interval estimates of treatment effects and difference. 
Inferences will rely on two kinds of tests: a 2-sided superiority test of size  of the null hypothesis 
Ho: “the difference is exactly zero”, and an equivalence test of size  of Ho: “magnitude of difference 
exceeds a clinically important threshold.” Equivalence test power levels are highest when regimens are 
identical in their effect. Primary consideration was given to the analyses for regimens H and Z.  
 
Table 7.   Target Numbers of Patients Successfully Started on Treatment 
Original Target Sample Sizes    
Updated Assumptions and Target Sample Sizes 
             Cirrhosis1 
             Cirrhosis2 
 
No 
Yes 
Total  
     Randomized 
 
No 
Yes 
Total 
PRO5 
H 
625 
625 
1250  
~ 723 
H  
320 
55 
3754 
300 
Z 
625 
625 
1250  
~ 723 
Z  
600 
107 
707  
566 
V 
625 
625 
1250  
    154 
V3 
122 
23 
146  
117 
3750  
 
 
1228 
982 
Assumptions 
Assumptions 

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1 50% will have cirrhosis   
2 Only 15% will have cirrhosis 
 
3 Regimen V was discontinued 
 
4 Rates of treatment starts for H 
 
5 80% will have complete PRO data   
 
Power curves and precision curves were analyzed assuming that only 15% of participants in each 
treatment cohort will have cirrhosis and that most of the cirrhotic patients will be in milder stages (e.g., 
MELD < 10).  The sample size available to each estimator and to each test procedure will vary. For 
purposes of sample size analysis, the power curves are based on the assumption that the test in question 
will be based on a unified model for the data –which is the proposed approach in the data analysis plan.  
For purposes of computation of these curves, we assume balance of covariates, inclusion of the baseline 
score in models for change from baseline, and that the tests are those of size =  = 0.05.   
We assume that 80% of the subjects will have complete PRO data, while about 100% of the subjects will 
have sufficiently complete SVR data.   
 
 
 
SVR -  Anticipated Precision  
What is the anticipated width of the confidence interval for an SVR rate?   The figure below addresses 
this question about the anticipated precision for SVR estimates (and other rates and proportions.) For 
binary outcomes such as SVR (yes, no), or medication adherence (high, low), the primary analyses will 
provide statistical estimates of the population rate (P). The anticipated level of precision for the estimated 
proportion can be obtained from the figure.   For example, if n = 700 and P = 0.95 is the observed point-
estimate, then half the width of a symmetric approximate 95% confidence interval (CI) is W = 0.016 and 
thus an approximate 95% CI would be 0.950  0.016 or [0.934, 0.966]. 
 

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SVR – Anticipated Power Curves for the Superiority Test:  
The null hypothesis is Ho “P1 = P2” in which P1 and P2 are the regimen-specific SVR rates in the target 
population.  The null hypothesis is a statement about the population from which the sample is drawn.  
Based on knowledge from previous studies, it is reasonable to conjecture that (P1 - P2) may have a value 
in the interval [0.00, 0.06].  The anticipated levels of power for the tests are summarized under the 
assumption that P1 > P2 for conjectured values of P1 and a range of values of (P1 - P2) in the figures below.   
The figure labeled “N = 375 + 707” refers to comparison of regimen H to regimen Z.    
Reading from the curve, if P1 = 0.92 and (P1 - P2)  0.062, then we could anticipate a 90% chance of 
drawing a sample of participants from the target population such that the test turns out to be statistically 
significant.  This also means there would be a 10% chance of not rejecting the null hypothesis.  Or if P1 = 
0.92 and (P1 - P2) = 0.035, then we could anticipate a 50% chance rejecting the null hypothesis, Ho “P1 = 
P2”.   If the null hypothesis is true, then there is a 5% chance of rejecting Ho, and this is true for all 
choices of sample size.  
 
