Interim User Guide for COVID-19 - balramchauhan

Interim User Guide

for COVID-19

Version 1.0

Revision History

Date Version

2020-04-21 1.0

See Appendix D for Representations and Warranties, Limitations of Liability, and Disclaimers

Notes to Readers

This document is based on SDTM v1.7 and SDTMIG v3.3.

CDISC Interim User Guide for COVID-19 Version 1.0

© 2020 Clinical Data Interchange Standards Consortium, Inc. All rights reserved Page 2 2020-04-21

CONTENTS

1 INTRODUCTION ................................................................................................................. 3

2 RISK FACTORS ................................................................................................................... 4 2.1 PRE-EXISTING MEDICAL CONDITIONS ................................................................................................................... 4 2.2 PERSONAL PROTECTIVE EQUIPMENT (PPE) ........................................................................................................... 4 2.3 TRAVEL .................................................................................................................................................................. 5 2.4 CONTACTS ............................................................................................................................................................. 6 2.5 SUBSTANCE USE .................................................................................................................................................... 7 2.6 EXPOSURE TO ANIMALS ......................................................................................................................................... 8

3 ONSET OF DISEASE ........................................................................................................... 9

4 SIGNS AND SYMPTOMS ................................................................................................. 10

5 LABORATORY TEST RESULTS .................................................................................... 16

6 DIAGNOSTICS AND VIROLOGY .................................................................................. 18 6.1 VIRUS IDENTIFICATION ........................................................................................................................................ 18 6.2 ANTIBODY TESTING ............................................................................................................................................. 18 6.3 SARS-COV-2 VIRAL LOAD ................................................................................................................................. 19

7 VITAL SIGNS AND URINE OUTPUT ............................................................................ 21

8 CONCOMITANT MEDICATIONS .................................................................................. 23

9 RESPIRATORY FINDINGS.............................................................................................. 24 9.1 IMAGING .............................................................................................................................................................. 24 9.2 PULMONARY FUNCTION TESTS ............................................................................................................................ 25

10 CARDIAC EVENTS/FINDINGS ....................................................................................... 26

11 HOSPITALIZATION ......................................................................................................... 27

12 PROCEDURES .................................................................................................................... 28 12.1 ASSISTED VENTILATION AND OXYGEN TREATMENTS ......................................................................................... 28 12.2 RENAL TREATMENT ............................................................................................................................................. 30

13 VACCINES .......................................................................................................................... 31

14 QUESTIONNAIRES, RATINGS, AND SCALES............................................................ 33 14.1 CLINICAL GLOBAL IMPRESSION AND SPONSOR-CREATED INSTRUMENTS ............................................................ 33

15 APPENDICES ...................................................................................................................... 35 APPENDIX A: NON-STANDARD VARIABLES (NSVS) ..................................................................................................... 35 APPENDIX B: GLOSSARY AND ABBREVIATIONS ............................................................................................................ 36 APPENDIX C: REFERENCES ........................................................................................................................................... 38 APPENDIX D: REPRESENTATIONS AND WARRANTIES, LIMITATIONS OF LIABILITY, AND DISCLAIMERS ....................... 39



1 Introduction In March 2020, CDISC launched a team to rapidly develop guidance on standardizing COVID-19 research data.

Due to the public health significance of COVID-19, a task force was assembled with participants from industry, the

US Food & Drug Association, the US National Institutes of Health (NIH), the World Health Organization (WHO),

and academia, who worked alongside CDISC over several weeks to develop this Interim User Guide. This

development did not follow the usual CDISC Standards Development Process detailed in COP-001 (available

at https://www.cdisc.org/system/files/about/cop/CDISC-COP-001-Standards_Development_2019.pdf). CDISC

publicized the development of this document through a press release and updates on the CDISC website

(www.cdisc.org). In order to increase transparency, the development of this guidance was publicly visible

throughout the accelerated development process.

This Interim User Guide provides examples and guidance on implementing CDISC standards for COVID-19 so that

researchers can collect, structure, and analyze data more effectively to amplify the full value of data, drive clinical

research forward, and improve global health.

https://www.cdisc.org/system/files/about/cop/CDISC-COP-001-Standards_Development_2019.pdf

http://www.cdisc.org/



2 Risk Factors At the time of publication of the Interim User Guide for COVID-19, information on risk factors is still limited.[1] Current information shows that risk factors for

COVID-19 may include old age or pre-existing medical conditions, including heart disease, lung disease, and diabetes.[2] This section also discusses personal

protective equipment (PPE), travel, contacts, substance use/smoking, and exposure to animals.

2.1 Pre-existing Medical Conditions

Example 1

Individuals with pre-existing medical conditions such as asthma, human immunodeficiency virus (HIV), and diabetes may be at higher risk for developing severe

illness from COVID-19. The following example shows how high-risk underlying medical conditions from a pre-specified list can be represented in the Medical

History (MH) domain. MHCAT = "RISK FACTOR FOR SEVERE ILLNESS FROM COVID-19" is used to group risk factors together. Subject 101 has asthma

and HIV, but does not have diabetes.

mh.xpt

Row STUDYID DOMAIN USUBJID MHSEQ MHTERM MHDECOD MHCAT MHPRESP MHOCCUR MHDTC

1 COV-1 MH 101 1 ASTHMA Asthma RISK FACTOR FOR SEVERE ILLNESS FROM COVID-19 Y Y 2020-03-05

2 COV-1 MH 101 2 DIABETES Diabetes mellitus RISK FACTOR FOR SEVERE ILLNESS FROM COVID-19 Y N 2020-03-05

3 COV-1 MH 101 3 HIV HIV infection RISK FACTOR FOR SEVERE ILLNESS FROM COVID-19 Y Y 2020-03-05

2.2 Personal Protective Equipment (PPE)

During the COVID-19 pandemic, it is recommended that health care workers use personal protective equipment (PPE) such as N95 respirators, gowns, goggles,

and face shields. Additionally, the general population is advised and, in some cases, required to wear face masks when out in public. Use of PPE can be

represented in the draft Environmental and Social Factors (ER) domain using ERCAT = "PPE".

