Clinical trial NCT04335552
Conditions: SARS-CoV-2
Keywords: COVID-19
Sponsor: Duke University
Start date: 2020-04-17; Completion date: 2020-06-26
Enrollment: 11 participants; Allocation: RANDOMIZED; Intervention model: FACTORIAL

Brief summary:
This is a pragmatic, randomized, open-label, incomplete factorial with nested randomization clinical trial evaluating the efficacy and safety of two potential treatments for hospitalized patients with confirmed SARS-CoV-2 infection. Participants who are hospitalized and have a positive nucleic acid amplification test for SARS-CoV-2 will undergo an initial randomization in a 1:1 ratio to one of the following regimens:

Arm 1: Standard of care alone

Arm 2: Standard of care plus hydroxychloroquine

Participants who meet eligibility criteria to receive azithromycin will undergo a second randomization in a 1:1 ratio to receive additional concurrent therapy. This will effectively result in four treatment groups:

1. Standard of care alone
2. Standard of care plus hydroxychloroquine
3. Standard of care plus azithromycin
4. Standard of care plus hydroxychloroquine plus azithromycin

Detailed description:

Arms: arm 1: None arm 2: Standard of care plus hydroxychloroquine for 5 days arm 3: Standard of care plus azithromycin for 5 days arm 4: Standard of care plus hydroxychloroquine plus azithromycin for 5 days
Interventions: intervention 1: Standard of care intervention 2: Hydroxychloroquine intervention 3: Azithromycin
Intervention descriptions: intervention 1: Standard of care intervention 2: Hydroxychloroquine will be administered orally or via feeding tube at a dosage of 800 mg on day 1, followed by 600 mg daily on days 2-5 intervention 3: Azithromycin will be administered orally or via feeding tube at a dosage of 500 mg on day 1, followed by 250 mg daily on days 2-5

Protocol documents:
ICF_002.pdf: 
Consent to Participate in a Research Study
ADULT
Phase 2 Pragmatic Trial of Hydroxychloroquine, Azithromycin, or both for treatment of SARS-CoV-2 
Infection 
Page 1 of 8
Subject*Initials_________
DUKE UNIVERSITY HEALTH SYSTEM
Form
M0345
You are being asked to take part in this research study because you have infection with SARS-CoV-2 
virus causing Coronavirus Disease 19 (COVID19). Research studies are voluntary and include only 
people who choose to take part.  Please read this consent form carefully and take your time making your 
decision. As your study doctor or study staff discusses this consent form with you, please ask him/her to 
explain any words or information that you do not clearly understand.  We encourage you to talk with 
your family and friends before you decide to take part in this research study.  The nature of the study, 
risks, inconveniences, discomforts, and other important information about the study are listed below.  If 
you are a caregiver, the terms “You” and “Your” refer to the patients for whom you are making 
decisions.
Your decision about participation in this study will have no effect on the regular care you will receive at 
Duke.
Please tell the study doctor or study staff if you are taking part in another research study.
Dr. Jason Stout will conduct the study and it is funded by Duke University. 
WHO WILL BE MY DOCTOR ON THIS STUDY?
If you decide to participate, Dr. Jason Stout will be your doctor for the study and will be in contact with 
your regular health care provider throughout the time that you are in the study and afterwards, if needed.
CONCISE SUMMARY
Coronavirus Disease 19 (COVID19) has emerged as a global pandemic, with hospitalization and 
mortality rates far exceeding that of the seasonal influenza viruses. At the present time, no targeted 
medications exist for treatment of COVID19. Potentially reusing already existing medications 
approved for use in other conditions, such as Hydroxychloroquine and/or Azithromycin, may benefit 
patients with this infection.   Note that these study drugs are not approved for COVID19.
By your participation in this study, we hope to assess whether treatment with 5 days of 
Hydroxychloroquine alone, 5 days of Azithromycin alone, or 5 days of a combination of 
Hydroxychloroquine and Azithromycin, have an effect on COVID19. 
There are some risks to these study drugs that are described in this document. Some of these risks 
include diarrhea, nausea/vomiting, visual changes, etc. 
If you are interested in learning more about this study, please continue reading below.
DUHS IRB
IRB NUMBER: Pro00105339
IRB REFERENCE DATE: 04/13/2020
IRB EXPIRATION DATE: 04/09/2021


Consent to Participate in a Research Study
ADULT
Phase 2 Pragmatic Trial of Hydroxychloroquine, Azithromycin, or both for treatment of SARS-CoV-2 
Infection 
Page 2 of 8
Subject*Initials_________
DUKE UNIVERSITY HEALTH SYSTEM
Form
M0345
WHY IS THIS STUDY BEING DONE?
The SARS-CoV-2 virus can cause serious disease or death in some people who become infected.  There 
are no treatments that are proven to help people infected with the virus at this time.  This study will test 
two medicines that are currently available to treat other conditions, azithromycin and 
hydroxychloroquine, to see if they might help people who are infected with this virus. These medicines 
have been approved by the U.S. Food and Drug Administration (FDA) for many years, but not for the 
treatment of COVID.  Therefore,  these medicines are considered investigational drugs as used in this 
study. The word “investigational” means the study drug is still being tested in research studies and is not 
approved by the U.S. Food and Drug Administration (FDA) to treat COVID-19. 
HOW MANY PEOPLE WILL TAKE PART IN THIS STUDY?
Approximately 500 people will take part in this study at Duke University Hospital, Duke Regional 
Hospital, Duke Raleigh Hospital, the Durham Veterans Affairs Medical Center, among other medical 
centers nationwide. 
WHAT IS INVOLVED IN THE STUDY?
If you agree to be in this study, you will be asked to sign and date this consent form.  Your medical 
records will then be reviewed to make sure that you are eligible to participate in the study. There are 4 
arms in this research study.  You will be randomly assigned (like drawing numbers from a hat) to 1 of 
the 4 arms.  You will have about a 3 out of 4 chance of receiving at least 1 study drug.  The arms are:
1) 5 days of hydroxychloroquine alone
2) 5 days of azithromycin alone
3) 5 days of hydroxychloroquine + azithromycin
4) 5 days of no study drug.
Patients in all 4 arms will receive supportive care throughout the study.  At present, there is no effective 
drug to treat COVID-19.  If you are assigned to arm 4, you will receive the same care as if you were not 
in this study.
HOW LONG WILL I BE IN THIS STUDY?
You will be in the study for 28 days or for the rest of the time that you are in the hospital, whichever is 
longer.
You can choose to stop participating at any time without penalty or loss of any benefits to which you are 
entitled. However, if you decide to stop participating in the study, we encourage you to talk to your 
doctor first.
Clinically relevant results of this research will be communicated with you after conclusion of the study, 
analysis of the data, and publication of the results. 
DUHS IRB
IRB NUMBER: Pro00105339
IRB REFERENCE DATE: 04/13/2020
IRB EXPIRATION DATE: 04/09/2021


Consent to Participate in a Research Study
ADULT
Phase 2 Pragmatic Trial of Hydroxychloroquine, Azithromycin, or both for treatment of SARS-CoV-2 
Infection 
Page 3 of 8
Subject*Initials_________
DUKE UNIVERSITY HEALTH SYSTEM
Form
M0345
WHAT ARE THE RISKS OF THE STUDY?
As a result of your participation in this study, you are at risk for the following side effects. You should 
discuss these with the study doctor and your regular health care provider if you choose. 
Hydroxychloroquine may cause some, all or none of the side-effects listed below.
More likely

 Visual changes (blurred vision, color changes) – but usually with long term use
Less Likely

Stomach pain 

Nausea

Diarrhea

Dizziness

Headache

Nervousness

Nightmares

Suicidal thoughts

Muscle weakness

Hearing loss

Allergic reaction 

Skin rash

Abnormal liver test / liver injury

Abnormal heartbeat
Reproductive Risks

The effects of maternal COVID-19 infection on a developing pregnancy or breastfeeding 
infant are not known.   It is also not known if pregnancy or breastfeeding affect the outcomes 
of maternal COVID-19 infection.    Hydroxychloroquine is routinely used during pregnancy 
and lactation as treatment for autoimmune disease with no evidence of any adverse effects.  
Azithromycin may cause some, all or none of the side-effects listed below.
More likely 

Stomach pain 

Nausea

Diarrhea
DUHS IRB
IRB NUMBER: Pro00105339
IRB REFERENCE DATE: 04/13/2020
IRB EXPIRATION DATE: 04/09/2021


Consent to Participate in a Research Study
ADULT
Phase 2 Pragmatic Trial of Hydroxychloroquine, Azithromycin, or both for treatment of SARS-CoV-2 
Infection 
Page 4 of 8
Subject*Initials_________
DUKE UNIVERSITY HEALTH SYSTEM
Form
M0345
Less Likely

Headache

Dizziness

Allergic reaction 

Skin rash

Change in hearing

Abnormal heartbeat

Abnormal liver test / liver injury
For Those of Reproductive Potential

Azithromycin is generally considered safe in pregnancy. 
Drug and Food Interactions: For your safety, you must tell the study doctor or nurse about all the 
prescribed medical foods and drugs, herbal products, over-the-counter (OTC) drugs, vitamins, natural 
remedies, and alcohol that you are taking before you start the study and before starting to take any of 
these products while you are on the study.
There may be risks, discomforts, drug interactions or side effects that are not yet known.
ARE THERE BENEFITS TO TAKING PART IN THE STUDY?
If you agree to take part in this study, there may be direct medical benefit to you if you are placed in a 
study arm receiving either or both drugs. Receiving a study drug may improve the course of your illness 
with COVID19, including: preventing death, preventing or decreasing the need (number of days) for 
mechanical ventilation, decreasing the number of days in the hospital, and/or decreasing the severity or 
number of days of symptoms. We hope that in the future the information learned from this study will 
benefit other people with COVID19.   If you are placed in arm 4 (no drug), it is not expected that you 
will receive direct benefit from being in the study since it is the same care you would receive if you were 
not participating.
WHAT ARE MY ALTERNATIVES TO PARTICIPATING IN THIS STUDY?
You can choose not to participate, and you will continue to receive Duke’s usual care.  Also, there may 
be other COVID studies for which you are eligible.  Please talk to your study doctor about these other 
studies.
WILL MY INFORMATION BE KEPT CONFIDENTIAL?
Participation in research involves some loss of privacy.  We will do our best to make sure that 
information about you is kept confidential, but we cannot guarantee total confidentiality. Your personal 
information may be viewed by individuals involved in this research and may be seen by people 
including those collaborating, funding, and regulating the study. We will share only the minimum 
DUHS IRB
IRB NUMBER: Pro00105339
IRB REFERENCE DATE: 04/13/2020
IRB EXPIRATION DATE: 04/09/2021


Consent to Participate in a Research Study
ADULT
Phase 2 Pragmatic Trial of Hydroxychloroquine, Azithromycin, or both for treatment of SARS-CoV-2 
Infection 
Page 5 of 8
Subject*Initials_________
DUKE UNIVERSITY HEALTH SYSTEM
Form
M0345
necessary information in order to conduct the research. Your personal information may also be given out 
if required by law. Your records may be reviewed in order to meet federal or state regulations. 
Reviewers may include representatives from the Food and Drug Administration, and the Duke 
University Health System Institutional Review Board, and others as appropriate. If any of these groups 
review your research record, they may also need to review your entire medical record.
The study results will be retained in your research record for at least six years after the study is 
completed. At that time either the research information not already in your medical record may be 
destroyed or information identifying you will be removed from such study results at DUHS.  Any 
research information in your medical record will be kept indefinitely.
While the information and data resulting from this study may be presented at scientific meetings or 
published in a scientific journal, your name or other personal information will not be revealed.
Some people or groups who receive your health information might not have to follow the same privacy 
rules. Once your information is shared outside of DUHS, we cannot guarantee that it will remain private. 
If you decide to share private information with anyone not involved in the study, the federal law 
designed to protect your health information privacy may no longer apply to the information you have 
shared.  Other laws may or may not protect sharing of private health information.
WHAT ARE THE COSTS TO YOU?
You or your insurance provider will be responsible and billed for all costs related to your routine 
medical care, including copayments and deductibles. Routine medical care services are those that you 
would have received for your condition if you were not participating in this research study. Not all 
services are covered by insurance.  Some procedures or scans may require pre-authorization by your 
insurance plan. We will notify you if we learn that a service is not covered by your insurance plan as 
part of the pre-authorization process. If it is not covered, you will be responsible for paying for it.  The 
amount of your out-of-pocket expense will depend on your insurance plan.  For beneficiaries with 
Medicare Advantage Plans, traditional Medicare is billed for the routine cost of a research study.  You 
may have more or higher co-pays than with a Medicare Advantage plan.  Please discuss the costs of the 
study with Dr. Jason Stout. At your request, a Financial Counselor in the clinic may provide you with an 
estimate of costs for routine services.
We will monitor your DUHS patient care charges to make sure that costs are directed appropriately.  If 
you have any questions or concerns about appropriate billing, contact your study team coordinator so 
that he/she can help find a resolution.
Please note: Taking part in this study may cost you and/or your insurance company more than the cost 
of getting regular medical treatment. The additional costs would include the cost of the study drugs 
hydroxychloroquine or azithromycin.
DUHS IRB
IRB NUMBER: Pro00105339
IRB REFERENCE DATE: 04/13/2020
IRB EXPIRATION DATE: 04/09/2021


Consent to Participate in a Research Study
ADULT
Phase 2 Pragmatic Trial of Hydroxychloroquine, Azithromycin, or both for treatment of SARS-CoV-2 
Infection 
Page 6 of 8
Subject*Initials_________
DUKE UNIVERSITY HEALTH SYSTEM
Form
M0345
WHAT ABOUT COMPENSATION?
You will not be reimbursed for your expenses related to your participation (parking, gas, and time).
WHAT ABOUT RESEARCH RELATED INJURIES?
Immediate necessary medical care is available at Duke University Medical Center in the event that you 
are injured as a result of your participation in this research study. However, there is no commitment by 
Duke University, Duke University Health System, Inc., or your Duke physicians to provide monetary 
compensation or free medical care to you in the event of a study-related injury.
For questions about the study or research-related injury, contact Dr. Jason Stout at 919-668-0826 during 
regular business hours and at 919-684-8111 after hours and on weekends and holidays and ask to have 
Dr. Stout paged.
WHAT ABOUT MY RIGHTS TO DECLINE PARTICIPATION OR WITHDRAW FROM THE 
STUDY?
You may choose not to be in the study, or, if you agree to be in the study, you may withdraw from the 
study at any time. If you withdraw from the study, no new data about you will be collected for study 
purposes unless the data concern an adverse event (a bad effect) related to the study.  If such an adverse 
event occurs, we may need to review your entire medical record.  
Your decision not to participate or to withdraw from the study will not involve any penalty or loss of 
benefits to which you are entitled, and will not affect your access to health care at Duke. If you do 
decide to withdraw, we ask that you contact Dr. Jason Stout in writing and let him know that you are 
withdrawing from the study. His mailing address is Box 102359-DUMC, Durham, NC 27710. 
We will tell you about new information that may affect your health, welfare, or willingness to stay in 
this study.
Your doctor may decide to take you off this study if your condition gets worse, if you have serious side 
effects, or if your study doctor determines that it is no longer in your best interest to continue. If this 
occurs, you will be notified and your study doctor will discuss other options with you.
DUHS IRB
IRB NUMBER: Pro00105339
IRB REFERENCE DATE: 04/13/2020
IRB EXPIRATION DATE: 04/09/2021


Consent to Participate in a Research Study
ADULT
Phase 2 Pragmatic Trial of Hydroxychloroquine, Azithromycin, or both for treatment of SARS-CoV-2 
Infection 
Page 7 of 8
Subject*Initials_________
DUKE UNIVERSITY HEALTH SYSTEM
Form
M0345
Biological Samples/Specimens 
As part of your regular medical treatment (not as part of this study), blood samples will be drawn. From 
those samples, for this study, we would like to collect left over blood.  If you would like to allow us to 
keep your leftover blood, you will be asked to sign a separate consent form titled “Duke Shared Data 
and Specimen Repository Regarding COVID-19 Patients.”  If you agree to allow your blood to be kept 
for future research with identifying information that could link your sample to you, you are free to 
change your mind at any time.
Study registered on the web site ClinicalTrials.gov
A description of this clinical trial will be available on https://clinicaltrials.gov/  as required by U.S. Law.  
This Web site will not include information that can identify you. At most, the Web site will include a 
summary of the results. You can search this Web site at any time.
WHOM DO I CALL IF I HAVE QUESTIONS OR PROBLEMS?
For questions about the study or a research-related injury, or if you have problems, concerns, questions 
or suggestions about the research, contact Dr. Jason Stout at 919-668-0826 during regular business hours 
and at 919-684-8111 after hours and on weekends and holidays.
For questions about your rights as a research participant, or to discuss problems, concerns or suggestions 
related to the research, or to obtain information or offer input about the research, contact the Duke 
University Health System Institutional Review Board (IRB) Office at (919) 668-5111.
DUHS IRB
IRB NUMBER: Pro00105339
IRB REFERENCE DATE: 04/13/2020
IRB EXPIRATION DATE: 04/09/2021


Consent to Participate in a Research Study
ADULT
Phase 2 Pragmatic Trial of Hydroxychloroquine, Azithromycin, or both for treatment of SARS-CoV-2 
Infection 
Page 8 of 8
*
DUKE UNIVERSITY HEALTH SYSTEM
Form
M0345
STATEMENT OF CONSENT
"The purpose of this study, procedures to be followed, risks and benefits have been explained to me. I 
have been allowed to ask questions, and my questions have been answered to my satisfaction. I have 
been told whom to contact if I have questions, to discuss problems, concerns, or suggestions related to 
the research, or to obtain information or offer input about the research. I have read this consent form and 
agree to be in this study, with the understanding that I may withdraw at any time.  I have been told that I 
will be given a signed and dated copy of this consent form."
__________________________________________
___________     ____________
Signature of Subject
Date
   Time
__________________________________________
___________     ____________
Signature of Person Obtaining Consent
Date
   Time
"The purpose of this study, procedures to be followed, risks and benefits have been explained to me. I 
have been allowed to ask questions, and my questions have been answered to my satisfaction. I have 
been told whom to contact if I have questions, to discuss problems, concerns, or suggestions related to 
the research, or to obtain information or offer input about the research. I have read this consent form and 
agree to be in this study, with the understanding that I may withdraw at any time. I have been told that I 
will be given a signed copy of this consent form."
 