The figure labeled “N =114 + 146” refers to comparison of regimen V to regimen H.   
If for example P1 = 0.92, the curve indicates there would be a 90% chance of rejecting the null hypothesis 
only if (P1 - P2)  0.143 in the target population --which means P2  0.78 while P1 = 0.92.   
    
 
SVR – Anticipated Power Curves for the Equivalence Test:  
The probability of rejecting the null hypothesis, “not equivalent”, is summarized in the figures below. 
Power levels are highest for cases in which the two regimens are identical in terms of the population rate; 
that is, (P1 - P2) = 0 in the target population. The power level decreases rapidly as the magnitude of 
difference, |P1 - P2 |, increases. In the figures, it is assumed that P1 is the larger rate and P2 is the smaller 
rate.  For “N = 375 + 707”, larger SVR rates are more favorable and power is anticipated to be near 80% 
when (P1-P2) is close to zero.   
For “N = 114+146” the curves are flat near 0.00; i.e., that test almost surely will be inconclusive. 

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SVR –  Chances that at least one of the two 
tests is statistically significant 
 
There can be a substantial probability that at least 
one of the two tests (equivalence, superiority) will 
be statistically significant.  The likelihood of that is 
a function of the values of P1 and (P1 - P2) in the 
target population as illustrated in the following 
figure.    The vertical axis is the probability that a 
sample of participants will be recruited such that it 
turns out that at least one of the two tests happens 
to be statistically significant.  
 
(Note:  In these figures, each point on each curve 
was obtained by simulating the study 1,000,000 
times using a test procedure which relied on a 
continuity-corrected Wald confidence interval.)   
 
 

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PROMIS Scores – Anticipated Power Curves for the Superiority Test 
 
The standardized T-scores have exhibited standard deviations (SD) ranging from 6 to 12 at baseline in 
previous studies of 32 HCV patients (Evon, data unpublished). The CID ranges from 3 to 6. Separate tests 
will be performed for each of the six T-scores.  
 
In the comparison of regimens H and Z (“N = 300 + 566”), anticipated power of the superiority test 
would be 90%, for example, if the population standard deviation is 10.0 (for both regimens) and the 
population mean difference is at least 2.319.   
 
Again, under the conjecture that the population standard deviation is 10.0 (for both regimens), for the H-
vs-V comparison (“N = 91 + 117”) the anticipated power of the superiority test exceeds 90% only when 
the population mean difference is at least 4.554. 
 
        
 
 
PROMIS Scores – Anticipated Power Curves for the Equivalence Test 
 
The standardized T-scores have exhibited standard deviations (SD) ranging from 6 to 12 at baseline in 
previous studies of 32 HCV patients (Evon, data unpublished). 
 
The probability of rejecting the null hypothesis, “not equivalent”, is summarized in the figures below. 
Power levels are highest for cases in which the two regimens are identical in terms of the mean difference 
in the target population. The power level decreases rapidly as the magnitude of difference increases. 
 
In the comparison of regimens H and Z (“N = 300 + 566”), anticipated power of the equivalence test 
would be 90%, for example, if the population standard deviation is 10.0 and the population mean 
difference is less than 2.908.   

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Again, under the conjecture that the population standard deviation is 10.0, for the H-vs-V comparison (“N 
= 91 + 117”) the anticipated power of the equivalence test exceeds 90% only when the population mean 
difference is less than 0.849. 
 
     
 
 
As discussed below, for the H - vs. - Z comparison (“N = 300 + 566”), it is likely that at least one of the 
two test procedures (equivalence, superiority) will be statistically significant.  
 
 

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HCV-PRO – Anticipated Power Curves for the Superiority Test 
 
The scale ranges from 0 to 100. A reduction of 10 or more points was considered clinically significant by 
Anderson, et al., (2013), with the estimates shown in the table.  
 
 
In the comparison of regimens H and Z (“N = 300 + 566”), anticipated power of the superiority test 
would be 90%, for example, if the population standard deviation is 31.68 (for both regimens) and the 
population mean difference is at least 7.346.    
 
