The Patient-Reported Outcomes Project of HCV-TARGET (PROP UP)
Conditions: Hepatitis C, Chronic, Liver Diseases
Sponsor: University of North Carolina, Chapel Hill

The Patient‐Reported Outcomes Project of HCV‐TARGET ("PROP UP") 
NCT02601820
May 13,2016 

 
  
 
 
 
Study Protocol, version 1.0, 30Aug2015, PROP UP 
Revised Protocol, Version 2.0, 24Sep2015, PROP UP 
Revised Protocol, Version 3.0, 13May2016, PROP UP 
 
 
The Patient-Reported Outcomes Project of HCV-TARGET ("PROP UP") 
PCORI Contract# CER-1408-20660 
  
 
 
 
Lead PI: 
Donna M. Evon, PhD 
8010 Burnett-Womack, CB#: 7584 
Division of Gastroenterology and Hepatology 
University of North Carolina 
Chapel Hill, NC 27599-7584 
Telephone: (919) 966-6732 
Email: Donna _Evon@med.unc.edu 
 
 
 
Co-PIs: 
Michael W. Fried, MD 
8015 Burnett-Womack, CB#: 7584 
Division of Gastroenterology and Hepatology 
University of North Carolina 
Chapel Hill, NC 27599-7584 
Telephone: (919) 966-2516 
Michael_Fried@med.unc.edu 
 
 
 
Carol E. Golin, MD 
725 Airport Rd, CB#: 7590  
Division of General Medicine and Clinical Epidemiology, UNC School of Medicine  
Department of Health Behavior, Gillings School of Global Public Health 
Chapel Hill, NC 27599 -7590 
Telephone: (919) 966-7939 
 
 
Carol_Golin@med.unc.edu 
 
 

 
  
DOCUMENT HISTORY 
 
Document 
Date of Issue 
Summary of Changes 
Revised Protocol, 
Version 3.0 
13May2016 
Based on the current landscape of HCV treatment options and 
feedback from investigators and the research team, the following 
changes/modifications will be incorporated into the PROP UP 
protocol:  
 
 
Based on changes/anticipated changes in treatment 
practices, the scope of this study has changed in order to 
capture the most accurate information on recent treatment 
practices. The brief summary has been updated to reflect the 
overall changes in the study protocol. 
 
Updated Section 1.0, Introduction, to reflect recent changes 
in HCV treatments. Several new DAA medications have been 
FDA approved but not extensively evaluated for long-term 
outcomes using patient reported outcomes. 
 
Updated Section 2.0, Study Rational, to describe that PROP 
UP will evaluate, characterize and compare the short-term 
and long-term harms and benefits associated with several 
HCV treatment regimens. 
 
Updated Section 3.1, Specific Aims, to reflect the 
fundamental protocol changes. The study will be focused on 
characterizing several HCV treatment regiments in terms of 
many harms and benefits captured via patient-reported 
outcomes collected before, during and after HCV treatment. 
o Updated Aim 1 to explain the study will evaluate 
changes from baseline to time points during treatment 
in order to characterize harms associated with each 
of the treatments. The study uses several different 
measures, and adds patient-reported pre-existing 
medical conditions to list of the measures.  
o Updated Aim 2. This aim will evaluation the difference 
in medication adherence between patients with and 
without a history of mental health/substance abuse by 
evaluating different measures as explained in the 
protocol. 
o Updated Aim 3 to characterize short-term benefits of 
cure in the combine sample of patients. 
o Updated Aim 4 to include pre-existing medical 
conditions and HCV-functional status, and the 
differences in all measures between patients with and 
without cirrhosis on various treatment regimens. 
 
Added Section 3.2, Auxiliary Aims to describe that the study 
will examine a number of benefits and harms associated with 
DAA treatment and viral cure as described in the previous 
aims as well as use the data to examine similarities and 
differences between treatment regimens using causal 
inference methods. 

 
  
 
Updated Section 4.2, Clinical Collaborating Settings, to 
include ninth site, UC-Davis in Table 1: Location of Liver 
Centers Participating in PROP UP. 
 
Updated Section 4.31. Inclusion Criteria, with expanded 
inclusion criteria. Any HCV genotype is now eligible. Patients 
on the follow regimens are also eligible: sofosbuvir/ledipasvir 
(Harvoni®) with or without ribavirin, 
ombitasvir/paritaprevir/ritonavir with dasabuvir (Viekera 
Pak®), VPK) with or without ribavirin, elbasvir/grazoprevir 
(Zepatier®) with or without ribavirin, daclatasvir/sofosbuvir, 
with or without ribavirin (DAC/SOF), sofosbuvir/velpatasvir 
(SOF/VEL). 
 
Updated section 4.3.2, Exclusion Criteria, to emphasis that 
patients participating in a pharmaceutical-sponsored trial of 
hepatitis C treatment will not be eligible. 
 
Updated section 8.1, Procedures for Baseline PRO Data 
Collection, to add a sentence that participants will be 
reminded their answers are confidential before each survey. 
Also added that participants may complete surveys over the 
phone with research coordinator as needed at baseline. 
 
Updated Table 2 in Section 8.2, Procedures for Baseline 
Collection of Clinical and Lab Data for the following: (a) add 
the new treatment regimens and prescribed treatment 
duration of 16 weeks, (b) update HIV status to collect HIV 
test conducted and HIV results status, (c) add stigma scale. 
 
Updated Section 12.0, Participant Reimbursement, to reflect 
that UNC or subsites will reimburse subjects, aided by the 
REDCap system and records of reimbursement should be 
retained by the party responsible for paying the participant. 
 
Updated Table 5 in Section 13.0, Clinical and Lab Data 
Collection at 12 Weeks Post-Treatment top add 16 weeks or 
other to Actual Treatment Duration in the table. 
 
Updated Section 15.0, sub-sections 15.2 through 15.10 have 
been overhauled to reflect overall changes in the statistical 
analysis plan for this study. Updates include: description of 
the analysis of PRO changes from baseline as a function of 
subgroup and/or treatment regimen, description of the 
supportive longitudinal analysis and interpretation of changes 
from baseline, strategies for analysis of subgroup 
heterogeneity of treatment effects, and an overview of the 
four planned milestone manuscripts from this dataset. 
 
Updated Section 15.12, Overview of Sample Size 
Considerations, to adjust the sample size considerations. 
 
Added Appendix for Sample Size Analyses on page 34 of the 
protocol to provide tables and graphs to supplement the 
statistical analysis plan for the study. 
 
Updated protocol with grammatical and minor content 
clarification changes through the entire document. 
 
 

 
  
 
 
Revised Protocol, 
version 2.0 
23Sep2015 
Based on Investigator feedback from a recent Site PI conference call 
on 22Sep2015, the following changes/modifications will be 
incorporated into the protocol: 
 
 
Based on current treatment guidelines, the protocol is being 
updated to include the enrollment of patients who are 
prescribed any “Harvoni-containing regimen” (e.g., Harvoni + 
Ribavirin). Section 4.3.1: Inclusion Criteria, Section 4.3.3: 
Discontinuation of Subjects from Study, Section 2: Study 
Rationale, Section 3: Study Aims, Section 6: Recruitment, 
and Section 8.2: Table 2 - Clinical and Laboratory Data 
Collection at Time of Consent have all been updated to 
reflect this change. 
 
Clinical judgment suggests that some patients may tend to 
under-report infectious disease status, specifically HIV.  The 
study will continue to collect patient-reported HIV status, but 
will also confirm HIV status via the patient’s medical record 
and extraction the HIV antibody (Anti HIV) for verification. 
Section 8.2: Table 2 - Clinical and Laboratory Data Collection 
at Time of Consent has been update to reflect this change. 
 
Based on clinical experience at each site, it may take up to 
90 days to receive prior authorization of medications and for 
patients to initiate treatment. The baseline PRO assessment 
window will therefore be increased from 45 to 90 days prior 
to start of treatment to allow adequate time for treatment 
approvals and initiation of therapy.   Section 8.1: Procedures 
for Baseline PRO Data Collection, Section 9: Enrollment 
Criteria and Section 10: PRO Data Collection Time Points 
have been updated to reflect this change. 
 
The language has been clarified that patients must be 21 
years of age or older (no upper limit) to be included in the 
study. The Brief Summary, Section 4.3: Study Population and 
Section 4.3.1: Inclusion Criteria have been updated to reflect 
this change. 
 
Based on site feedback and in order to reduce missing data 
points from baseline assessment, the timeframe for valid 
HCV Viral Load has been expanded from 3 months to 12 
months prior to consent.  The timeframe for valid Aspartate 
Aminotransferase, Alanine Aminotransferase, Albumin, Total 
Bilirubin, Creatinine, International Normalized Ratio, Platelets 
and Hemoglobin lab tests has been expanded from 3 months 
to 6 months prior to consent.  HCV genotype is not time-
sensitive; most recent test should be extracted. Section 8.2: 
Table 2 - Clinical and Laboratory Data Collection at Time of 
Consent has been update to reflect this change. 
 
Original Protocol, 
version 1.0 
30Aug2015 
Not applicable 
 
 

 
  
CONFIDENTIALITY STATEMENT 
 
This PROP UP study protocol is the confidential and proprietary information of the University of North Carolina at 
Chapel Hill (UNC). By reviewing this document, the investigator agrees to keep it confidential and to use and disclose 
it solely for the purpose of conducting PROP UP. Permitted disclosures will be made only on a confidential basis 
within your institution or to your IRB. Any other use, copying, disclosure or dissemination of this protocol is prohibited 
unless authorized by the UNC investigators. Supplemental information that may be added to this protocol during the 
study is also confidential. Please provide a copy of this study protocol to research personnel who will be directly 
working on the PROP UP study.  
 
 

 
  
BRIEF SUMMARY 
Title of Study: The Patient-Reported Outcomes Project of HCV-TARGET ("PROP UP") 
 
Newer, more effective all-oral regimens for hepatitis C viral (HCV) infection have been approved in recent years and 
more are expected in the future. Minimal patient-centered outcome research (PCOR) data are currently available for 
the majority of these new drug regimens and enormous evidence gaps remain. In-depth information about these 
regimens is critical to informed decision-making, patient-provider communication, and patient adherence. Regimens 
may be relatively similar on SVR rates, but may differ on other short-term and long-term harms and benefits that 
matter to patients making treatment decisions. Data collected from pharmaceutical-sponsored trials do not provide all 
the answers, nor do their data represent what will happen when a broad spectrum of patients are treated in real-world 
practice. Trials also exclude vulnerable subgroups, focus mainly on short-term efficacy and clinician-rated adverse 
events, rarely obtain the patient’s perspective, and do not investigate long-term harms of treatment or benefits of viral 
cure. Therefore, obtaining the requisite information in order to make informed decisions may prove challenging to 
patients and providers. Given these limitations, patient-centered outcomes research (PCOR) studies that evaluate 
short-term and long-tern treatment harms and benefits that matter most to patients, are needed. 
 
PROP UP is funded by The Patient Centered Outcomes Research Institute (PCORI). PROP UP is a multi-centered 
patient-centered outcomes study designed to evaluate, characterize, and compare several patient-reported outcomes 
(PROs) during and after treatment for HCV with newly approved all-oral regimens. PROP UP uses a prospective, 
observational cohort study design to collect PRO data before, during and after HCV treatment to rigorously evaluate 
HCV-associated symptoms, treatment side effects, medication adherence, out of pocket costs, and long-term benefits 
of cure and harms of treatment in various HCV treatment regimens and among important patient subgroups. PROP 
UP was designed with significant involvement from patients with the disease and is a collaborative effort between 
behavioral and biomedical researchers, a HCV Patient Engagement Group (HCV-PEG), and a patient advocacy 
organization (HCV Advocate).  
 
Nine U.S. liver centers will collaborate to conduct PROP UP. Approximately 1920 patients diagnosed with chronic 
HCV will be consented and will complete baseline PRO assessments. Patients who are 21 years of age, infected with 
chronic HCV, and prescribed one of several directing acting antiviral (DAA) treatment regimens for chronic HCV will be 
recruited. We anticipate that approximately 15%-20% of the 1920 patients who are consented will not commence HCV 
therapy, primarily due to insurance denials. Therefore we intend to enroll 1600 patients into longitudinal data 
collection. Enrollment criteria will include informed consent, completion of baseline PRO surveys, and administration of 
one dose of a prescribed regimen. These 1600 participants will be followed up to 1 year after HCV treatment ends. 
Participants will complete several PRO surveys at the following 5 assessment periods: (T1) Baseline, (T2) week 4 on-
treatment, (T3) last 2 weeks on-treatment, (T4) 3 months post-treatment, and (T5) 12 months post-treatment for a total 
study duration of up to 20 months. PRO survey data will be collected via 3 options, selected by each participant: 
personal technology (home computer, tablet, smartphone) into web-based data capture system; phone-administered 
surveys with the UNC Call Center; or as a last resort, computer at regular clinic visits. PROs surveys are designed to 
measure HCV-associated symptoms, pre-existing conditions, treatment side effects, functional status, medication 
adherence, and out of pocket costs.  
 
Longitudinal data collection of multiple novel PROs before, during and after treatment for HCV are being collected to 
better understand a variety of issues that are important to patients, clinicians, and stakeholders. Specifically, we will 
evaluate: (a) prevalence of pre-existing baseline symptoms associated with HCV; (b) the development of new onset 
treatment side effects and exacerbation of pre-existing symptoms during HCV treatment; (c) medication adherence 
and out of pocket costs related to HCV treatment; (d) changes in HCV-associated symptoms and functional status in 
patients who are cured; and (e) long-term patient-reported harms associated with treatments and long-term benefits 
associated with viral cure.  
 