Example 1

This example shows data from a study on health care workers. An overall question about the use of PPE was asked, followed by questions about the use of

specific PPE in the past 14 days. Information about the type and manufacture of the PPE was also collected. PPE can be considered a device and this additional

information can be represented in the Device Identifiers (DI) domain. The Sponsor Defined Device Identifier (SPDEVID) variable is used in ER to specify which

PPE was used.

Row 1: Shows that the subject used PPE.

Rows 2-4: Show that the subject used an N95 respirator, a gown, and a face shield.

https://wiki.cdisc.org/pages/viewpage.action?pageId=29918868



er.xpt

Row STUDYID DOMAIN USUBJID ERSEQ SPDEVID ERTERM ERCAT ERPRESP EROCCUR ERDTC EREVLINT

1 CVD-4 ER 400 1 Use of Personal Protective Equipment PPE Y Y 2020-04-10 -P14D

2 CVD-4 ER 400 2 100 Use of N95 Respirator PPE Y Y 2020-04-10 -P14D

3 CVD-4 ER 400 3 200 Use of Gown PPE Y Y 2020-04-10 -P14D

4 CVD-4 ER 400 4 300 Use of Face Shield PPE Y Y 2020-04-10 -P14D

The DI domain is used to represent information about the PPE type and manufacturer.

di.xpt

Row STUDYID DOMAIN SPDEVID DISEQ DIPARMCD DIPARM DIVAL

1 CVD-4 DI 100 1 DEVTYPE Device Type N95 Respirator

2 CVD-4 DI 100 2 MANUF Manufacturer Company A

3 CVD-4 DI 200 1 DEVTYPE Device Type Gown

4 CVD-4 DI 200 2 MANUF Manufacturer Company B

5 CVD-4 DI 300 1 DEVTYPE Device Type Face Shield

6 CVD-4 DI 300 2 MANUF Manufacturer Company C

2.3 Travel

Traveling to areas with confirmed COVID-19 cases may increase an individual's risk of becoming infected. Studies may collect information about international,

interregional, and interstate travel during a specified period of time in order to assess risk of exposure to COVID-19. Questions about travel can be represented in

the draft Environmental and Social Factors (ER) domain.

Studies may require investigators to ask questions of varying levels of specificity regarding a subject's travel history. There may be differences in how countries

describe geographic regions within a country (e.g., state, province). Examples of these variations include:

• Have you traveled to an area with confirmed COVID-19 cases?

• Have you traveled internationally? If yes, to which countries?

• Have you traveled between States? If yes, to which States?

• Have you traveled between Provinces? If yes, to which Provinces?

Example 1

The example below shows how data regarding travel can be represented in the draft Environmental and Social Factors (ER) domain. Subjects were asked

whether or not they traveled to 14 days prior to symptom onset. If yes, subjects were asked to list country, region, and start and end dates for each location

visited. ERCAT = "COVID-19 RISK FACTOR" and ERSCAT="TRAVEL" is used to group these questions together. Subjects were asked if they had traveled

in the 14 days prior to onset of symptoms (EVINTX). If a subject had traveled, the study collected: country, region, and dates of travel. Start and end dates of

travel are represented in ERSTDTC and ERENDTC. Details about the county and region can be represented as non-standard variables. In this example, the NSV




CNTRY is populated with ISO 3166-1-alpha-3 country codes, whereas the NSV REGION is populated with ISO 3166-2 codes. To allow separate timing of individual countries/regions visited within the past 14 days

prior to symptom onset, each country and/or region is represented on a separate row.

Row 1: Shows that subject 100 did travel 14 days prior to symptom onset.

Row 2: Shows that subject 100 traveled to the US state of Massachusetts within the between shown in ERSTDTC and ERENDTC, all within 14 days prior to symptom onset.

Row 3: Shows that subject 100 traveled to the US state of New York within the between shown in ERSTDTC and ERENDTC, all within 14 days prior to symptom onset.

Row 4: Shows that subject 101 did travel 14 days prior to symptom onset.

Row 5: Shows that subject 101 traveled to the Lombardy region of Italy during the dates shown in ERSTDTC and ERENDTC, all within 14 days prior to symptom onset.

Row 6: Shows that subject 101 traveled to Madrid, Spain during the dates shown in ERSTDTC and ERENDTC, all within 14 days prior to symptom onset.

Row 7: Shows that subject 102 did not travel 14 days prior to symptom onset.

er.xpt

Row STUDYID DOMAIN USUBJID ERSEQ ERGRPID ERTERM ERCAT ERSCAT ERPRESP EROCCUR ERDTC ERSTDTC ERENDTC EVINTX ERCNTRY ERREGION

1 COV-7 ER 100 1 1 TRAVEL COVID-19 RISK FACTOR TRAVEL Y Y 2020-02-23 14 DAYS PRIOR TO SYMPTOM ONSET

2 COV-7 ER 100 2 1 TRAVEL COVID-19 RISK FACTOR TRAVEL 2020-02-23 2020-02-11 2020-02-14 14 DAYS PRIOR TO SYMPTOM ONSET USA US-MA

3 COV-7 ER 100 3 1 TRAVEL COVID-19 RISK FACTOR TRAVEL 2020-02-23 2020-02-14 2020-02-16 14 DAYS PRIOR TO SYMPTOM ONSET USA US-NY

4 COV-7 ER 101 1 2 TRAVEL COVID-19 RISK FACTOR TRAVEL Y Y 14 DAYS PRIOR TO SYMPTOM ONSET

5 COV-7 ER 101 2 2 TRAVEL COVID-19 RISK FACTOR TRAVEL 2020-02-23 2020-02-10 2020-02-13 14 DAYS PRIOR TO SYMPTOM ONSET ITA IT-25

6 COV-7 ER 101 3 2 TRAVEL COVID-19 RISK FACTOR TRAVEL 2020-02-23 2020-02-13 2020-02-19 14 DAYS PRIOR TO SYMPTOM ONSET ESP ES-M

7 COV-7 ER 102 1 TRAVEL COVID-19 RISK FACTOR TRAVEL Y N 2020-02-23 14 DAYS PRIOR TO SYMPTOM ONSET

ER NSV Metadata

Variable Label Type Codelist Role Origin

ERCNTRY Country text ISO 3166-1 alpha-3 Non-standard Record Qualifier CRF

ERREGION Geographical Region text ISO 3166-2 Non-standard Record Qualifier CRF

2.4 Contacts

Example 1

Information about exposure to people or facilities that could potentially increase the risk of developing a COVID-19 infection can be represented in the draft Environmental and Social Factors (ER) domain.