Again, under the conjecture that the population standard deviation is 31.68 (for both regimens), in the H-
vs-V comparison (“N = 91 + 117”) the anticipated power of the superiority test procedure would be 90% 
on if the population mean difference is at least 14.426.  
 
 
 
HCV-PRO – Anticipated Power Curves for the Equivalence Test 
 
The scale ranges from 0 to 100. A reduction of 10 or more points was considered clinically significant by 
Anderson, et al., (2013), with estimates shown in the table. 
 

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The probability of rejecting the null hypothesis, “not equivalent”, is summarized in the figures below.  
Power levels are highest for cases in which the two regimens are identical in terms of the mean difference 
in the target population. The power level decreases as the magnitude of difference increases.   
 
In the comparison of regimens H and Z (“N = 300 + 566”), anticipated power of the equivalence test 
would be 90%, for example, if the population standard deviation is 31.68 and the population mean 
difference is less than 3.373.    
 
Again, under the conjecture that the population standard deviation is 31.68, in the H-vs-V comparison (“N 
= 91 + 117”) the equivalence test is more likely to be inconclusive.  
 
    
      
 
 
For the H-vs.-Z comparison (“N = 300 + 566”), it is likely that at least one of the two test procedures 
(equivalence, superiority) will be statistically significant.  
 
 

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Medication Adherence – Anticipated Power Curves for the Superiority Test 
 
Based on patient-reported Voils’ Medication Adherence Surveys, each participant’s level of adherence 
will be classified as “high” or “low”.  We anticipate that P = 70% to 95% of participants will achieve the 
“high” level of adherence; that is, P1 has a value between 0.70 and 0.95.     
 
In the comparison of regimens H and Z (“N = 300 + 566”), anticipated power of the superiority test 
would be 90%, for example, if P1 = 0.90 and (P1-P2)   0.076   --which means P2  0.824.    
 
In the comparison of regimens H and V (“N = 91 + 117”), anticipated power of the superiority test would 
be 90%, for example, if P1 = 0.90 and (P1-P2)   0.173    --which means P2  0.727.     
 
      
 
 
 
 
 

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Medication Adherence – Anticipated Power Curves for the Equivalence Test 
 
Based on patient-reported Voils’ Medication Adherence Surveys, each participant’s level of adherence 
will be classified as “high” or “low”.  We anticipate that P = 70% to 95% of participants will achieve the 
“high” level of adherence; that is, P1 has a value between 0.70 and 0.95.  In the comparison of regimens H 
and Z (“N = 300 + 566”) the equivalence test is likely to be inconclusive.  For H-vs.-V “N = 91 + 117”, 
the equivalence test is almost sure to be inconclusive. 
        
 
 
 
Adherence –   Chances that at least one of the two 
tests is statistically significant 
 
There can be a substantial probability that at least one of 
the two tests (superiority, equivalence) will be statistically 
significant.  The likelihood of that is a function of the 
values of P1 and (P1 - P2) in the target population --as 
illustrated in the figure at left. 
 
The label “N = 300 + 566” refers to the sample sizes for 
regimens H and Z.    The vertical axis is the probability 
that a sample of participants will be recruited such that it 
turns out that at least one of the two tests happens to be 
statistically significant.   There is a small chance that both 
tests (superiority test, equivalence test) will happen to be 
statistically significant.   
 
 

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14.  DATA MANAGEMENT  
14.1 Overview 
 
HCV-TARGET will establish standardized systems and operational protocols to ensure data quality control, 
security, and compliance with all applicable standards.    
 
Data Quality and Integrity is a central requirement of research.  Data collection and data entry in multi-
center studies can be very complex, with high variability amongst centers50,51,52. In multi-center, practice-
based studies, high rates of errors and inconsistencies have been observed with abstraction of protocol 
defined data points, lack of protocol defined data contained within the medical record, incorrect 
transcription of data from a medical record, and variability of conventions used to standardize data entry 39.  
Studies of practice-based research have shown benefits to utilizing a central data management center to 
ensure data quality and consistency and reduce these types of errors 38.   
 