Study results will be disseminated via partnership with patient advocacy organizations and the HCV-TARGET network, 
as well as through traditional scholarly output. The findings from this study will help patients, providers, and 
stakeholders involved in decision-making by providing them with novel information they need to decide whether or not 
to proceed with HCV treatment and if so, what the short-term and long-term benefits and harms of HCV treatment, 
may be.   
 

 
  
 
TABLE OF CONTENTS 
 
TITLE PAGE ................................................................................................................................................... 2 
DOCUMENT HISTORY .................................................................................................................................. 3 
CONFIDENTIALITY STATEMENT ................................................................................................................. 6 
BRIEF SUMMARY .......................................................................................................................................... 7 
TABLE OF CONTENTS .................................................................................................................................. 8 
1 
 INTRODUCTION ............................................................................................................................. 10 
2 
STUDY RATIONALE ........................................................................................................................ 11 
3 
STUDY AIMS .................................................................................................................................... 11 
4 
STUDY DESIGN ............................................................................................................................... 13 
4.1 Observational Study Design ............................................................................................................... 13 
4.2 Clinical Collaborating Settings ............................................................................................................ 13 
4.3 Study Population ................................................................................................................................ 14 
4.3.1    Inclusion Criteria ................................................................................................................. 14 
4.3.2 
Exclusion Criteria ................................................................................................................ 14 
4.3.3 
Discontinuation of Subjects from Study .............................................................................. 14 
5  
REDCap DATA COLLECTION ......................................................................................................... 14 
6  
RECRUITMENT ................................................................................................................................ 15 
7 
INFORMED CONSENT .................................................................................................................... 15 
8  
DATA COLLECTION PROCEDURES AT CONSENT/BASELINE VISIT ......................................... 15 
8.1 Procedures for Baseline PRO Data Collection ................................................................................... 15 
8.2 Procedures for Baseline Collection of Clinical and Lab Data ............................................................. 17 
9  
ENROLLMENT CRITERIA ................................................................................................................ 17 
10 
PRO DATA COLLECTION TIME POINTS ........................................................................................ 17 
11 
PRO DATA COLLECTION PROCESS ............................................................................................. 18 
11.1 Data entry via participant home-based computer/tablet/smartphone ............................................... 18 
11.2 Data entry via UNC Centralized Call Center phone interviews ......................................................... 18 
11.3 Data entry via computer during regular clinic visit ............................................................................ 18 
11.4 PRO Data Assessment Time Schedule ............................................................................................ 19 
12  
PARTICIPANT REIMBURSEMENT .................................................................................................. 19 
13  
CLINICAL AND LAB DATA COLLECTION AT 12 WEEKS POST-TREATMENT ............................ 20 
14 
MEASURES: PATIENT-REPORTED OUTCOMES SURVEYS........................................................ 20 
14.1 Memorial Symptom Assessment Scale (MSAS) (Aims 1a, 3a, 4a) .................................................. 20 
14.2 PROMIS short forms (Aim 1b, 3a, 4b) .............................................................................................. 20 
14.2.1 
PROMIS short forms to measure HCV-associated symptoms ........................................... 21 
14.2.2   PROMIS short forms to measure treatment side effects .................................................... 21 
14.3  Headache Impact Test (HIT) to measure headache as a treatment side effect .............................. 21 
14.4  HCV-PRO to measure well-being and functioning (Aim 1c, 3b, 4d) ................................................ 21 

 
  
14.5  Out of Pocket Costs survey to measure costs of treatment reported by patients (Aim 1e) ............. 21 
14.6  Voils Medication Adherence Survey (VMAS) to measure medication adherence (Aim 1f) ............. 21 
14.7  Sociodemographic Survey ............................................................................................................... 22 
14.8  Psychiatric and Substance Abuse History ....................................................................................... 22 
15 
STATISTICAL ANALYSIS STRATEGY ............................................................................................ 22 
15.1 Analysis plans registered in the master protocol document .............................................................. 22 
15.2 Strategy for analysis of PRO change from baseline as a function of subgroup and/or treatment regimen
 22 
15.3 Supportive longitudinal analysis and interpretation of changes from baseline ................................ 22 
15.4 Strategy for analysis of subgroup heterogeneity of treatment effects (HTE) .................................... 23 
15.5 Overview of Plans for Manuscript #1: Change in Treatment Side Effects from T1 to T2/T3 ............ 23 
15.6  Overview of Plans for Manuscript #2: Medication Adherence during T1 to T2/T3 .......................... 23 
15.7  Overview of Plans for Manuscript #3: Benefits of Achieving SVR ................................................... 24 
15.8  Overview of Plans for Manuscript #4: Long-term Benefits / Harms ................................................. 25 
15.9 No Interim Analysis .......................................................................................................................... 25 
15.10  Role of Causal Inference Methods ................................................................................................. 25 
15.11 Methods for Coping with Missing Data ............................................................................................ 26 
15.12 Overview of Sample Size Considerations ....................................................................................... 26 
16 
STUDY CONDUCT ........................................................................................................................... 28 
16.1  Ethics ............................................................................................................................................... 28 
16.2  Responsibilities within the Study ..................................................................................................... 28 
16.3  Reports and Publications ................................................................................................................. 29 
16.4  Database Retention and Archiving .................................................................................................. 29 
17 
DATA SAFETY MONITORING BOARD (DSMB).............................................................................. 29 
18 
DATA AND STUDY MONITORING PLAN (DSMP) .......................................................................... 29 
19 
PATIENT SAFETY AND MONITORING PLAN (PSMP) ................................................................... 29 
19.1  Standard Medical Care .................................................................................................................... 29 
19.2  Risks of Study Participation ............................................................................................................. 30 
19.3  Handling of Non-Study Related Harms or Adverse Events ............................................................. 30 
19.4  Handling of Study-related harms or unanticipated adverse events ................................................. 30 
20 
PROP UP RESEARCH TEAM .......................................................................................................... 31 
GLOSSARY OF TERMS AND ABBREVIATIONS ........................................................................................ 31 
References ................................................................................................................................................... 33 
Appendix for Sample Size Analyses ............................................................................................................. 36 
 
 

 
  
  
1  INTRODUCTION 
 
Chronic Hepatitis C virus (HCV) causes numerous liver-related complications and death, leading to tremendous 
burden on millions of people and the US healthcare system1-3. HCV kills >12,000 people per year in the US from 
liver-related complications such as liver failure, cirrhosis, liver cancer4. Over the course of 20-30 years, 20% of 
patients will develop life-threatening cirrhosis and 10% will develop liver cancer5. Morbidity and mortality rates 
are expected to increase dramatically in the next few decades as Baby Boomers suffer the long-term 
consequences of HCV6. 
 
People infected with chronic HCV also frequently suffer from chronic, systemic symptoms, other chronic 
conditions, and poorer quality of life, compared to the general US population7,8. In addition to liver-related 
morbidity and mortality, many people with HCV complain of diffuse physical (e.g., fatigue, abdominal pain, 
nausea, poor appetite, joint/muscle achiness) and neuropsychiatric symptoms (e.g., mental fatigue, depression, 
irritability, insomnia, cognitive impairment)9. Many patients with HCV also have higher rates of comorbid 
conditions (e.g., psychiatric, addiction, diabetes, skin, HIV, renal) compared to the general population2,9-12. Not 
surprisingly, people with HCV report poorer health-related quality of life (HRQOL) on many domains of functioning 
compared to their healthy counterparts. This relationship remains significant even after controlling for substance 
abuse history13,14. The reasons for poor HRQOL are complex and likely multi-factorial, but may include symptoms 
due to chronic systemic viral inflammation of the central nervous system, comorbid conditions, feelings of social 
stigma, and constant health-related anxiety and uncertainty that their health will deteriorate in the future8-10,13,15-
17. 
 
Antiviral treatment for chronic HCV can permanently eliminate the virus. Patients who successfully complete 
treatment can achieve a sustained virological response (SVR) or “viral cure” 12 weeks after treatment ends. 
SVR is associated in some patients with reversal of liver damage, and reductions in liver disease, liver-related 
death, and death due to all causes (e.g., cardiovascular, diabetes)18-20. In addition, SVR is associated with 
improvements in HRQOL and the symptom of fatigue at 3 months post-treatment21,22.  Importantly, many other 
benefits that may accompany viral cure have not been evaluated.   
 
In the last 3 years, several new DAA medications have been FDA-approved for the treatment of chronic HCV 23-
26. Other medications for the treatment of HCV are expected to be approved in 2016. Cure rates have typically 
been between 70% - 90% in phase III drug trials, depending on patient characteristics such as genotype and 
cirrhosis status27. Treatment lasts between 8 and 24 weeks as opposed to previous interferon-based regimens 
of 24 or 48 weeks. These newly-approved all-oral regimens appear much more tolerable and efficacious in 
phase III trials, compared to previous interferon-based regimens. 
 
These exciting, newly-approved regimens have not been extensively evaluated, particularly with regard to 
issues that patients care about or longer-term harms and benefits. Differences between specific subgroups of 
patients have also not been evaluated. Although cure rates are relatively high and side effects fewer and less 
severe than prior interferon regimens, treatment side effects still exist and may be different between regimens, 
especially in vulnerable subgroups (e.g., those with cirrhosis, mental health or substance abuse issues). 
Moreover, the only treatment harms measured in previous trials were captured as clinician-reported adverse 
events (AEs), as opposed to patient reported. Fatigue, headache, nausea, insomnia, body weakness, diarrhea 
and rash were reported as AEs in >10% of participants in previous drug trials. Previous research demonstrates 
that clinician-reported AEs often underestimate the patients’ experience of side effects. Since most symptoms 
and side effects are a highly subjective, personal experience, the correlation between clinician-reported and 
patient-reported side effects is often quite low28. Finally, patients care about long-term benefits of being cured 
and whether symptoms associated with HCV attenuate, but few studies address these patient-centered 
outcomes. Therefore, outcomes chosen by, and reported by patients with the disease, are needed. 
 
Currently, major evidence gaps exist that significantly limit our understanding of the short-term and long-term 
harms and benefits of these new treatments and thus, patients and clinicians ability to make informed  treatment 
decisions. Patient-centered outcomes research (PCOR) studies are needed to ensure that patients and clinicians 
understand all of the short term and long-term harms and benefits of these new regimens. The only data currently 

 
  
available are from phase III clinical trials, which have inherent limitations: First, clinical trials notoriously under-
represent or exclude many subgroups, such as patients with cirrhosis, psychiatric and addiction conditions, so-
called ‘high risk’ patients. Phase III trials included between 0% and 20% of patients with cirrhosis; yet, these 
patients have the greatest need for treatment. Over 60% of HCV patients seeking treatment in clinical practice 
have psychiatric or addiction issues29,30, yet these patients are often excluded from clinical trials. Thus, clinical 
trials data do not represent the broad spectrum of patients seeking treatment and do not reflect what happens in 
real-world clinical settings31. Secondly, phase III clinical trials do not provide any comparison of different regimens 
or important patient subgroups, such as those with psychiatric or addiction histories. Third, clinical trials have 
focused narrowly on short-term efficacy (SVR) and AEs, but have not captured additional information that is 
important to patients. Fourth, the short-term harms of treatment in clinical trials have usually been captured via 
clinician-reported adverse events. Research in other medical populations demonstrates that clinical data under-
represent the frequency and severity of side effects compared to patient-reported experiences28. To date, no 
PCOR studies have been conducted to characterize, evaluate, and compare different treatment options or patient 
subgroups on PROs that are of great interest to patients and stakeholders. The sparse PRO data that has been 
published thus far were derived from drug trials, focused only on health-related quality of life (HRQOL) and one 
symptom (fatigue), and did not fully evaluate nor compare treatment regimens or patient subgroups22,32. Finally, 
because clinical trials are focused on short-term efficacy and safety, they do not capture longer term benefits of 
cure or harms of treatment that are also extremely important for patients to consider when making decisions 
about treatment.  
 
2 
STUDY RATIONALE 
 
PROP UP is a multi-site prospective observational PCOR study that will evaluate, characterize, and compare 
several short-term and long-term harms and benefits associated with several HCV treatment regimens. The 
PCOR study proposed by PROP UP is unique, powered by patients affected by HCV, and will provide novel 
information for patients, clinicians, and stakeholders to enhance informed decision-making about HCV 
treatment.  
 
In this study, we will collect information directly from the patients via PRO surveys measuring symptoms 
associated with HCV, co-morbid medical conditions, side effects associated with treatment, functional status, 
and out of pocket costs and medication adherence during treatment. This information will allow us to better 
evaluate and characterize HCV symptoms that are present at baseline, symptoms that remit after viral cure, 
treatment side effects/toxicity associated with various treatment options, long-term harms that may be 
associated with treatment, and benefits associated with viral cure.  
 
Study results will be disseminated rapidly via partnership with patient advocacy organizations and the HCV-
TARGET network, as well as through traditional scholarly output. The findings from this study will be useful to 
patients, their families, providers, and stakeholders who are involved in decision-making about whether or not to 
proceed with HCV treatment, and if so, what the short-term and long-term benefits and harms of HCV 
treatment, may be.  
 