Row 1: Shows that the subject was in close contact with a COVID-19 case in the past 14 days.

Row 2: Shows that the subject was not present at a health care facility where COVID-19 infections have been managed in the past 14 days.

Row 3: Shows that the subject was not present in a laboratory handling suspected or confirmed COVID-19 samples in the past 14 days.




er.xpt

Row STUDYID DOMAIN USUBJID ERLNKID ERSEQ ERTERM ERCAT ERPRESP EROCCUR ERSTDTC EREVLINT

1 COVID-3 ER 100 1 1 Close contact with a confirmed or probable case of COVID-19, while that case was symptomatic COVID-19 RISK FACTOR Y Y 2020-02-25 -P14D

2 COVID-3 ER 100 2 Presence in a healthcare facility where COVID-19 infections have been managed COVID-19 RISK FACTOR Y N -P14D

3 COVID-3 ER 100 3 Presence in a laboratory handling suspected or confirmed COVID-19 samples COVID-19 RISK FACTOR Y N -P14D

When a subject has been in close contact with a person who has a confirmed or probable case of COVID-19, additional information may be collected on this potential source case. Data on the potential source case

can be represented in the Associated Persons (AP) domains. In this case, additional information was collected regarding the diagnosis of this potential source and has been represented in APMH. The RSUBJID

corresponds to the subject's USUBJID; SREL indicates the associated person's relationship to the subject. The variables MHLNKID and ERLNKID are used to connect the diagnosis information of the confirmed

case to the ER record describing the exposure.

apmh.xpt

Row STUDYID DOMAIN APID MHSEQ RSUBJID SREL MHLNKID MHTERM MHDECOD MHSTDTC

1 COVID APMH 200 1 100 MOTHER, BIOLOGICAL 1 COVID-19 Coronavirus infection 2020-04-01

This relrec dataset shows that the ER and APMH datasets can be connected using --LNKID.

relrec.xpt

Row STUDYID RDOMAIN USUBJID IDVAR IDVARVAL RELTYPE RELID

1 COVID ER ERLNKID ONE A

2 COVID APMH MHLNKID ONE A

All subsequent data collected on the potential source are handled in APxx datasets, where "xx" is the 2-letter code for the corresponding domain where data from the subject would be represented (e.g., potential

source case COVID-19 identification tests would be represented in the APMB domain).

2.5 Substance Use

Example 1

This example shows how substance use data could be represented. In this case, the case report form (CRF) collected smoking status of "current", "never", and "former" cigarette use.

Row 1: Shows that the subject is a current smoker, starting sometime in 2001.

Row 2: Shows that the subject has never smoked. SUOCCUR="N" and the dosing and timing fields are null.

Row 3: Shows that the subject is a former smoker, quitting sometime in 2010.

Row 4: Shows that the subject is a current user of e-cigarettes, beginning sometime in 2018.



su.xpt

Row STUDYID DOMAIN USUBJID SUSEQ SUTRT SUCAT SUPRESP SUOCCUR SUDOSE SUDOSU SUDOSFRQ SUSTDTC SUENDTC SUSTTPT SUSTRTPT SUENTPT SUENRTPT

1 CVD-7 SU 700 1 CIGARETTES TOBACCO Y Y 2 PACK QD 2001 2020-01-01 BEFORE 2020-01-01 ONGOING

2 CVD-7 SU 701 1 CIGARETTES TOBACCO Y N

3 CVD-7 SU 702 1 CIGARETTES TOBACCO Y Y 1 PACK QD 2010 2020-03-15 BEFORE

4 CVD-7 SU 703 1 E-CIGARETTES E-LIQUID Y Y 5 mL QD 2018 2020-04-01 BEFORE 2020-04-01 ONGOING

2.6 Exposure to Animals

In rare cases, coronaviruses may be spread from infected animals to humans (zoonotic transmission), and then spread between humans. Examples of zoonotic diseases include severe acute respiratory syndrome

(SARS) and Middle East respiratory syndrome (MERS). The exact source of COVID-19 is unknown at this time.[3]

Example 1

This example shows the representation of data for pre-specified questions regarding animal exposure within the past 14 days, using the draft Environmental and Social Factors (ER) domain. In this example study,

exposure to animals was considered a potential risk factor for COVID-19; thus, ERCAT = "COVID 19 RISK FACTOR" and ERSCAT = "ANIMAL EXPOSURE" were used to group these questions together. The

variable EREVLINT was used to indicate that the question was intended to capture animal exposure during the past 14 days.

er.xpt

Row STUDYID DOMAIN USUBJID ERSEQ ERTERM ERCAT ERSCAT ERPRESP EROCCUR ERDTC EREVLINT

1 CVD-01 ER 100 1 EXPOSURE TO BIRDS COVID-19 RISK FACTOR ANIMAL EXPOSURE Y N 2020-03-20 -P14D

2 CVD-01 ER 100 2 EXPOSURE TO BATS COVID-19 RISK FACTOR ANIMAL EXPOSURE Y N 2020-03-20 -P14D

3 CVD-01 ER 100 3 EXPOSURE TO LIVESTOCK COVID-19 RISK FACTOR ANIMAL EXPOSURE Y Y 2020-03-20 -P14D

4 CVD-01 ER 100 4 INSECT OR TICK BITE COVID-19 RISK FACTOR ANIMAL EXPOSURE Y N 2020-03-20 -P14D

5 CVD-01 ER 100 5 EXPOSURE TO SICK OR DEAD ANIMAL COVID-19 RISK FACTOR ANIMAL EXPOSURE Y Y 2020-03-20 -P14D

6 CVD-01 ER 100 6 EXPOSURE TO ANIMAL FECES COVID-19 RISK FACTOR ANIMAL EXPOSURE Y Y 2020-03-20 -P14D

7 CVD-01 ER 100 7 EXPOSURE TO PIGS COVID-19 RISK FACTOR ANIMAL EXPOSURE Y Y 2020-03-20 -P14D




3 Onset of Disease Example 1

In this example, the date of onset of symptoms and date of diagnosis were collected for the study. The date of

diagnosis was based on a positive test, and the CRF collected an identifier for the laboratory test with the positive

result.