14.2 Centralized Chart Data Abstraction 
In order to reduce chart data abstraction errors and inconsistencies and improve data quality, PRIORITIZE 
will utilize a specially trained Centralized Chart Data Abstraction Service team at the CCC/respective 
country Abstraction Core (CDAS) as the method for chart abstraction. Participating sites will provide copies 
of clinically available medical record source data on enrolled participants to the CDAS. This data includes 
clinic notes, nursing/staff telephone notes, evaluations and lab results generated in standard care to monitor 
the HCV baseline condition, on-treatment safety and efficacy as well as long-term health outcomes. The 
CDAS will abstract and enter the data from those provided participant medical records into the database.   
 
14.3 REDCap Electronic Data Importer (RED-I) 
In addition to CDAS to submit health records data, the University of Florida CTS-IT team built RED-I to 
securely obtain redacted data directly from the electronic health record (EMR) and push it into REDCap 
in an automated fashion.  A site level patient index with the patient identifiers mapped to HCVT Target 
Subject Numbers is maintained at the site and used by the site level EMR data teams so patient EMR data 
is accessed without sharing the identifiers centrally to the RED-I software maintainers.  The PHI with the 
exception of dates of service is removed from the EMR data and replaced with the subject’s PRIORITIZE 
identifier before pushing it over an encrypted pathway into the study REDCap database. The UF CTS-IT 
team will work directly with each respective site’s IT and/or EMR team to establish and maintain the 
software and data feed along with quality checks to ensure secure processes.  Where RED-I software is 
established at the site, electronically mapped data will be submitted in conjunction with CDAS.  
 
14.4 Submitting Records for Abstraction 
Before submitting records for abstraction, site staff will redact all elements of PHI (see section 14.2) defined 
by HIPAA except dates of services on all laboratory tests, procedures, clinic/telephone notes and records 
related to adverse event and serious adverse event reporting.  Sites will add a study-coded identifier to the 
submitted records to help maintain subject confidentiality.  Patient identifiers such as patient name, full 
date of birth, address, etc. can be viewed by the DCC or CCC to facilitate onsite and remote monitoring of 
the data and compliance with the protocol, however, with the exception of dates, PHI identifiers will not be 
included on any datasets used for the overall safety and efficacy database and analyses, making the clinical 
database a limited data set.  In instances where a PHI identifier other than a date of service is present on a 
redacted record received for CDAS, delegated CDAS personnel will redact that information.   

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To ensure security with transmitting the records, sites will upload the redacted medical records into the 
Data Management System. Chart Data Abstractors will access the redacted records from this system to 
abstract the protocol-defined data into the study database.  Those records will be maintained by CDAS staff 
to facilitate data monitoring as needed. 
 
14.5 The Data Coordinating Center (DCC) & Data Management System 
The DCC resides in the School of Medicine, College of Gastrointestinal and Biological Disease (CGIBD) 
at UNC-Chapel Hill, CGIBD provides the systems and associated support resources to enable efficient 
professional collection and management of research data.  The web-based Research Electronic Data 
Capture (REDCap) database software is the proposed Data Management System.  
 
REDCap has been used in over 248,000 projects with over 340,000 end users in 99 countries.  REDCap is 
a mature, robust system designed expressly for the purpose of interactive web-based recording of research 
data.  
 
All data will be collected, processed, transmitted and stored via REDCap.  This system will be housed on 
a computing infrastructure that enables compliance with FDA 21 CFR Part 11, HIPAA, HITECH, and 
other applicable standards pertaining to the security of sensitive data (PHI) at rest and in transit. Should 
compliance with additional standards become necessary in the future, our selection of hosting provider 
will make possible the adoption of such standards. 
 
The DCC personnel also provide programming and validation for data quality assurance processes, 
scheduled and ad-hoc progress reports, medical coding of research data, and documentation of database 
modifications (audit logs).  DCC is also responsible for validating and documenting standards 
compliance, database integrity checks, information security (individual user logins, permissions based on 
need, and encrypted data transmission), and data retrieval and export.   
 