“I am the representative of the subject and am acting on behalf of the subject. I am not aware of any 
factor that might create a conflicting interest for me in this role (for example, something that might bring 
me personal benefit). I consent to the subject's participation in this study.
__________________________________________
___________   ___________
Signature of Legal Representative
Date
    Time
__________________________________________
Relationship to Subject
__________________________________________
___________   ___________
Signature of Person Obtaining Consent
Date                  Time
DUHS IRB
IRB NUMBER: Pro00105339
IRB REFERENCE DATE: 04/13/2020
IRB EXPIRATION DATE: 04/09/2021

SAP_003.pdf: 
Date: May 1, 2020 
Version 1.0 
Page 1 
 
 
 
 
 
 
 
 
PROTECT Trial 
STATISTICAL ANALYSIS PLAN 
 
 
May 1, 2020 
 
Version 1.0 
 
 
 


Date: May 1, 2020 
Version 1.0 
Page 2 
TABLE OF CONTENTS 
 
1 
ABBREVIATIONS .................................................................................................................................... 3 
2 
INTRODUCTION ..................................................................................................................................... 3 
3 
STUDY DESIGN AND OBJECTIVES .......................................................................................................... 3 
3.1 
Primary Objective.......................................................................................................................... 4 
3.2 
Secondary Objectives .................................................................................................................... 4 
3.3 
Tertiary Objectives (Exploratory) .................................................................................................. 4 
4 
RANDOMIZATION METHODOLOGY ...................................................................................................... 4 
5 
POPULATIONS FOR EFFICACY AND SAFETY ANALYSES ......................................................................... 5 
5.1 
Intention-to-treat population ....................................................................................................... 5 
6 
DESCRIPTION OF EFFICACY ENDPOINTS ............................................................................................... 5 
6.1 
Primary Endpoint .......................................................................................................................... 5 
7 
GENERAL ANALYSIS CONSIDERATIONS ................................................................................................. 6 
7.1 
Missing Data .................................................................................................................................. 6 
7.2 
Pooling Across Trial Sites .............................................................................................................. 7 
7.3 
Withdrawals, Dropouts, Loss to Follow-up ................................................................................... 7 
8 
ANALYSIS OF THE PRIMARY ENDPOINT ................................................................................................ 7 
8.1 
Parametric Win Ratio Analysis ...................................................................................................... 7 
8.2 
Calculation Formulas for the Parametric Win Ratio ..................................................................... 8 
8.3 
Statistical Model ........................................................................................................................... 9 
8.4 
Estimation Methods .................................................................................................................... 10 
8.5 
Secondary Analyses of the Primary Endpoint ............................................................................. 11 
8.6 
Contingency for Violation of Proportional Odds Assumption .................................................... 12 
8.7 
Exploratory Pairwise Group Comparisons .................................................................................. 12 
9 
ANALYSIS OF SECONDARY EFFICACY ENDPOINTS ............................................................................... 12 
10 
PRESENTATION OF SAFETY DATA .................................................................................................... 13 
11 
INTERIM ANALYSES ......................................................................................................................... 14 
11.1 
Multiplicity considerations for interim analyses ......................................................................... 15 
12 
REFERENCES .................................................................................................................................... 15 
 
 
 
 
 


Date: May 1, 2020 
Version 1.0 
Page 3 
 
 
1 
ABBREVIATIONS 
 
Abbreviation 
Description 
AZM 
Azithromycin 
DSMB 
Data Safety Monitoring Board 
HCQ 
Hydroxychloroquine 
SOC 
Standard of Care 
 
 
2 
INTRODUCTION 
 
The purpose of this document is to describe statistical analysis plans for the PROTECT Trial interim and 
final analyses.  It includes an overview of the project, description of endpoints, general analysis 
conventions, analysis populations, handling of missing data, statistical analyses, and guidelines for 
interpreting interim analysis results. The statistical team intends to perform all statistical analyses as 
specified in the protocol. However, it is conceivable that unanticipated changes to the course of the 
study may preclude some scheduled analyses. Study conditions or analysis results may identify a need 
for additional data review.  
 
3 
STUDY DESIGN AND OBJECTIVES 
 
PROTECT is an open-label, factorial randomized clinical trial with two factors and nested randomization.  
Patients hospitalized with confirmed SARS-CoV-2 infection will be initially randomized to one of two 
arms in a 1:1 ratio: 1) Standard of care treatment or 2) Standard of care treatment plus 5 days of 
hydroxychloroquine (HCQ).  Patients with no contraindication to azithromycin (AZM) who have not 
received AZM in the seven days prior to enrollment will undergo a second randomization in a 1:1 ratio to 
either receive 1) No AZM or 2) 5 days of AZM. The resulting treatment group combinations are 
summarized in Table 1. Participants will be followed for 28 days after randomization or until hospital 
discharge, whichever is later. The primary endpoint is the World Health Organization (WHO) ordinal 
scale for clinical improvement as measured on day 14 after randomization (see Section 6.1 for details). 
 
Table 1. Treatment groups 
 
AZM: No 
AZM: Yes 
AZM: Not Eligible 
HCQ: No 
Group 1: 
SOC 
Group 3: 
SOC + AZM 
Group 5: 
SOC, AZM-ineligible 
HCQ: Yes 
Group 2: 
SOC + HCQ 
Group 4: 
SOC + HQC + AZM 
Group 6: 
SOC + HCQ, AZM-ineligible 
HCQ = hydroxychloroquine, AZM = azithromycin, SOC = standard of care 
Hypothesis #1 (HCQ versus no HCQ): Groups 2+4+6 versus 1+3+5 
Hypothesis #2 (AZM versus no AZM): Groups 3+4 versus 1+2 
 


Date: May 1, 2020 
Version 1.0 
Page 4 
3.1 
Primary Objective 
 
The PROTECT trial aims to simultaneously test the following two primary hypotheses: 
 
• 
Hypothesis #1 (HCQ versus no HCQ):  The addition of HCQ improves outcomes as measured by 
the day 14 WHO ordinal scale (primary endpoint) when added to standard of care and possible 
concomitant AZM. The analysis will be a comparison of groups 2+4+6 versus 1+3+5 as defined in 
Table 1.  
 
• 
Hypothesis #2 (AZM versus no AZM): The addition of AZM improves outcomes as measured by 
the day 14 WHO ordinal scale (primary endpoint) when added to standard of care and possible 
concomitant HCQ. The analysis will be a comparison of groups 3+4 versus 1+2 as defined in 
Table 1. 
 
3.2 
Secondary Objectives 
 
The trial will also evaluate the HCQ and AZM hypotheses using the following secondary endpoints: 
 
• 
Mortality during the index hospitalization 
• 
Number of days on mechanical ventilation during the index hospitalization 
• 
Progression to mechanical ventilation during index hospitalization 
• 
World Health Organization ordinal scale on day 28 
• 
Days from randomization until hospital discharge 
• 
Duration of fever after randomization 
• 
Duration of supplemental oxygen use after randomization 
 
3.3 
Tertiary Objectives (Exploratory) 
 
The trial will perform additional exploratory pairwise treatment group comparisons for the primary and 
secondary endpoints as follows (see Table 1 for definitions of study groups): 
 
• 
SOC + HCQ versus SOC (group 2 versus 1) 
• 
SOC + AZM versus SOC (group 3 versus 1) 
• 
SOC + HCQ + AZM versus SOC (group 4 versus 1)  
• 
SOC + AZM versus SOC + HCQ (group 3 versus 2) 
• 
SOC + HCQ + AZM versus SOC + HCQ (group 4 versus 2) 
• 
SOC + HCQ + AZM versus SOC + AZM (group 4 versus 3) 
 
4 
RANDOMIZATION METHODOLOGY 
 
Patients meeting entry criteria will be stratified by eligibility to undergo randomizations for both study 
drugs or only HCQ.  
 
Stratum 1: Eligible for both study drugs 
Participants who are eligible for both study drugs will be randomized in a 1:1:1:1 ratio to one of the 
following:  
Group 
Description 


Date: May 1, 2020 
Version 1.0 
Page 5 
1 
Standard of Care 
 
 
2 
Standard of Care + HCQ 
 
3 
Standard of Care 
 
+ AZM 
4 
Standard of Care + HCQ + AZM 
 
Stratum 2: Ineligible for azithromycin 
Participants who are ineligible to be randomized to azithromycin will be randomized in a 1:1 ratio to one 
of the following groups 
Group 
Description 
5 
Standard of Care 
-- 
 
6 
Standard of Care + HCQ 
 
 
Randomizations within each stratum will use permuted blocks with random block sizes and will be 
further stratified by ventilator status at baseline.  
 
5 
POPULATIONS FOR EFFICACY AND SAFETY ANALYSES 
 
5.1 
Intention-to-treat population 
 
The intention-to-treat (ITT) population will include all participants who receive a randomized treatment 
assignment, including those who are later determined not to meet trial eligibility criteria, unless the 
randomization was an unintentional administrative error, as determined by the coordinating center at 
the Duke Office of Clinical Research. Patients will be assigned to treatment groups based on each 
patient's randomized treatment group assignment regardless of which treatment if any the patient 
actually received. 
 
 
6 
DESCRIPTION OF EFFICACY ENDPOINTS 
 
6.1 
Primary Endpoint 
 
The primary outcome measure is the World Health Organization (WHO) ordinal scale for clinical 
improvement as measured on day 14 after randomization. The WHO scale has 9 levels numbered 0 to 8 
with 0 denoting no clinical or viroligic evidence of infection and 8 denoting death.  
 
Table 2. World Health Organization ordinal scale for clinical improvement 
Descriptor  
Score 
No clinical or virologic evidence of infection  
0 
No limitation of activities  
1 
Limitation of activities  
2 
Hospitalized, no oxygen therapy  
3 
Oxygen by mask or nasal cannula  
4 
Non-invasive ventilation or high-flow oxygen  
5 
Intubation and mechanical ventilation 
6 
Mechanical ventilation + additional organ support (pressors, renal replacement therapy, 
ECMO)  
7 
Death  
8 


Date: May 1, 2020 
Version 1.0 
Page 6 
 
 
7 
GENERAL ANALYSIS CONSIDERATIONS 
 
Analyses will be performed according to the principle of "intention-to-treat" with subjects analyzed (and 
endpoints attributed) according to the group to which enrolled subjects were randomized, regardless of 
subsequent medications or treatment crossover. All major treatment group comparisons will be 
performed using Bayesian statistical methods. The output of a Bayesian analysis is a posterior 
probability distribution describing the relative likelihood of different numerical estimates for unknown 
quantities. This posterior distribution can be used to determine the likelihood of a clinically important 
treatment benefit or harm in light of the study data. The Bayesian approach provides an especially 
useful perspective for interpreting results of small studies that are likely to be accompanied by 
substantial statistical uncertainty. The Bayesian analog of a confidence interval, known as a credible 
interval, has a direct and intuitively appealing interpretation as an interval containing the true value with 
a specified probability. Point estimates will be calculated as posterior means and accompanied with 95% 
equal-tailed credible intervals. Analysis results will also be framed in terms of probability statements, for 
example, the probability that the study drugs lead to improved outcomes on the primary endpoint. The 
analysis plan does not include frequentist hypothesis testing and does not make adjustment for multiple 
comparisons. Additional considerations related to multiple comparisons are discussed in Sections 11.1. 
 
7.1 
Missing Data 
 
Every effort will be made to obtain complete data. In the case where missing data remain, the following 
procedures will be followed. These procedures are based on the assumption that missing data will be 
rare and may be revised if that assumption is violated.  
• 
Primary endpoint. If a day 14 WHO scale assessment is unavailable then analysis will be based 
on the closest assessment within 21 days of randomization with ties broken by taking the earlier 
assessment. If a patient is known to have died or been re-hospitalized but the exact date is 
unknown then data entry may be based on an estimated value. If no estimate of a patient's 
status is available within 21 days of randomization then the primary endpoint will be regarded 
as missing and will not be imputed. The approach to handling missing primary endpoint data 
may be revised if >5% of patients have no assessments within a window of 14 ± 3 days or >2% of 
patients have no assessments within a window of 14 ± 6 days. 
• 
Mortality during the index hospitalization. Missing in-hospital mortality status will not be 
imputed.  
• 
Number of days on mechanical ventilation during index hospitalization.  No imputation will be 
performed for this endpoint. 
• 
Progression to mechanical ventilation during index hospitalization. No imputation will be 
performed for this endpoint.  
• 
Day 28 WHO scale.  If unavailable then analysis will use the closest measurement from days 14 
to 40 with ties broken by taking the later assessment. Data entry may be based on estimated 
dates if exact dates for a status assessment is unavailable.  
• 
Days from randomization until hospital discharge. No imputation will be performed for this 
endpoint.  
• 
Duration of fever after randomization.  No imputation will be performed for this endpoint. 
• 
Duration of supplemental oxygen use after randomization.  No imputation will be performed 
for this endpoint. 


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7.2 
Pooling Across Trial Sites 
 
All data from all sites will be pooled for analysis. Study site will be ignored in the primary analysis of the 
primary endpoint but will be included as a covariate in a planned covariate-adjusted secondary analysis. 
 
7.3 
Withdrawals, Dropouts, Loss to Follow-up 
 
All patients and all data will be included in the analyses. Patients who withdraw from the study or are 
lost to follow-up before collection of the primary endpoint will be analyzed using their last available 
follow-up data according to the imputation rules described in Section 7.1. Participants with no 
analyzable follow-up data for any safety or efficacy endpoints will be excluded and will not appear in 
tabulations of baseline data. The number of such exclusions, if any, will be reported.  
 
8 
ANALYSIS OF THE PRIMARY ENDPOINT 
 
8.1 
Parametric Win Ratio Analysis 
 
The primary endpoint analysis will focus on assessing the overall effects of standard of care plus HCQ 
versus no HCQ (Hypothesis #1) and AZM versus no AZM (Hypothesis #2), as detailed in Section 3.1. 
Analysis will be performed in the intention-to-treat (ITT) population, as defined in Section 3.1. The 
analytic approach will be a model-based parametric implementation of the win ratio framework. [1] In a 
conventional win ratio analysis, the win ratio statistic is calculated by forming all possible pairs of 1 
participant from the treatment group and 1 participant from the control group and then dividing the 
proportion of pairs for which the treated patient has a better outcome by the proportion of pairs for 
which the untreated patient has a better outcome. The PROTECT trial analysis will estimate this same 
underlying win ratio quantity but will do so parametrically using a statistical model. The parametric 
approach was chosen because it facilitates analysis in a Bayesian statistical framework using a range of 
Bayesian prior distributions. A Bayesian nonparametric implementation of the win ratio with a non-
informative prior distribution was tested in simulations prior to trial launch and was found to be anti-
conservative in the sense that the prior distribution assigned high prior probability to the hypothesis of 
large or small win ratio and this led to high probability of a spurious signal during interim analyses. The 
underlying quantities to be estimated in this analysis are as follows: 
 
Win Ratio for Hypothesis #1 (HCQ versus no HCQ): The win ratio for HCQ versus no HCQ is defined as 
the probability that a randomly selected patient who was randomized to HCQ has a better outcome 
than a randomly selected patient from the same AZM subgroup who was randomized to no HCQ divided 
by the probability that a randomly selected patient who was randomized to HCQ has a worse outcome 
than a randomly selected patient from the same AZM subgroup who was randomized to no HCQ.  
 
Win Ratio for Hypothesis #2 (AZM versus no AZM): The win ratio for AZM versus no AZM is defined as 
the probability that a randomly selected patient who was randomized to AZM has a better outcome 
than a randomly selected patient from the same HCQ subgroup who was randomized to no AZM divided 
by the probability that a randomly selected patient who was randomized to AZM has a worse outcome 
than a randomly selected patient from the same HCQ subgroup who was randomized to no AZM. 
 


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8.2 
Calculation Formulas for the Parametric Win Ratio 
 
The WHO primary endpoint is a categorical variable with 9 categories labeled 0 to 8 where 0 represents 
no clinical or virological evidence of infection and category 8 represents death. Because there are 9 
possible values, the probability distribution of the primary endpoint within each treatment group can be 
described by a set of 9 probabilities which sum to 1. We will use notation 𝜋𝑔𝑗 to denote the probability 
that the primary endpoint of a patient in group 𝑔 takes the value 𝑗 (see Table 3). Using this notation, the 
probability that a patient in group 𝑔 has a better outcome (win) than a patient in group ℎ can be 
calculated by the expression: 
𝑊𝑔:ℎ= 𝑊𝑔:ℎ(𝝅) = Pr(𝑌𝑔< 𝑌ℎ) = ∑Pr(𝑌𝑔= 𝑗) Pr(𝑌ℎ> 𝑗) = ∑𝜋𝑔𝑗(𝜋ℎ,𝑗+1 + ⋯+ 𝜋ℎ,8) 
7
𝑗=0
7
𝑗=0
 
and this expression holds for all 𝑔, ℎ= 1,2, … ,6. We use the notation 𝑊𝑔:ℎ= 𝑊𝑔:ℎ(𝝅) to emphasize 
that 𝑊𝑔:ℎ is implicitly a function of the unknown 𝜋𝑔𝑗's as defined in Table 3. The win ratio comparing 
groups 𝑔 versus ℎ is then given by 
Win-Ratio𝑔:ℎ= 𝑊𝑔:ℎ
𝑊ℎ:𝑔
. 
 
Hypothesis #1 (HCQ). The win ratio for Hypothesis #1 is a stratified version of the win ratio. It first 
randomly selects a patient from one of the HCQ groups (groups 2, 4, or 6) and then randomly selects a 
comparison patient from the corresponding non-HCQ group within the same AZM stratum, such that 
group 2 is paired with group 1, group 4 is paired with 3, and group 6 is paired with 5. The win ratio is the 
probability that the patient receiving HCQ has a better outcome than the patient not receiving HCQ 
divided by the probability that the patient receiving HCQ has a worse outcome than the patient not 
receiving HCQ. Mathematically, this turns out to be equivalent to a weighted average of 3 pairwise win 
ratios for groups 2 versus 1, 4 versus 3, and 6 versus 5. Specifically, the calculation formula for the 
hypothesis #1 win ratio is 
Win-RatioHQC = (𝑛1 + 𝑛2
𝑛
)  𝑊2:1
 𝑊1:2
  + (𝑛3 + 𝑛4
𝑛
)  𝑊4:3
 𝑊3:4
 + (𝑛5 + 𝑛6
𝑛
)  𝑊6:5
 𝑊5:6
  
where 𝑛𝑔is the number of participants in the 𝑔-th treatment stratum and 𝑛= 𝑛1 + ⋯+ 𝑛6 is the total 
sample size.  
 
Hypothesis #2 (AZM). The win ratio for Hypothesis #2 is a stratified version of the win ratio. It first 
randomly selects a patient from one of the randomized AZM groups (groups 3 or 4) and then randomly 
selects a comparison patient from the corresponding non-AZM group within the same level of HCQ, such 
that group 3 is paired with 1 and group 4 is paired with 2. The win ratio is the probability that the 
patient receiving AZM has a better outcome than the patient not receiving AZM divided by the 
probability that the patient receiving AZM has a worse outcome than the patient not receiving AZM. 
Mathematically, this turns out to be equivalent to a weighted average of 2 pairwise win ratios for groups 
3 versus 1 and 4 versus 2. Specifically, the calculation formula for the hypothesis #1 win ratio is 
Win-RatioAZM = (
𝑛1 + 𝑛2
𝑛1 + 𝑛2 + 𝑛3 + 𝑛4 )  𝑊2:1
 𝑊1:2
  + (
𝑛3 + 𝑛4
𝑛1 + 𝑛2 + 𝑛3 + 𝑛4
)  𝑊4:3
 𝑊3:4
. 
 