Row 1: Shows the date of onset of symptoms.

Row 2: Shows the date of diagnosis. MHLNKID has been populated so that it can be related to the lab record

which confirmed diagnosis. Neither the lab dataset nor the related records (RELREC) dataset are

included in this example.

mh.xpt

Row STUDYID DOMAIN USUBJID MHSEQ MHLNKID MHTERM MHEVDTYP MHDTC MHSTDTC MHENDTC MHDY MHSTDY MHENDY

1 COVID-6 MH 103 1 COVID-19

SYMPTOM ONSET

2020-04-05

2020-03-31

1 -5

2 COVID-6 MH 103 2 1 COVID-19

DIAGNOSIS 2020-04-05

2020-04-04

1 -1



4 Signs and Symptoms In COVID-19 studies, data about signs and symptoms is likely to focus on occurrence. Vaccine trials may include

assessments of reactogenicity symptoms; see Vaccines. For the purpose of this guide, the term symptoms is used to

refer to both signs and symptoms.

The examples in this section include the variable --DY, Study Day. Study day is relative to the study reference start

date (RFSTDC) in the Demographics domain. In interventional studies, the reference start date is usually the date of

start of treatment.

The domain in which data about the occurrence events is represented depends on whether data is about the event as

a whole, or is an assessment for a part of the event—that is, an assessment at a point in time (a snapshot) or a period of time within the event (a slice). Occurrence data about an event as a whole is represented in the Events domains,

whereas data about a part of an event is represented in the Findings About (FA) domain.

Occurrence data about symptoms collected at the beginning of the study are generally represented in the Medical

History (MH) domain or in the FA domain, in the famh.xpt dataset. There is an exception if data collected at the

beginning of the study are the same as data collected repeatedly during the study; in this case all data are represented

in the same findings about dataset, usually the face.xpt dataset. In either case, records are likely to include a --CAT

value (e.g., "COVID-19 SYMPTOMS").

Questions about pre-specified symptoms may vary, as illustrated in the following table.

Question Domain/Dataset Timing variables

Has the symptom occurred since the onset of acute illness?

MH MHDTC is date of assessment, EVINTX="SINCE ONSET OF ACUTE ILLNESS".

Was the symptom present at diagnosis?

FAMH FADTC is date of diagnosis. If diagnosis is defined as a disease milestone, MIDS is diagnosis, RELMIDS is "AT TIME OF".

Is the symptom present now? FAMH FADTC is date of assessment.

Data collection forms may include a place to enter symptoms which are not pre-specified. Those terms would be

represented in the MH domain.



Example 1

In this example, data were collected at entry about symptoms that had occurred since the start of COVID-19.

Rows 1-7: Show occurrence data for pre-specified symptoms.

Row 8: Shows a symptom entered in a field for specifying other symptoms.

mh.xpt

Row STUDYID DOMAIN USUBJID MHSEQ MHTERM MHDECOD MHCAT MHPRESP MHOCCUR MHSTAT MHREASND MHDTC MHDY MHEVINTX

1 COV6 MH 102 1 Fever Fever COVID-19 SYMPTOMS

Y Y 2020-04-02

1 SINCE ONSET OF ACUTE ILLNESS

2 COV6 MH 102 2 Chills Chills COVID-19 SYMPTOMS

Y Y 2020-04-02


3 COV6 MH 102 3 Muscle aches Myalgia COVID-19 SYMPTOMS

Y Y 2020-04-02


4 COV6 MH 102 4 Sore throat Sore throat COVID-19 SYMPTOMS

Y N 2020-04-02


5 COV6 MH 102 5 Shortness of breath

Dyspnoea COVID-19 SYMPTOMS

Y Y 2020-04-02


6 COV6 MH 102 6 Loss of smell Anosmia COVID-19 SYMPTOMS

Y N 2020-04-02


7 COV6 MH 102 7 Loss of taste Ageusia COVID-19 SYMPTOMS

Y Y 2020-04-02


8 COV6 MH 102 8 Nausea Nausea COVID-19 SYMPTOMS

2020-04-02


Example 2

In this example, eligibility criteria included diagnosis of COVID-19. At entry, questions on the CRF asked whether pre-specified symptoms were present at

diagnosis. Because these were assessments about a point in time, the data are represented in FAMH. Although the data were gathered at the start of the study (as

indicated by the visit variables), FADTC was populated with the date of diagnosis, which was the time that was the focus of the question.

famh.xpt

Row STUDYID DOMAIN USUBJID FASEQ FATESTCD FATEST FAOBJ FACAT FAORRES FASTRESC FASTAT FAREASND VISITNUM VISIT FADTC FADY

1 COVID3 FA 123 1 OCCUR Occurrence Indicator

Cough COVID-19 SYMPTOMS

Y Y 1 Entry 2020-04-02

-2



N N 1 Entry 2020-04-02

-2


Fever COVID-19 SYMPTOMS

Y Y 1 Entry 2020-04-02

-2


Myalgia COVID-19 SYMPTOMS

N N 1 Entry 2020-04-02

-2



Sponsors may choose to identify diagnosis as a trial disease milestone in the Trial Disease Milestones (TM) domain (not shown). In such a case, the Subject Disease Milestones (SM) domain (not shown) would be

submitted; the FAMH dataset would include the additional timing variables MIDS, RELMIDS, and MIDSDTC, as presented in the following table.

famh.xpt

Row STUDYID DOMAIN USUBJID FASEQ FATESTCD FATEST FAOBJ FACAT FAORRES FASTRESC FASTAT FAREASND VISITNUM VISIT FADTC FADY MIDS RELMIDS MIDSDTC

1 COVID3 FA 123 1 OCCUR Occurrence Indicator Cough COVID-19 SYMPTOMS Y Y 1 Entry 2020-04-02 -2 DIAGNOSIS AT THE TIME OF 2020-04-02

2 COVID3 FA 123 2 OCCUR Occurrence Indicator Dyspnoea COVID-19 SYMPTOMS N N 1 Entry 2020-04-02 -2 DIAGNOSIS AT THE TIME OF 2020-04-02

3 COVID3 FA 123 3 OCCUR Occurrence Indicator Fever COVID-19 SYMPTOMS Y Y 1 Entry 2020-04-02 -2 DIAGNOSIS AT THE TIME OF 2020-04-02

4 COVID3 FA 123 4 OCCUR Occurrence Indicator Myalgia COVID-19 SYMPTOMS N N 1 Entry 2020-04-02 -2 DIAGNOSIS AT THE TIME OF 2020-04-02

Data collection may include questions about groups of symptoms, such as

• Gastrointestinal (GI) symptoms (e.g., nausea, vomiting, diarrhea)

• Cough (e.g., non-productive, productive, haemoptysis)

In general, a name for the group of symptoms would be represented in --TERM and --SCAT; the --SCAT value would also be used for subsequent questions about specific symptoms within the group.