Weekly vulnerability detection scans of DCC computing resources are performed by a third-party vendor, 
which include full administrative credentials to perform maximum detection techniques.  Real-time virus 
protection software is implemented and routine full system virus scans are performed. 
 
14.5.1 Data Quality Assurance  
The DCC has designed and implemented web-based data collection instruments in REDCap to support 
the data collection and analyses for this protocol.  These instruments utilize real-time data type and rule-
based validation, and skip logic techniques to prevent collection of erroneous interdependent data, and 
maximize the use of pre-defined selection options and computer-derived values to reduce capture of 
inaccurate data due to human error. 
 
Selected data elements are pre-coded for statistical analysis as a part of the data collection instrument 
design and implementation.  Most of these coded data are continuously available for reporting and 
extraction by the Data Manager and Biostatistics faculty and staff.  Those selected elements that are 
unable to be coded automatically are coded routinely by DCC medical coding personnel. 
 
Each user is provided an individual username and password to access REDCap for this protocol.  
REDCap uses a role-based permissions system to ensure that users are given access to the proper 

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information and operations necessary to their role in the protocol.  Pursuant to applicable standards, 
REDCap automatically and non-destructively records all data collection entries/modifications and 
associated values along with the user account and date/time stamp information. 
 
14.5.2 Standards Compliance of Data Management System 
The REDCap system is implemented and supported by the DCC for the PRIORITIZE registry program.  
US FDA Title 21 Code of Federal Regulations (CFR) governs Food and Drugs. Part 11 sets forth the 
criteria under which the Agency considers electronic records, electronic signatures, and handwritten 
signatures executed to electronic records to be trustworthy, reliable, and generally equivalent to paper 
records and handwritten signatures executed on paper, and states that such records should be validated, 
should produce a time-stamped audit trail of data modifications, should require electronic signatures and 
should restrict access to authorized users.  The REDCap Data Management system itself is validated by 
its developers. Additionally, the instruments and programming implemented for the PRIORITIZE registry 
will be validated to comply with the specified FDA recommendations. Validation of such systems 
documents that the system performs in an expected and predictable manner, and annual internal audits are 
performed to ensure compliance is maintained. 
 
The PRIORITIZE Data Management systems are compliant with multiple Federal standards designed to 
ensure the safety, security and integrity of sensitive information. 
 
14.5.3 Continuous Data Quality Monitoring 
To help minimize the frequency of errors, the Data Manager conducts routine and ad hoc meetings with 
the Clinical Monitoring and/or Abstraction Core staff to discuss any consistently observed deficiencies in 
the use of the data management system and abstracted data. The DCC team maintains regular contact with 
the CDAS staff to address identified deficiencies. Also, provision of timely data quality reports will be an 
important aspect of the Data Management function.  In addition to documenting exemplary performance, 
these reports will provide a basis for setting goals for high-quality data collection, and for tracking 
progress towards achieving those goals.  Data queries will be generated by the DCC team in order to 
identify problems on an on-going basis.  Such data checks will include, but are not limited to: 
• 
Frequencies on selected variables by CDAS, to identify differences in the application or 
interpretation of study protocol or abstraction conventions; 
• 
Tabulations and listings of incomplete or inconsistent responses on data collection forms; 
tabulations and listings of expected forms not received in a timely manner; and tabulations of 
clinical center error rates in data entry; 
• 
Analyses of digit preferences for clinical measurements (e.g., blood pressure, weight, height) and 
other evidence suggesting inadequate or erroneous data entry; and 
• 
The collection of repeated measures for quality control purposes as selectively implemented. 
 
14.6 Training & Certification of Chart Data Abstraction Specialists (CDAS) 
Designated CCC and Abstraction Core staff receive detailed protocol, REDCap and disease specific 
training as well as gain familiarity with the Study Reference Manual prior to being authorized for access 
to the PRIORITIZE data management system.  