 
3 
STUDY AIMS 
 
3.1 Specific Aims 
This study is focused on characterizing several HCV treatment regimens in terms of HCV-associated 
symptoms, treatment side effects, medication adherence, out of pocket costs, and long-term benefits of cure 
and harms associated with all-oral treatments for chronic hepatitis C, as indicated by the following patient-
reported outcomes (PROs) collected before, during and up to one year after HCV treatment:  
 
Aim 1: Evaluate changes from baseline (T1) to during treatment (T2, T3) to characterize harms associated with 
each treatment regimen (see manuscript #1 below) in terms of the following measures: 
 1a. The Memorial Symptom Assessment Scale (MSAS) 33,34 
 1b. Specific side effects as measured by multiple PROMIS surveys33 

 
  
 1c. HCV-specific functional status as measured by the HCV-PRO34,35 
 1d. Pre-existing medical conditions 
 1e. Cumulative out of pocket costs during treatment 
 
Aim 2: Evaluate differences in medication adherence between patients with and without history of mental 
health/substance abuse (MH/SA Hx) (see manuscript #2 below) 
 2a. Characterize and compare the two groups (with and without MH/SA Hx) on medication adherence while 
accounting for treatment regimen and pill burden.  
 2b. Estimate the effects of pill burden on medication adherence in the combined sample. 
 2c. Estimate the prevalence rates of reasons for nonadherence in the combined sample.  
 2d. Estimate the effect of medication adherence on the SVR rate at 3 months post-treatment.  
 
Aim 3: Evaluate changes from baseline (T1) to 3 months after end of treatment (T4) to characterize short-term 
benefits of cure in the combined sample of patients (see manuscript #3 below) 
 3a: Amelioration of HCV-associated symptoms as measured by the MSAS and PROMIS surveys 
 3b. HCV-functional status as measured by the HCV-PRO 
 
Aim 4: Evaluate changes from baseline (T1) to 1 Year (T5) after end of treatment to characterize long-term 
benefits or harms (see manuscript #4 below) 
 4a. Long-term symptoms as measured with the MSAS 
 4b. Long-term side effects as measured by PROMIS surveys  
 4c. Pre-existing medical conditions 
 4d. HCV-functional status, as measured by the HCV-PRO 
 4e. Differences in 4a-4d between patients with and without cirrhosis 
 
3.2 Auxiliary Aims 
The main objective of this study is to characterize a number of benefits and harms associated with DAA treatment 
and viral cure as described in Aims 1-4. However, we will also take the opportunity to examine similarities and 
differences between the treatment regimens using causal inference methods (see manuscripts #1 and #3 below.)     
 
Planned Manuscripts to Address Specific Aims 1-4
Analysis 
Aim 1: 
Treatment  
Side Effects 
Manuscript describing PRO changes from baseline to during treatment to characterize 
each regimen in terms of treatment harms such as side effects (T2/T3 data). Auxiliary 
analyses will compare regimens.
page 
22,25-26 
Aim 2: 
Medication 
Adherence 
Manuscript on medication adherence will compare patients with and without history of 
mental health/substance abuse, characterize the effects of adherence on SVR rate, 
explore reasons for nonadherence, and evaluate effects of pill burden on adherence.
page 
22,25-26 
Aim 3: Benefits 
of achieving 
SVR 
Manuscript evaluating changes from baseline to 3-months post-treatment (T4) in HCV 
symptoms and other PROs in patients who achieve SVR to characterize short-term 
benefits of cure. The main analysis will characterize change in PROs for the total 
sample and auxiliary analyses will explore differences between regimens.  
page 
23,25-26 
Aim 4: Long-
term 
Benefits/Harms  
Report of long-term patient reported harms and benefits associated with HCV 
treatment at 1 year post-treatment. Evaluate changes in PROs from baseline to T5, 
and evaluate differences between patients with and without cirrhosis. Auxiliary 
analyses will explore differences between regimens. 
page 
23,25-26 
PRO 
Psychometrics 
Manuscript to evaluate the psychometric properties of several PROs (HCV-PRO, 
MSAS, PROMIS) in the HCV population
 
Study Protocol 
Manuscript describing the PROP UP study design, methodology, and protocol 
Baseline 
Characteristics 
Manuscript describing baseline patient characteristics of the study sample, including 
HCV-associated symptoms, pre-existing medical conditions, and functional status. 
 
 
 

 
  
4 
STUDY DESIGN 
 
4.1 Observational Study Design 
 
This is a multi-center, longitudinal prospective, observational PCOR study that will provide 
characterizations and comparisons in terms of specific short-term and long-term PROs during and 
following DAA treatment for chronic HCV. These PROs were selected after qualitative interviews with 
patients and significant involvement of a patient engagement group. UNC-CH (PIs: Evon, Fried, Golin) is 
the lead site and the Data Coordinating Center (DCC).  
 
No drug therapy will be administered by the research team. The study does not require drawing blood, 
performing lab tests, biological monitoring, or conducting physical exams. This observational study is 
designed to assess patient experiences in “real world” settings and hence to follow the timing and 
procedures for patients managed in a manner consistent with the standard of care for HCV treatment. 
The maximum study duration is up to 20 months, depending on length of prescribed treatment regimen.  
  
PRO evaluation and data collection will occur on 5 occasions before, during and after HCV treatment. 
Participants will provide responses to several PRO surveys that measure HCV symptoms, treatment 
side effects, functional status, medication adherence, and out of pocket costs.  Participants will self-
select their preferred mode of responding to surveys in the web-based data capture system: (1) via 
home computers, tablet or smartphone; (2) via phone interview with research staff, or (3) via computer 
during clinic visit with assistance of research staff (if needed). Clinical and lab data will be entered by 
site research coordinators at T1 baseline and at T4: 12-weeks post-treatment.  
 
4.2 Clinical Collaborating Settings 
   
Nine clinical liver centers in the U.S. (Table 1) most of whom are part of the HCV-TARGET research network will 
participate. Each site will have a designated site PI/hepatologist and Research Coordinator(s) (RC) dedicated to 
the study. Each site will be under the jurisdiction, and report to, their own Institutional Review Board (IRB).   
 
Table 1: Location of Liver Centers Participating in PROP UP 
 
Institution 
Location 
Principal Investigator(s)
Type of Center
Rush University 
Chicago, IL 
Nancy Reau, MD
Clinical 
St. Louis 
University 
St Louis, MO 
Adrian Di Bisceglie, MD 
Clinical 
University of 
Florida 
Gainesville, 
FL 
David Nelson, MD 
Clinical 
University of 
Michigan 
Ann Arbor, MI 
Anna Lok, MD 
Clinical  
University of 
North Carolina 
Chapel Hill, 
NC 
Donna Evon, PHD 
Michael Fried, MD  
Carol Golin, MD
Clinical, Data 
Coordinating 
Center 
University of 
Pennsylvania 
Philadelphia, 
PA 
Rajender Reddy, MD 
Clinical 
Virginia 
Commonwealth 
University 
Richmond, 
VA 
Richard Sterling, MD 
Clinical  
Yale University 
New Haven, 
CT 
Joseph Lim, MD 
Clinical 
UC-Davis 
Davis, CA 
Souvik Sarkar, MD
Clinical 

 
  
 
 
4.3 Study Population 
 
Based on >4000 patients previously enrolled in HCV-TARGET, we anticipate patients being 21 years of age 
and older,  62% male, 14% African-American, 6% Hispanic, and about 50% may have cirrhosis. Investigators 
will consent and collect baseline PRO data for approximately 1920 patients who are prescribed an all-oral, 
interferon-free, treatment regimen for HCV by a liver provider. Approximately 15%-20% of those consented and 
who complete baseline PROs (~320 patients) may not be approved by insurance payors to start HCV treatment, 
and thus will not qualify to participate in the longitudinal study. We will enroll 1600 patients who meet the 
following three enrollment criteria to participate in the longitudinal study: (1) provide written consent; (2) 
complete baseline PRO surveys; and (3) take one dose of medication.  
 
 4.3.1    Inclusion Criteria 
1. Diagnosed with chronic HCV, any genotype 1-6 
2. English-speaking 
3. Age 21 or older 
4. Medically cleared and being prescribed one of the following DAA regimens: 
a. sofosbuvir/ledipasvir (Harvoni®) with or without ribavirin 
b. ombitasvir/paritaprevir/ritonavir with dasabuvir (Viekera Pak®), VPK) with or without 
ribavirin 
c. elbasvir/grazoprevir (Zepatier®) with or without ribavirin 
d. daclatasvir/sofosbuvir, with or without ribavirin (DAC/SOF) 
e. sofosbuvir/velpatasvir (SOF/VEL) 
 
4.3.2 
Exclusion Criteria  
1. Inability to provide written informed consent 
2. Currently participating in a pharmaceutical-sponsored drug trial of hepatitis C treatment  
3. Major cognitive or mental impairment 
4. Unable to read or speak English 
5. Unwilling or unable to complete survey questionnaires 
 
Pregnant and breastfeeding women are not treated with antiviral medications due to teratogenic effects, and 
therefore will not be included in the study population. 
 
4.3.3 
Discontinuation of Subjects from Study 
Subjects who are consented and complete baseline data, but who do not commence therapy within 90 
days will fail to qualify for the longitudinal study. Once participants commence therapy and are officially 
enrolled, we do not anticipate any reason to withdraw subjects from the study after that time. If a 
patient commences therapy but is prematurely discontinued from therapy, he/she will be encouraged 
to continue in the study and complete the remaining assessments.  
 
Participants will be discontinued from the study for the following reasons: 
 
 
If a participant withdraws informed consent verbally or in writing 
 
If the study is terminated by UNC (sponsor) or PCORI (funding agency) 
 
5  REDCap DATA COLLECTION 
  
All data collected for PROP UP will be directly entered and stored in the web-based research electronic data 
capture system, called REDCap. The REDCap database for PROP UP will be stored, maintained, and 
monitored by the PROP UP Data Coordinating Center (DCC). The REDCap system is a secure, web-based 
application designed to support survey and data collection for thousands of biomedical research studies. UNC 
has a license to host the REDCap system. Access to the PROP UP REDCap database will be carefully 
restricted to authorized research team members as needed to perform their job functions, pursuant to Federal 

 
  
regulations. Site RCs have access only to their site study participants. Each time research staff access 
REDCap, a unique electronic signature (login) is required, and REDCap maintains an audit trail of all activity. 
Research staff who access the REDCap system for any purpose will use a unique user ID provided by the UNC 
DCC. These user IDs may not to be shared or reassigned to other staff. The REDCap application for this study 
is hosted on a secure server environment located at UNC and governed by standard University, School of 
Medicine, and Federal information security policies and standards. 
 
6  RECRUITMENT 
 
Patients who meet inclusion/exclusion criteria and have been prescribed an all-oral treatment regimen for 
chronic HCV at a collaborating site should be recruited to participate in PROP UP. Patients may be recruited in-
person in the clinic or by phone using a site IRB-approved phone recruitment guide. If patients are recruited by 
phone, research staff will leave no more than 3 voicemail messages.  Eligible patients who have had 
prescriptions written but are waiting for medications to be approved should be approached, consented, and 
assisted in providing baseline PRO data in REDCap. Fifteen to 20% of patients may not start HCV treatment 
and therefore will not qualify to participate in the longitudinal study. Therefore, patients are not considered 
officially enrolled until first dose of medication has been taken.  
 
7 
INFORMED CONSENT 
 
The investigator must obtain written IRB approval of the written informed consent form and any other 
information that will be provided to the participants during the consent process. Only participants able to provide 
written informed consent will be included in this study. 
 
As part of conducting the informed consent process with each participant, research staff must:  
 
 Provide a written copy of the consent form prior to study participation. The language must be non-technical and 
easily understood. UNC will provide a template consent form which can be modified for site purposes.  
 Discuss the full details of the study with the patient in a private space.  
 Allow sufficient time for patients to ask questions about the study and express understanding.  
 Obtain written informed consent and HIPAA waiver signed and personally dated by the patient and by the 
person who conducted the informed consent process.  
 Write or affix label with unique subject ID# on each page of the consent form.  
 Research staff will maintain a site-specific, secure master linkage list and screen-consent log of all study 
participants who provide consent for the study. The linkage list/consent log may include the following data 
consistent with local IRB: unique subject ID, name, medical record number, date of screen/consent, and reason 
for non-consent if patient is not consented for the study. This log serves several purposes: (1) serves as a 
master linkage list in case of human or data error; (2) to ensure that the site does not issue the same subject ID 
twice; (3) allows RCs to identify patients who were previously consented to track for treatment start 
date/enrollment date; and (4) allows researchers to identify proportion of patients approached vs consented and 
reasons for non-consent, which is recommended by the CONSORT guidelines for observational studies and 
PCORI Methodological Standards. 
 
The RC must verify informed consent has taken place for the individual by uploading a signed copy of the 
informed consent form to the REDCap system. The RC will store the original copies in a secure location 
according to standard operations approved by site IRB. 
 
8  DATA COLLECTION PROCEDURES AT CONSENT/BASELINE VISIT 
 
8.1 Procedures for Baseline PRO Data Collection 
 
Baseline PRO data collection needs to be collected within a 90 day window prior to the patient taking his/her 
first dose of HCV medication, allowing up to 90 days after baseline PRO assessment to start date of HCV 
treatment. 

 
  
 
Informed consent and collection of baseline PRO data should occur during the same clinic visit to the extent 
possible. After written consent is obtained, the RC will open and start the web-based REDCap research record 
for each new study participant. A unique subject ID number will be given specific to each site.  
 