Example 3

In this example, the collection at study entry of data about COVID-19 symptoms included a question about cough. If the subject answered yes, subsequent questions were asked about more specific kinds of cough.

Row 1: Shows occurrence data for the term "cough". Because more detailed subsequent questions were asked, this was treated as a question about a group of symptoms. MHTERM and MHSCAT have the same

value "COUGH". Records for this question were created so that records for subjects without cough would be available for use in analysis.

Rows 2-4: Show occurrence data for more specific kinds of cough within the group "COUGH". Note different types of cough could have occurred; in this case, a subject had both a non-productive cough and a

productive cough but did not have a cough that produced bloody sputum.

mh.xpt

Row STUDYID DOMAIN USUBJID MHSEQ MHTERM MHLLT MHDECOD MHCAT MHSCAT MHPRESP MHOCCUR MHSTAT MHREASND MHDTC MHDY MHEVINTX

1 COV6 MH 102 1 COUGH COVID-19 SYMPTOMS COUGH Y Y 2020-04-02 1 SINCE ONSET OF ACUTE ILLNESS

2 COV6 MH 102 2 Non-productive cough Cough, non-productive Cough COVID-19 SYMPTOMS COUGH Y Y 2020-04-02 1 SINCE ONSET OF ACUTE ILLNESS

3 COV6 MH 102 3 Productive cough Productive cough Productive cough COVID-19 SYMPTOMS COUGH Y Y 2020-04-02 1 SINCE ONSET OF ACUTE ILLNESS

4 COV6 MH 102 4 Cough with bloody sputum Bloody sputum Haemoptysis COVID-19 SYMPTOMS COUGH Y N 2020-04-02 1 SINCE ONSET OF ACUTE ILLNESS

Data collected about symptoms during a study are often represented in the Clinical Events (CE) domain, rather than the Adverse Events (AE) domain. Note that there may be criteria under which especially severe or

long-lasting symptoms are reportable as adverse events.

Note that the following examples showing symptom data collected during the study do not include fever; temperature measurements are more accurate for determining whether fever occurred and how severe it was.

Temperature would be represented in the Vital Signs (VS) domain.

Known Issue: If a clinical event meets criteria for reporting as an adverse event, a record will be created in the AE domain (along with, possibly, record(s) in the faae.xpt dataset), but it is not clear whether data

about the event should be removed from the CE domain (and, possibly, from the face.xpt dataset). It is recommended to consult the regulatory division to which the data will be submitted on this point.



Data collected about symptoms during the study may include approaches such as illustrated in the following table.

Question/Instruction Domain/Dataset Timing variables

Record symptoms related to COVID-19 (not pre-specified) CE (or AE) CESTDTC, CEENDTC

Did the symptom occur during the study? CE (or AE and FAAE) EVINTX = "DURING THE STUDY"

Did the symptom occur within the past day? FACE (or FAAE) FADTC is date of assessment, EVLINT = "-P1D"

Has the symptom occurred since the last visit? FACE (or FAAE) FADTC is date of assessment, EVINTX = "SINCE LAST VISIT"

If symptoms are assessed periodically for occurrence or for occurrence and severity, data are represented in the FA domain. If this type of data is collected using

the same questions at baseline as during the study, then the baseline assessment should be represented in the face.xpt dataset rather than the famh.xpt dataset.

Example 4

In this example, data were collected daily about the occurrence of pre-specified symptoms. In this study, because subjects were hospitalized, date and study day

(rather than visit) were used to identify the timing of assessments. Note that although the values in FAOBJ are Medical Dictionary for Regulatory Activities

(MedDRA) terms, the CRF may have used language more familiar to subjects (e.g., "runny nose" instead of or in addition to the medical term "rhinorrhea").

face.xpt

Row STUDYID DOMAIN USUBJID FASEQ FATESTCD FATEST FAOBJ FACAT FAORRES FASTRESC FADTC FADY FAEVLINT

1 CVD-5 FA 500 1 OCCUR Occurrence Indicator Cough COVID-19 SYMPTOMS Y Y 2020-04-01 2 -P1D

2 CVD-5 FA 500 2 OCCUR Occurrence Indicator Rhinorrhoea COVID-19 SYMPTOMS N N 2020-04-01 2 -P1D

3 CVD-5 FA 500 3 OCCUR Occurrence Indicator Ear pain COVID-19 SYMPTOMS N N 2020-04-01 2 -P1D

4 CVD-5 FA 500 4 OCCUR Occurrence Indicator Wheezing COVID-19 SYMPTOMS Y Y 2020-04-01 2 -P1D

5 CVD-5 FA 500 5 OCCUR Occurrence Indicator Chest Pain COVID-19 SYMPTOMS N N 2020-04-01 2 -P1D

6 CVD-5 FA 500 6 OCCUR Occurrence Indicator Dyspnoea COVID-19 SYMPTOMS Y Y 2020-04-01 2 -P1D

Severity of symptoms can be assessed using the traditional adverse event severity mild/moderate/severe codes, but also can be represented using numeric rating

scales or visual analog scales (VAS). The following examples illustrate each of these approaches.