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The DCC will monitor the centrally abstracted chart data from the data provided by all clinical sites 
through standard reporting and methods.  
 
14.7 Monitoring Activities 
DCC personnel in conjunction with the CCC closely monitor clinical center adherence to study protocol 
and data collection practices for complete and accurate research data.  Monitoring is performed following 
an established Data Management and Clinical Monitoring Plan to facilitate the smooth conduct of the study.  
DCC personnel will have access to all study and patient documents and to clinical center personnel.  All 
patient and study documents will be kept confidential.  Identifiers such as patient name and address can be 
viewed by the DCC or CCC to facilitate study processes, including remote monitoring, but these identifiers 
will not be included on any datasets used for data analyses.  
 
DCC personnel and CCC personnel meet regularly to discuss study status, recruitment, compliance with 
the protocol, clinical center participation, and other issues that arise during the course of the study. The 
DCC will provide statistical computations, reports, and recommendations to the Steering Committee.   
 
The PRIORITIZE registry team will commission qualified resources to conduct monitoring of the data.  
Clinical site visits and data monitoring will be performed in accordance with the Clinical Monitoring Plan 
(CMP) Monitors will inspect the operations to ensure that: 
• 
The protocol is followed and implemented in compliance with Good Clinical Practices; 
• 
Accurate and complete records are maintained; 
• 
Staff are trained, certified, and are performing the agreed-upon activities and not delegated to 
other unspecified staff. 
All monitoring activities will be completed with a formal, written report. The report will summarize the 
findings and highlight all recommendations and action items. 
15. HUMAN PARTICIPANT ISSUES 
This study will comply with the Department of Health and Human Services (DHHS) Federal Policy 
for the Protection of Human Research Subjects, reflected in HHS regulation 45 CFR 46.  This 
regulation includes the Common Rule and will rely on National Institutes of Health (NIH) 
GUIDANCE and its interpretation of the Common Rule.  PRIORITIZE will observe individual site IRB 
and federal requirements for protection of human subjects and fulfilment of HIPAA in the same 
manner as the established HCV-TARGET network.   
 
Personnel involved in conducting this study will be qualified by education, training, and experience 
to perform their respective tasks.  The assurance of each staff member’s education and training will 
be collected by the CCC regulatory director and/or qualified staff member and reviewed by the DCC 
monitors in accordance with ICH guidelines.   Specifically, a CV (evidencing qualifications of 
investigators and sub-investigators) and medical license will be required of all staff members 
providing medical care to subjects prior to participation in the trial.  A CV or equivalent form of 
verification of qualification to perform delegated duties will be required of all staff engaging in 
human subject research activities.  In accordance with PCORI requirements, all key personnel are 
required to provide proof of completion of the NIH Protection of Human Research Participants 
module or equivalent training prior to participation in the PRIORITIZE project.  The project 
manager, monitors of the DCC, and regulatory director will provide additional training and 

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education on the principles of Good Clinical Practice and protection of human research participants 
during site initiation visits and/or investigator meetings (in person and/or remote).  
 
Sites will be provided a template consent form to modify according to local regulations and 
requirements.  In order to ensure that site ICFs do not conflict with the template ICF and/or the 
protocol, the CCC regulatory staff will review all site ICFs prior to submission to local IRBs or Ethics 
Committee. Following review and approval of the site specific ICF, the study protocol, consent 
forms, and surveys/questionnaires will be submitted to each local IRB for review and approval.  
Any additional patient educational material specific to PRIORITIZE will also be submitted for 
approval prior to distribution.  A site may not engage in PRIORITIZE human subject research 
activities until IRB approval has been forwarded to the CCC and the DCC and CCC have confirmed 
the site for initiation of study activities.  
 
Given the epidemiology of HCV infection, participants enrolled in this study will include a diverse 
population including Black African Americans and Hispanics.   It is anticipated that males will be 
more frequently enrolled than women also reflecting the epidemiology of this disease. We 
anticipate that the participants recruited from multiple sources, including community and tertiary 
referral populations, will capture the entire spectrum of HCV infection. 
 