Table 3. Notation for defining the distribution of WHO categories within each treatment group 
 
Group 1 
Group 2 
Group 3 
Group 4 
Group 5 
Group 6 
0 
𝜋10 
𝜋20 
𝜋30 
𝜋40 
𝜋50 
𝜋60 
1 
𝜋11 
𝜋21 
𝜋31 
𝜋41 
𝜋51 
𝜋61 


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2 
𝜋12 
𝜋22 
𝜋32 
𝜋42 
𝜋52 
𝜋62 
3 
𝜋13 
𝜋23 
𝜋33 
𝜋43 
𝜋53 
𝜋63 
4 
𝜋14 
𝜋24 
𝜋34 
𝜋44 
𝜋54 
𝜋64 
5 
𝜋15 
𝜋25 
𝜋35 
𝜋45 
𝜋55 
𝜋65 
6 
𝜋16 
𝜋26 
𝜋36 
𝜋46 
𝜋56 
𝜋66 
7 
𝜋17 
𝜋27 
𝜋37 
𝜋47 
𝜋57 
𝜋67 
8 
𝜋18 
𝜋28 
𝜋38 
𝜋48 
𝜋58 
𝜋68 
Note: 𝜋𝑔1 + 𝜋𝑔2 + ⋯+ 𝜋𝑔8 = 1 for all 𝑔= 1,2, … ,6. 
 
A point estimate of the win ratio can be calculated using the "plug-in" method by substituting (i.e. 
plugging in) data-based estimates 𝜋̂𝑔𝑗 in place of the unknown 𝜋𝑔𝑗's in the calculation formulas given 
above. This leads to estimates of the form 
Win-Ratio
̂
HQC = (𝑛1 + 𝑛2
𝑛
)  𝑊̂2:1
 𝑊̂1:2
  + (𝑛3 + 𝑛4
𝑛
)  𝑊̂4:3
 𝑊̂3:4
 + (𝑛5 + 𝑛6
𝑛
)  𝑊̂6:5
 𝑊̂5:6
 
Win-Ratio
̂
AZM = (
𝑛1 + 𝑛2
𝑛1 + 𝑛2 + 𝑛3 + 𝑛4
) 𝑊̂2:1
 𝑊̂1:2
  + (
𝑛3 + 𝑛4
𝑛1 + 𝑛2 + 𝑛3 + 𝑛4
)  𝑊̂4:3
 𝑊̂3:4
 
 where   𝑊̂𝑔:ℎ= ∑𝜋̂𝑔𝑗(𝜋̂ℎ,𝑗+1 + ⋯+ 𝜋̂ℎ,8),    𝑔, ℎ= 1,2,3,4,5,6
7
𝑗=0
, 
and 𝜋̂𝑔𝑗 is a data-based estimator of 𝜋𝑔𝑗. For example, in a simple (non-Bayesian) nonparametric 
analysis we could plug in 𝜋̂𝑔𝑗= 𝑛𝑔𝑗/𝑛𝑔∙where 𝑛𝑔𝑗 is the number of participants in group 𝑔 with a WHO 
score equal to 𝑗.  The primary analysis method is similar to this but uses Markov Chain Monte Carlo 
methods for inference and will estimate 𝜋𝑔𝑗's parametrically using a statistical model as defined in 
Section 8.3.  
 
8.3 
Statistical Model 
 
The trial's primary endpoint is a numeric variable taking the values 0 to 8 where 0 represents no clinical 
or virological evidence of infection and category 8 represents death. To account for this variable's 
discreteness and reduce dependence on modeling assumptions, the outcome will be analyzed as an 
ordered categorical variable without assuming a specific parametric distribution. The primary analysis 
will be performed using a parametric cumulative logits (aka proportional odds) model. The proportional 
odds methodology is an extension of binary logistic regression to accommodate 𝐾> 2 ordered outcome 
categories. The model considers all possible ways of dichotomizing 𝐾 categories into a binary outcome 
and assumes that the set of all possible binary outcomes is related to covariates through a set of 
ordinary binary logistic regression models with shared regression coefficients. The specific form of the 
model is 
logit Pr(𝑌≤𝑘|𝐻, 𝐴, 𝑥) =
{
  
 
  
 𝜃𝑘+ 𝜇+ 𝛾2 + 𝛿2 + 𝜷′𝒙
if  𝐻= 0, 𝐴= 0   (group 1)
𝜃𝑘+ 𝜇+ 𝛾2 −𝛿1 + 𝜷′𝒙
if  𝐻= 1, 𝐴= 0   (group 2)
𝜃𝑘+ 𝜇+ 𝛾1 + 𝛿2 + 𝜷′𝒙
if  𝐻= 0, 𝐴= 1   (group 3)
𝜃𝑘+ 𝜇+ 𝛾1 + 𝛿1 + 𝜷′𝒙
if  𝐻= 1, 𝐴= 1   (group 4)
𝜃𝑘+ 𝜇+ 𝛾2 −𝛿2 + 𝜷′𝒙
if  𝐻= 0, 𝐴= 2   (group 5)
𝜃𝑘+ 𝜇+ 𝛾2 + 𝛿2 + 𝜷′𝒙
if  𝐻= 1, 𝐴= 2   (group 6)
,      𝑘= 0,1, … ,7 
where logit 𝑝= log 𝑝/(1 −𝑝), 𝑌 denotes the outcome, 𝐻 is an indicator of HCQ randomization 
assignment (0 = randomized to no HCQ, 1 = randomized to HCQ), 𝐴 is an indicator of AZM randomization 
assignment (0 = randomized to no AZM, 1 = randomized to AZM, 2 = N/A, not eligible for AZM 


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randomization), the 𝜃𝑘's (𝑘= 0,1, … ,7) are intercepts describing the cumulative frequency of WHO 
categories within each treatment group, and 𝜇, 𝛾1, 𝛾2, 𝛿1,𝛿2 are main effects and interaction 
parameters describing outcome differences across treatment groups. The terms 𝛿1 and 𝛿2 are 
interaction terms and they describe the extent to which the treatment effect of randomization to HCQ 
versus no HCQ to differs depending on AZM group assignment and vice versa. Sample size calculations 
for PROTECT were based on fitting a model that omits interaction effects and assumes that 𝛿1 = 𝛿2 = 0. 
Under the assumed model we have the following expressions for the probabilities defined in Table 1: 
 
Table 4. Expressions for cell probabilities as a function of proportional odds model parameters 
 
𝜋1𝑗=
exp(𝜃𝑗)
1 + exp(𝜃𝑗) −
exp(𝜃𝑗−1)
1 + exp(𝜃𝑗−1) 
 
𝜋2𝑗=
exp(𝜃𝑗+ 𝜇)
1 + exp(𝜃𝑗+ 𝜇) −
exp(𝜃𝑗−1 + 𝜇)
1 + exp(𝜃𝑗−1 + 𝜇) 
 
𝜋3𝑗=
exp(𝜃𝑗+ 𝛾1)
1 + exp(𝜃𝑗+ 𝛾1) −
exp(𝜃𝑗−1 + 𝛾1)
1 + exp(𝜃𝑗−1 + 𝛾1) 
 
𝜋4𝑗=
exp(𝜃𝑗+ 𝜇+ 𝛾2 + 𝛿2)
1 + exp(𝜃𝑗+ 𝜇+ 𝛾2 + 𝛿2) −
exp(𝜃𝑗−1 + 𝜇+ 𝛾2 + 𝛿2)
1 + exp(𝜃𝑗−1 + 𝜇+ 𝛾2 + 𝛿2) 
 
𝜋4𝑗=
exp(𝜃𝑗+ 𝜇+ 𝛾1 + 𝛿1)
1 + exp(𝜃𝑗+ 𝜇+ 𝛾1 + 𝛿1) −
exp(𝜃𝑗−1 + 𝜇+ 𝛾1 + 𝛿1)
1 + exp(𝜃𝑗−1 + 𝜇+ 𝛾1 + 𝛿1) 
 
𝜋5𝑗=
exp(𝜃𝑗+ 𝛾2)
1 + exp(𝜃𝑗+ 𝛾2) −
exp(𝜃𝑗−1 + 𝛾2)
1 + exp(𝜃𝑗−1 + 𝛾2) 
 
𝜋6𝑗=
exp(𝜃𝑗+ 𝜇+ 𝛾2 + 𝛿2)
1 + exp(𝜃𝑗+ 𝜇+ 𝛾2 + 𝛿2) −
exp(𝜃𝑗−1 + 𝜇+ 𝛾2 + 𝛿2)
1 + exp(𝜃𝑗−1 + 𝜇+ 𝛾2 + 𝛿2) 
for 𝑗= 0,1, … 8, where 𝜃−1 = −∞ and 𝜃8 = ∞. 
 
8.4 
Estimation Methods 
 
Model parameters will be estimated in a Bayesian statistical framework using Markov Chain Monte 
Carlo sampling for inference [2]. Advantages of the Bayesian framework include the ability to express 
analysis results in terms of clinically relevant probabilities and the ability to perform exact inference on 
complicated functions of model parameters, for example, the win ratio.  
 
Prior distribution 
 
Bayesian analysis requires the specification of a probability distribution representing prior information 
about the set of unknown model parameters before observing the study data. Because no single choice 
of prior can accurately capture the viewpoints of all potential stakeholders, the analysis will be 
performed with multiple choices for the prior distribution. For the primary analysis, the prior for 
treatment main and interaction effects will be a set of independent normal distributions:  


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𝜇∼𝑁(mean = 0, SD = 0.3537)   (main effect) 
𝛾1 ∼𝑁(mean = 0, SD = 0.3537)   (main effect) 
𝛾2 ∼𝑁(mean = 0, SD = 0.3537)   (main effect) 
𝛿1 ∼𝑁(mean = 0, SD = 0.2651)   (interaction) 
𝛿2 ∼𝑁(mean = 0, SD = 0.2651)   (interaction) 
The main effects SD = 0.3537 was chosen to imply that odds ratios for HCQ versus no HCQ and AZM 
versus no AZM are between 0.5 and 2.0 with 95% probability assuming that the interaction effects are 
zero. The interaction SD = 0.2651 was chosen to imply that the ratio of odds ratios for HCQ versus no 
HCQ across two levels of AZM and the ratio of odds ratios for AZM versus no AZM across two levels of 
HCQ would each be between 0.8 and 1.25 with 80% probability. The intercept parameters 𝜃𝑘will be 
assigned central 𝑡 distributions with 3 degrees of freedom and SD = 10 subject to the constraint 𝜃0 <
𝜃2 < ⋯< 𝜃7, which is the default prior in the R package 'brms'. To explore sensitivity to the choice of 
prior, the analysis will be repeated using two alternative forms for the prior distribution. The first 
alternative prior distribution will be the same as above but will set 𝛿1 = 𝛿2 = 0 with 100% probability. 
The second alternative prior will assign a non-informative improper uniform distribution to the set of 
main effects and interaction terms. Additional prior distributions may be implemented post-hoc for 
manuscript presentations or by request of external reviewers and stakeholders.  
 
Computation 
 
Posterior means and credible intervals for the Win Ratio quantities of interest will be calculated using 
Hamiltonian Markov Chain Monte Carlo (MCMC) simulations as implemented in the R package 'brms'. 
[4,4] To reduce Monte Carlo error, we will generate a large number of simulated parameter values and 
will perform graphical and other diagnostic checks to ensure convergence. To perform inference on 
Win-RatioHQC and Win-RatioAZM we note that each of these quantities is a function of the cell 
probabilities 𝝅 defined in Table 3 which in turn are functions of the model parameters Θ =
(𝜃0, 𝜃1, 𝜃2, 𝜃3, 𝜃4, 𝜃7, 𝜃6, 𝜃7, 𝜇, 𝛾1, 𝛾2, 𝛿1, 𝛿2). We use notation Win-RatioHQC(Θ) and Win-RatioAZM(Θ) 
to denote the value of the win ratios as a function of unknown model parameters. Posterior mean point 
estimates of the win ratios will be calculated as  
Win-Ratio
̂
HCQ = 1
𝑀∑Win-RatioHCQ(Θ(𝑖))
𝑀
𝑖=1
 
Win-Ratio
̂
AZM = 1
𝑀∑Win-RatioAZM(Θ(𝑖))
𝑀
𝑖=1
 
where 𝑀 is the number of MCMC iterations and Θ(𝑖) is the simulated value of Θ on the 𝑖-th iteration of 
the MCMC procedure. A 95% credible for the win ratios will be obtained by calculating the 2.5th and 
97.5th empirical percentiles of the quantities Win-RatioHCQ(Θ(𝑖) and Win-RatioAZM(Θ(𝑖)) across the 𝑀 
simulated values. Finally, the probability that each win ratio falls above or below a clinically relevant 
threshold will be calculated by counting the proportion of simulated win ratio values that fall above or 
below the threshold.  
 
8.5 
Secondary Analyses of the Primary Endpoint 
 
The primary analysis is unadjusted for baseline covariates but a covariate-adjusted analysis will also be 
presented for the major hypotheses in order to target a potentially more clinically relevant treatment 
effect estimand. Baseline covariates for this analysis will include ventilator status at the time of 


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randomization and enrolling site. To implement the covariate-adjusted analysis, baseline ventilator 
status and site will be included as main effects covariate adjustments in the proportion odds model 
along with the set of treatment group indicators used in the primary analysis. Win ratios for HCQ and 
AZM will be defined in a manner analogous to the primary analysis. The covariate-adjusted win ratio for 
HCQ will be a comparison between a hypothetical randomly selected patient from one of the HCQ 
groups (2, 4, or 6) and a hypothetical randomly selected patient from the same site, same baseline 
ventilator status, and same AZM subgroup who was randomized to no HCQ. The covariate-adjusted win 
ratio for AZM will be a comparison between a hypothetical randomly selected patient from one of the 
AZM groups (3 or 4) and a hypothetical randomly selected patient from the same site, same baseline 
ventilator status, and same HCQ subgroup who was randomized to no AZM. 
 
8.6 
Contingency for Violation of Proportional Odds Assumption 
 
The proportionality assumption underlying the proportional odds model will be assessed by examining 
plots of empirical cumulative logits across treatment groups and comparing observed versus model-
predicted probabilities. If there is substantial evidence of an unacceptable degree of model 
misspecification (e.g. the empirical cumulative logits from different treatment groups are clearly 
crossing) then a nonparametric instead of parametric win ratio analysis will be presented. To implement 
a Bayesian nonparametric version of the win ratio analysis, cell probabilities underlying the win ratio 
calculation (Table 3) will be estimated empirically by assigning noninformative independent Dirichlet 
distributions to the set of category probabilities within each treatment group. Other details of the 
calculations are essentially identical to those described for the primary analysis. The prior for this 
nonparametric Bayesian analysis was chosen for simplicity and computational convenience and may be 
revised in a subsequent version of the Statistical Analysis Plan.  
 
8.7 
Exploratory Pairwise Group Comparisons 
 
The treatment effects estimated by the primary analysis are averages in the sense that the comparison 
of HCQ versus no HCQ is aggregated over AZM subgroups and the comparison of AZM versus no AZM is 
aggregated over HCQ subgroups. The primary reason for targeting average as opposed to subgroup-
specific treatment effects which are potentially more informative for practice is the expected lack of 
statistical precision for estimating subgroup-specific effects. In order to shed light on potential 
treatment effect heterogeneity across AZM and HCQ subgroups, we will report estimated odds ratios 
and accompanying 95% credible intervals comparing treatment groups on a pairwise basis from the 
primary analysis proportional odds model.  
 
9 
ANALYSIS OF SECONDARY EFFICACY ENDPOINTS 
 
The major treatment group comparisons of HCQ versus no HCQ and AZM versus no AZM will be 
repeated using the following secondary clinical endpoints in place of the primary endpoint: 
• 
Mortality during the index hospitalization 
• 
Number of days on mechanical ventilation during the index hospitalization 
• 
Progression to mechanical ventilation during index hospitalization. 
• 
Day 28 WHO ordinal scale 
• 
Days from randomization until hospital discharge 
• 
Duration of fever after randomization 
• 
Duration of supplemental oxygen use after randomization 


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Analysis of index hospitalization mortality status and mechanical ventilation will be performed using 
logistic regression. The analysis will use the same predictors as the primary endpoint proportional odds 
model and will use the same Bayesian prior distribution for the main effects and interaction effects 
parameters. For the ventilation endpoint, patients on ventilator at baseline will be excluded. To facilitate 
interpretation, parameter estimates from the logistic regression model will be re-expressed as win 
ratios, risk ratios, and/or risk differences.   
 
Analysis of the day 28 WHO scale will be identical to the primary endpoint analysis using the day 28 
assessment in place of the 14 day assessment.  
 
Analysis of length of hospital stay, duration of fever, and duration of supplemental oxygen use will be 
based on a continuation ratio model for discrete time-to-event data treating death as a competing risk. 
For length of stay, the continuation ratio approach models that probability of being discharged on day 
𝑑+ 1 conditional on being alive and in-hospital on day 𝑑 and assumes that covariates have a 
multiplicative effect on this probability. For patients who die prior to discharge, the patient's discharge 
date will be set to the last date of the patient's potential follow-up time. The interpretation is similar for 
duration of fever and supplemental oxygen. Predictor variables in the continuation ratio model will be 
identical to the primary endpoint proportional odds model and will use a similar prior distribution for 
the main effects and interaction terms.  
 
10 PRESENTATION OF SAFETY DATA 
 
Safety data will be collected for all randomized participants from the time of randomization through day 
28 unless the participant withdraws from the study before day 28.  The information to be collected on 
safety-related events includes event narratives, investigator-assigned likelihood of relatedness to study 
treatments (unlikely, possibly, probably), distinctions between serious and non-serious adverse events, 
expectedness of the event, and the event outcome. Event severity will be classified using the Common 
Terminology Criteria for Adverse Events (CTCAE) v3.0. Tabulations of these data will be performed in the 
intention to treat population using the treatment groups defined in Section 5.1. Safety data will be 
tabulated by treatment group and will include the following. 
 
• 
Frequency and percentage of serious adverse events (SAEs) overall, by treatment group, and by 
various cross classifications of treatment group, CTCAE classification, expectedness, relatedness 
to study treatments, and outcome. 
• 
Frequency and percentage of all-cause study drug discontinuation overall and by treatment 
group 
• 
Frequency and percentage of each of the following adverse events of special interest (EOSI) 
overall and by treatment group: 
o Arrhythmias (ventricular), not including torsade de pointes 
o Torsade de pointes 
o Hepatic Failure 
o Bone marrow failure 
o Aplastic anemia 
o Prolonged QT interval 
o Angioedema 
o Exfoliative dermatitis  
o Acute generalized exanthematous pustulosis (AGEP) 


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o Psychosis 
o Suicidal Ideation 
o Seizure 
• 
Narrative descriptions of unanticipated problems 
• 
Patient- and event-level listings and additional tabulations as requested by the DSMB 
 
 
11 INTERIM ANALYSES 
 
The primary objective of interim analyses is to ensure the safety of the participants enrolled in the trial 
and to evaluate the accumulating safety and efficacy data by treatment group to test for possible 
differences favoring any of the randomized treatments or treatment combinations. In addition, interim 
monitoring will involve a review of participant recruitment, compliance with the study protocol, status 
of data collection, an assessment of whether control group event rates are consistent with the rates 
hypothesized in the sample size calculations, and other factors which reflect the overall progress and 
integrity of the study including potential geographic differences.  
 