With the research record open, the RC will gather the following information from the patient and enter into the first 
form in REDCap:  
 
Preferred modes of responding to future PRO assessments (see section 11 below) 
 
Email address if selects home-based computer as a possible option  
 
Phone numbers if selects Call Center as a possible option  
 
Hometown and zip code (to calculate travel/mileage for treatment cost) 
 
Patient-approved address to send study reimbursement 
 
The RC will instruct the patient to respond to all items in the Baseline PRO assessment survey. The surveys 
should be self-administered by the patient, but with Coordinator-assistance as needed. Participant responses to 
PRO surveys are completely confidential; the RC is not allowed to share these data with the participant’s clinical 
providers. Participants should be reminded before each survey assessment that their responses to surveys are 
confidential and not shared with their provider or placed in their medical record. 
 
Study participants will respond to the following PRO surveys listed in Table 3:  
 
Table 3: Baseline PRO Data Collection 
PRO surveys 
Items 
Sociodemographic information 
10
MSAS Symptom Assessment 
32
PROMIS Fatigue 
7
PROMIS Pain Interference 
8
PROMIS Sleep Disturbance 
8
PROMIS Depression 
8
PROMIS Cognition Concerns 
8
PROMIS Anger 
5
PROMIS Anxiety 
4
PROMIS Belly Pain 
6
PROMIS Diarrhea 
6
PROMIS Nausea/Vomiting 
4
Headache Impact Test (HIT) 
6
HCV-PRO health status 
16
Mental health history 
5
Alcohol and drug history 
5
Stigma scale 
8
Pre-existing medical conditions 
checklist
 
 RC will provide patient with study information sheet and study contact information.  
 
 RC will provide patient with Out of Pocket Cost Log and envelope for receipts and describe how to use 
these tools to help participants track treatment-related costs during treatment. Participants should refer to 
these tools when responding to PRO surveys during treatment that are related to out of pocket costs. 
 
If the baseline PRO assessment cannot be completed during the clinic visit, with patient opt-in to receive 
surveys by email, site RCs can send a survey invitation to the participant’s email address. Study participants 
can also complete the surveys with their site RC over the phone, if needed. 

 
  
 
8.2 Procedures for Baseline Collection of Clinical and Lab Data 
 
The RC is responsible for entering the data fields listed in Table 2 in REDCap within one week of the date of 
consent. The data fields will be extracted from participants’ electronic medical records.  
 
Table 2: Clinical and Laboratory Data Collection at Time of Consent 
Clinical and Lab Data 
Description 
Prescribed Treatment regimen 
 - sofosbuvir/ledipasvir (Harvoni®) with or without ribavirin 
 - ombitasvir/paritaprevir/ritonavir with dasabuvir (Viekera  
Pak®), VPK) with or without ribavirin 
 - elbasvir/grazoprevir (Zepatier®) with or without ribavirin 
 - daclatasvir/sofosbuvir, with or without ribavirin (DAC/SOF) 
 - sofosbuvir/velpatasvir (SOF/VEL)
Prescribed Treatment Duration 
8, 12, 16, 24 weeks
HCV Genotype 1-6 
Confirm genotype 1-6 with most recent lab date 
HCV Viral Load 
HCV RNA quantitative viral load within last 12 months 
IU/mL
Evidence of cirrhosis 
- 
No evidence  
- 
Yes evidence based on source(s): Fibroscan, biopsy, 
ultrasound, Fibrosure blood test, clinician judgment
FibroSCAN 
kPa stage and grade from Fibroscan results submitted for 
insurance approval 
HIV status 
Test conducted and HIV status 
Aspartate Aminotransferase 
AST IU/L within last 6 months
Alanine Aminotransferase 
ALT IU/L within last 6 months
Albumin 
ALB g/dL within last 6 months
Total Bilirubin 
BILI mg/dL within last 6 months
Creatinine 
Creatinine mg/dL within last 6 months
International Normalized Ratio 
INR within last 6 months
Platelets 
PLAT 10^3/uL within last 6 months 
Hemoglobin 
HGB g/dL within last 6 months
 
9  ENROLLMENT CRITERIA 
 
(1) Patient has provided written informed consent; 
(2) Patient has completed baseline PRO surveys within 90 days prior of starting treatment; and 
(3) Patient has taken at least one dose of the prescribed medication regimen.  
 
The RC will work with clinical staff to monitor when consented patients are approved for treatment. Sites should 
develop their own standard operating procedures to track treatment start dates of consented patients. To 
officially enroll a patient in the longitudinal study, the RC will confirm enrollment criteria has been met in 
REDCap and will complete three data fields: “Treatment Start Date”, “Prescribed Treatment Regimen” and 
“Prescribed Treatment Duration.” These data fields must be entered within 7 days of the patient commencing 
therapy so that the PRO assessment schedule is triggered to prompt patients to complete week 4 PRO 
assessment.  
 
10 PRO DATA COLLECTION TIME POINTS 
 
Study participants will respond to PRO surveys 5 time points during the study: once before treatment begins, 
twice during treatment, and twice after treatment:  
 
 
T1: Baseline assessment within 90 days prior to start of treatment (ideally in clinic at time of consent) 
 
T2: Treatment week 4 (+/- 1 week) 

 
  
 
T3: Late in treatment  
o During 7th-8th week of 8 week regimen 
o During the 10th -12th week of 12 week regimen 
o During the 22nd-24th week of 24 week regimen  
 
T4: 12 weeks after treatment ends (+/- 3 weeks) 
 
T5: 12 months after treatment ends (+/- 2 months post-treatment) 
 
 
11 PRO DATA COLLECTION PROCESS  
 
All PRO data will be entered directly into REDCap system by the patient, the UNC Call Center, or the site RC. 
The site RC will assist patients in responding to T1 baseline PRO surveys in REDCap. Site RCs are responsible 
for capturing all T1 data. The DCC and UNC Call Center will manage, monitor, and prompt T2-T5 PRO data 
collection.   
 
T2-T5 PRO survey data can be entered directly into REDCap via 3 options: (a) the study participant through 
his/her home computer, tablet, smartphone, (b) the UNC Call Center staff during phone –administered surveys, 
or as a last resort (c) the study participant with assistance from the research staff during regular clinic visits. For 
patients who have access to home-based computers, tablets or smartphones, responding to surveys on their 
own computer should be highly encouraged. For patients with no convenient computer access, responding to 
survey via phone administration is second preference. Participants will consent to storage of email addresses 
and phone numbers in the REDCap database in order to facilitate data collection of PRO surveys via home 
computers or Call Center. At the baseline T1 visit, the site RC will describe how the REDCap system works, and 
will discuss the three data entry options below. The participant’s preferred methods will be stored in the 
REDCap system for collection of T2-T5 assessments. Each site RC is responsible for monitoring the insurance 
approval status of consented patients and initiating the patient record in REDCap to initiate enrollment. This is 
critical to ensure adherence to the pre-determined survey schedule in REDCap, which prompts participants 
and/or Call Center staff to complete each patient’s T2-T5 assessments.  
 
11.1 Data entry via participant home-based computer/tablet/smartphone 
 
The preferred mode of data entry, to the extent possible, is for patients to complete follow-up PRO surveys 
independently from home computers, laptops, tablets or smartphones. Patients who opt in to storing their email 
address and receiving their surveys by email will be sent scheduled email reminders containing a URL link for 
each PRO assessment period. This link is unique to this patient at this assessment. No additional verification of 
identity is necessary, providing the simplest possible patient experience. When the last survey at each 
assessment is completed, the next invitation is sent automatically at a pre-determined time and date. 
 
11.2 Data entry via UNC Centralized Call Center phone interviews 
 
Participants will have the second option to complete PROs via phone interview with the UNC Centralized Call 
Center. The DCC will prompt the UNC Call Center to contact study participants from all 9 sites for assessment 
periods T2-T5. The Call Center will record participant responses to survey questions directly into the REDCap 
system. Phone surveys are a necessary option for patients without access to computers or with low literacy 
levels.  
 
11.3 Data entry via computer during regular clinic visit 
 
As a last resort, if a study participant does not respond to PRO survey assessment via home-computer or Call 
Center, the DCC will contact the site RC to request completion of PRO surveys on a laptop at a regular clinic 
visit. Data must be collected during eligible time window for data to be valid and participant to be reimbursed. 
Patients who are managed in a manner consistent with the standard of care for HCV treatment will typically 
attend 1 or 2 treatment visits during HCV treatment, a 12-week visit to determine SVR, and many will be 
scheduled for annual follow-up with their liver providers. As such, PRO survey assessments T2-T5 should 

 
  
coincide with these clinic visits. Participant responses to all PRO items are to be kept confidential by the RC and 
not shared with the patient’s clinical providers.  
 
11.4 PRO Data Assessment Time Schedule 
 
Table 4 
T1 
T2 
T3 
T4 
T5 
 
Baseline 
Week 
4 of 
TX 
Last 2 
weeks 
of TX 
12 weeks 
post-TX 
1 year 
post-TX 
PROs 
 
 
 
 
 
Sociodemographic 
X 
 
 
MSAS Symptom 
Assessment 
X 
X 
X 
X 
X 
PROMIS Fatigue 
X 
X
X
X
X 
PROMIS Pain 
Interference 
X 
X 
X 
X 
X 
PROMIS Sleep 
Disturbance 
X 
X 
X 
X 
X 
PROMIS Depression 
X 
X
X
X
X 
PROMIS Cognition 
Concerns 
X 
X 
X 
X 
X 
PROMIS Irritability 
X 
X
X
X
X 
PROMIS Anxiety 
X 
X
X
X
X 
PROMIS Belly Pain 
X 
X
X
X
X 
PROMIS Diarrhea 
X 
X
X
X
X 
PROMIS 
Nausea/Vomiting 
X 
X 
X 
X 
X 
Headache Impact 
Test (HIT) 
X 
X 
X 
X 
X 
HCV-PRO 
health/QOL 
X 
X 
X 
X 
X 
Voils Med 
Adherence 
 
X 
X 
 
 
Out of Pocket Cost 
 
X
X
X
 
Pre-existing 
conditions 
X 
X 
X 
 
X 
Stigma 
X 
 
X 
Mental Health Hx 
X 
 
X 
Alcohol and Drug Hx 
X 
 
X 
 
12  PARTICIPANT REIMBURSEMENT 
 
At each PRO survey assessment, participants will respond to several questions in REDCap or by phone-
administered interview with the Call Center. PRO experts suggest that a reasonable amount of time to ask 
participants to complete PROs is ~15-20 minutes(79). Our HCV Patient Engagement Group (n=6) completed a 
paper packet of PRO surveys, yielding an average time for completion of 18 minutes (range: 15-23). The HCV-
PEG unanimously agreed that response burden was not a concern. 
 
 
$25 for completing T1 PRO baseline assessment within 90 days prior to treatment start 
 
$25 for completing T2 PRO assessment at treatment week 4 (+/- 1 week) 
 
$25 for completing T3 PRO assessment at end of treatment 
o During 7th-8th week of 8 week regimen 
o During 10th -12th week of 12 week regimen 
o During 22nd-24th week of 24 week regimen  

 
  
 
$40 for completing T4 PRO assessment at 12 weeks after treatment ends (+/- 3 weeks) 
 
$40 for completing T5 PRO assessment at 12 months after treatment ends (+/- 2 months) 
 
UNC or subsites will reimburse subjects each time they complete survey assessments. Notification of survey 
completion is identifiable in the REDCap system to trigger reimbursement to be sent. UNC and the subsites can 
reimburse patients with checks, cash, or gift cards for the allotted amount. UNC and subsites will ensure that 
study participants receive reimbursement within 4 weeks of survey completion. A tracking log of subject ID, 
assessment time period (T1-T5), date and type of disbursement, and disbursement amount should be retained 
by whichever party (UNC or subsite) is responsible for subject reimbursement and maintain with internal study 
records.   
 
13  CLINICAL AND LAB DATA COLLECTION AT 12 WEEKS POST-TREATMENT 
 
Within 30 days of a participant’s 12-week visit (+/- 3 weeks), the RC will extract the data listed in Table 5 from 
participants’ medical records and accurately record the data in REDCap database.  
 
 
Table 5: Clinical and Laboratory Data Collection at 12-weeks post-treatment SVR visit 
Clinical and Lab Data 
Description 
Treatment Stop Date 
mm/dd/yyyy
Actual Treatment duration 
8, 12, 16, 24 weeks or Other
HCV Viral Load 
HCV RNA quantitative viral load or below level of 
quantitation
Sustained Viral Response 
SVR achieved Yes/No
Aspartate Aminotransferase  
AST IU/L 
Alanine Aminotransferase  
ALT IU/L 
Total Bilirubin 
BILI mg/dL
Creatinine 
Creatinine mg/dL
International Normalized Ratio  
INR 
Platelets 
PLAT 10^3/uL  
Hemoglobin 
HGB g/dL
 
14 MEASURES: PATIENT-REPORTED OUTCOMES SURVEYS 
 
14.1 Memorial Symptom Assessment Scale (MSAS) (Aims 1a, 3a, 4a)  
 
The MSAS is a reliable and validated 32-item instrument that will be used to measure a number of pre-existing 
HCV-associated symptoms, potential treatment side effects during treatment, and change in symptoms and side 
effects post-treatment38,39. The MSAS evaluates 32 prevalent symptoms or side effects that commonly occur in 
medical populations and during medical treatments. Patients will first indicate the presence or absence of the 
symptom/side effect, and if present, will rate the construct on severity, frequency and interference. An overall 
treatment toxicity score using all the items (referred to as TMAS) can be analyzed as well as descriptive 
statistics about each symptom/side effect.   
 