Consent for study participation will be obtained according to Section 6.1.  
 
15.1 Potential Benefits/Discomforts and Risks/Subject confidentiality 
 
Study sites and the CCC Chart Data Abstraction team will be responsible for the confidentiality of 
the data associated with participants in PRIORITIZE in the same manner they are responsible for 
the confidentiality of any patient information within their spheres of responsibility. In order to 
maintain subject confidentiality, all data forms used for the study data will be identified by a code.  
The link between the code and each subject will be kept in secure, password-protected file or 
locked files, if paper copy, accessible only to PRIORITIZE study staff.  Any printed records will be 
kept in locked files at study sites and CCC with access limited to PRIORITIZE study staff. All study 
staff will identify participants by the coded identifier number generated at the study site. Clinical 
information will not be released without written permission of the participant, except as necessary 
for monitoring by the IRB or DCC and centralized abstraction at the CCC. Participants grant 
permission to share research data with these entities in the consent document. Federal regulations 
govern the protection of patient’s rights relative to data confidentiality and use of research data.   
 
Consent procedures and forms, and the communication, transmission and storage of patient data 
will comply with individual site IRB and federal requirements for compliance with HIPAA.  The 
commercial central laboratory draw site and the associated testing facility may collect PHI from 
participants as part of the samples collection process.  
 
15.2 HIPAA Privacy Rule Elements of PHI 
Established in 1996, the U.S. Department of Health and Human services issued the Privacy Rule as 
part of the Health Insurance Portability and Accountability Act to establish a national set of standards 
for the protection of certain health information.  This rule protects all “individually identifiable health 

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information” held or transmitted by a covered entity or its business associate in any form or media 
whether electronic, paper, or oral.  A list of 18 Identifiers was established: 
 
1. Names 
2. All geographical subdivisions smaller than a State, including street address, city, county, 
precinct, zip code, and their equivalent geocodes, except for the initial three digits of a zip 
code, if according to the current publicly available data from the Bureau of the Census: (1) 
The geographic unit formed by combining all zip codes with the same three initial digits 
contains more than 20,000 people; and (2) The initial three digits of a zip code for all such 
geographic units containing 20,000 or fewer people is changed to 000. 
3. All elements of dates (except year) for dates directly related to an individual, including birth 
date, admission date, discharge date, date of death; and all ages over 89 and all elements of 
dates (including year) indicative of such age, except that such ages and elements may be 
aggregated into a single category of age 90 or older 
4. Phone numbers 
5. Fax numbers 
6. Electronic mail addresses 
7. Social Security numbers 
8. Medical record numbers 
9. Health plan beneficiary numbers 
10.  Account numbers 
11.  Certificate/license numbers 
12.  Vehicle identifiers and serial numbers, including license plate numbers 
13.  Device identifiers and serial numbers 
14.  Web Universal Resource Locators (URLs) 
15.  Internet Protocol (IP) address numbers 
16. Biometric identifiers, including finger and voice prints 
17.  Full face photographic images and any comparable images 
18.  Any other unique identifying number, characteristic, or code (note this does not mean the 
unique code assigned by the investigator to code the data) 
 
Records submitted for Centralized Abstraction and through RED-I are redacted for these PHI 
identifiers except for dates of service/activities.  In instances where a PHI identifier other than a date 
of service is present on a redacted record delegated CCC personnel will redact that information. 
 
Except where payment for research participation by the University of Florida’s Human Subject 
Payment (HSP) Program is prohibited, payment for participation in this research study will be 
handled through the University of Florida’s Human Subject Payment (HSP) Program. Subjects’ 
name, address, date of birth, and social security number will be recorded and maintained in a 
confidential and secure manner on University of Florida’s encrypted HSP system to facilitate 
compensation. This information will be reported to the appropriate University of Florida employees 
for making and recording the payment as required by law.  This information will be separated from 
health information via additional passwords and access limited to PRIORITIZE site coordinator(s), 
UF Hepatology Research Staff, and the University of Florida’s Human Subject Payment (HSP) 
Program.  Additionally, subjects will be randomly assigned a specific identification (ID) number to 
protect subjects’ identity. 
 