An independent DSMB will review safety data on a regular basis according to the schedule specified in 
the DSMC charter. A team of one or two independent statisticians (i.e., the DSMB reporting statisticians) 
will be the only individuals (aside from the DSMB) with knowledge of interim outcomes by treatment 
group. Safety listings and tabular summaries will be generated regularly for the DSMB review. 
Unplanned meetings may be called if the DSMB members deem it to be necessary. The frequency of 
generating/sending these tables and listings to the DSMB is specified in the DSMC Charter.  
 
Interim efficacy analyses will focus on the primary endpoint (World Health Organization ordinal scale) 
and death during the index hospitalization. Analyses will be performed both for the comparison of 
hydroxychloroquine versus no hydroxychloroquine (Hypothesis #1) and for the comparison of 
azithromycin versus no azithromycin (Hypothesis #2). The first pre-planned interim review of efficacy 
data will be performed after completion of data collection for the primary endpoint of the first 75 
participants and subsequent pre-planned efficacy reviews will be performed approximately bi-weekly or 
based on a schedule specified in the DSMB charter. Considerations for multiple testing of the 
accumulating trial data are discussed in Section 11.1.  
 
Statistical methods for interim analyses will be identical to those described in Section 8 for the final 
analysis. For the WHO scale primary endpoint, the statistical framework will be a Bayesian parametric 
win ratio analysis based on the proportional odds model. For mortality, the statistical framework will be 
a Bayesian logistic regression analysis. Guidelines proposed to the DSMB for interpretation of interim 
results are summarized in Table 5: 
 
Table 5. Proposed guidelines for DSMB statistical monitoring 
 
Definition 
Monitoring Guideline 
Moderate efficacy. 
Win Ratio ≥1.25  
favoring study drug over no study drug 
Signal if probability is >80% 
Any efficacy 
Win Ratio >1.0  
favoring study drug over no study drug 
Signal if probability is >95% 


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Inefficacy 
Win Ratio <1.0 
favoring no study drug over study drug 
Signal if probability is >80% 
Moderate harm 
Win Ratio <0.9 
favoring no study drug over study drug 
Signal if probability is >75% 
Note: Study drug refers to the comparison of HCQ versus no HCQ (hypothesis #1) or the comparison of 
AZM versus no AZM (hypothesis #2). Win ratios will be estimated for both the primary endpoint and 
death during the index hospitalization.  
 
11.1 Multiplicity considerations for interim analyses 
 
The repeated analysis of multiple endpoints across multiple time points gives rise to the possibility of 
drawing an incorrect conclusion as a result of the play of chance. Based on Monte Carlo simulations 
performed during protocol development, we estimate that the probability of a signal occurring for 
moderate or any efficacy if outcomes are monitored continuously across 500 patients and there is truly 
no between group difference in the primary endpoint is 14%. The Bayesian approach to controlling the 
probability of an incorrect conclusion involves selecting a prior distribution that faithfully reflects the 
user's prior degree of skepticism concerning the possibility of a clinically meaningful treatment benefit 
or harm. If the Bayesian prior distribution is well calibrated to the user's degree of skepticism, then the 
calculated posterior probabilities are appropriate to use for decision making without the requirement 
for a multiple comparisons adjustment. Although we have specified a set of guidelines for monitoring by 
the DSMB, we do not specify a degree of Bayesian certainty that should be regarded as "definitive 
evidence" at the end of the trial. Instead, we assume that stakeholders will use the calculated 
probabilities to inform their decision making and that different users may apply different thresholds for 
determining whether the degree of certainty is sufficient to warrant any particular conclusion or action 
based on the data.  
 
12 REFERENCES 
 
 
1. Pocock SJ, Ariti CA, Collier TJ, Wang D. The win ratio: a new approach to the analysis of 
composite endpoints in clinical trials based on clinical priorities. European heart journal. 2012 
Jan 1;33(2):176-82. 
2. Gelman A, Carlin JB, Stern HS, Dunson DB, Vehtari A, Rubin DB. Bayesian data analysis. CRC 
press; 2013 Nov 1. 
3. Bürkner P (2017). brms: An R Package for Bayesian Multilevel Models Using Stan. Journal of 
Statistical Software, 80(1), 1–28. doi: 10.18637/jss.v080.i01 
4. Stan Development Team. 2018. RStan: the R interface to Stan. R package version 2.17.3.   
http://mc-stan.org 
 
 
 


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STATISICAL ANALYSIS PLAN REVISION HISTORY 
 
Version 
Date 
Description of Changes 
1.0 
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Original SAP 
 
 
 
 
 
 
 
 
 
 
 

Prot_000.pdf: 
Pragmatic trial of hydroxychloroquine/azithromycin for COVID 
Version 1.0 7 April 2020 
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TITLE 
Pragmatic Factorial Trial of Hydroxychloroquine, Azithromycin, or both for treatment of 
SARS-CoV-2 Infection  
 
 
 
Funding agencies: 
Duke University School of Medicine 
ClinicalTrials.gov Identifier 
NCT04335552 
 
Version Number: 1.0 
7 April 2020 
 
 


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Statement of Compliance 
This trial will be conducted in compliance with the protocol, International Conference on Harmonisation 
Good Clinical Practice E6 (ICH-GCP), U.S. Code of Federal Regulations 45 CFR 46 and 21 CFR, and 
applicable site-specific regulatory requirements.   
 
 


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Contents 
1. 
Protocol Synopsis .................................................................................................................................. 5 
2. 
Background Information and Scientific Rationale ................................................................................ 7 
2.1 Need for therapeutic agents for SARS-CoV-2 ..................................................................................... 7 
2.2 Scientific rationale .............................................................................................................................. 7 
2.2.1  Mechanism of action of chloroquine and hydroxychloroquine in SARS-CoV-2 .......................... 7 
2.2.2 Mechanism of action of azithromycin in SARS-CoV-2 ................................................................. 8 
2.3 Evidence for chloroquine and hydroxychloroquine ............................................................................ 8 
2.3.1 In vitro studies.............................................................................................................................. 8 
2.3.2 In vivo studies .............................................................................................................................. 8 
2.3.4 Evidence for hydroxychloroquine and azithromycin combination therapy ................................ 9 
2.3.5  How this study complements other planned work ................................................................... 10 
3. 
Descriptions of Study Drugs ................................................................................................................ 11 
3.1 
Hydroxychloroquine .................................................................................................................... 11 
3.2 Azithromycin ..................................................................................................................................... 12 
4. 
Objectives............................................................................................................................................ 14 
2.1 
Definitions ................................................................................................................................... 14 
2.2 
Primary ........................................................................................................................................ 14 
2.3 
Secondary .................................................................................................................................... 15 
5. 
Study Design........................................................................................................................................ 15 
6. 
Study Population ................................................................................................................................. 16 
7. 
Enrollment and Randomization .......................................................................................................... 18 
7.1 
Enrollment Procedures ............................................................................................................... 18 
7.2 
Randomization ............................................................................................................................ 18 
8. 
Study Procedures ................................................................................................................................ 19 
8.1 
Clinical Evaluations......................................................................... Error! Bookmark not defined. 
8.2 
Concomitant Medications ........................................................................................................... 22 
8.3 
Laboratory Evaluations ............................................................................................................... 23 
8.4 
Loss to Follow Up ........................................................................................................................ 23 
8.5 
Management of Participants Who Discontinue Study Treatment ............................................. 23 
9. 
Study Schedule .................................................................................................................................... 23 
10. 
Study Intervention/Investigational Drugs ....................................................................................... 24 


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10.1 
Study Drugs ................................................................................................................................. 24 
10.2 
Study Drug Acquisition ................................................................................................................ 25 
10.3 
Administration and Dosage of Study Drugs ................................................................................ 25 
10.4 
Criteria for Discontinuation of Study Drugs ................................................................................ 25 
11. 
Assessment of Safety ...................................................................................................................... 25 
11.1.1  Definition of Adverse Events ....................................................................................................... 25 
11.1.2  Definition of Serious Adverse Events .......................................................................................... 26 
11.1.3  Assessment of Adverse Events .................................................................................................... 26 
11.1.4  Adverse Event Reporting............................................................................................................. 27 
11.1.5  Reporting of pregnancy outcome ............................................................................................... 28 
12. 
Statistical Considerations ................................................................................................................ 29 
12.1 Study Hypotheses ........................................................................................................................... 29 
12.2  Analysis Groups .............................................................................................................................. 30 
12.3  Analysis Plan ................................................................................................................................... 30 
12.3.1.  Primary efficacy analysis ........................................................................................................ 30 
12.3.2  Secondary efficacy analyses .................................................................................................... 31 
12.3.3  Safety analyses ........................................................................................................................ 31 
12.4 Sample Size Considerations ............................................................................................................ 32 
13. 
Protection of Human Subjects ........................................................................................................ 38 
13.1  Institutional Review Board ............................................................................................................. 38 
13.2  Informed consent process ............................................................................................................. 38 
13.3  Participant confidentiality .............................................................................................................. 38 
13.4  Study discontinuation .................................................................................................................... 39 
14. 
Data Handling and Record Keeping ................................................................................................ 39 
15. 
Publications and Dissemination of Study Results ........................................................................... 39 
 
 
 


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1.  Protocol Synopsis 
Protocol Title: Pragmatic Factorial Trial of Hydroxychloroquine, Azithromycin, or both for 
treatment of SARS-CoV-2 Infection 
Treatment Indication: SARS-CoV-2 Infection requiring hospitalization 
Trial Objective: Assess the impact of hydroxychloroquine, azithromycin, or both on clinically 
relevant outcomes in a real-world population of hospitalized persons with confirmed SARS-CoV-
2 infection. 
Trial Design: Open-label, factorial randomized clinical trial with two factors and nested 
randomization.  Patients hospitalized with confirmed SARS-CoV-2 infection will be initially 
randomized to one of two arms in a 1:1 ratio: 1) Standard of care treatment or 2) Standard of 
care treatment plus 5 days of hydroxychloroquine.  Patients with no contraindication to 
azithromycin who have not received azithromycin in the seven days prior to enrollment will 
undergo a second randomization in a 1:1 ratio to either receive 1) No azithromycin or 2) 5 days 
of azithromycin.  Randomization will be stratified by hospital and by whether the patient is 
receiving mechanical ventilation at the time of randomization or not.  Participants will be 
followed for 28 days after randomization or until hospital discharge, whichever is later.   
Patient population: A total of 500 hospitalized male and female patients (≥ age 12 years or 
older), newly diagnosed with SARS-CoV-2 infection by a validated nucleic acid amplification 
assay and hospitalized due to symptoms of SARS-CoV-2 disease, who do not have 
documented allergy or intolerance to hydroxychloroquine and who have not received 
hydroxychloroquine in the 180 days prior to enrollment. 
Treatment arms: Study participants will be randomized 1:1 to receive one of the following: 
Randomization 1 Treatment 
1) 
Standard of care 
2) 
Standard of care plus hydroxychloroquine 800 mg on day 1, followed by 600 mg 
daily for a total of 5 days 
Participants who have not received azithromycin in the 7 days prior to enrollment and who do 
not have documented contraindication to azithromycin will undergo a second randomization 1:1 
for concurrent treatment: 
Randomization 2 Treatment: 
1) 
Treatment dictated by Randomization 1 alone 
2) 
Treatment dictated by Randomization 1 plus azithromycin 500 mg on day 1, 
followed by 250 mg daily for 4 additional days 
 
Criteria for evaluation: 
Primary endpoint: 
(1) WHO ordinal scale measured at 14 days after enrollment: The ordinal scale is an 
assessment of the clinical status at the first assessment of a given study day. The scale is 
as follows: 1) Death; 2) Hospitalized, on invasive mechanical ventilation or extracorporeal 
membrane oxygenation (ECMO); 3) Hospitalized, on non-invasive ventilation or high flow 
oxygen devices; 4) Hospitalized, requiring supplemental oxygen; 5) Hospitalized, not 


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requiring supplemental oxygen - requiring ongoing medical care (COVID-19 [coronavirus 
disease 2019] related or otherwise); 6) Hospitalized, not requiring supplemental oxygen - no 
longer requires ongoing medical care; 7) Not hospitalized, limitation on activities and/or 
requiring home oxygen; 8) Not hospitalized, no limitations on activities. 
Secondary endpoints: 
(1) Death during the index hospitalization 
(2) Number of days on mechanical ventilation  
(3) Proportion of patients not receiving mechanical ventilation at baseline who progress to 
requiring mechanical ventilation during the index hospitalization 
(4) WHO ordinal scale measured at 28 days after enrollment 
(5) Hospital length of stay in days for the index hospitalization 
(6) Days of fever (temperature ≥38.0) after randomization 
(7) Days on supplemental oxygen after randomization 
(8) All-cause study medication discontinuation 
(9) Drug-associated adverse events of special interest 
Study sites: 
Study participants will be recruited from Duke University Hospital, Duke Regional Hospital, Duke 
Raleigh Hospital, and the Durham VA Medical Center. 
Study duration: 
It is anticipated that three months will be required for recruitment and enrollment of study 
participants.  The estimated duration of participation for each study participant is approximately 
28 days, including treatment and follow-up. 
 
 


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2. Background Information and Scientific Rationale 
2.1 Need for therapeutic agents for SARS-CoV-2 
On December 31, 2019, China reported an outbreak of an unknown respiratory illness in Hubei 
Province, now identified as SARS-CoV-2 (1). The WHO declared a Public Health Emergency of 
International Concern on January 30, 2020, and a global pandemic on March 12, 2020. As of 
April 2, 2020, there have been 941,949 cases of COVID-19 and 47,522 deaths globally. In the 
United States, cases have rapidly risen with the total number of cases currently 216,722, 
including 5,137 deaths (Johns Hopkins Coronavirus Resource Center accessed at 
https://coronavirus.jhu.edu/map.html on April 2, 2020). 
To date, no randomized, controlled trials (RCTs) exist that demonstrate the efficacy of any 
therapeutic agent for treatment of SARS-CoV-2. However, several therapeutic agents have 
been postulated to have some effect against SARS-CoV-2, including remdesivir, 
lopinivir/ritonavir, tocilizumab, chloroquine/hydroxychloroquine, interferon-1b, and convalescent 
plasma.  Data to support any of these treatments are sparse at best (1).  Therefore, in the 
context of a pandemic, it is critically important that therapeutic agents are investigated in 
scientifically and ethically sound studies. Large clinical trials are currently underway globally to 
establish an evidence base therapies used to target COVID-19. 
2.2 Scientific rationale 
We are proposing to examine the effect of hydroxychloroquine and azithromycin, alone and in 
combination, on clinically relevant outcomes in hospitalized patients with SARS-CoV-2 infection.  
Due to its in-vitro activity against SARS-CoV-2 and its wider availability in the United States 
compared with chloroquine, hydroxychloroquine has frequently been administered to 
hospitalized COVID-19 patients on an uncontrolled basis. No data from RCTs currently exist to 
inform clinical guidance on the use, dosing, or duration of hydroxychloroquine for treatment of 
SARS-CoV-2 infection. Azithromycin has been used in combination with hydroxychloroquine in 
limited case series and has been postulated to provide additional efficacy. 
2.2.1  Mechanism of action of chloroquine and hydroxychloroquine in SARS-CoV-2 
Hydroxychloroquine is an anti-malarial 4-aminoquinoline approved by the FDA for treatment in 
rheumatoid arthritis, systemic lupus erythematosus, and other inflammatory conditions. A 
derivative of chloroquine, it was first synthesized in 1946 by introducing a hydroxyl group to 
chloroquine. Hydroxychloroquine has pharmacokinetics similar to that of chloroquine with rapid 
gastrointestinal absorption and renal elimination, but it has a more favorable risk-benefit ratio 
than chloroquine due to a wider therapeutic index and better side-effect profile (2, 3).  
 
Investigators have postulated several mechanisms to explain potential activity of chloroquine 
and hydroxychloroquine against SARS-CoV-2 (4):  
1) Inhibition of viral entry. Hydroxychloroquine inhibits biosynthesis of sialic acids and 
interferes with protein glycosylation, which may disrupt interactions necessary for viral 
attachment and entry (5, 6). 
2) Inhibition of viral release into the host cell. Hydroxychloroquine blocks endosomal 
acidification, which activates endosomal proteases. These proteases are required to 
initiate coronavirus/endosome fusion that releases viral particles into the cell (7). 
3) Reduction of viral infectivity. Hydroxychloroquine has been shown to inhibit protein 
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have shown a resulting accumulation of non-infective viral particles, or an inability of viral 
particles to bud out of the host cell (8, 9). 
4) Immune modulation. Hydroxychloroquine reduces toll-like receptors and cGAS-STING 
signaling. It has been shown to reduce release of a number of pro-inflammatory 
cytokines from several immune cell types (10), such as interleukin-6 thereby blocking the 
pathway that subsequently leads to acute respiratory distress syndrome (ARDS) (11). By 
this mechanism, hydroxychloroquine might show benefit in treating cytokine storm that 
occurs in some critically ill patients with SARS-CoV-2 (12). 
 
2.2.2 Mechanism of action of azithromycin in SARS-CoV-2 
In addition to antibacterial effects, azithromycin has anti-inflammatory effect, particularly in the 
lungs.  A mouse model of viral bronchiolitis demonstrated that azithromycin decreased 
inflammatory mediators in bronchoalveolar lavage fluid and enhanced resolution of chronic 
airway inflammation (13).  Azithromycin has also been associated with improved lung function in 
patients with cystic fibrosis and diffuse panbronchiolitis, independent of bacterial eradication 
(14, 15).  Macrolides have also been associated with improved survival in patients with 
community acquired pneumonia when paired with a beta lactam antibiotic, regardless of 
pneumonia etiology, suggesting an additional effect beyond bacterial killing (16). In a 
nonrandomized, retrospective analysis of 349 critically ill MERS patients, macrolide therapy 
(primarily azithromycin) was associated with a nonsignificant reduction in 90-day mortality (odds 
ratio 0.84, 95% confidence interval 0.47-1.51) (17). 
2.3 Evidence for chloroquine and hydroxychloroquine 
2.3.1 In vitro studies 
Chloroquine has been shown to have in vitro activity against a diverse group of RNA viruses 
(18-20). Furthermore, chloroquine and hydroxychloroquine have been demonstrated to be 
active against a number of coronaviruses in vitro, including SARS-CoV-1 (21, 22). 
 
In one study, chloroquine appeared to block SARS-CoV-2 at low-micromolar concentration in a 
Vero E6 cells assay (23). This study also demonstrated the proof-of-concept that that 
chloroquine functioned at both entry and post-entry stages of the SARS-CoV-2 infection in Vero 
E6 cells. Hydroxychloroquine (EC50=0.72 μM) was shown to be more potent that chloroquine 
(EC50=5.47 μM) in an in vitro anti-SARS-CoV-2 study (12). This study also demonstrated 
through a PBPK model that lung concentrations of hydroxychloroquine rapidly increased and 
reached steady state after a loading dose and maintenance doses, and reached levels three 
times the potency of chloroquine. 
2.3.2 In vivo studies of hydroxychloroquine 
In February 2020, early results from a number of Chinese clinical trials on chloroquine used for 
SARS-CoV-2 pneumonia demonstrated that in 100 patients, chloroquine was superior to 
standard of care in inhibiting the exacerbation of pneumonia, improving lung imaging findings, 
promoting earlier viral conversion, and shortening the disease course (24). Severe adverse 
reactions to chloroquine were not noted. Based on these data, the National Health Commission 
of the People's Republic of China recommended inclusion of chloroquine in the Guidelines for 
the Prevention, Diagnosis, and Treatment of Pneumonia Caused by COVID-19 (25).  
 