Example 5

In this example, symptom occurrence was assessed daily. If a symptom occurred within the past day, the severity of the symptom was assessed using the codes "MILD", "MODERATE", and "SEVERE".

face.xpt

Row STUDYID DOMAIN USUBJID FASEQ FATESTCD FATEST FAOBJ FACAT FAORRES FASTRESC FADTC FADY FAEVLINT


2 CVD-5 FA 500 2 SEV Severity/Intensity Cough COVID-19 SYMPTOMS SEVERE SEVERE 2020-04-01 2 -P1D




6 CVD-5 FA 500 6 SEV Severity/Intensity Wheezing COVID-19 SYMPTOMS SEVERE SEVERE 2020-04-01 2 -P1D

7 CVD-5 FA 500 7 OCCUR Occurrence Indicator Chest pain COVID-19 SYMPTOMS N N 2020-04-01 2 -P1D


9 CVD-5 FA 500 9 SEV Severity/Intensity Dyspnoea COVID-19 SIGNS AND SYMPTOMS MODERATE MODERATE 2020-04-01 2 -P1D

Example 6

In this example, symptom occurrence was assessed daily. If a symptom occurred within the past day, the severity of the symptom was assessed using a scale of 1 to 5 (where 1 = "Very mild" and 5 = "Very severe",

but no text was associated with intermediate values).

face.xpt

Row STUDYID DOMAIN USUBJID FASEQ FATESTCD FATEST FAOBJ FACAT FAORRES FASTRESC FASTRESN FADTC FADY FAEVLINT RNGVALLO RNGTXTLO RNGVALHI RNGTXTHI


2 CVD-5 FA 500 2 SEV Severity/Intensity Cough COVID-19 SYMPTOMS 4 4 4 2020-04-01 2 -P1D 1 VERY MILD 5 VERY SEVERE




6 CVD-5 FA 500 6 SEV Severity/Intensity Wheezing COVID-19 SYMPTOMS 3 3 3 2020-04-01 2 -P1D 1 VERY MILD 5 VERY SEVERE

7 CVD-5 FA 500 7 OCCUR Occurrence Indicator Chest pain COVID-19 SYMPTOMS N N 2020-04-01 2 -P1D


9 CVD-5 FA 500 9 SEV Severity/Intensity Dyspnoea COVID-19 SYMPTOMS 2 2 2 2020-04-01 2 -P1D 1 VERY MILD 5 VERY SEVERE

FACE NSV Metadata

Variable Label Type Codelist Role Origin Comment

RNGVALLO Range Value Low integer Non-standard Record Qualifier CRF Pre-specified on CRF

RNGTXTLO Range Text Low text Non-standard Record Qualifier CRF Pre-specified on CRF

RNGVALHI Range Value High integer Non-standard Record Qualifier CRF Pre-specified on CRF

RNGTXTHI Range Text High text Non-standard Record Qualifier CRF Pre-specified on CRF



Example 7

In this example, symptom occurrence was assessed daily. If a symptom occurred within the past day, the severity of the symptom was assessed using a 50mm VAS where the text at the low end of the scale was "Not

at all severe" and the text at the high end of the scale was "As severe as possible".

face.xpt

Row STUDYID DOMAIN USUBJID FASEQ FATESTCD FATEST FAOBJ FACAT FAORRES FAORRESU FASTRESC FASTRESN FASTRESU FAMETHOD FADTC FADY FAEVLINT RNGVALLO RNGTXTLO RNGVALHI RNGTXTHI

1 CVD-5 FA 500 1 OCCUR Occurrence Indicator

Cough COVID-19 SYMPTOMS

Y Y 2020-04-01

2 -P1D

2 CVD-5 FA 500 2 SEV Severity/Intensity Cough COVID-19 SYMPTOMS

41 mm 41 41 mm VISUAL ANALOG SCALE (50 MM)

2020-04-01

2 -P1D 0 Not at all severe

50 As severe as possible


Rhinorrhoea COVID-19 SYMPTOMS

N N 2020-04-01

2 -P1D

4 CVD-5 FA 500 4 OCCUR Occurrence

Indicator

Ear pain COVID-19

SYMPTOMS

N N 2020-

04-01

2 -P1D


Wheezing COVID-19 SYMPTOMS

Y Y 2020-04-01

2 -P1D

6 CVD-5 FA 500 6 SEV Severity/Intensity Wheezing COVID-19 SYMPTOMS

30 mm 30 30 mm VISUAL ANALOG SCALE (50 MM)

2020-04-01

2 -P1D 0 Not at all severe

50 As severe as possible


Chest pain COVID-19 SYMPTOMS

N N 2020-04-01

2 -P1D



Y Y 2020-04-01

2 -P1D

9 CVD-5 FA 500 9 SEV Severity/Intensity Dyspnoea COVID-19

SYMPTOMS

28 mm 28 28 mm VISUAL ANALOG

SCALE (50 MM)

2020-

04-01

2 -P1D 0 Not at all

severe

50 As severe as

possible

FACE NSV Metadata

Variable Label Type Codelist Role Origin Comment

RNGVALLO Range Value Low integer Non-standard Record Qualifier CRF Pre-specified on CRF

RNGTXTLO Range Text Low text Non-standard Record Qualifier CRF Pre-specified on CRF

RNGVALHI Range Value High integer Non-standard Record Qualifier CRF Pre-specified on CRF

RNGTXTHI Range Text High text Non-standard Record Qualifier CRF Pre-specified on CRF



5 Laboratory Test Results The LB domain is a findings domain that contains laboratory test data such as hematology, clinical chemistry, and urinalysis. This domain does not include microbiology, virology, or pharmacokinetic data, which are

stored in separate domains. For information about virus identification and viral load for COVID-19, see Virus Identification.