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16. DATA DISSEMINATION 
 
Our stakeholders – which include patients, patient organizations, public and private payers, 
government agencies, health systems, clinical practice guidelines committees, pharmacy benefit 
managers and specialty pharmacies – share a strong commitment to collaborating in multiple ways 
to ensure dissemination and implementation of the findings. Our stakeholders have been invited to 
partner during the study to: 1) inform their community of the study and provide updates; 2) attend 
the Quarterly Pragmatic HCV Assembly calls; and 3) share in disseminating results. Further, our 
HCV-Patient Engagement Group and Patient Organization Partnership Committee will work with 
and have representation on the Steering Committee to plan and ensure dissemination of the 
findings.  
In partnership with our stakeholders and in alignment with PCORI’s Dissemination & Implementation 
Framework, we envision a multifaceted approach to assess the evidence and plan for suitable 
dissemination and implementation activities that can inform care-related decisions in a rapid and 
contextually appropriate manner. We will be able to utilize data and feedback obtained through patient 
engagement activities, quarterly assembly calls, patient interviews, patient surveys and patient town halls 
to develop patient-centered dissemination strategies and communicate the final findings in 
understandable, usable language and materials. Dissemination to patients will include sharing findings 
through our nine patient organization partners, which include The Caring Ambassadors Hepatitis C 
Program, NATAP, and The Hepatitis C Support Project/HCV Advocate, among others. These patient 
organizations have a strong social media presence and produce information resources such as newsletters, 
websites, information packets and more. As examples of their reach, Jules Levin and NATAP have a 
listserv of more than 400,000 clients, and HCV Advocate receives 600,000 website hits per week. We 
will work closely with PCORI and stakeholders to ensure the responsible release of data in accordance 
with our statistical plan as well as PCORI’s process for the peer review and public release of research 
findings.  
HCV-TARGET has a well-established publication and dissemination plan to translate study findings for 
broad clinical communities, including non-specialists. We will publish in peer-reviewed scientific 
journals that play a key role in influencing practice guidelines and policy decisions. Importantly, our 
stakeholders include the professional societies responsible for updating U.S. treatment guidelines 
(AASLD, IDSA). In addition, Drs. Nelson, Fried and Sulkowski have developed multiple continuing 
medical education (CME) programs related to hepatitis C, with a focus on clinical implementation of new 
treatment regimens. CME programs are an important mechanism for disseminating findings to clinicians. 
A multicomponent dissemination strategy for clinicians also might include development of supporting 
communication materials, such as evidence summaries or decision aids. 
 
 
 
 
 
 
 
 
 
 

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17. REFERENCES 
 
1.Te HS, Jensen DM. Epidemiology of hepatitis B and C viruses: a global overview. Clin Liver Dis 
2010;14(1):1-21. 
 
2  Alter MJ. Epidemiology of hepatitis C virus infection. World J Gastroenterol 2007;13:2436-41. 
 
3 Alter MJ, Kruszon-Moran D, Nainan OV, McQuillan GM, Gao F, Moyer LA, Kaslow RA, Margolis HS. 
The prevalence of hepatitis C virus infection in the United States, 1988 through 1994. N Engl J Med 
1999;341:556-62. 
 
4 Rustgi VK. The epidemiology of hepatitis C infection in the United States. J Gastroenterol 
2007;42:513-21. 
 
5 Weiss, JJ, Adherence in the Age of HCV Antiviral Therapy, Presented at ICVH2014 
 
6 Smith BD, Morgan RL, Beckett GA, Falck-Ytter Y, Holtzman D, Teo CG, Jewett A, Baack B, Rein DB, 
Patel N, Alter M, Yartel A, Ward JW; Centers for Disease Control and Prevention. Recommendations 
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