On March 25, 2020, a small randomized study from China compared the use of 
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severe SARS-CoV-2 infection randomized to HCQ or control. There was no difference in 
respiratory pharyngeal swab viral conversion or clinical outcome at Day 7 between the two 
groups, but patients received multiple treatments including antivirals (26). Several larger clinical 
studies are planned or underway, designed to establish the role of chloroquine and 
hydroxychloroquine for COVID-19 treatment (27) (see section 2.3.5). 
 
A randomized, unblinded study of 62 patients in Wuhan, China (not yet peer-reviewed) with mild 
SARS-CoV-2 illness examined the impact of hydroxychloroquine 200 mg twice-daily for 5 days, 
and found a 1-day reduction in fever duration among patients receiving hydroxychloroquine and 
a higher rate of radiographic resolution at day 6 in the hydroxychloroquine group (25/31, 80.6% 
improved in the hydroxychloroquine group vs. 17/31, 54.8% in the control group) (28). 
2.3.3 In vivo studies of hydroxychloroquine and azithromycin combination therapy 
A recent non-randomized study from France of hydroxychloroquine (200 mg every 8 hours x 10 
days) (n=26) for patients hospitalized with SARS-CoV-2 who had symptoms of upper and lower 
tract infections without oxygen requirement found that hydroxychloroquine decreased viral 
shedding at Day 6 compared to the untreated group (n=16) (70% vs 12.5%, p= 0.001). Six 
patients in the hydroxychloroquine group were receiving concomitant azithromycin for 
prevention of secondary bacterial pneumonia. On Day 6, all patients treated with the 
combination (hydroxychloroquine and azithromycin) demonstrated virologic clearance, 
compared to 57.1% of patients treated with hydroxychloroquine alone (n= 20) (29). 
This study had several limitations, including the following:  
1) Six patients in the hydroxychloroquine arm with poor outcomes (including death, ICU 
transfer, treatment intolerance) were excluded from the analysis.  
2) Use of an arbitrary, unvalidated virologic clearance on Day 6 was used as the primary 
outcome. For example, the authors reported that one patient tested negative for the virus 
on Day 6 but subsequently tested positive on Day 8, indicating that a single, negative 
polymerase chain reaction (PCR) test on a nasopharyngeal swab may not indicate 
persistent virologic clearance.  
3) The control group was not systematically selected, introducing allocation bias. 
 
A follow-up manuscript from the same authors (published online on March 28, not yet peer 
reviewed) reported a non-comparative study of 80 patients hospitalized with SARS-CoV-2 
infection without oxygen requirement (only 15% had fevers and 4 patients were asymptomatic) 
who were treated with the same doses of hydroxychloroquine and azithromycin for 3-10 days. 
One patient died; 3 transferred to ICU; 15% progressed to oxygen requirement; and 81.3% were 
improved at discharge. 83% of patients had negative PCR tests of nasopharyngeal swabs by 
Day 7, and 93% had negative PCR studies by Day 8. 97.5% of patients had negative viral 
cultures by Day 5. Mean hospital stay was 4.6 days. Toxicity data were not reported. ECG was 
performed before and 2 days after treatment, but QTc data were not reported (30).  A 
subsequent, smaller study of 11 patients treated with hydroxychloroquine/azithromycin at a 
different site in France did not suggest any benefit of the combination on viral clearance or 
clinical outcomes, and one patient had medications discontinued because of QTc prolongation 
(31). 
 


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Given the substantial limitations of existing in vivo studies, further trials are urgently needed to 
better understand the role of hydroxychloroquine and azithromycin in the treatment of SARS-
CoV-2.  
2.3.4  How this study complements other planned work 
Investigators across the U.S. have recently designed multiple clinical trials to evaluate impact of 
several experimental pharmacologic agents and other therapies when administered to patients 
with COVID-19. For example, three multicenter studies are actively enrolling to analyze efficacy 
and safety of remdesivir for hospitalized patients with moderate or severe disease from COVID-
19 (NCT04292730, NCT04292899, and NCT04280705). Each of these studies excludes 
patients with mild disease, moderate renal insufficiency, or moderate transaminitis. Other U.S. 
studies actively recruiting patients are assessing efficacy and safety of sarilumab in hospitalized 
patients with severe COVID-19 (NCT04315298) or nitric oxide inhalational therapy for 
mild/moderate (NCT04305457) or severe (NCT04306393) disease. Investigators have designed 
additional studies to analyze the potential impact of numerous other experimental agents, 
including losartan (NCT04312009), intravenous aviptadil (NCT04311697), PUL-042 inhalation 
solution (NCT04312997), CD24Fc (NCT04317040), and convalescent plasma (NCT04325672); 
however, these COVID-19 studies are not yet recruiting patients.  
While providers commonly prescribe hydroxychloroquine and/or azithromycin to treat 
hospitalized patients with COVID-19, no high-quality data exists to demonstrate that either of 
these treatments are effective. Investigators associated with a single U.S. study plan to evaluate 
efficacy of hydroxychloroquine versus azithromycin for hospitalized patients with COVID-19 
(NCT04329832); however, this study is not yet recruiting patients and does not randomize 
patients to a control arm where patients receive neither experimental therapy.  A randomized, 
placebo-controlled study in Alberta, Canada will randomize patients to 5 days of 
hydroxychloroquine versus placebo to examine whether hydroxychloroquine reduces the 
incidence of severe disease (NCT04329611).  The AIDS Clinical Trials Group is planning a 
multicenter study to examine the combination of hydroxychloroquine/azithromycin in outpatients 
and plans to collaborate with Novartis to do a similar treatment trial in inpatients; however, it is 
not clear when those studies will begin, and the Novartis study will reportedly exclude critically ill 
patients.  The NHLBI-funded PETAL network is also planning an inpatient trial of 
hydroxychloroquine versus placebo (NCT04332991). 
Our proposed study is unique and complements other planned studies because our study will 
allow systemic comparison of clinical outcomes for patients who receive hydroxychloroquine 
versus azithromycin, as well as for patients who receive neither or both experimental agents. 
Other studies evaluating these agents to date have not randomized patients to a control group 
that receives standard of care (i.e., neither experimental agent); however, inclusion of a 
randomized control group is critical to understanding efficacy and safety of 
hydroxychloroquine and/or azithromycin when used to treat COVID-19. Finally, many 
hospitalized patients in the proposed study population would not qualify for treatment via 
existing clinical trials due to insufficient disease severity, renal dysfunction, or transaminitis. 
Therefore, this study provides a mechanism for interested patients who would not otherwise 
qualify for a clinical trial to participate in a study and receive protocolized pharmacologic therapy 
targeting COVID-19. 
 
 


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3.  Descriptions of Study Drugs 
3.1 Hydroxychloroquine 
3.1.1 Formulation, Appearance, Packaging, and Labeling 
Hydroxychloroquine sulfate tablets are provided as a white/off-white, film-coated, peanut-
shaped tablets.  Each tablet contains 200 mg of the active ingredient (HCQ sulfate).  The non-
active ingredients in the formulation include black ink, calcium hydrogenophosphate, carnauba 
wax, cornstarch, magnesium stearate, Opadry White YS-I-7443 and polyethylene glycol 400. 
3.1.2 Dosing and administration 
Participants will receive an 800 mg loading dose the first day, followed by 600 mg daily for 4 
more days.  All study drug doses will be administered orally.  Study drug will be supplied as 200 
mg tablets. 
3.1.3 Rationale for selection of dose 
Hydroxychloroquine is an aminoquinolone antimalarial agent that is also approved and used for 
the treatment of autoimmune diseases including rheumatoid arthritis and systemic lupus 
erythematosus.  
Both chloroquine and hydroxychloroquine have been reported to have in vitro antiviral activity 
against SARS-CoV-2 (23, 32). In vitro testing using Vero cells vary; Yao et al demonstrated an 
EC50 of 23.90 and 5.47 uL for chloroquine at 24 and 48 hours respectively, compared to 6.14 
and 0.72 for HCQ (12). Liu et al reported on four multiplicities of infection (MOIs) (0.01, 0.02, 
0.2, and 0.8); the 50% maximal effective concentration (EC50) for chloroquine was (2.71, 3.81, 
7.14, and 7.36 μM) and for hydroxychloroquine was (4.51, 4.06, 17.31, and 12.96 μM) (32). 
Hydroxychloroquine may exhibit higher activity to chloroquine in protecting Vero cells from 
infection (“prophylaxis”); when Vero cells were pre-treated with drug before SARS-CoV-2 
challenge, EC50 for chloroquine was >100 and 18.01 uL at 24 and 48 hours, respectively, 
compared to 6.25 and 5.85 for HCQ (32). In animals, both drugs share similar tissue distribution 
patterns, with high concentrations in the liver, spleen, kidney, and lung reaching levels of 200–
700 times higher than those in the plasma (33).  
The optimal dose of hydroxychloroquine for treatment or prophylaxis is unknown. Absorption 
after oral dosing is incomplete and variable (~70% [range: 25 to 100%]) (2, 34). Metabolism is 
primarily hepatic with metabolites including bidesethylchloroquine, desethylhydroxychloroquine, 
and desethylchloroquine (35). The drug has long half-life elimination of approximately 40 days 
(2). Standard dosing in other medical conditions include: systemic lupus erythematosus (200-
400 mg daily given once or divided BID), malaria treatment (800 x1, followed by 400 mg at 6, 24 
& 48 h after initial dose), Q fever (600 mg/day in 1 to 3 divided doses) and rheumatoid arthritis 
(200-400 mg daily in 1-2 divided doses). The recommended maximum dose of HCQ is 5 mg/kg 
actual body weight daily. 
The dose chosen for this study is 800 mg orally once daily on day 1 as a loading dose followed 
by 600 mg QD for an additional 4 days. This dose was chosen for several reasons:  
 
current in vitro studies report a wide range of EC50 for SARS-CoV-2,  
 
variability of absorption and of tissue distribution into the lung,  


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 
due to a lack of phase 1b data for this drug in SARS-CoV-2 infection, the optimal 
pharmacokinetic/pharmacodynamic target is unknown.  
Yao et al made assumptions regarding the absorption and tissue distribution that were optimistic 
and recommended as an optimal treatment dose 400 mg BID on day 1 as a loading dose 
followed by 200 mg BID daily for the remainder of the treatment course (12). There is concern 
that this dose will not meet the necessary pharmacokinetic/pharmacodynamic targets for 
efficacy, in which case a negative study would not be due to failure of the antiviral efficacy but of 
suboptimal dosing. Yao et al also noted that the drug exposure was the same for 200 mg BID or 
400 mg QD daily dosing. We propose a higher loading dose of 800 mg once daily on day 1 to 
ensure more rapid steady state tissue distribution and 600 mg daily (versus 200 mg three times 
daily) dosing for ease of dosing and adherence. 
 
3.2 Azithromycin 
Azithromycin is an azalide antibacterial that is FDA-approved for treatment of acute bacterial 
exacerbations of chronic obstructive pulmonary disease, acute bacterial sinusitis, community-
acquired pneumonia, pharyngitis/tonsillitis, uncomplicated skin and skin structure infections, 
urethritis and cervicitis, and genital ulcer disease.  Between 2013-2015, it was one of the most 
commonly prescribed antibiotics in the United States, with an average of 443 prescriptions per 
1,000 Express Scripts beneficiaries (~15 million prescriptions per year) (36). 
3.2.1  Formulation, appearance, labeling and packaging 
Azithromycin tablets are supplied as pink film-coated tablets containing azithromycin dihydrate 
equivalent to 250 mg of azithromycin. 
3.2.2.  Dosing and administration 
Azithromycin will be dosed at 500 mg orally on day 1 of treatment, followed by 250 mg once 
daily on days 2-5 of treatment.   
3.2.3  Rationale for dose selection 
This dosing is a commonly used dose for community-acquired pneumonia; as the potential 
mechanism of action and pharmacodynamics of azithromycin when used to treat SARS-CoV-2 
are unknown, we chose a dose that has been demonstrated safe in a large number of patients.  
Mechanism of Action / Potential activity in COVID19: 
- 
Antibacterial effect: Binds bacterial 50S ribosomal subunit and inhibits RNA-dependent 
protein synthesis (37). Can potentially serve to prevent bacterial super infection in 
patients with COVID19. 
- 
Immunomodulatory effect (studied mainly in COPD and Cystic Fibrosis): Inhibits NFB 
activation and expression of activator protein-1, reduces number and function of 
neutrophils leading to lower concentrations of neutrophil elastase, IL-8, and IL-1. This 
in turn leads to a reduction in cellular damage/tissue injury (38, 39). Adjunct therapy in 
moderate to severe ARDS has been shown to improve survival and reduce days on 
mechanical ventilation, which may be related to this immunomodulatory effect (40). 


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- 
Direct antiviral effect: invitro studies; Suppresses viral replication of Rhinovirus in 
bronchial epithelial cells (exact mechanism unclear) (41-43), inactivates endocytic 
activity of A(H1N1)pdm09 blocking internalization in early infection (exact mechanism 
unclear) (44). Azithromycin has no studied direct antiviral effect with the Coronaviridae 
family. 
- 
Combination of Hydroxychloroquine (HCQ) and Azithromycin studied in a small 
prospective non-randomized trial could suggest that Azithromycin might augment the 
effects of HCQ, but this is still unclear in true effect, clinical significance as well as 
underlying mechanism (29) 
 
Oral Pharmacokinetics:  
- 
Immediate release, bioavailability 34 – 52% with a half-life of 68 – 72 hours.  
- 
Extended release bioavailability, 28 – 43% with a half-life of 59 hours.  
- 
Metabolized hepatically to inactive metabolites and excreted in both bile and urine with 
50% and 6 – 14% being unchanged, respectively.  
 
Drug-drug interactions:  
- 
CYP3A4 substrate 
- 
P-glycoprotein/ABCB1 inhibitor  
- 
Potentially drug-drug interactions relevant to our study include:  
o Chloroquine; QT prolongation and ventricular arrythmias 
o Other QT prolonging drugs such as antiemetics, antidepressants, antipsychotics, 
and other antimicrobials  
 
Safety and tolerability (Oral, Adults):  
- 
Single dose regimens tend to be associated with higher frequency of adverse events, 
however this is not relevant to our study given that the dosing of azithromycin will be a 
daily oral dose for 5 days.  
- 
The majority of adverse events are gastrointestinal with an incidence of approximately 
>10%: Loose stools (≤14%), diarrhea (2% - 9%), nausea (≤7%), and vomiting (≤2%). 
- 
Other (systems based) adverse events occur at lower rates of 1 – 10%: Cardiovascular: 
Chest pain (≤1%), palpitations (≤1%); Central nervous system: Dizziness (≤1%), 
drowsiness (≤1%), fatigue (≤1%), headache (≤1%), vertigo (≤1%); Dermatologic: Skin 
rash (≤5%), pruritus (≤2%), skin photosensitivity (≤1%); Endocrine & metabolic: 
Increased lactate dehydrogenase (1% – 3%), increased gamma-glutamyl transferase 
(1% –2%), increased serum potassium (1% – 2%), decreased serum bicarbonate (≥1%), 
decreased serum glucose (>1%); Gastrointestinal: Abdominal pain (1% – 7%), anorexia 
(≤2%), dysgeusia (≤1%), dyspepsia (≤1%), flatulence (≤1%), gastritis (≤1%), melena 
(≤1%), mucositis (≤1%), oral candidiasis (≤1%); Genitourinary: Vaginitis (≤3%), genital 
candidiasis (≤1%); Hematologic & oncologic: decreased hematocrit (>1%), decreased 
hemoglobin (>1%), increased neutrophils (>1%), thrombocythemia (adults: >1%), 
eosinophilia (≥1%), lymphocytopenia (≥1%); Hepatic: Increased serum ALT (≤6%), 


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increased serum AST (≤6%), increased serum bilirubin (≤3%), cholestatic jaundice 
(≤1%); Neuromuscular & skeletal: Increased creatine phosphokinase (1% – 2%); Renal: 
Increased serum creatinine (≤6%), increased blood urea nitrogen (≤1%), nephritis 
(≤1%); Respiratory: Bronchospasm (≤1%). 
- 
Other (rare) adverse events potentially relevant to our study include: 
o QT prolongation; Azithromycin can inhibit the rapid component of the delayed 
rectifier K+ current channels and induce QT prolongation, however several 
studies and analyses have shown that Azithromycin-induced QT prolongation 
does not lead to Torsade de Pointes (45, 46). 
o Increased risk of death from cardiovascular events; Some studies have 
suggested that Azithromycin has been associated with death from cardiovascular 
events in high risk individuals, however several subsequent studies and analyses 
have not shown an association (47, 48). 
- 
Pregnancy: Azithromycin crosses the placenta but is generally considered safe in 
pregnancy (Category B) (37, 49, 50); a recent study did associate macrolides with an 
increased incidence of genital malformations, but azithromycin was not specifically 
studied (51). 
- 
Breast Feeding: Azithromycin is present in breast milk and has been shown to have a 
half-life of ~15 hours, with some studies detecting Azithromycin in breast milk up to 30 
days after single dose administration (52, 53). There is conflicting data of the 
incidence/nature of macrolide-induced infantile hypertrophic pyloric stenosis in infants 
exposed in the first 2 weeks of life (54, 55). Some infants may experience adverse 
gastrointestinal events such as diarrhea and should be monitored while the mother is 
receiving therapy (55). It is generally considered safe in breast feeding mothers 
(Category B). 
- 
Contraindications: Hypersensitivity to macrolides, history of macrolide induced 
hepatitis/cholestatic jaundice 
4.  Objectives 
4.1  Definitions 
The World Health Organization ordinal scale is defined as an assessment of the clinical status 
of a study participant at the first assessment of a given study day.  For purposes of this study, 
this assessment will be considered to have occurred at 9 a.m. on the study day. 
The ordinal scale is an assessment of the clinical status at the first assessment of a given study 
day. The scale is as follows: 1) Death; 2) Hospitalized, on invasive mechanical ventilation or 
extracorporeal membrane oxygenation (ECMO); 3) Hospitalized, on non-invasive ventilation or 
high flow oxygen devices; 4) Hospitalized, requiring supplemental oxygen; 5) Hospitalized, not 
requiring supplemental oxygen - requiring ongoing medical care (COVID-19 related or 
otherwise); 6) Hospitalized, not requiring supplemental oxygen - no longer requires ongoing 
medical care; 7) Not hospitalized, limitation on activities and/or requiring home oxygen; 8) Not 
hospitalized, no limitations on activities. 
4.2 Primary 
(1) To compare the efficacy of each experimental treatment (azithromycin and 
hydroxychloroquine) to the efficacy of supportive care, using the World Health Organization 
ordinal scale measured on day 14 after enrollment 