14.2 PROMIS short forms (Aim 1b, 3a, 4b) 
 
While the MSAS is capable of capturing a comprehensive set of many potential HCV-associated symptoms and 
toxic treatment side effects, the Patient-Reported Outcomes Measurement Information System® (PROMIS®) 
short forms will be used to precisely measure very specific constructs most common or salient to HCV and its 
treatment. The PROMIS short forms are a comprehensive set of highly reliable and validated tools that measure 
symptoms or treatment side effects across a wide range of chronic medical conditions. These constructs are not 
confounded by items measuring other symptoms or aspects of HRQOL. Each PROMIS short form includes a 
subset of items from a larger item bank that were the best performing items in content validity and reliability40,41. 
PROMIS raw total scores are rescaled to a standardized T-score, which has a mean of 50 and standard 
deviation (SD) of 10 in the US general population.  

 
  
 
14.2.1 
PROMIS short forms to measure HCV-associated symptoms  
 
PROMIS Fatigue -7a 
 
PROMIS Sleep Disturbance-8a 
 
PROMIS General Cognitive Concerns-8a   
 
PROMIS Pain Interference-8a 
 
PROMIS Belly/Liver Pain-6 
 
PROMIS Nausea/vomiting-4 
 
PROMIS Diarrhea-6 
 
PROMIS Irritability-5a 
 
PROMIS Depression-8a 
 
PROMIS Anxiety-4a 
 
 
14.2.2   PROMIS short forms to measure treatment side effects   
 
PROMIS Fatigue -7a 
 
PROMIS Sleep Disturbance-8a 
 
PROMIS Nausea/vomiting-4 
 
PROMIS Diarrhea-6 
 
PROMIS Irritability-5a 
 
PROMIS Anxiety-4a 
 
14.3  Headache Impact Test (HIT) to measure headache as a treatment side effect  
Headaches are reported as adverse events in recent Phase III trials. The PROMIS measures do not include a 
short form to evaluate headache. We will measure headache as a side effect of treatment with the validated 6-
item Headache Impact Test42. Participants select responses from a 5-point Likert scale ranging from “Never” to 
“Always.” Higher scores are indicative of worse headaches and greater impact on the functioning.  
 
14.4  HCV-PRO to measure well-being and functioning (Aim 1c, 3b, 4d) 
The HCV-PRO is a newly developed survey designed to assess the well-being and functional status of patients 
with HCV43,44. It was developed in accordance with the PRO guidelines issued by the US FDA and 
demonstrated good reliability and convergent validity was moderate-high (r > 0.50) 74. HCV-PRO items 
measure physical, emotional and social functioning, productivity, intimacy, and perception of quality of life. 
Participants select responses from a 5-point Likert scale: 1=‘‘all of the time’’ to 5=‘‘none of the time”. A higher 
total score indicates higher functioning.  
 
14.5  Out of Pocket Costs survey to measure costs of treatment reported by patients (Aim 1e) 
The personal cost of undergoing HCV treatment with new all-oral treatments is unknown, may vary considerably 
by insurance status and coverage, and may be a key consideration during patients’ decision-making. The 
literature describes the importance of measuring both direct and indirect costs of treatment. Patients will be 
asked to estimate the cost of 5 direct and 5 indirect costs associated with HCV treatment. Direct costs include: 
HCV medication co-pays, co-pays for prescriptions to manage side effects, over the counter remedies for side 
effects, doctor co-pays, blood draw copays. Indirect costs include: patient’s missed work/lost hourly wages, 
caregiver lost wages, childcare expenses, borrowing of money, gas and mileage to/from clinic.  
 
14.6  Voils Medication Adherence Survey (VMAS) to measure medication adherence (Aim 1f) 
 
Medication adherence (how well patients take their medications every day as prescribed) and the reason for 
missed doses, may vary between treatment regimens, treatment durations and among patient subgroups. The 
VMAS consists of 3 items that evaluated the extent of adherence using a 5-point Likert scale from 1=None of 
the time to 5=All of the time36,37. The 3 items assess how often participants missed doses, skip doses, or do not 
take doses over the past 7 days and are averaged into a single score shown to be reliable (alpha = 0.84). A 

 
  
dichotomous variable will be created to categorize patients as 100% or <100% adherent. The VMAS has 
undergone qualitative testing in patients with HCV on antiviral therapy and is currently being validated in a HCV 
population on all-oral antiviral therapy.   
 
14.7  Sociodemographic Survey 
 
Participants will respond to sociodemographic questions at T1 baseline to characterize the study sample and 
explore as confounding variables: age, sex at birth, race, marital status, educational status, income level, living 
situation, employment status, and health coverage.   
 
14.8  Psychiatric and Substance Abuse History 
 
Patients with histories of psychiatric and addiction histories are important subgroups to evaluate, as they may 
have different outcomes compared to patients with psychiatric and addiction history. Participants will respond to 
5 questions related to psychiatric history and 5 questions related to drug and alcohol use. Psychiatric questions 
include use of psychiatric medications, diagnosis of mental health problems, use of mental health treatment or 
services, and history of psychiatric hospitalizations. Addiction questions include frequency and amount of 
alcohol consumption, heavy drinking, and use of nonprescription drugs and prescribed drugs45,46. 
 
15 STATISTICAL ANALYSIS STRATEGY  
 
15.1 Analysis plans registered in the master protocol document 
 
To help ensure reproducible results, these a priori plans specify detailed steps for the major 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 (1) 
use of supportive analyses of subscales as an aid for understanding and interpreting the major analysis results, 
(2) a role for outcome-dependent exploratory analyses for hypothesis generation / refinement, and (3) 
necessary descriptive graphical and tabular methods used to characterize the participants, visualize the data 
and examine relationships among variables. 
 
15.2 Strategy for analysis of PRO change from baseline as a function of subgroup and/or treatment regimen 
 
Characterization of each subgroup or treatment regimen in terms of the interval-scale PRO variables will be 
based on N=1600 participants. Cirrhosis is expected in approximately 50% (n=800) of the subjects. Because 
subgroups, such as patients with cirrhosis, may have different experiences during and after treatment, 
estimation and inference characterizing the treatment regimens may be subgroup-specific (e.g., in manuscript 
#1 and #4).  In contrast, primary analysis of the benefits of viral cure (SVR) may be all-inclusive without regard 
to treatment regimen (e.g., manuscript #2). The general model for change from baseline for each outcome 
variable (e.g., Total MSAS) may condition on covariates which include cirrhosis status, age, race, sex at birth, 
treatment regimen, the cirrhosis-by-regimen interaction, and the baseline score (e.g., Total MSAS). The models 
fitted will provide parameter estimates that will be used to obtain point estimates and confidence intervals (CI) 
to characterize each treatment regimen and/or each subgroup. A limited number of statistical hypotheses will 
also be tested. For binary PRO scales or subscales, a similar strategy will rely on logistic regression model 
methods.  
 
15.3 Supportive longitudinal analysis and interpretation of changes from baseline  
 
HCV-related symptom scores will be measured longitudinally.  As an aid to interpretation of the primary results, 
and for purposes of generating new hypotheses, auxiliary longitudinal analyses of these repeated measures 
may also be explored.   
 
Any increments from Baseline (T1) during treatment (T2/T3) will represent worsening of HCV-related 
symptoms or commencement of new onset treatment side effects. Similarly, decrements from Treatment 
(T2/T3) to 12-weeks post-treatment (T4) will represent amelioration or disappearance of symptoms.  For any 

 
  
symptoms remaining at T4, decrements from T4 to T5 will represent further healing.  Thus for each individual 
the longitudinal trajectories of the scores represents that individual’s history of waxing and/or waning of HCV-
related symptoms.  Secondarily, complementary analyses of each of the 32 symptoms will be used to 
investigate whether side effects that begin during treatment tend to resolve and to investigate the incidence of 
new symptoms or side effects that appear after treatment ends.  
 
Treatment-related side-effects scores will also be measured longitudinally.  Ideally, any increment from T1 to 
T2/T3 will be completely reversed by a decrement from T2/T3 to T4 or T5.  Thus for each individual, the 
longitudinal trajectories of the scores represents that individual’s history of waxing and/or waning treatment-
related side-effects and HCV-related symptoms. These trajectories will be summarized descriptively via 
estimates of occasion-specific mean levels (with confidence intervals) and in terms of patterns of the trajectories 
represented, for example, by the proportion of patients for whom all treatment-related side-effects disappeared 
by T4/T5.    
 
15.4 Strategy for analysis of subgroup heterogeneity of treatment effects (HTE) 
 
While a head to head drug comparison is not the primary goal of this study, we will take the opportunity to 
examine similarities and differences between the treatment regimens using causal inference methods 
(described in section 15.10). Fitted models will provide parameter estimates that will be used to obtain point 
estimates, confidence intervals (CI) and hypothesis tests to characterize and compare treatment regimens 
within each subgroup.  For each outcome variable these auxiliary comparisons of regimens will include an 
equivalence test procedure as well as a superiority test procedure. The subgroup-specific treatment effects will 
be compared to evaluate evidence of HTE. For purposes of hypothesis generation and not testing, exploratory 
analyses of HTE for other subgroups will be performed; e.g, such as medication adherence rates among 
subgroups with mental health issues or drug and alcohol use (MH/SA Hx), or other groups that may be 
suggested by the data. Hypotheses will be generated but not tested. 
 
15.5 Overview of Plans for Manuscript #1: Change in Treatment Side Effects from T1 to T2/T3 
 
The primary analyses for manuscript #1 will rely on a linear model for change from baseline for each PRO 
variable conditional on baseline covariates which include cirrhosis status, age, race, sex at birth, treatment 
regimen, cirrhosis-by-regimen interaction, and the baseline PRO score. Inclusion of the baseline PRO score as 
a covariate has several advantages for clarity of interpretation and improved precision of estimators of interest. 
The analysis will focus on point estimates and confidence intervals. 
PRO variables of interest in manuscript #1 are described here by aim:  
 
Aim 1a, MSAS.  The outcome variable will be change from baseline (T1) to the larger of the two MSAS 
scores (T2 and T3) during treatment. As an aid to interpretation, additional supportive tabulations for each of the 
32 side effects will be examined; e.g., the incidence of new side effects and the exacerbation of existing 
symptoms during treatment will be characterized in regard to the raw frequency, severity and distress items.     
 
Aim 1b, PROMIS®. The primary analyses will focus on 6 side effect-specific PROMIS® T-scores and 1 HIT 
headache score. The outcome variable will be change from baseline (T1) to the larger of the two T-scores (T2 
and T3) during treatment. As an aid to interpretation of the main results, additional supportive tabulations for 
specific survey items will be examined.    
  
Aim 1c, HCV-PRO. In the primary analysis, the outcome variable will be change from baseline to the larger 
of the two HCV-PRO scores (T2 and T3) during treatment.    
  
Aim 1d, Pre-existing medical conditions. For each of several selected pre-existing condition at baseline, we 
will descriptively examine which conditions stay the same, get worse, or get better, during HCV treatment. 
 
Aim 1e, OOP Costs.  This outcome variable will be patient-reported cumulative (T2-T4) direct costs and 
indirect costs on log10 scale. Sensitivity analyses will include use of a generalized log-linear model. Treatment 
differences in OOP costs could affect adherence and / or persistence and hence impact SVR. The co-variation 
of OOP costs with other outcomes will be explored in order to generate new hypotheses about the role of OOP 
costs. 
 
 
15.6  Overview of Plans for Manuscript #2: Medication Adherence during T1 to T2/T3 
 
Aim 2, Medication Adherence. The analyses concerning adherence will be based on the patient-reported 
Voils’ Medication Adherence Survey (VMAS) at 3 months post-treatment.   

 
  
 
Aim 2a. In the combined convenience sample of 1600 participants, two subgroups defined by mental health 
or substance abuse history (MH/SU Hx: yes, no) will be characterized and compared in terms of medication 
adherence using the VMAS.  We anticipate 50% (n=800) of participants having a MH/SU Hx and 50% (n=800) 
without a MU/SU Hx. We hypothesize that the two subpopulations are equivalent with regard to medication 
adherence (<5% difference in medication adherence). Each participant’s level of adherence will be classified as 
high (100% adherent) or low (<100% adherent) for purposes of the analysis. Overall, we anticipate that about 
75% of participants will report perfect 100% adherence.  Individual adherence may vary depending on treatment 
regimen, pill burden and patient characteristics.  The adherence literature suggests that adherence decreases 
as the number of pills in the regimen increases (Claxton). The primary characterization of each subgroup, and 
their comparison, we rely on a logistic regression model for adherence conditional on subgroup, pill burden, 
cirrhosis status, age, race, and sex at birth. The analysis will focus on point estimates and confidence intervals.  
In particular, the rate (P) of high adherence for each subgroup, and the magnitude of difference between those 
two rates, are of greatest interest. Of less interest, an equivalence test procedure will be used to test the null 
hypothesis that the subpopulations do not have equivalent rates. ‘Equivalent’ will be defined to mean that the 
difference between population rates, (P1 - P2), is less than 5%, and thus the null hypothesis is |P1 – P2| > 5%.   
For purposes of generating new hypotheses, variations on the model will be explored using additional or 
alternative covariates such as marital status, educational status, income level, living situation, employment 
status, health coverage, and selected two-way interactions thereof.   
 
Aim 2b.  We will investigate the relationship between adherence and pill burden via a logistic regression 
model for adherence conditional on pill burden and the following covariates:  cirrhosis status, age, race, and sex 
at birth.  The analysis will focus on point- and interval-estimates of the rate of perfect adherence as a function of 
pill burden evaluated at reference levels of the covariates.     
 