Additional information on the LB domain may be found in the SDTMIG v3.3, Section 6.3.6 (available at https://www.cdisc.org/standards/foundational/sdtmig)

Example 1

This example shows data from an arterial blood gas panel. The Sponsor Device Identifier (SPDEVID) was included because the sponsor was interested in the device used for the testing. Information about the device

identified by SPDEVID was represented in the Device Identifiers (DI) domain.

lb.xpt

Row STUDYID DOMAIN USUBJID SPDEVID LBSEQ LBTESTCD LBTEST LBCAT LBSCAT LBORRES LBORRESU LBORNRLO LBORNRHI LBSTRESC LBSTRESN LBSTRESU LBSTNRLO LBSTNRHI LBSTNRC LBNRIND LBLOINC LBSPEC VISITNUM VISIT VISITDY LBDTC

1 CVD-12 LB CVD-123 ABG01 1 PH pH CHEMISTRY BLOOD GAS ANALYSIS

7.39 7.35 7.45 7.39 7.39 7.35 7.45 NORMAL 2744-1 ARTERIAL BLOOD

1 1 1 2020-03-07T08:30

2 CVD-12 LB CVD-123 ABG01 2 PCO2 Partial Pressure Carbon Dioxide

CHEMISTRY BLOOD GAS ANALYSIS

52 mmHg 35 45 52 52 mmHg 35 45 HIGH 2019-8 ARTERIAL BLOOD

1 1 1 2020-03-07T08:30

3 CVD-12 LB CVD-123 ABG01 3 PO2 Partial Pressure Oxygen


60 mmHg 80 100 60 60 mmHg 80 100 LOW 2703-7 ARTERIAL BLOOD

1 1 1 2020-03-07T08:30

4 CVD-12 LB CVD-123 ABG01 4 BICARB Bicarbonate CHEMISTRY BLOOD GAS ANALYSIS

30 mmol/L 22 26 30 30 mmol/L 22 26 HIGH 1960-4 ARTERIAL BLOOD

1 1 1 2020-03-07T08:30

5 CVD-12 LB CVD-123 ABG01 6 OXYSAT Oxygen Saturation


90 % 94 100 90 90 % 94 100 LOW 2708-6 ARTERIAL BLOOD

1 1 1 2020-03-07T08:30

6 CVD-12 LB CVD-123 ABG01 7 FIO2 Fraction of Inspired Oxygen


40 % 40 % ARTERIAL BLOOD

1 1 1 2020-03-07T08:30

The sponsor was interested in the details of the particular blood gas analyzer used for the blood gas analysis. In this example, the blood gas analyzer was identified using device type, manufacturer, and model.

di.xpt


1 ABC DI ABG01 1 DEVTYPE Device Type Blood Gas Analyzer

2 ABC DI ABG01 2 MANUF Manufacturer CheckURBreathing

3 ABC DI ABG01 4 MODEL Model PO277

https://www.cdisc.org/standards/foundational/sdtmig



The following table shows common lab test names and test codes.

LB Test Name - LBTEST LB Test Code - LBTESTCD

Activated partial thromboplastin time APTT

Alanine aminotransferase AST

Aspartate aminotransferase ALT

Bilirubin BILI

C reactive protein CRP

Creatinine CREAT

Glucose GLUC

Hemoglobin HGB

Hematocrit HCT

Lactic acid LACTICAC

Leukocytes WBC

Lymphocytes LYM

Neutrophils NEUT

Platelets PLAT

Potassium K

Procalcitonin PCT

Prothrombin time PT

Prothrombin international normalized ratio INR

Sodium SODIUM

Urea Nitrogen UREAN

Controlled terminology can be found in the Lab Test Name and Lab Test Code codelists at https://www.cdisc.org/standards/terminology. Sponsors may request new terms as needed. A link to applicable codelists is

included in the SDTMIG domain specification tables.

https://www.cdisc.org/standards/terminology



6 Diagnostics and Virology

6.1 Virus Identification

Identification of viruses from a collected sample is represented in the Microbiology Specimen (MB) domain.

Example 1

This example shows the results of tests to detect SARS-CoV-2, the virus that causes COVID-19, in 2 different subjects.

Row 1: Shows a subject who tested positive for SARS-CoV-2 by quantitative reverse transcriptase polymerase chain reaction (PCR) of an endotracheal fluid specimen.

Row 2: Shows a subject who tested negative for SARS-CoV-2 by quantitative reverse transcriptase PCR of a throat swab specimen.

mb.xpt

Row STUDYID DOMAIN USUBJID MBSEQ MBREFID MBGPRID MBTESTCD MBTEST MBTSTDTL MBORRES MBSTRESC MBSPEC MBLOC MBMETHOD VISITNUM VISIT MBDTC

1 ABC MB ABC-01-601

1 60101 1 SARSCOV2 Severe Acute Resp Syndrome Coronavirus 2

DETECTION POSITIVE POSITIVE ENDOTRACHEAL FLUID

QUANTITATIVE REVERSE TRANSCRIPTASE POLYMERASE CHAIN REACTION

1 SCREENING 2020-03-27T14:15

2 ABC MB ABC-01-722

2 72201 1 SARSCOV2 Severe Acute Resp Syndrome Coronavirus 2

DETECTION NEGATIVE NEGATIVE SWABBED MATERIAL

THROAT QUANTITATIVE REVERSE TRANSCRIPTASE POLYMERASE CHAIN REACTION

1 SCREENING 2011-04-01T10:00

6.2 Antibody Testing

Antibody testing provides a more rapid indication of current or past infection than testing for viral RNA by PCR-based methods.

Example 1

This example demonstrates the testing of immunoglobulin M (IgM) and immunoglobulin G (IgG) antibodies to the SARS-CoV-2 virus in subject serum samples. The example does not cover quantification of

antibodies. Such tests would be handled using the same MBTESTCD/MBTEST terminology, and with MBTSTDTL= QUANTIFICATION.

Rows 1-2: Show the screening of subject 011 for the separate detection of IgM and IgG antibodies to the SARS-CoV-2 virus, performed at the baseline visit. The subject tested positive for IgM and negative for

IgG.