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4.3 Secondary 
(1) To compare the rates of death during the index hospitalization among participants receiving 
each experimental treatment and participants receiving supportive care alone 
(2) To compare the number of days on mechanical ventilation among participants receiving 
each experimental treatment and participants receiving supportive care alone 
(3) To compare the proportion of participants not receiving mechanical ventilation at baseline 
who progress to requiring mechanical ventilation during the index hospitalization among 
participants receiving each experimental treatment and participants receiving supportive 
care alone 
(4) To compare the World Health Organization ordinal scale measured on day 28 after 
enrollment between participants receiving each experimental treatment and participants 
receiving supportive care alone 
(5) To compare the total length of hospitalization during the index hospitalization among 
participants receiving each experimental treatment and participants receiving supportive 
care alone 
(6) To compare the duration of fever (defined as temperature ≥38.0 C measured at any site) 
after randomization among participants receiving each experimental treatment and 
participants receiving supportive care alone 
(7) To compare the duration of supplemental oxygen use after randomization among 
participants receiving each experimental treatment and participants receiving supportive 
care alone 
(8) To describe the rates of all-cause discontinuation of study medication among patients 
receiving experimental treatment 
(9) To compare the rates of drug-associated adverse events of special interest among patients 
receiving each experimental treatment and participants receiving supportive care alone 
during the first fourteen days after enrollment 
5.  Study Design 
This will be a pragmatic, randomized, open-label, incomplete factorial with nested randomization 
clinical trial evaluating the efficacy and safety of two potential treatments for hospitalized 
patients with confirmed SARS-CoV-2 infection.  Participants who are hospitalized and have a 
positive nucleic acid amplification test for SARS-CoV-2 will undergo an initial randomization in a 
1:1 ratio to one of the following regimens: 
Arm 1: Supportive care alone 
Arm 2: Supportive care plus hydroxychloroquine 
Participants who meet eligibility criteria to receive azithromycin will undergo a second 
randomization in a 1:1 ratio to receive additional concurrent therapy.  This will effectively result 
in four treatment groups: 
1) Supportive care alone 
2) Supportive care plus hydroxychloroquine  
3) Supportive care plus azithromycin 
4) Supportive care plus hydroxychloroquine plus azithromycin 


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6.  Study Population 
500 hospitalized male and female patients (≥ age 12 years or older) diagnosed with SARS-CoV-
2 related infection, and who meet all study eligibility criteria will be enrolled in the study. 
Participants will be enrolled at all three DUHS hospitals: Duke University Hospital, Duke 
Regional Hospital and Duke Raleigh Hospital, as well as the Durham VA Medical Center. We 
anticipate that most participants enrolled in the study will be residents of the 12-county 
Raleigh/Durham Combined Statistical Area. Estimated time of screening to end of study for an 
individual subject will be 28 days, including treatment and follow up.  
 
Participant eligibility will be confirmed by one of the study co-investigators prior to enrollment.  
 
Inclusion Criteria 
 
To participate in the study, participants must meet ALL of the following criteria:  
1) Admitted to participating hospital with symptoms suggestive of SARS-CoV-2 infection 
OR develop symptoms of SARS-CoV-2 during hospitalization  
2) Subject (or legally authorized representative) can provide written informed consent (in 
English or Spanish) affirming intention to comply with planned study procedures prior to 
enrollment  
3) Male or female aged 12 years or older at the time of enrollment  
4) Has laboratory-confirmed SARS-CoV-2 infection determined by a validated nucleic acid 
amplification assay (public health or commercial) in any respiratory specimen collected 
within 14 days of randomization 
5) Illness of any duration that includes 
 
Radiographic evidence of pulmonary infiltrates (chest X-ray or CT scan) OR 
 
Clinical documentation of lower respiratory symptoms (cough, shortness of 
breath, or wheezing) OR  
 
Any documented SpO2 ≤ 94% on room air OR 
 
Any inpatient initiation of supplemental oxygen regardless of documented cause 
Exclusion Criteria  
Participants with ANY of the following criteria will be excluded from the study:  
1) Participating in any other clinical trial of an experimental agent for SARS-CoV-2   
2) On hydroxychloroquine at any time during hospitalization, or within 180 days of 
hospitalization for COVID-19 regardless of indication  
3) History of cirrhosis, long QT syndrome or porphyria of any classification 
4) Most recent ECG prior to time of screening with QTc of ≥500 msec  
5) Known hypersensitivity to hydroxychloroquine or 4-aminoquinoline derivatives 
6) Weight less than 40 kg 
7) Death anticipated within 48 hours of enrollment 
8) Inability to obtain informed consent from the patient or designated medical decision 
maker 
 
Inclusion of Vulnerable Subjects 
Hydroxychloroquine has been shown to permeate across the placenta, with cord blood 
concentrations equivalent to those found in maternal blood. Despite theoretical concerns of 
retinal toxicity and ototoxicity, numerous cohort studies have demonstrated its safety in 


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pregnant women exposed to the medication. Hydroxychloroquine has been used extensively as 
an immunomodulatory agent in pregnant women and the American College of Rheumatology 
recommends continuation of the drug among pregnant women with SLE who were initiated prior 
to pregnancy. After careful assessment of available data, consultation with local experts, and 
the lack of alternative therapeutic options for persons with SARS-CoV-2, the study team 
deemed that inclusion of pregnant women in the trial was warranted. 
Persons under the age of 18 are significantly less likely present with symptoms warranting 
hospitalization than the rest of the population. As a result, little clinical trial data exist on 
therapeutics for COVID-19 in this subset of the population. This trial presents an opportunity to 
systematically collect data on the impact of two widely available, low-cost agents on a 
potentially life-threatening infection, with no known therapeutic options. Both azithromycin and 
hydroxychloroquine have been shown to be safe in adolescents. Based on the risk/benefit 
analysis for prospective hospitalized patients in this age group, inclusion of adolescents (age 
12-18) in the trial is warranted.  
Prisoners will not be enrolled in this study because it does not involve one of the Health and 
Human Services permissible categories of research involving prisoners. 
 
Lifestyle Considerations 
Study participants will be asked to avoid participation in other trials of pharmacologic agents 
with possible activity against SARS CoV-2. 
  
Screen Failures 
At completion of prospective participant screening, the principal investigator (or designee) will 
review eligibility criteria to determine the patient’s suitability for study inclusion. Data on reason 
for ineligibility will be collected for all screen failures. Persons who fail study screening will be 
notified about the reason for their ineligibility. Patients who are deemed ineligible due to 
eligibility criteria based on clinical findings/data can be re-screened again at a subsequent time 
based on investigator’s discretion.  
Strategies for Recruitment and Retention  
Recruitment 
All patients admitted to study site hospitals for SARS-CoV-2 will be screened for participation in 
the study. No external recruitment efforts will occur beyond this subset of patients. Study 
coordinators will track the clinical course of every hospitalized SARS-CoV-2 patient in DUHS, 
with particular attention to whether or not they were offered enrollment into a trial involving 
another investigational agent. Through review of the electronic health record, the study 
coordinator will determine the reason patient was not enrolled. If failure to enroll was not due to 
one of this protocol’s exclusion criteria, or a broad declination of participation in SARS-CoV-2 -
associated clinical trials (available in OnCore), the patient will be screened and approached for 
inclusion in the study. Targeted groups of clinicians within the health system will be notified 
about the trial prior to the study’s commencement and on the day the study is open to 
enrollment via e-mail. Clinician groups to be targeted include: emergency department faculty, 
trainees and staff; critical care faculty, trainees and staff; hospitalist physicians; infectious 
diseases faculty trainees and staff; transplant faculty, trainees, and staff; Internal Medicine, 
General Surgery and Anesthesia house staff. Study details will also be available to all DUHS 
faculty, trainees and staff via the COVID-19 clinical trials section of CustomID.  
 
The IRB will approve the recruitment process and all materials prior to any recruitment to 
prospective subjects directly.  


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To minimize unnecessary exposure to SARS-CoV-2, study staff will be instructed to conduct as 
much screening for eligibility by electronic health record review as possible, and informed 
consent will be preferentially obtained by telephone. 
 
Retention  
Significant participant attrition is not expected given that this study primarily follows patients 
while hospitalized.  Study investigators will be available to the participant’s clinical team to 
discuss alterations in clinical course that may influence their decision to keep the patient in the 
trial.  
 
Compensation 
Participants will not be compensated for their participation in the study.  
 
Costs 
Participants will be charged for study drugs as part of their hospital care.  Participants will be 
informed of this by the study coordinator prior to obtaining informed consent.  
 
7.  Enrollment and Randomization 
7.1 Enrollment Procedures 
Individuals who are hospitalized with a positive nucleic acid amplification test for SARS-CoV-2 
and who are not enrolled in another therapeutic trial for SARS-CoV-2 will be invited to 
participate in this study.  Interested individuals will be provided with information about the study 
including risks and potential benefits of all study procedures.  If site staff are satisfied that the 
potential participant understands the information and the potential participant is willing, the 
potential participant will be asked to participate in the study.  Study-specific procedures will be 
initiated only after the participant has provided written, informed consent.  The consent process 
will be performed by providing the patient or designated healthcare provider a copy of the 
consent form (this will be given to an individual who is going into the room; the study coordinator 
will not enter the room).  The patient will be provided an opportunity to review the consent, and 
when they are ready, the consent process will occur by e-consent on study iPads.    If the 
patient is unable to provide written, informed consent and they have a designated medical 
decision maker, that person will be approached either in person or by telephone with information 
about the study.  The consent process with the medical decision maker will occur using e-
consent also. 
 
7.2 Randomization 
This will be a randomized trial.  Randomization and treatment arm assignment will be generated 
with randomly permuted blocks of size 2, 4, 6, and 8.  Participants will undergo two 
randomizations.  The first randomization (to standard of care or hydroxychloroquine) will be 
stratified by whether or not the patient is receiving mechanical ventilation at the time of 
enrollment and by hospital site.  Eligible patients who have provided informed consent will be 
randomized with equal probability to each arm.  Participants who meet inclusion criteria for the 
second randomization (to add or not add azithromycin) will be randomized with equal probability 
to each of these treatments.  Random assignment sequences will be generated in a way that 


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limits the imbalance between arms within strata while ensuring that the sequence is not 
predictable based on previous assignments. 
8.  Study Procedures 
8.1 Ascertainment of potential participants 
Potential participants will be ascertained in one of two ways: 1) Daily review of all positive 
SARS-CoV-2 tests from the relevant hospital laboratories and 2) Referral from treating 
providers. 
8.2 Baseline screening and eligibility determination 
By chart review prior to patient encounter:  
 
Confirm positive SARS-Cov2 test  
 
Confirm patient meets demographic criteria  
 
Confirm patient meets clinical criteria  
 
Ascertain in OnCore research portal that patient is not enrolled in any other COVID-19 
related clinical trial  
 
Review chart for azithromycin within 7 days and hydroxychloroquine use within 180 days 
of planned baseline encounter (including outpatient records)  
 
Review medical history for exclusionary conditions 
 
Review allergy record for evidence of hypersensitivity to azithromycin or 
hydroxychloroquine or related drugs  
 
Locate and have investigator review EKG in electronic health record obtained within 7 
days of planned encounter for evidence of prolonged QTc  
At enrollment encounter (Day 1):  
 
Locate hospital and unit where patient is located 
 
Verify with treating clinical team that patient is appropriate for the trial  
 
Determine whether the patient can provide informed consent. If not, identify patient’s 
legally authorized representative.  
 
If the patient cannot provide informed consent, patient’s legally authorized representative 
should be contacted and the informed consent process should be executed through 
them. 
 
The patient or legally authorized representative should be provided a copy of the written 
informed consent document to review. 
 
Informed consent should be preferentially obtained by e-consent as outlined above 
rather than in person. 
8.3  Initial assessment and treatment assignment 
Study Intervention Procedures 
Immediately post enrollment (Day 1):  
 
Conduct randomization procedure  
 
Inform treating team of patient’s enrollment. Study coordinator (in conjunction with on-
call investigator) will advise the team on their patient’s treatment assignment, and will 
advise the team to write treatment orders accordingly. 


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 
Inform team to perform ECG (if none available in the preceding 7 days). For women of 
childbearing potential (and no clear evidence of pregnancy), inform team to obtain urine 
qualitative HCG.  
Other activities on Day 1:  
 
Complete case report form (CRF) in a timely manner. Obtain the following data from 
EHR to complete CRF including the following:  
o Demographic data  
o Most recent height and weight  
o Chronic medical conditions related to study eligibility  
o Date of onset of COVID-19 symptoms  
o Data on hospitalization including date of admission, date of ICU transfer (if 
applicable), presenting complaint, vitals on presentation, selected laboratory data 
on presentation  
o Medications administered (with dates) for index illness prior to presentation and 
during hospitalization to date  
o Medication allergies on record  
o Findings of last documented lung examination  
o Results of chest X-ray or CT scan on presentation  
o Most recent vital signs prior to time of enrollment  
o Most recent complete blood count, basic metabolic panel and hepatic function 
panel obtained prior to the time or enrollment  
o QTc of most recent ECG 
o Urine pregnancy test (if applicable)  
o Respiratory support status (ECMO, invasive mechanical ventilation, non-invasive 
ventilation, high-flow nasal cannula (with oxygen flow rate), standard nasal 
cannula (with oxygen flow rate) 
o Level of care (ICU, stepdown, standard)  
o WHO ordinal scale value (in conjunction with study investigator)  
For patients enrolled at DUHS, all of this data will be automatically captured in Redcap as part 
of the overall COVID research plan, so the coordinator will not need to extract any data.  For 
patients at other sites, data will need to be entered into the Redcap database. 
8.4  Assessment during study 
Daily Assessment (Days 2-13):  
 
Study coordinator will complete CRF based on clinical data abstracted from chart with 
the following information:  
o Vital signs conducted most proximal to CRF entry  
o Maximum temperature in prior 24 hours (9am-8:59 am) 
o New medications administered (with dates) for index illness during interval since 
last assessment  
o Interim complete blood count, basic metabolic panel and hepatic function panel  
o QTc of most recent EKG conducted in interim  
o Respiratory support status (ECMO, invasive mechanical ventilation, non-invasive 
ventilation, high-flow nasal cannula (with oxygen flow rate), standard nasal 
cannula (with oxygen flow rate) 


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o Level of care (ICU, stepdown, standard)  
o Adverse event documentation  
 
For patients enrolled at DUHS, all of this data will be automatically captured in Redcap 
as part of the overall COVID research plan, so the coordinator will not need to extract 
any data.  For patients at other sites, data will need to be entered into the Redcap 
database. 
 
Day 14 Assessment:  
 
Study coordinator will complete CRF based on clinical data abstracted from chart with 
the following information: 
o Vital signs conducted most proximal to CRF entry  
o Medications related to index illness still being administered, or written for 
discharge  
o Most proximal chest X-ray or CT scans  
o Most proximal complete blood count, basic metabolic panel and hepatic function 
panel  
o QTc of most recent ECG conducted in interim  
o Review for possible drug-related adverse events of special interest 
o Need for supplemental oxygen on discharge (mode of delivery, and supplemental 
oxygen requirement) 
o Discharge disposition  
o If hospitalized, level of care (ICU, stepdown, standard)  
o WHO ordinal scale value (in conjunction with investigator)  
 
For patients enrolled at DUHS, all of this data will be automatically captured in Redcap 
as part of the overall COVID research plan, so the coordinator will not need to extract 
any data.  For patients at other sites, data will need to be entered into the Redcap 
database. 
 
Day 28 Assessment  
 
Study coordinator will complete CRF based on clinical data abstracted from chart as 
follows:  
 
If hospitalized:  
o Number of days since enrollment on which the participant had a measured 
temperature ≥38.0 C 
o Number of days since enrollment on which the participant was on mechanical 
ventilation 
o Number of days since enrollment on which the participant was on noninvasive 
ventilation 
o Number of days since enrollment on which the participant was on supplemental 
oxygen 
o Level of care (ICU, stepdown, standard)  
o WHO ordinal scale value (in conjunction with investigator)  


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If discharged:  
o Interim visit to emergency department or urgent care  
o Interim admission to hospital  
o Interim admission into ICU 
o Supplemental oxygen requirement  
o Level of long-term care required (skilled nursing facility, assisted living, home)  
o Functional status reported by outpatient provider (when available)  
o Recurrence of fever or respiratory symptoms  
o Lung examination reported by provider (when available)  
o Follow up lung imaging (when available)  
o WHO ordinal scale value (in conjunction with investigator)  
Day 45 Assessment: 
o Review of medical record to determine vital status and hospitalization status 
o Count of total hospital length of stay 
WHO Ordinal Scale  
 
The WHO Ordinal Scale for Clinical Improvement is an assessment developed by the 
World Health Organization as part of their COVID-19 therapeutic trial (World Health 
Organization. “WHO R&D Blueprint: Novel Coronavirus COVID-19 Therapeutic Trial 
Synopsis” 2020, Geneva, Switzerland URL: https://www.who.int/blueprint/priority-
diseases/key-action/COVID-
19_Treatment_Trial_Design_Master_Protocol_synopsis_Final_18022020.pdf. Accessed 
3/31/2020).  The assessment tool is intended to report on the clinical status of COVID-19 
patients in therapeutic trials on any given day. Details of the scale are below:  
Patient State
Descriptor 
Score 
Uninfected  
No clinical or virologic evidence of infection  
0 
Ambulatory 
No limitation of activities 
1
Limitation of activities 
2
Hospitalized, Mild Disease  
Hospitalized, no oxygen therapy  
3 
Oxygen by mask or nasal cannula 
4
Hospitalized, Severe Disease 
Non-invasive ventilation or high-flow oxygen  
5 
Intubation and mechanical ventilation
6
Mechanical ventilation + additional organ support 
(pressors, renal replacement therapy, ECMO) 
7 
Death  
Death  
8 
 
 
 
All designations of WHO ordinal scale will be made by the study PI or co-investigators.  
 
A study physician licensed to make medical diagnoses and listed on the delegation log 
will be responsible for all trial-related decisions.  
 