Aim 2c. Descriptive analyses will also be performed investigate prevalence of various reasons patients miss 
taking medication (i.e., are <100%). The investigation will be based on the responses of those participants who 
reported imperfect adherence (n  400 =  ¼ 1600).   Each participant will be asked to rate 8 reasons for missing 
pills, based on a 5 point scale from “not at all” to “very much” We will calculate a score for each reason to 
determine the most common reasons for nonadherence. 
 
Aim 2d. We will explore the relationship between medication adherence and SVR rate at 3 months post-
treatment. The investigation will be based on the combined convenience sample of 1600 participants and will 
rely on a logistic regression model for SVR that conditions on adherence group (100% vs < 100% adherent) and 
the following covariates: cirrhosis status, age, race, and sex at birth.  Variations on this model will be explored.  
The analysis will focus on point- and interval-estimates of the SVR rate as a function of adherence and pill 
burden evaluated at reference levels of the covariates.    
 
 
15.7  Overview of Plans for Manuscript #3: Benefits of Achieving SVR  
 
In the combined convenience sample of participants who achieve SVR (estimated to be ~1500), subgroups 
defined by achievement of SVR will be characterized and compared in terms of changes in PRO measures. The 
primary analyses for manuscript #3 will rely on a linear model for change from baseline for each PRO variable 
conditional on covariates which include SVR status, cirrhosis status, age, race, sex at birth, treatment regimen, 
subgroup-by-regimen interaction, cirrhosis-by-regimen interaction, and the baseline PRO score. Including the 
baseline PRO score as a covariate has several advantages for clarity of interpretation and improved precision of 
estimators of interest. The analysis will focus on point estimates and confidence intervals.  PRO variables of 
interest in manuscript #3 are described here by aim:  
 
Aim 3a1, MSAS.  The outcome variable will be change from baseline (T1) to 3 months after end of treatment 
(T4). As an aid to interpretation, additional supportive tabulations for each of the 32 symptoms will be examined; 
e.g., change in side effects or pre-existing symptoms will be characterized in regard to change in raw frequency, 
severity and distress items.     
 
Aim 3a2, PROMIS®. The primary analyses will focus on 10 symptom-specific PROMIS® T-scores and 1 HIT 
headache score. The outcome variable will be change from baseline (T1) to 3 months after end of treatment 
(T4). As an aid to interpretation of the main results, additional supportive tabulations for specific survey items 
will be examined.     
  
Aim 3b, HCV-PRO. In the primary analysis, the outcome variable will be change from baseline (T1) to 3 
months after end of treatment to determine benefit to well-being and functioning after cure (T4).     
 

 
  
15.8  Overview of Plans for Manuscript #4: Long-term Benefits / Harms 
 
The primary analyses for manuscript #4 will rely on a linear model for change from baseline(T1) to one year 
post treatment (T5) for each PRO variable conditional on baseline covariates which include cirrhosis status, 
age, race, sex at birth, treatment regimen, cirrhosis-by-regimen interaction, and the baseline PRO score.  
Including the baseline PRO score as a covariate has several advantages for clarity of interpretation and 
improved precision of estimators of interest. The analysis will focus on point estimates and confidence intervals. 
As an aid to interpretation of the primary results, and for purposes of generating new hypotheses, auxiliary 
longitudinal analyses of the repeated measures will also be explored.  The PRO variables of interest in 
manuscript #4 are described here by aim:  
 
Aim 4a, MSAS.  The outcome variable will be change from baseline (T1 to T5) in the total MSAS score. As 
an aid to interpretation, additional supportive tabulations for each of the 32 side effects will be examined; e.g., 
change in side effects/pre-existing symptoms will be characterized in regard to the raw frequency, severity and 
distress items.    
 
Aim 4b, PROMIS. The primary analyses will focus on 10 symptom-specific PROMIS® T-scores and 1 HIT 
headache score. The outcome variable will be change from baseline (T1 to T5) in the total score. As an aid to 
interpretation of the main results, additional supportive tabulations for specific survey items will be examined.     
 
Aim 4c, Pre-existing medical conditions. For each of several patient selected pre-existing conditions at 
baseline, we will descriptively examine which conditions stay the same, get worse, or get better one year after 
treatment ends. For the primary analyses, the outcome variable will be change from baseline (T1 to T5).   
  
Aim 4d, HCV-PRO. The outcome variable will be change from baseline (T1 to T5).     
 
Aim 4e, Cirrhosis differences.  For each regimen we will evaluate the apparent effect of cirrhosis status on 
change from baseline (T1 to T5) for each of the outcome variables (4a, 4b, 4c, 4d).  The results will be obtained 
from the models fitted for Aims 4a, 4b, 4c and 4d.    
 
Auxiliary analyses comparing treatment regimens. Although not the purpose of this study, we will also take 
the opportunity to examine similarities and differences between regimens.  Causal inference methods (section 
15.10) will be used to fit response models similar to those fitted for Aims 3a, 3b, 3c and 3d.   
 
15.9 No Interim Analysis 
 
Interim analyses will be conducted for two purposes:  (1) To coincide with submission of abstracts to professional 
conferences and (2) To use portions of the earlier data as it accrues for protocol monitoring, and development and 
coding of statistical algorithms in SAS. Blinding to treatment condition or group will be used if deemed necessary. 
Interim analyses for the purpose of early treatment or study discontinuation, as a function of evidence of treatment 
efficacy, safety issues, or futility, will not be conducted.  
  
15.10  Role of Causal Inference Methods 
 
The participants will comprise two or more regimen-specific treatment cohorts. The auxiliary analyses 
comparing regimens will require application of causal inference methods. 
 
Two stages of analysis. The causal inference analysis strategy comprises (1) a design stage involving 
estimation and use of a propensity score model for purposes of achieving balance of baseline covariates, and 
(2) an outcomes analysis stage for treatment effect estimation and inference separately for each outcome 
variable. For these two stages we may rely on the approach proposed by Cao et al.47 building on previous work 
by Tan48,49, Robins et al50, Funk et al51 and others. Rotnitzky et al52 proposed a competing approach and 
compared the performance of their method to that of Cao et al.47. In the manner of Cao et al., we will use an 
improved doubly robust (DR) estimator obtained via enhancements in the estimation of the propensity score 
model and the inverse-probability weighted (IPW) outcome model. Confidence intervals will rely on bootstrap 
methods. Similar analytic methods will be employed to compare patient subgroups or different treatment 
durations.  
 
Sensitivity Analyses and Diagnostics.   Both stages will involve careful use of diagnostic methods (e.g., for 
covariate balance) and an extensive set of sensitivity analyses. Additionally, to ensure covariate balance in 
each of the two cirrhosis subgroups, it will be necessary to take steps in the design stage to, for example, 
appropriately account for subgroup differences in the propensity score model and examine subgroup-specific 
diagnostics for covariate balance and for propensity score distribution overlap. 

 
  
  
Unverifiable Assumptions.  All baseline variables that have a causal effect on treatment assignment and on 
the outcome variables must be included in the set of covariates used in the design stage. The required 
assumption of “no unmeasured confounders” is unverifiable. Although limited by the necessity of making 
additional assumptions and conjectures, efforts will be made to investigate the potential magnitude of residual 
bias that would exist if any unmeasured confounders exist. Additionally, if a strong instrumental variable (IV) has 
been identified for use in analysis of a particular outcome variable, then an auxiliary analysis will be performed 
using the IV approach however, the IV results would only be used to guide confidence in the main results 
obtained by the IPW approach and would not replace those results. The unverifiable assumption of the IV 
approach is that the instrument is not correlated with an unobservable error term. 
  
15.11 Methods for Coping with Missing Data 
 
The analysis plan relies on an extensive set of covariates measured at baseline. For purposes of estimation of 
the propensity score model, missing covariate values will be addressed via multiple imputation; furthermore, for 
each participant, the resulting multiplicity of propensity scores will be averaged together as proposed by Mitra 
and Reiter53. The alternatives (e.g., average results from multiple outcome models) will be explored for 
purposes of sensitivity analysis. More 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 even when 
the participant terminates treatment earlier than scheduled. Depending on the mechanisms which cause loss-to-
follow-up for outcomes such as the MSAS at 1 year, multiple imputation methods may be appropriate. 
Competing model-based methods will be examined for purposes of sensitivity analysis. 
 
15.12 Overview of Sample Size Considerations  
 
The proposed PROP UP sample size is N = 1600 participants. The rationale for this choice was based on aim-
specific considerations of the availability of eligible subjects, feasible rates of recruitment, the length of time 
available to conduct the study, the per-subject costs in time and effort, and considerations of the anticipated 
levels of precision of estimators and the anticipated levels of power of statistical hypothesis tests. The 1600 
participants will comprise two to five treatment cohorts.  Participants receiving Harvoni® are expected to 
comprise about 60% of the participants (n  960), while perhaps 5% will receive Viekira Pak® (n  80)and 10% 
may receive Zepatier® (n  160).  Other treatment cohorts may comprise 10% (n  160), or 15% (n  240) 
shares of the total sample size of 1600 participants. These numbers are approximations based on the current 
treatment landscape, and are subject to change. In each treatment cohort, subgroups of interest are expected 
to be about equally prevalent; for example, about 50% will have cirrhosis, and for example about 50% are 
expected to have a history of mental health conditions or substance abuse. In contrast, the subgroup of 
participants who achieve SVR is anticipated to comprise roughly 94% of the total sample size (n  1500). 
 
Table 6. Anticipated Sample Sizes that May be Observed 
 
Treatment  Regimen 
Potential 
Subsample* 
Potential 
Subsample* 
Combined 
   Genotype 1 
Harvoni® (H) 
480 
480 
960 
Zepatier®  (Z) 
80 
80 
160 
VPK® 
40 
40 
80 
   Genotype 2 & 3 
Daclatasvir/sofosbuvir 
40 
40 
80 
**Sofosbuvir/velpatasvir 
60 
60 
120 
 
Combined 
800 
800 
1600 
      Note: * Potential subsamples within treatment regimens may include patients with and without cirrhosis or patients with and without 
a mental health or substance abuse history. ** SOF/VEL is pan-genotypic and may also be used with Geno 1. Anticipated FDA-approval 
June 28, 2016. ***Participants with rare genotypes (4, 5, 6) are expected to represent <3% of the sample and will be analyzed based on 
prescribed treatment regimen, not genotype.                     .   

 
  
 
The primary objective of the study will focus on characterizing each treatment regimen or a subgroup of 
interest. For this purpose, point and interval estimates of mean changes from baseline for the PRO variables of 
interest will be estimated as a function of subgroups defined by cirrhosis status and other characteristics.   
 
Auxiliary analyses to conduct head to head comparisons of treatment regimens is not the purpose of this 
study; however, we will take the opportunity to examine similarities and differences between regimens using 
causal inference methods.   
 
Population inferences will rely on point and interval estimates, and secondarily on two kinds of tests: a 2-
sided superiority test of the null hypothesis Ho: “the difference is exactly zero”, and an equivalence test of the 
null hypothesis Ho: “the magnitude of the difference exceeds a threshold that defined ‘equivalence’.”  
Equivalence tests will be used for those analyses in which there is an a priori belief that equivalence is 
plausible; for example, in manuscript #2, it is conjectured that the subgroups of interest (patients with and 
without mental health/substance abuse histories) may be equivalent in regard to medication adherence. 
 
The proposed primary hypothesis tests regarding subgroup differences or temporal changes in mean levels 
of outcomes will be cirrhosis-subgroup-specific; consequently, the effective sample size available to each test is 
approximately 800 subjects. For purposes of analysis of the anticipated levels of precision of estimators and the 
anticipated levels of power of test procedures, we assumed balance of covariates, inclusion of baseline score in 
models for change from baseline, and that the tests are those of size  = 0.05. 
 
Anticipated levels of precision for interval-scale estimates used to characterize change in PROs.   
The appendix provides manuscript-specific details regarding the performance characteristics of the estimators 
and tests of interest.   
 
For MSAS estimators of mean change () from baseline, a change of =0.10 points is considered clinically 
important to patients.  The half-widths of the confidence intervals for mean change are highly likely (80% 
chance) to be < 0.14 for N=80, < 0.10 for N=160, and < 0.04 for N=960.   (Appendix Figure 1-1 to Figure 1-6). 
 
For PROMIS estimators of mean change () from baseline, a change of =3 points is considered clinically 
important.  The half-widths of the confidence intervals for mean change are highly likely (80% chance) to be < 
2.37 for N=80, < 1.63 for N=160, and < 0.65 for N=960.   (Appendix Figure 2-1 to Figure 2-6).  
 
For HCV-PRO estimators of mean change () from baseline, a change of =10 points is considered 
clinically important.  The half-widths of the confidence intervals for mean change are highly likely (80% chance) 
to be <6.14 for N=80, <4.23 for N=160, and < 1.67 for N=960. (Appendix Figure 3-1 to Figure 3-6). 
 
Anticipated levels of precision for estimates of adherence rates 
For estimators of the rate of successful adherence to treatment protocol, population rates that differ by <0.05 
will be considered equivalent.  The half-widths of the confidence intervals for mean change are highly likely 
(90% chance) to be <0.09 for N=80, <0.06 for N=160, and < 0.03 for N=960. (Appendix Figure 4-1 to Figure 4-
6). 
 
Anticipated levels of power of tests for interval scale variables to examine group differences.  The appendix 
provides manuscript-specific details regarding the performance characteristics of the estimators and tests of 
interest.   
 
 MSAS:  The anticipated power level of a test of ‘no difference’ (=0) between two subgroups each of size 
N=80 is 80% if =0.27.  For two subgroups of size N=800, anticipated power is 80% if =0.08.  (Appendix 
Figure 1-13 to Figure 1-20). The difference, , is considered clinically important if  ≥ 0.10. 
 
 PROMIS:  The anticipated power level of a test of ‘no difference’ (=0) between two subgroups each of 
size N=80 is 80% if =4.46.  For two subgroups of size N=800, anticipated power is 80% if =1.40.  (Appendix 
Figure 2-13 to Figure 2-20). The difference, , is considered clinically important if  ≥ 3. 
 
 HCV-PRO:  The anticipated power level of a test of ‘no difference’ (=0) between two subgroups each of 
size N=80 is 80% if =11.55.  For two subgroups of size N=800, anticipated power is 80% if =3.63.  (Appendix 
Figure 3-13 to Figure 3-20). The difference, , is considered clinically important if  ≥ 10. 
 
 
Anticipated level of power of equivalence tests for adherence rates 
The anticipated power level of a test of equality between two subgroups each of size N=800 is >90% if the 
subgroup difference is =0.0. If the magnitude of difference between subgroups is larger than 0.0, then the 
power level is smaller.  

 
  
 
Anticipated precision of rates and proportions, in general 
The figure below illustrates precision for rates and proportions corresponding to binary outcomes indicating, for 
example, presence or change of a side-effect,  perfect medication adherence, and resolution of a symptom.  The 
analyses will provide statistical estimates of the population proportion (P). The anticipated level of precision for the 
estimated proportion can be obtained from the figure. For example, hypothetically if N=100 and P=0.50 is the 
observed rate of perfect compliance for a treatment regimen, then half the width of a symmetric 95% confidence 
interval is W = 0.10 and thus the approximate 95% confidence interval would be  0.50  0.10  or   “[0.40, 0.60].  
Larger sample sizes yield narrower confidence intervals. 
 
 
 
16 STUDY CONDUCT 
 
16.1  Ethics 
 
This study will be conducted in accordance with Good Clinical Practice (GCP), as defined by the International 
Conference on Harmonization (ICH) and in accordance with the ethical principles underlying European Union 
Directive 2001/20/EC and the United States Code of Federal Regulations, Title 21, Part 50 (21CFR50). 
 
The study will be conducted in compliance with this protocol. The protocol and any amendments and the subject 
informed consent will receive Institutional Review Board (IRB) approval prior to initiation of the study. 
 
All potential protocol deviations should be reported to UNC. Any serious breach to the protocol or principles of 
GCP in connection with the study or the protocol, which are likely to affect the physical or mental safety of study 
participants or the integrity of the study should be reported to UNC. 
 
Personnel involved in conducting this study will be qualified by education, training, and experience to perform 
their respective tasks. 
 
16.2  Responsibilities within the Study 
 
 

 
  
The study shall be conducted as described in this approved protocol. Investigators should not implement any 
deviation or change to the protocol without prior discussion with UNC. 
 
16.3  Reports and Publications 
 
The confidentiality of records that could identify participants within the database must be protected, respecting 
the privacy and confidentiality rules in accordance with the applicable regulatory requirement(s). The data 
collected during this study are confidential and proprietary to UNC. Any publications or abstracts arising from 
the PROP UP study require approval by UNC, the study sponsor, prior to submission of a publication or 
presentation.  Investigators who wish to use PROP UP data for secondary analyses should present initial 
concept sheet to Steering Committee. Steering Committee will require 2 weeks to review abstracts prior to 
submission to scientific conferences and 1 month to review manuscripts prior to submission to a peer-reviewed 
journal.   
 
16.4  Database Retention and Archiving 
 
Location of database and supporting documentation will be outlined in the final progress report submitted to 
PCORI.  
 
The site investigators must retain all study records and source documents for at least 5 years after study 
completion (2023). Site investigators must contact UNC investigators prior to destroying any records associated 
with the PROP UP study. 
 
17 DATA SAFETY MONITORING BOARD (DSMB) 
 
There are minimal physical or other safety concerns associated with an observational study in which patients 
complete surveys. Because this study poses minimal harm and safety issues to study participants, no DSMB 
was established.  
 
18 DATA AND STUDY MONITORING PLAN (DSMP) 
 
The UNC investigators and DCC will meet weekly to review and monitor all aspects of the study: site 
recruitment, data completeness, data quality, protocol deviations, and any reported study-related adverse 
events. Regular reports will be prepared by the DCC to share with collaborating sites. Tables will show study 
progress by each clinical center and overall, including numbers consented, enrolled, data collected at each 
time point, study-related adverse events, and descriptive characteristics of the study sample.  
 
PROP UP will utilize the secure REDCap data capture application hosted by UNC and the database will be 
monitored, maintained, and secured by REDCap data analysts of the DCC. REDCap has been used in over 
15,360 projects with over 23,000 end users across 6 continents. REDCap is designed for interactive web-
based data entry with real-time field validation. The DCC will also be responsible for database integrity checks, 
security (individual user logins, permissions based on need, and encrypted data transmission), and data 
retrieval and export. The secure server environment housing the database hardware is located within a 
hardened data center on the UNC campus, and is governed by standard University and School of Medicine 
information security guidelines. Weekly vulnerability detection scans, 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 weekly full system virus scans are performed.  
 
19 PATIENT SAFETY AND MONITORING PLAN (PSMP) 
 
19.1  Standard Medical Care  
 
Site clinical hepatology teams are expected to oversee the health needs and medical treatment of patients who 
are enrolled in this observational study. Prior to enrolling in this study, participants will have been medically 

 
  
cleared for HCV treatment by a site hepatology provider.  Once HCV therapy commences, patients are 
managed by the site clinical team according to site standard clinical practices.  
 
19.2  Risks of Study Participation 
 
The psychological risks directly posed by an observational study and survey completion are judged to be 
minimal and rare (<1%). Patients could experience mild embarrassment when responding to questions if posed 
by research staff. To reduce this risk and prepare patients, the RC will remind study participants that 
participation is completely voluntary and that they do not have to answer questions that make them 
uncomfortable. RCs will also remind participants of all study procedures in place to protect the confidentiality of 
their data. RCs will be trained to collect PRO data in a professional, objective, nonjudgmental and supportive 
manner. 
 
The risk of breach of confidentiality of patient information is judged to be minimal and rare (<1%). This risk, and 
all procedures to prevent it, should be discussed by the RC during the consenting process. RC will remind 
patients of safeguards to protect personal information and breach of confidentiality including use of private 
rooms, storage of hard copy documents in locked offices and/or cabinets, compliance with site information 
technology security recommendations, and use of a secure, encrypted database.   
 
The social risks are judged to be minimal and rare (<1%) but could include loss of reputation or social stigma 
if participation in this study leads others to become aware of a patient’s medical condition. The RC will discuss 
this risk and encourage patients to consider risk prevention, especially as related to communication with 
research staff via email and phone interviews. 
 
19.3  Handling of Non-Study Related Harms or Adverse Events 
 
Treatment for HCV may cause side effects and adverse events related to pre-existing conditions and advanced 
liver disease. These harms are not considered related to study participation and are expected to be handled 
and managed by the site clinical providers per site standard clinical protocols for handling medical or psychiatric 
concerns. Non-study related harms or adverse events will not be reportable to UNC, the UNC IRB, or the 
sponsor.  
 
The site research team or the UNC Call Center may become aware of a patient’s medical or psychiatric concern 
through in-person or phone contact. The research staff will explain to the patient that research is a separate 
activity from clinical care and will encourage the patient to notify the clinical hepatology team at their center. In 
the event that a patient expresses an urgent matter or a crisis (e.g., suicidality, homicidality), the research team 
will be trained to use good clinical judgement and standard operating procedures (e.g., refer to liver provider, go 
to closest emergency room). RCs should review site standard operating procedures for handling medical and 
psychiatric crises. 
 
19.4  Handling of Study-related harms or unanticipated adverse events 
 
Harms or adverse events related to study participation in this observational survey study are expected to be 
extremely rare. Nonetheless, should an unanticipated study-related harm occur at a site that is judged by the 
site PI to be partially or fully related to study participation, the site will report this study harm to their own IRB if 
indicated by the site IRB standard operating procedures. Unanticipated study-related adverse events may be 
physical, psychological, social, or legal in nature. The site must notify UNC of the event within 10 days for study 
purposes. UNC will not report these events to the UNC IRB, since sites are under the jurisdiction of their own 
IRBs. However, overall study-related harms or unanticipated adverse events will be tracked by UNC and 
included in six-month progress reports to PCORI.  The UNC investigators will discuss any study-related adverse 
events that are reported and the DCC will maintain a cumulative summary table of events, by site and date 
reported.  
 
 

 
  
20 PROP UP RESEARCH TEAM 
  
 
 
GLOSSARY OF TERMS AND ABBREVIATIONS 
 
 
Adverse event (AE) 
 
Agency for Health Research and Quality (AHRQ) 
 
Center for Gastrointestinal Biology and Disease Center (CGIBD) 
 
Clinically Important Difference (CID) 
 
Comparative Effectiveness Research (CER) 
 
Confidence Intervals (CI) 
 
Consolidated Standards of Reporting (CONSORT) 
 
Data Coordinating Center (DCC) 
 
Data Safety Monitoring Board (DSMB) 
 
Data and Safety Monitoring Plan (DSMP) 
 
Doubly Robust (DR) 
 
Food and Drug Administration (FDA) 
 
Good Clinical Practice (GCP) 
 
Headache Impact Test (HIT) 

 
  
 
Health Insurance Portability and Accountability Act (HIPAA) 
 
Health-related Quality of Life (HRQOL) 
 
Hepatitis C Virus (HCV) 
 
Heterogeneity of Treatment Effect (HTE) 
 
Human Immunodeficiency Virus (HIV) 
 
International Conference on Harmonisation (ICH)  
 
Interferon (IFN) 
 
Institutional Review Board (IRB) 
 
Instrumental Variable (IV) 
 
Inverse-probability Weighted (IPW) 
 
Information Technology Services (ITS) 
 
Memorial Symptom Assessment Scale (MSAS) 
 
Patient-centered Outcomes Research (PCOR) 
 
The Patient Centered Outcomes Research Institute (PCORI) 
 
Patient Engagement Group (PEG) 
 
Principal Investigator (PI) 
 
Patient Reported Outcome (PRO) 
 
Patient-Reported Outcomes Measurement Information System (PROMIS) 
 
Patient-Reported Outcomes Project of HCV-TARGET (PROP-UP) 
 
Research Electronic Data Capture system (REDCap) 
 
Research Coordinator (RC) 
 
Sofosbuvir (SOF) 
 
Standard Deviation (SD) 
 
Standard Operating Procedures (SOP) 
 
Sustained Virological Response (SVR) 
 
Total Memorial Symptom Assessment Scale (TMSAS) 
 
Voils Medication Adherence Survey (VMAS) 
 
 

 
  
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Appendix for Sample Size Analyses 
 
 
Table of Contents 
 
1.   Anticipated Sample Sizes 
 
2.  Tabular Summary of Performance Curve Figures 
            MSAS 
            PROMIS 
            HCV-PRO 
            ADHERENCE 
    
3.  Performance Curve Figures:  Anticipated Precision of Estimators and Anticipated Power of Tests 
            MSAS 
            PROMIS 
            HCV-PRO 
            ADHERENCE 
 
 
 
1.  Anticipated Sample Sizes that May be Observed 
 
 
Anticipated Sample Sizes that May be Observed 
 
 
Treatment  Regimen 
Cirrhotic 
non-Cirrhotic 
Combined 
   Genotype 1 
Harvoni 
480 
480 
960 
Zepatier 
80 
80 
160 
Viekira Pak 
40 
40 
80 
   Genotype 2 & 3 
daclatasvir/sofosbuvir  
40 
40 
80 
sofosbuvir/velpatasvir**
60 
60 
120 
 
Combined 
800 
800 
1600 
Note: * Potential subsamples within treatment regimens may include patients with and without cirrhosis or patients with and without a 
mental health or substance abuse history. ** SOF/VEL is pan-genotypic and may also be used with genotype 1 patients. Anticipated FDA 
approval: June 28, 2016                                                           .   
 