8.5 Concomitant Medications 
The use of all non-study drugs from enrollment until 14 days after enrollment will be monitored 
and recorded.  Per standard of care, all potential drug interactions with hydroxychloroquine and 
azithromycin will be reviewed prior to administration and discussed with the treating team.  If a 


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potential interaction between hydroxychloroquine and a concurrent medication is deemed 
potentially harmful by the investigator or treating team, a formal discussion of risks and benefits 
of hydroxychloroquine will take place between the investigator and the treating team.  If either 
the investigator or the treating team deem that the risk of the concurrent medication outweighs 
potential benefit, hydroxychloroquine will not be administered and the patient will be withdrawn 
from the study. 
8.6 Laboratory Evaluations 
Laboratory evaluations will be performed per standard of care under the direction of the treating 
team.   
ECG testing will be recommended as a standard of care intervention prior to and during study 
drug administration for participants with baseline cardiac conduction abnormalities or electrolyte 
abnormalities that might predispose to cardiac arrhythmias (see section 11.6). 
8.7 Loss to Follow Up 
Patients who are discharged from the hospital prior to 14 days after study enrollment will be 
contacted to ascertain their status on day 14 after enrollment.  Patients who cannot be 
contacted after at least three separate attempts will be assigned a World Health Organization 
ordinal scale based on health status at the time of hospital discharge. 
8.8 Management of Participants Who Discontinue Study Treatment 
Participants who prematurely discontinue study treatment will be followed as for other 
participants and will not receive any additional study treatment during the hospitalization.  
Participants assigned to receive two study drugs who only discontinue one drug should 
complete the full course of the other study drug unless there is a contraindication.    
If the study is terminated early, study treatment may be continued at the discretion of the 
investigator and treating team if it is deemed in the participant’s best interest. 
8.9 Collection of specimens for pharmacokinetic analysis 
While no specific specimens will be collected from study participants, we will request permission 
to use blood left over from routine laboratory blood draws for potential future 
pharmacokinetic/pharmacodynamic analyses.  Blood will either be stored at -80C or will be 
stored at room temperature as dried blood spots.  The future pharmacokinetic/phamacodynamic 
analyses would consist of measuring the concentrations of study drug (hydroxychloroquine and 
azithromycin) and correlating these concentrations with clinical outcomes. 
9  Study Schedule 
The schedule of study activities is summarized in Table 1 below. 


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Table 1.  Schedule of study activities. 
 
 
In addition to the activities outlined above, there will be a single evaluation at the time of hospital 
discharge to assess length of hospital stay and WHO ordinal scale, if discharge occurs later 
than 28 days after enrollment. 
10 Study Intervention/Investigational Drugs 
10.1 Study Drugs 
The study drugs are hydroxychloroquine and azithromycin.  Each of the study drugs is 
described in section 3. 
The study drugs will be combined into the following study treatment regimens: 
Arm 1 (control) Standard of care 
Arm 2: Hydroxychloroquine orally for 5 days 
Arm 3: Azithromycin orally for 5 days 
 
Screen 
Baseline
Treatment 
Period  
End of 
Treatment 
Inpatient  
Follow-up 
Day 28 follow-
up  
Day +/- Window -1 or 1  
1 
1 to 5  
5 
6-14 
28 ± 2 
ELIGIBILITY  
Demographics & Medical History 
Review
X 
 
 
 
 
 
Review SARS CoV-2 results 
X
Hospital Course Review 
X
Clinical Data Review (including 
EKG for QTc screen) 
X 
 
 
 
 
 
Informed consent 
X
STUDY INTERVENTION  
Randomization 
X
Study medication administration
X
STUDY PROCEDURES  
Vital signs including SpO2
X
Daily
Daily 
Clinical data collection 
X
Daily
X
Daily
Review of laboratory/ECG data
X
Daily
Daily
Targeted medication review 
X
Daily
Daily
Adverse event evaluation 
X
Daily
Daily
X
WHO ordinal scale adjudication 
X
Daily 
X
Daily 
X
EHR review for re-admission or 
death 
 
 
 
 
 
X 
SAFETY INVESTIGATIONS 
Pregnancy test for females of 
childbearing potential (if no clear 
clinical evidence/history of 
pregnancy) 
 
X 
 
 
 
 


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Arm 4: Hydroxychloroquine orally for 5 days plus azithromycin orally for 5 days 
10.2 Study Drug Acquisition 
As this is a pragmatic trial using readily available FDA-approved medications, study drug will be 
supplied by the pharmacy of the hospital where the patient is receiving treatment. 
10.3 Administration and Dosage of Study Drugs 
Hydroxychloroquine will be administered orally or via feeding tube at a dosage of 800 mg on 
day 1, followed by 600 mg daily on days 2-5. 
 
Patients who do not tolerate the 600 mg daily dose may be dose-reduced to a 400 mg 
daily dose at the discretion of the study investigator 
Azithromycin will be administered orally or via feeding tube at a dosage of 500 mg on day 1, 
followed by 250 mg daily on days 2-5.  If oral azithromycin is not available, intravenous 
azithromycin at the same dosages may be substituted.  
10.4 Criteria for Discontinuation of Study Drugs 
Participants who meet any one or more of the following criteria will be discontinued from study 
treatment: 
 
Participant request for premature discontinuation of study treatment 
 
Any clinical adverse event, laboratory abnormality, or other medical condition occurs 
such that continued administration of study treatment is deemed not in the best interest 
of the patient 
11 Assessment of Safety 
11.1  Definition of Adverse Events 
An adverse event (AE) is any unfavorable and unintended sign (including an abnormal 
laboratory finding), symptom, or disease that occurs to a study participant during the course of 
the study.  
Adverse Event Grading 
 
Mild (Grade 1): Transient or mild symptoms; no limitation in activity; no intervention 
required. The AE does not interfere with the participant’s normal functioning level.   
 
 
Moderate (Grade 2): Symptom results in mild to moderate limitation in activity; no or 
minimal intervention required. The AE produces some impairment of functioning, but it is 
not hazardous to health.   
 
 
Severe (Grade 3): Symptom results in significant limitation in activity; medical 
intervention may be required. The AE produces significant impairment of functioning or 
incapacitation. 
 
 
Potentially life-threatening (Grade 4): Extreme limitation in activity, significant assistance 
required, significant medical intervention or therapy required, or hospitalization required. 
 
[Note: ‘Life-threatening’ as a Grade 4 severity refers to a ‘potential’ threat to life whereas ‘life 


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threatening’ as a ‘serious adverse event’ refer to an ‘immediate’ threat to life.] 
11.2  Definition of Serious Adverse Events  
 
An AE is considered to be ‘serious’ if it results in one of the following outcomes. An AE 
needs to meet only one of the above criteria to be considered serious.  
 
Death, 
 
Life-threatening event (the participant is at immediate risk of death), 
 
Requires inpatient hospitalization or prolongation of existing hospitalization 
 
Results in persistent or significant disability/incapacity (a substantial disruption of a 
person's ability to conduct normal life functions),  
 
Results in congenital anomaly/birth defect 
 
Important medical event that may not be immediately life-threatening or results in 
death or hospitalization but may jeopardize the participant or may require 
intervention to prevent one of the other outcomes listed in the definition above.  
11.3  Assessment of Adverse Events 
Both hydroxychloroquine and azithromycin have a track record of safety since their FDA-
approval in 1955 and 2002, respectively. There is extensive experience with these drugs in 
clinical practice. However, because the medicines have not been used in COVID-19 patients, 
and the use of hydroxychloroquine and azithromycin in combination can increase the risk for 
major cardiac toxicity including QT prolongation, only drug-specific AEs that are listed in the 
FDA Warning List for the study drugs and only AEs Grade 3 or higher will be collected.  
Hydroxychloroquine has been used for decades for the treatment and prevention of malaria 
and for autoimmune conditions including rheumatoid arthritis and lupus. The following system 
abnormalities have been listed under the FDA Warning List for Hydroxychloroquine (mostly with 
long-term use for autoimmune conditions) 
Hypoglycemia: may be severe necessitates close serum glucose monitoring. 
Dermatologic: Erythema multiforme, may precipitate a severe attack of psoriasis and porphyria 
Nervous system: Dizziness, vertigo, tinnitus, proximal myopathy and muscle weakness, 
extrapyramidal symptoms, seizure, and suicidal behavior. Close observation in patients with 
neurological or seizure disorders.  
Ocular: irreversible retinal damage has occurred with only with prolonged use (> 5 years) and in 
individuals with subnormal glomerular filtration, and those with concurrent macular disease (up 
to 7.5%) 
Cardiac: risk of QT prolongation and torsades de pointes, AV block, and ventricular arrythemia. 
Risk is increased in in patients with underlying QT-prolongation and/or on concurrent QT-
prolonging agents.  
G6PD deficiency: Although warning exists regarding the potential hemolysis in G6PD-deficient 
patients, studies indicate the risk is very low for hydroxychloroquine and treatment can be 
initiated while awaiting G6PD test results. 
Risk of fetal toxicity: no increase in rate of birth defects has been reported; however as the data 
are considered limited, birth outcomes will be collected at the end of pregnancy. 
Drug-drug interactions: See University of Liverpool drug interaction checkers: 
http://www.covid19-druginteractions.org 


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The following drugs should not be co-administered: amiodarone, bepridil, mexiletine, rifampicin, 
and rifapentine 
The following drugs may require dose monitoring, alteration of dosage or timing of 
coadministration: digoxin, propofol, sevoflurane, tizanidine, hydrocodone, methadone, 
disopyramide, dofelitide, propafenone, quinidine, azithromycin, clarithromycin, erythromycin, 
levofloxacin, moxifloxacin, ofloxacin, clofazimine, delamanid, bedaquiline, pyrazinamide, 
telithromycin, mefloquine 
Use in children: safety has not been established in children. Fatalities have been reported 
following accidental ingestion of chloroquine but not of hydroxychloroquine. 
Azithromycin has been used extensively for treatment of acute bacterial sinusitis, traveler 
diarrhea, and community-acquired pneumonia. The following system abnormalities have been 
listed under the FDA Warning List for arithromycin: 
Hypersensitivity: angioedema, anaphylaxis, and dermatologic reactions including Stevens 
Johnson Syndrome and toxic epidermal necrolysis have been reported rarely 
Cardiac: potential risk of QT prolongation and torsades de pointes have been seen, usually in 
settings of proarrhythmic conditions such as hypokalemia, hypomagnesemia, bradycardia, or 
those receiving hydroxychloroquine, or antiarrhythmic drugs (quinidine, procainamide, defetilide, 
amiodarone, sotalol), Risk is also higher in elderly patients. Monitoring for QT prolongation, 
particularly in setting of concomitant drugs with risk of QT prolongation.  
Hepatotoxicity: abnormal liver function, hepatitis, cholestatic jaundice, hepatic necrosis, and 
hepatic failure have been reported 
Clostridium difficile-associated diarrhea: this risk is associated with all antibiotic use 
Risk of adverse pregnancy outcome: A recent study suggested that macrolides may confer a 
higher risk of birth defects compared to penicillins according to a recent study (51). This study 
compared 100,000 women who had either a single course of a macrolide antibiotic or a 
penicillin during gestation. The prevalence of major congenital malformations (primarily 
cardiovascular) associated with first trimester exposure was 28 per 1000 live births compared to 
18 in the penicillin group. Second and third trimester prescriptions were not associated with 
malformations. Macrolide prescriptions in any trimester were associated with genital 
malformations (mainly hypospadias) in 5 vs 3 per 1000 live births. The absolute numbers of 
azithromycin compared to other macrolides (clarithromycin and erythromycin) were too small to 
analyze separately and so it is not clear that the conclusions apply to azithromycin specifically.  
 
 
11.4  Adverse Event Reporting 
Non-serious adverse events will not be collected with the exception of adverse events of special 
interest possibly related to hydroxychloroquine, which are as follows: 
 
Arrhythmias (ventricular) 
 
Hepatic Failure 
 
Bone marrow failure 
 
Aplastic anemia 
 
Prolonged QT interval 


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 
Angioedema 
 
Exfoliative dermatitis  
 
Acute generalized exanthematous pustulosis (AGEP) 
 
Psychosis 
 
Suicidal Ideation 
 
Seizure 
Serious adverse events which occur between initial dose of study medication and day 14 will be 
recorded in the electronic case report form. These events, along with the adverse events of 
special interest listed above, will be entered into the study database and provided to the Data 
and Safety Monitoring Board upon safety review as required.  
Hydroxychloroquine and azithromycin are FDA-approved medicines being used at standard 
dosing. Reporting to the IRB will occur in a summary format after each Data and Safety 
Monitoring Board review,  
11.5  Reporting of pregnancy outcome 
For participants who are pregnant women, we will obtain permission to review the medical 
record of both the participant and the infant to assess for any complications of the pregnancy 
and the outcome of the pregnancy.  Specific pregnancy-associated outcomes that will be 
collected are as follows: 
 
miscarriage in the first trimester 
 
any fetal deaths and gestational age 
 
spontaneous preterm birth 
 
premature rupture of membranes 
 
fetal growth restriction 
 
gestational diabetes 
 
indicated preterm birth 
 
preeclampsia and severity 
 
gestational age at delivery 
 
mode of delivery 
 
neonatal birth weight 
 
fetal malformation 
 
APGAR scores  
 
neonatal length of stay 
 
Neonatal intensive care unit admission 
 
Neonatal death 
 
11.6  Management of adverse events 
For adverse events that in the investigator’s judgment may be due to study drugs, one of the 
protocol investigators will discuss the adverse event with the treating physician, and a joint 
decision will be made whether to discontinue study therapy.  If study therapy has already been 
completed at the time of the adverse event, the patient will be followed per protocol by the study 
team to assess for resolution of the adverse event.  If resolution of the adverse event has not 
occurred by the day 14 assessment, the adverse event will be reassessed at the day 28 
assessment to determine whether resolution has occurred. 


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Participants who experience adverse events requiring temporary or permanent discontinuation 
of study drug will still considered to be part of the study and will be followed as outlined above. 
11.6.1  Monitoring and management of QTc interval prolongation 
The management will be according to the recommendations of the Duke COVID-19 Therapeutic 
Group as follows: 
All patients who are randomized to hydroxychloroquine and/or azithromycin will be placed on 
telemetry 
After 2nd dose of study drug (approx. >24h), repeat ECG 
a. If QTc change is <50ms, continue telemetry, no further ECGs 
b. If QTc change >50ms or QTc>500, the patient is considered a ‘QT reactor’: continue 
telemetry, mitigate QT prolonging factors: including correcting any K+ or Mg+ abnormality 
and stop azithromycin (if patient is in the azithromycin group), repeat ECG in 24h 
c. If further prolonged, or remains >500ms, stop hydroxychloroquine 
11.7  Data and Safety Monitoring Board 
A data and safety monitoring board (DSMB) will be assembled consisting of three individuals 
with complementary expertise.  At least one member will have expertise in infectious diseases 
or critical care, and at least one member will have expertise in clinical trials.  DSMB members 
will not otherwise be involved in the study.  The DSMB will be apprised of ongoing study results 
and will meet approximately monthly, or more often as needed. 
11.8  Interim Monitoring and Analyses by the Data and Safety Monitoring Board 
Evaluation of potential adverse events and tolerability will be performed as close to “real time” 
as possible by the study team and will be regularly reviewed by the DSMB.  As the planned 
Bayesian analysis permits “real-time” looks at the efficacy results without adjustment, an interim 
efficacy analysis will be available at each DSMB meeting.  The DSMB may recommend early 
closure of either experimental arm or the trial if, in their judgment, interim evidence is sufficiently 
strong that one of the trial interventions is clearly indicated/contraindicated because of 
differences in safety and/or efficacy.  The interim results will be presented as described in 
section 12.3. 
12 Statistical Considerations 
12.1 Study Hypotheses 
 
1) The World Health Organization ordinal scale measured at day 14 after enrollment will be 
higher (better) in participants receiving hydroxychloroquine than in participants who do not 
receive hydroxychloroquine. 
2) The World Health Organization ordinal scale measured at day 14 after enrollment will be 
higher (better) in participants receiving azithromycin than in participants who do not receive 
azithromycin. 
3) The proportion of participants not on mechanical ventilation at baseline who progress to 
requiring mechanical ventilation during the index hospitalization will be lower in participants 
receiving hydroxychloroquine than in participants who do not receive hydroxychloroquine. 


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4) The proportion of participants not on mechanical ventilation at baseline who progress to 
requiring mechanical ventilation during the index hospitalization will be lower in participants 
receiving azithromycin than in participants who do not receive azithromycin 
5) The World Health Organization ordinal scale measured at day 28 after enrollment will be 
higher (better) in participants receiving hydroxychloroquine than in participants who do not 
receive hydroxychloroquine. 
6)  The World Health Organization ordinal scale measured at day 28 after enrollment will be 
higher (better) in participants receiving azithromycin than in participants who do not receive 
azithromycin. 
7) The median length of hospitalization during the index hospitalization will be lower among 
participants receiving hydroxychloroquine than in participants who do not receive 
hydroxychloroquine. 
8) The median length of hospitalization during the index hospitalization will be lower among 
participants receiving azithromycin than in participants who do not receive azithromycin. 
12.2  Analysis Groups 
Intention to treat (ITT): Includes all participants who receive a treatment assignment 
Modified intention to treat (mITT): Includes all participants who received at least one dose of 
study medication 
Per protocol (PP): Includes all participants who received all assigned study medication 
12.3  Analysis Plan 
All major treatment group comparisons will be performed according to the principle of "intent-to-
treat;" that is, participants will be analyzed (and outcomes attributed) according to the 
randomized treatment, regardless of actual treatments received. The primary analysis of all 
primary and secondary endpoints will be performed in the modified intent-to-treat population. 
Treatment group comparisons will involve the following randomized treatment groups: 
 
A. Standard of care plus hydroxychloroquine 
   A1. Standard of care + hydroxychloroquine + sub-randomization to azithromycin 
   A2. Standard of care + hydroxychloroquine + sub-randomization to no azithromycin 
   A3. Standard of care + hydroxychloroquine, not eligible for azithromycin sub-randomization 
B. Standard of care without hydroxychloroquine 
   B1. Standard of care + azithromycin 
   B2. Standard of care + no azithromycin 
   B3. Standard of care, not eligible for azithromycin sub-randomization 
 
The two major treatment group comparisons to be performed are:   
 
Comparison #1: Hydroxychloroquine versus no hydroxychloroquine.  
o Aggregate of (A1 + A2 + A3) versus (B1 + B2 + B3) 
 
Comparison #2: Azithromycin versus no azithromycin.  
o Aggregate of (A1 + B1) versus (A2 + B2) 


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12.3.1.  Primary efficacy analysis 
The primary analysis of the primary efficacy endpoint, the World Health Organization scale 
measured on day 14 after enrollment, will be performed using the proportional odds model for 
ordered categorical data.  The proportional odds methodology is an extension of binary logistic 
regression to accommodate 𝑘> 2 ordered outcome categories. The model considers all 
possible ways of dichotomizing 𝑘 categories into a binary outcome and assumes that the set of 
all possible binary outcomes is related to covariates through a set of ordinary binary logistic 
regression models. Treatment group differences in the proportional odds model are expressed 
as odds ratios with an odds ratio less than 1 suggesting that treatment is better than the control 
and an odds ratio greater than 1 suggesting that treatment is worse than the control. The 
magnitude of the odds ratio describes the extent to which treated and untreated patients tend to 
have outcomes shifted toward better or worse ranking categories. To increase power and 
enhance interpretability, the proportional odds model may be adjusted for a set of relevant 
covariates, such as enrolling site and ventilator status at baseline. Covariates will be carefully 
selected and defined in the trial's Statistical Analysis Plan document. The comparison of 
hydroxychloroquine versus no hydroxychloroquine will be further adjusted for azithromycin 
assignment and the comparison of azithromycin versus no azithromycin will be adjusted for 
hydroxychloroquine assignment.  Interaction (effect modification) between hydroxychloroquine 
and azithromycin will be specifically examined, and estimates of the potential magnitude and 
credible intervals around that interaction term will be generated.  
Parameters of the proportional odds model will be estimated in a Bayesian statistical framework 
by specifying a prior probability distribution for unknown parameters. The output of a Bayesian 
analysis is a posterior probability distribution describing the relative likelihood of different 
numerical estimates for the unknown parameter values. This posterior distribution can be used 
to determine the likelihood of a clinically important treatment benefit or harm in light of the study 
data. The Bayesian approach provides an especially useful perspective for interpreting results 
of small studies that are likely to be accompanied by substantial statistical uncertainty. The 
Bayesian approach allows decisions to be made based on the estimated probability of a 
clinically important treatment benefit, as opposed to an arbitrary dichotomization of results as 
"significant" or "non-significant." 
12.3.2  Secondary efficacy analyses 
Mechanical ventilation.  
The proportion of participants not on mechanical ventilation at baseline who progress to 
requiring mechanical ventilation will be compared for patients belonging to the following 
treatment groups as defined above at the beginning of section 12.3: 
1) Hydroxychloroquine versus no hydroxychloroquine. 
2) Azithromycin versus no azithromycin.  
The comparison will be performed using logistic regression and will be adjusted for the same 
covariates as the primary endpoint proportional odds model.  
World Health Organization ordinal scale measured at day 28 
The World Health Organization ordinal scale at day 28 will be compared for the following 
treatment groups as defined above at the beginning of section 12.3:  


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1) Hydroxychloroquine versus no hydroxychloroquine. 
2) Azithromycin versus no azithromycin. 
 
Analysis will be based on the proportional odds model and will be similar to the analysis of the 
primary endpoint as described above.  
Length of hospitalization 
The distribution of days from randomization to hospital discharge will be compared for the 
following treatment groups as defined above at the beginning of section 12.3: 
1) Hydroxychloroquine versus no hydroxychloroquine. 
2) Azithromycin versus no azithromycin. 
 
The comparison will be based on a semi-parametric or rank based analysis. For participants 
who die during the enrollment hospitalization, the time from randomization to discharge will be 
regarded as infinite.  
12.3.3  Safety analyses 
There will be two comparisons for the primary safety analysis; both will consider the modified 
intention to treat population during the first fourteen days after enrollment.  Comparison 1 will 
compare the rate of severe adverse events in participants who received hydroxychloroquine 
versus the rate in participants who did not receive hydroxychloroquine.  Comparison 2 will 
compare the rate of severe adverse events in participants who received azithromycin versus the 
rate in participants who did not receive azithromycin.  An experimental arm will be deemed less 
safe than the standard of care arm if the observed rate of severe adverse events is greater than 
the control arm and the 95% credible interval (using a neutral prior distributions) around the 
difference in rates excludes zero. 
The secondary safety analyses will examine the rates of all-cause study drug 
(hydroxychloroquine and azithromycin) discontinuation in the modified intention to treat 
population, and will describe them as point estimates and 95% credible intervals (using a 
neutral prior distribution). 
12.4 Sample Size Considerations 
Table 2 summarizes frequentist considerations of sample size, based on comparison of the 
primary outcome between the group of participants who received hydroxychloroquine and those 
who did not receive hydroxychloroquine.  This assumes that the aggregate probabilities of all 
trial participants to have a day 14 World Health Organization ordinal scale score of 1-8 are as 
follows: Death 5%, mechanical ventilation/ECMO 10%, noninvasive ventilation/high flow oxygen 
15%, hospitalized on supplemental oxygen 35%, hospitalized not requiring supplemental 
oxygen 5%, hospitalized not requiring ongoing medical care 5%, not hospitalized, limitation on 
activities and/or requiring home oxygen 5%, not hospitalized, no limitations on activities 20%. 
Table 2.  Frequentist estimates of power with given odds/win ratios and sample sizes. 
Two-Sided
Odds
Win
Power  (Two-Group Trial With Total Sample Size N)
Alpha
Ratio
Ratio
N = 200
N = 300
N = 400
N = 500


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0.05
0.75
1.26
20%
29%
36%
44%
0.70
1.33
29%
41%
51%
61%
0.65
1.41
40%
55%
67%
77%
0.60
1.50
52%
70%
82%
89%
0.55
1.61
66%
83%
92%
96%
0.50
1.73
78%
92%
97%
99%
0.45
1.89
88%
97%
99%
>99%
0.40
2.07
95%
99%
>99%
>99%
0.10
0.75
1.26
31%
40%
49%
56%
0.70
1.33
41%
53%
64%
72%
0.65
1.41
52%
67%
78%
85%
0.60
1.50
64%
80%
89%
94%
0.55
1.61
76%
89%
96%
98%
0.50
1.73
86%
96%
99%
>99%
0.45
1.89
93%
99%
>99%
>99%
0.40
2.07
98%
>99%
>99%
>99%
 
The table above is based on the Wilcoxon rank sum test. Group-specific probabilities are 
assumed to be described by a proportional odds model i.e. randomization to 
hydroxychloroquine decreases the odds of being in one of the k worst outcome categories and 
the same odds ratio applies to all possible choices of k. When OR=0.5 the group-specific 
probabilities are HCQ: 3.41%, 7.28%, 12.14%, 34.39%, 5.61%, 5.79%, 5.95%, 25.43% and 
standard care: 6.59%, 12.72%, 17.86%, 35.61%, 4.39%, 4.21%, 4.05%, 14.57%. The Win Ratio 
implied by these two sets of probabilities is 1.73. 
 
To examine sample size from a Bayesian perspective, we used Monte Carlo simulations to 
study trial operating characteristics under a range of hypothetical true treatment effects. The 
operating characteristics of interest were frequentist power, type-I error, and expected study 
duration. Simulations are based on a two-arm trial that enrolls patients until declaring the 
treatment of interest to be efficacious, stopping for evidence of harm or inefficacy, or reaching a 
pre-specified maximum sample size, which we assumed to be N = 200, 300, 400, or 500. The 
primary endpoint is the WHO 8-level ordinal scale and the primary measure of treatment effect 
is the win ratio. Treatment group differences were assessed by fitting a proportional odds model 
with the WHO scale as an ordinal outcome and treatment group as a covariate. Properties of a 
fully Bayesian analysis were approximated by assuming that the maximum likelihood estimate 
of the treatment effect coefficient was normally distributed. The prior distribution assigned 2.5% 
probability to the hypothesis of a true odds ratio below 0.5 (highly efficacious) and 2.5% 
probability to the hypothesis of a true odds ratio exceeding 2.0 (highly harmful). In each 
simulated trial we assumed that interim analyses were performed sequentially after each patient 
beginning after collecting data from the first 20 patients. Signals for harm and efficacy were 
defined as follows:  
 
Moderate efficacy: The win ratio exceeds 1.25 with at least 80% Bayesian probability 


Pragmatic trial of hydroxychloroquine/azithromycin for COVID 
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 
Any efficacy: The win ratio exceeds 1.00 with at least 95% Bayesian probability 
 
Moderate harm: The win ratio is less than 0.90 with at least 75% Bayesian probability 
 
Inefficacy/any Harm: The win ratio is less than 1.00 with at least 80% Bayesian 
probability 
For simplicity, the simulation assumes that each patient's outcome is known before the next 
patient is randomized. In each simulated trial, the true probabilities for the 8 WHO categories in 
aggregate across two treatment groups were assumed to be 5%, 10%, 15%, 35%, 5%, 5%, 5%, 
20%. Data were generated under scenarios with true odds ratios ranging from 0.4 (benefit) to 
2.0 (harm). We simulated 500 trials per odds ratio scenario and estimated operating 
characteristics by averaging across simulated trial results.  
 
 
 
 
 
Table 3. Probability of reaching threshold for moderate or any efficacy as function of true 
odds ratio if enrollment is capped at 200, 300, 400, or 500 patients.  
True
Max N = 200
Max N = 300
Max N = 400
Max N = 500
Odds 
Ratio 
Moderate
Any
Moderate
Any
Moderate
Any
Moderate
Any
Power
OR = 0.75
19%
27%
27%
43%
35%
55%
40%
66%
OR = 0.70
24%
36%
39%
55%
46%
71%
55%
80%
OR = 0.65
41%
51%
56%
70%
65%
81%
71%
88%
OR = 0.60
52%
64%
70%
84%
80%
93%
87%
96%
OR = 0.55
62%
71%
81%
90%
89%
96%
93%
99%
OR = 0.50
76%
84%
90%
96%
96%
99%
99%
>99%
OR = 0.45
86%
93%
95%
98%
98%
99%
>99%
>99%
OR = 0.40
93%
96%
99%
99%
99%
>99%
>99%
>99%
Type-I 
Error 
OR = 1.00
4%
8%
5%
10%
5%
13%
6%
14%
OR = 1.05
4%
5%
5%
7%
5%
8%
5%
9%
OR = 1.10
1%
2%
2%
4%
2%
4%
2%
4%
OR = 1.15
1%
1%
1%
1%
1%
2%
1%
2%
OR = 1.25
1%
1%
1%
1%
1%
1%
1%
1%
OR = 1.50
<1%
<1%
<1%
<1%
<1%
<1%
<1%
<1%
OR = 2.00
<1%
<1%
<1%
<1%
<1%
<1%
<1%
<1%
 
 
 


Pragmatic trial of hydroxychloroquine/azithromycin for COVID 
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Table 4. Probability of reaching threshold for inefficacy or harm as function of true odds 
ratio if enrollment is capped at 200, 300, 400, or 500 patients.  
True
Max N = 200
Max N = 300
Max N = 400
Max N = 500
Odds 
Ratio 
Harm
Inefficacy
Harm
Inefficacy
Harm
Inefficacy
Harm
Inefficacy
Power
OR = 1.00
22%
37%
28%
43%
31%
47%
33%
49%
OR = 1.05
32%
45%
37%
52%
40%
55%
42%
59%
OR = 1.10
32%
45%
39%
55%
43%
61%
47%
65%
OR = 1.15
43%
56%
49%
64%
54%
71%
58%
77%
OR = 1.25
55%
67%
65%
76%
70%
81%
74%
87%
OR = 1.50
73%
84%
85%
93%
91%
96%
94%
98%
OR = 2.00
97%
98%
>99%
>99%
>99%
>99%
>99%
>99%
Type-II 
Error 
OR = 0.75
6%
10%
6%
11%
6%
11%
6%
11%
OR = 0.70
4%
8%
4%
8%
4%
8%
4%
8%
OR = 0.65
2%
5%
2%
5%
2%
5%
2%
5%
OR = 0.60
1%
2%
1%
2%
1%
2%
1%
2%
OR = 0.55
1%
3%
1%
3%
1%
3%
1%
3%
OR = 0.50
<1%
1%
<1%
1%
<1%
1%
<1%
1%
OR = 0.45
<1%
1%
<1%
1%
<1%
1%
<1%
1%
OR = 0.40
<1%
<1%
<1%
<1%
<1%
<1%
<1%
<1%
 
Table 5. Expected looks until reaching threshold for moderate efficacy or reaching 
enrollment cap as function of true odds ratio 
Odds Ratio
Max N = 200
Max N = 300
Max N = 400
Max N = 500
OR = 0.75
182
259
327
390
OR = 0.70
181
249
306
355
OR = 0.65
167
218
257
289
OR = 0.60
155
193
218
234
OR = 0.55
145
173
187
197
OR = 0.50
133
150
156
158
OR = 0.45
115
124
127
128
OR = 0.40
101
104
105
105
 
 


Pragmatic trial of hydroxychloroquine/azithromycin for COVID 
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Table 6. Expected looks until stopping for futility or harm or reaching enrollment cap as 
function of true odds ratio 
Odds Ratio
Max N = 200
Max N = 300
Max N = 400
Max N = 500
OR = 1.00
159
219
274
326
OR = 1.05
149
200
246
289
OR = 1.10
146
196
238
275
OR = 1.15
131
170
203
228
OR = 1.25
117
146
168
184
OR = 1.50
96
107
113
116
OR = 2.00
59
60
60
60
 
12.5  Interim Analysis 
For ethical reasons, interim examination of clinical endpoints and key safety events will be 
performed at regular intervals (approximately monthly) during the course of the trial. An 
independent Data and Safety Monitoring Board (DSMB) will be appointed to monitor participant 
safety and to review overall trial performance. The primary objective of these interim analyses 
will be to ensure the safety of trial participants and evaluate the accumulating evidence for 
safety and efficacy. In addition, interim monitoring will involve a review of participant 
recruitment, compliance with the study protocol, status of data collection, and other factors 
which reflect the overall progress and integrity of the study.   
Interim efficacy analyses will focus on the primary endpoint (World Health Organization ordinal 
scale) and will be performed both for the comparison of hydroxychloroquine versus no 
hydroxychloroquine and for the comparison of azithromycin versus no azithromycin. At each 
interim analysis, we will use the Bayesian proportional odds model to evaluate the probabilities 
for each of the following hypotheses in light of accruing study data: 
Hydroxychloroquine 
 
Moderate efficacy. 
o Defined as an odds ratio of 0.80 or less favoring treatment hydroxychloroquine 
over no hydroxychloroquine 
 
Any efficacy 
o Defined as an odds ratio of less than 1.0, favoring treatment hydroxychloroquine 
over no hydroxychloroquine 
 
Inefficacy 
o Defined as an odds ratio greater than 1.0, favoring treatment no 
hydroxychloroquine over hydroxychloroquine 
 
Moderate harm 
o Defined as an odds ratio greater than 1.1, favoring treatment no 
hydroxychloroquine over hydroxychloroquine 
 
Azithromycin 
 
Moderate efficacy. 


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o Defined as an odds ratio of 0.80 or less favoring treatment azithromycin over no 
azithromycin 
 
Any efficacy 
o Defined as an odds ratio of less than 1.0, favoring treatment azithromycin over 
no azithromycin 
 
Inefficacy 
o Defined as an odds ratio greater than 1.0, favoring treatment no azithromycin 
over azithromycin 
 
Moderate harm 
o Defined as an odds ratio greater than 1.1, favoring treatment no azithromycin 
over azithromycin 
 
The following events will be regarded as signals for review and consideration of early stopping.  
 
Probability of at least moderate efficacy is >80%.  
 
Probability of any efficacy is >95% 
 
Probability of inefficacy is >80% 
 
Probability of moderate harm is >75%  
 
If any of the above signals are triggered, the DSMB will be notified and enrollment will be 
temporarily suspended while the DSMB considers whether to recommend continuing or 
terminating the study. 
It is important to emphasize the triggers listed above are intended as a guide for interpreting the 
interim analyses and not as a strict rule for early termination.  The DSMB will consider a variety 
of results, including efficacy analyses of secondary endpoints, results from other ongoing and 
recently completed studies, and all aspects of safety.  
12.6 Multiplicity Considerations 
With the various primary and secondary endpoints, and two major treatment group 
comparisons, we recognize that there is a multiplicity of analyses to be performed, which leads 
to an increased probability that at least one of the comparisons could be statistically "significant" 
by chance. The Bayesian statistical framework addresses multiplicity by focusing on the 
probability that a treatment is beneficial or harmful as opposed to the probability of observing a 
significant difference if the treatment effect is literally zero. If the prior distribution is chosen to 
be a faithful reflection of the prior evidence in favor or against a clinically important treatment 
benefit, then posterior probabilities are an appropriate reflection of the posterior evidence and 
can be used for decision making without the need for an ad hoc multiplicity adjustment. 
Importantly, the results of the trial will not be explicitly tied to a labeling decision or 
recommendation for practice but will be reported in an objective manner in order to provide 
evidence to be used by multiple stakeholders. Although the analysis will not be explicitly 
adjusted to account for multiple comparisons, we will be appropriately conservative in the 
interpretation of these multiple comparisons, taking into account the magnitude of observed 
differences and looking for consistency across endpoints and subgroups. Publications 
presenting trial results will present a balanced interpretation and will call attention to the 
potential for results to be impacted by random sampling variation.  


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13 Protection of Human Subjects 
This study will be conducted in conformity with the ethical standards set out in the latest version 
of the Declaration of Helsinki.  
 
13.1  Institutional Review Board 
Each participating institution will provide for the review and approval of this protocol and the 
associated informed consent documents by an appropriate institutional ethics committee (IEC) 
or Institutional Review Board (IRB). Any amendments to the protocol or consent materials must 
also be approved before they are placed into use. 
 
13.2  Informed consent process 
Only individuals who provide written informed consent, or in the absence of ability to provide 
consent have consent provided by their appointed medical decision-maker, will be enrolled in 
this study.  Written informed consent is required before any study-specific procedures or receipt 
of study medications. Potential participants and/or their medical decision makers will have the 
conditions of the study explained to them, including potential harms and benefits, the nature and 
timing of study procedures, alternatives to study participation, that study participation is 
voluntary, that a decision to not participate in the study will not affect the quality of their future 
medical care, and that they may withdraw from participation at any time.  Literate individuals will 
be provided with a language-appropriate document to read; illiterate individuals (i.e. individuals 
who speak and understand, but do not read and write, the language in which the consent 
discussion is conducted) will have the contents of the document explained to them by a trained 
study staff member; such individuals can be enrolled by ‘making their mark’ on the consent 
document.  Potential participants will have the opportunity to ask questions of the site 
investigator or delegate, and to discuss participation with their family and/or friends or think 
about the study prior to deciding whether or not to participate.  A copy of the signed informed 
consent document will be given to the participant for his/her records.  
 
13.3  Participant confidentiality 
All records identifying the participant will be kept confidential and, to the extent permitted by the 
applicable laws and regulations, will not be made publicly available without sufficient de-
identification procedures.  
 
All paper study records will be stored in a locked office and electronic study records will be 
stored on password-protected computers; only designated trained study staff will have access to 
study records.   
 
Clinical data will be maintained in a secure, HIPAA compliant, password-protected RedCap 
database managed by the Duke Office of Clinical Research (DOCR) Research Management 
Team. The database resides on Duke Health Technology Services (DHTS) managed servers 
behind a Duke firewall and is accessible only by designated study staff with a password 
protected account.  
 
Study monitors and/or regulatory authorities may inspect all documents and records required to 
be maintained by the Investigator, including but not limited to, medical records, primary 
laboratory data, and pharmacy records for study participants; this information will be provided to 


Pragmatic trial of hydroxychloroquine/azithromycin for COVID 
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participants during the Informed Consent process.  The clinical study site will permit access to 
such records. 
 
13.4  Study discontinuation 
The Data and Safety Monitoring Board may recommend study termination, termination of a 
study arm, or termination of a study site. If the study is closed or enrollment is terminated at a 
site, the DUHS Institutional Review Board will be notified.  Participants experiencing an adverse 
event at the time of early termination should be followed until resolution or stabilization of the 
event.  Participants who were receiving study treatment at the time of early termination will 
continue care per the preferences of their treating medical providers.  
 
14 Data Handling and Record Keeping 
Information from the medical record will be directly downloaded into a secure RedCap 
database.  The directly downloaded data will be supplemented with electronic medical record 
review by one of the investigators, the results of which will also be entered into the RedCap 
database.  After study completion, the secure data will be retained for six years per DUHS 
policy. 
15 Publications and Dissemination of Study Results 
Study results will be analyzed and published promptly after approval by all investigators.  No 
identifying information regarding individual participants will be included in any publication. 
 
 


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