 
 
 

 
  
2.  Tabular Summary of Performance Curve Figures 
 
PRO_measure = MSAS            with Conjectures = { SD = 0.6 [0.45, 0.75] and serial correlation is R = 0.50 } 
 
 
 
 
 
a difference of  0.10 points on the MSAS scale will be considered clinically important 
 
 
Figure 
MS 
Groups N 
procedure 
X_80 
X_90 
1-1 
1, 3,  4 
1 1500 
Confidence interval   [1] 
0.03      [0.02,0.04] 0.03      [0.02,0.04] 
1-2 
1, 3,  4 
1 960 
Confidence interval   [1] 
0.04      [0.03,0.05] 0.04      [0.03,0.05] 
1-3 
1, 3,  4 
1 160 
Confidence interval   [1] 
0.10      [0.07,0.12] 0.10      [0.08,0.13] 
1-4 
1, 3,  4 
1 120 
Confidence interval   [1] 
0.11      [0.09,0.14] 0.12      [0.09,0.15] 
1-5 
1, 3,  4 
1 100 
Confidence interval   [1] 
0.13      [0.09,0.16] 0.13      [0.10,0.16] 
1-6 
1, 3,  4 
1 80 
Confidence interval   [1] 
0.14      [0.11,0.18] 0.15      [0.11,0.18] 
1-7 
1, 3,  4 
1 1500 
test Ho: 'mean change is zero'   [2] 0.04      [0.03,0.05] 0.05      [0.04,0.06] 
1-8 
1, 3,  4 
1 960 
test Ho: 'mean change is zero'   [2] 0.05      [0.04,0.07] 0.06      [0.05,0.08] 
1-9 
1, 3,  4 
1 160 
test Ho: 'mean change is zero'   [2] 0.13      [0.10,0.17] 0.15      [0.12,0.19] 
1-10 
1, 3,  4 
1 120 
test Ho: 'mean change is zero'   [2] 0.15      [0.12,0.19] 0.18      [0.13,0.22] 
1-11 
1, 3,  4 
1 100 
test Ho: 'mean change is zero'   [2] 0.17      [0.13,0.21] 0.20      [0.15,0.25] 
1-12 
1, 3,  4 
1 80 
test Ho: 'mean change is zero'   [2] 0.19      [0.14,0.24] 0.22      [0.17,0.28] 
1-13 
1, 3A, 4 
2 800 + 800 
test Ho: 'mean diff. is zero'   [3] 
0.08      [0.06,0.11] 0.10      [0.07,0.12] 
1-14 
1, 3A, 4 
2 1500 + 100 test Ho: 'mean diff. is zero'   [3] 
0.18      [0.13,0.22] 0.20      [0.15,0.25] 
1-15 
1, 3A, 4 
2 400 + 400 
test Ho: 'mean diff. is zero'   [3] 
0.12      [0.09,0.15] 0.14      [0.10,0.17] 
1-16 
1, 3A, 4 
2 160 + 120 
test Ho: 'mean diff. is zero'   [3] 
0.20      [0.15,0.25] 0.24      [0.18,0.29] 
1-17 
1, 3A, 4 
2 160 + 80 
test Ho: 'mean diff. is zero'   [3] 
0.23      [0.17,0.29] 0.27      [0.20,0.33] 
1-18 
1, 3A, 4 
2 80 + 80 
test Ho: 'mean diff. is zero'   [3] 
0.27      [0.20,0.33] 0.31      [0.23,0.39] 
1-19 
1, 3A, 4 
2 960 + 80 
test Ho: 'mean diff. is zero'   [3] 
0.20      [0.15,0.25] 0.23      [0.17,0.29] 
1-20 
1, 3A, 4 
2 960 + 160 
test Ho: 'mean diff. is zero'   [3] 
0.14      [0.11,0.18] 0.17      [0.13,0.21] 
 
[1]  Pr[ Confidence Interval's  half-width will be < X_80 ] = 0.80 
[2]  Pr[ p < alpha | population mean change = X_80] = 0.80 
[3]  Pr[ p < alpha | population mean difference = X_80] = 0.80 
[4]  Pr[ p < alpha | population rate change = X_80 ] = 0.80 
[5]  Pr[ p < alpha | population rate difference = X_80 ] = 0.80 
 
 
 

  
  
38
PRO_measure = PROMIS 
with Conjectures = { SD = 10 [6, 12] and serial correlation is R = 0.50 } 
 
 
 
 
 
a difference of  3 points on a PROMIS scale will be considered clinically important 
 
Figure 
MS 
Groups N 
procedure 
X_80 
X_90 
2-1 
1, 3,  4 
1 1500 
Confidence interval   [1] 
0.52      [0.31,0.62] 0.52      [0.31,0.63] 
2-2 
1, 3,  4 
1 960 
Confidence interval   [1] 
0.65      [0.40,0.78] 0.66      [0.41,0.79] 
2-3 
1, 3,  4 
1 160 
Confidence interval   [1] 
1.63      [0.98,1.96] 1.67      [1.01,2.01] 
2-4 
1, 3,  4 
1 120 
Confidence interval   [1] 
1.90      [1.14,2.29] 1.96      [1.18,2.35] 
2-5 
1, 3,  4 
1 100 
Confidence interval   [1] 
2.10      [1.26,2.52] 2.16      [1.30,2.60] 
2-6 
1, 3,  4 
1 80 
Confidence interval   [1] 
2.37      [1.42,2.84] 2.45      [1.47,2.94] 
2-7 
1, 3,  4 
1 1500 
test Ho: 'mean change is zero'   [2] 0.72      [0.44,0.87] 0.84      [0.50,1.01] 
2-8 
1, 3,  4 
1 960 
test Ho: 'mean change is zero'   [2] 0.91      [0.54,1.09] 1.05      [0.63,1.26] 
2-9 
1, 3,  4 
1 160 
test Ho: 'mean change is zero'   [2] 2.23      [1.34,2.67] 2.58      [1.55,3.09] 
2-10 
1, 3,  4 
1 120 
test Ho: 'mean change is zero'   [2] 2.58      [1.55,3.09] 2.98      [1.79,3.58] 
2-11 
1, 3,  4 
1 100 
test Ho: 'mean change is zero'   [2] 2.83      [1.70,3.39] 3.27      [1.96,3.93] 
2-12 
1, 3,  4 
1 80 
test Ho: 'mean change is zero'   [2] 3.17      [1.90,3.81] 3.67      [2.20,4.40] 
2-13 
1, 3A, 4 
2 800 + 800 
test Ho: 'mean diff. is zero'   [3] 
1.40      [0.84,1.68] 1.62      [0.97,1.95] 
2-14 
1, 3A, 4 
2 1500 + 100 test Ho: 'mean diff. is zero'   [3] 
2.92      [1.75,3.50] 3.38      [2.03,4.05] 
2-15 
1, 3A, 4 
2 400 + 400 
test Ho: 'mean diff. is zero'   [3] 
1.98      [1.19,2.38] 2.29      [1.38,2.75] 
2-16 
1, 3A, 4 
2 160 + 120 
test Ho: 'mean diff. is zero'   [3] 
3.40      [2.04,4.08] 3.93      [2.36,4.72] 
2-17 
1, 3A, 4 
2 160 + 80 
test Ho: 'mean diff. is zero'   [3] 
3.86      [2.32,4.63] 4.47      [2.68,5.36] 
2-18 
1, 3A, 4 
2 80 + 80 
test Ho: 'mean diff. is zero'   [3] 
4.46      [2.67,5.35] 5.16      [3.09,6.19] 
2-19 
1, 3A, 4 
2 960 + 80 
test Ho: 'mean diff. is zero'   [3] 
3.29      [1.98,3.95] 3.81      [2.29,4.57] 
2-20 
1, 3A, 4 
2 960 + 160 
test Ho: 'mean diff. is zero'   [3] 
2.40      [1.44,2.88] 2.78      [1.67,3.34] 
 
 
[1]  Pr[ Confidence Interval's  half-width will be < X_80 ] = 0.80 
[2]  Pr[ p < alpha | population mean change = X_80] = 0.80 
[3]  Pr[ p < alpha | population mean difference = X_80] = 0.80 
[4]  Pr[ p < alpha | population rate change = X_80 ] = 0.80 
[5]  Pr[ p < alpha | population rate difference = X_80 ] = 0.80 
 
 
 

  
  
39
PRO_measure = HCV-PRO 
with Conjectures = { SD = 25.92 [23.641, 28.835] and serial correlation is R = 0.50 } 
 
 
 
 
 
a difference of  10 points on the HCV-PRO scale will be considered clinically important 
 
Figure 
MS 
Groups N 
procedure 
X_80 
X_90 
3-1 
1, 3,  4 
1 1500 
Confidence interval   [1] 
1.34      [1.24,1.50] 
1.35      [1.26,1.51] 
3-2 
1, 3,  4 
1 960 
Confidence interval   [1] 
1.67      [1.54,1.88] 
1.71      [1.57,1.90] 
3-3 
1, 3,  4 
1 160 
Confidence interval   [1] 
4.23      [3.86,4.71] 
4.34      [3.96,4.83] 
3-4 
1, 3,  4 
1 120 
Confidence interval   [1] 
4.94      [4.50,5.49] 
5.07      [4.63,5.64] 
3-5 
1, 3,  4 
1 100 
Confidence interval   [1] 
5.44      [4.96,6.05] 
5.61      [5.11,6.24] 
3-6 
1, 3,  4 
1 80 
Confidence interval   [1] 
6.14      [5.60,6.83] 
6.35      [5.79,7.06] 
3-7 
1, 3,  4 
1 1500 
test Ho: 'mean change is zero'   [2] 1.88      [1.71,2.09] 
2.17      [1.98,2.42] 
3-8 
1, 3,  4 
1 960 
test Ho: 'mean change is zero'   [2] 2.35      [2.14,2.61] 
2.71      [2.48,3.02] 
3-9 
1, 3,  4 
1 160 
test Ho: 'mean change is zero'   [2] 5.78      [5.27,6.42] 
6.68      [6.10,7.43] 
3-10 
1, 3,  4 
1 120 
test Ho: 'mean change is zero'   [2] 6.68      [6.10,7.43] 
7.73      [7.05,8.60] 
3-11 
1, 3,  4 
1 100 
test Ho: 'mean change is zero'   [2] 7.33      [6.69,8.16] 
8.48      [7.74,9.44] 
3-12 
1, 3,  4 
1 80 
test Ho: 'mean change is zero'   [2] 8.22      [7.50,9.14] 
9.51      [8.67,10.58] 
3-13 
1, 3A, 4 
2 800 + 800 
test Ho: 'mean diff. is zero'   [3] 
3.63      [3.31,4.04] 
4.20      [3.83,4.68] 
3-14 
1, 3A, 4 
2 1500 + 100 test Ho: 'mean diff. is zero'   [3] 
7.56      [6.90,8.41] 
8.75      [7.98,9.74] 
3-15 
1, 3A, 4 
2 400 + 400 
test Ho: 'mean diff. is zero'   [3] 
5.14      [4.69,5.72] 
5.95      [5.43,6.62] 
3-16 
1, 3A, 4 
2 160 + 120 
test Ho: 'mean diff. is zero'   [3] 
8.80      [8.03,9.79] 
10.19    [9.29,11.33] 
3-17 
1, 3A, 4 
2 160 + 80 
test Ho: 'mean diff. is zero'   [3] 
10.00    [9.12,11.13] 
11.58    [10.56,12.88] 
3-18 
1, 3A, 4 
2 80 + 80 
test Ho: 'mean diff. is zero'   [3] 
11.55    [10.54,12.85] 13.37    [12.19,14.87] 
3-19 
1, 3A, 4 
2 960 + 80 
test Ho: 'mean diff. is zero'   [3] 
8.54      [7.79,9.50] 
9.88      [9.01,10.99] 
3-20 
1, 3A, 4 
2 960 + 160 
test Ho: 'mean diff. is zero'   [3] 
6.23      [5.68,6.93] 
7.21      [6.57,8.02] 
 
 
[1]  Pr[ Confidence Interval's  half-width will be < X_80 ] = 0.80 
[2]  Pr[ p < alpha | population mean change = X_80] = 0.80 
[3]  Pr[ p < alpha | population mean difference = X_80] = 0.80 
[4]  Pr[ p < alpha | population rate change = X_80 ] = 0.80 
[5]  Pr[ p < alpha | population rate difference = X_80 ] = 0.80 
 
 
 

  
  
40
PRO_measure = ADHERENCE 
 
with Conjectures = { rate P1 = 0.80 [0.60, 0.90] } 
 
 
 
 
 
 
population rates that differ by less than 0.05 will be considered equivalent 
 
 
Figure 
MS 
Groups N 
procedure 
X_80 
X_90 
4-1 
1, 2 
1 1500 
Confidence interval   [1] 
0.02      [0.03,0.02] 0.02      [0.03,0.02] 
4-2 
1, 2 
1 960 
Confidence interval   [1] 
0.03      [0.03,0.02] 0.03      [0.03,0.02] 
4-3 
1, 2 
1 160 
Confidence interval   [1] 
0.06      [0.08,0.05] 0.07      [0.08,0.05] 
4-4 
1, 2 
1 120 
Confidence interval   [1] 
0.07      [0.09,0.06] 0.08      [0.09,0.06] 
4-5 
1, 2 
1 100 
Confidence interval   [1] 
0.08      [0.10,0.07] 0.08      [0.10,0.07] 
4-6 
1, 2 
1 80 
Confidence interval   [1] 
0.09      [0.11,0.07] 0.09      [0.11,0.08] 
4-7 
1, 2, 3A 
2 800 + 800 test Ho: 'rate difference is zero'   [5] 
0.06      [0.07,0.05] 0.07      [0.08,0.05] 
4-8 
1, 2, 3A 
2 800 + 800 test Ho: 'rates are equivalent(0.05)'   [5] 
0.00      [0.00,0.00] 0.00      [0.00,0.00] 
 
 
[1]  Pr[ Confidence Interval's  half-width will be < X_80 ] = 0.80 
[2]  Pr[ p < alpha | population mean change = X_80] = 0.80 
[3]  Pr[ p < alpha | population mean difference = X_80] = 0.80 
[4]  Pr[ p < alpha | population rate change = X_80 ] = 0.80 
[5]  Pr[ p < alpha | population rate difference = X_80 ] = 0.80 
 
 
 

  
41 
Revised Protocol, verison 3.0 
Date: 13May2016 
 
 
 
41
3.  Performance Curve Figures:  Anticipated Precision of Estimators and Anticipated Power of Tests 
 
       
    .   
   
 

  
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