Row 3: Shows the screening of subject 022 for the detection of IgG and/or IgM antibodies to the SARS-CoV-2 virus, performed at the baseline visit. The subject tested positive for this combined test, indicating

that the presence of 1 or both of these antibodies. This test does not differentiate between the presence of IgG and IgM; the presence of either will give a positive result.

mb.xpt

Row STUDYID DOMAIN USUBJID MBSEQ MBREFID MBTESTCD MBTEST MBTSTDTL MBORRES MBSTRESC MBSPEC MBMETHOD VISITNUM VISIT MBDTC

1 COVID-ABC MB COVID-ABC-011 1 13668 SAR2IGM SARS-CoV-2 IgM Antibody DETECTION POSITIVE POSITIVE SERUM ELISA 1 BASELINE 2020-04-27

2 COVID-ABC MB COVID-ABC-011 2 13668 SAR2IGG SARS-CoV-2 IgG Antibody DETECTION NEGATIVE NEGATIVE SERUM ELISA 1 BASELINE 2020-04-27

3 COVID-ABC MB COVID-ABC-022 1 23433 SAR2IGGM SARS-CoV-2 IgG/IgM Antibody DETECTION POSITIVE POSITIVE SERUM ELISA 1 BASELINE 2020-04-29



6.3 SARS-CoV-2 Viral Load

Quantification of viral shedding in SARS-CoV-2 infection is an evolving science. The following example uses data from a published source in the primary literature[4] as a starting point, where the results were

expressed in units of log 10 copies/ml. Units of copies/ml may also be used at the implementer's discretion.

Example 1

This example follows 1 subject through a series of viral load assessments over the course of a 10-day period.

The testing process took place in 2 parts: determination of threshold cycle and conversion of the threshold cycle readout to a viral load readout (i.e., copies/mL). The threshold cycle (Ct) represents the number of

cycles the PCR completed before the signal generated by amplification of viral RNA rose above the threshold set as a parameter of the experiment. In this example, records indicating the threshold cycle are grouped

with the preceding records of viral load using MBGRPID.

For the qRT-PCR assay illustrated in this example, conversion from the Ct readout to a viral load readout requires the use of a known concentration of reference standard sample of the target RNA to be run parallel

with the subject sample. It is important to note that in the case of emerging pathogens like SARS-CoV-2 such reference standards may not be available. In such cases only the Ct value will be available and a

quantitative viral load expressed as number of copies per unit volume will not be reported.

Rows 1-6: Show the subject's viral load expressed as log 10 copies/mL of SARS-CoV-2 RNA and the associated threshold cycle value over the course of days 3, 5, and 6.

Rows 7-9: Show the subject's viral load became undetectable at day 8, and remained undetectable on days 10 and 12. MBTSTDTL is not populated because there is nothing to quantify.

mb.xpt

Row STUDYID DOMAIN USUBJID SPDEVID MBSEQ MBGRPID MBREFID MBTESTCD MBTEST MBTSTDTL MBORRES MBORRESU MBSTRESC MBSTRESN MBSTRESU MBSPEC MBMETHOD MBLOBXFL VISITNUM VISIT MBDTC

1 ABC MB ABC-001 PCR01 1 1 001-02 SAR2RNA SARS-

CoV-2 RNA

VIRAL LOAD 3.9 log 10

copies/mL

3.9 3.9 log 10

copies/mL

SPUTUM QUANTITATIVE REVERSE

TRANSCRIPTASE POLYMERASE CHAIN REACTION

Y 3 DAY

3

2020-

03-19

2 ABC MB ABC-001 PCR01 2 1 001-02 SAR2RNA SARS-CoV-2 RNA

THRESHOLD CYCLE

27.43 27.43 27.43 SPUTUM QUANTITATIVE REVERSE TRANSCRIPTASE POLYMERASE CHAIN

REACTION

Y 3 DAY 3

2020-03-19


VIRAL LOAD 4.7 log 10 copies/mL

4.7 4.7 log 10 copies/mL

SPUTUM QUANTITATIVE REVERSE TRANSCRIPTASE POLYMERASE CHAIN REACTION

5 DAY 5

2020-03-21


THRESHOLD CYCLE

23.11 23.11 23.11 SPUTUM QUANTITATIVE REVERSE TRANSCRIPTASE POLYMERASE CHAIN REACTION

5 DAY 5

2020-03-21

5 ABC MB ABC-001 PCR02 5 3 001-04 SAR2RNA SARS-

CoV-2 RNA

VIRAL LOAD 4.5 log 10

copies/mL

4.5 4.5 log 10

copies/mL



6 DAY

6

2020-

03-22

6 ABC MB ABC-001 PCR02 6 3 001-04 SAR2RNA SARS-CoV-2

RNA

THRESHOLD CYCLE

23.22 23.22 23.22 SPUTUM QUANTITATIVE REVERSE TRANSCRIPTASE

POLYMERASE CHAIN REACTION

6 DAY 6

2020-03-22

7 ABC MB ABC-001 PCR02 7 001-05 SAR2RNA SARS-CoV-2 RNA

TARGET NOT DETECTED

TARGET NOT DETECTED

SPUTUM QUANTITATIVE REVERSE TRANSCRIPTASE

8 DAY 8

2020-03-24



Row STUDYID DOMAIN USUBJID SPDEVID MBSEQ MBGRPID MBREFID MBTESTCD MBTEST MBTSTDTL MBORRES MBORRESU MBSTRESC MBSTRESN MBSTRESU MBSPEC MBMETHOD MBLOBXFL VISITNUM VISIT MBDTC

POLYMERASE CHAIN REACTION

8 ABC MB ABC-001 PCR01 8 001-06 SAR2RNA SARS-CoV-2 RNA

TARGET NOT DETECTED

TARGET NOT DETECTED

SPUTUM QUANTITATIVE REVERSE TRANSCRIPTASE POLYMERASE CHAIN REACTION

10 DAY 10

2020-03-26

9 ABC MB ABC-001 PCR02 9 001-07 SAR2RNA SARS-

CoV-2 RNA

TARGET

NOT DETECTED

TARGET NOT

DETECTED



12 DAY

12

2020-

03-28

Properties of the assays used to determine viral load are represented in the Device domains. In this example, the lot numbers of the assays used changed, and the sponsor chose to keep track of this parameter. Had the

lot number not changed or were it not of interest, a single SPDEVID could have been used to link to a single set of parameters in the Device Identifiers (DI) dataset.

Rows 1-4: Show the device type, manufacturer, trade name, and lot number for the RT-qPCR kit identifed by SPDEVID="PCR01".

Rows 5-8: Show the device type, manufacturer, trade name, and lot number for the RT-qPCR kit identifed by SPDEVID="PCR02".

di.xpt


1 ABC DI PCR01 1 DEVTYPE Device Type RT-qPCR kit

2 ABC DI PCR01 2 MANUF Manufacturer Acme

3 ABC DI PCR01 3 TRADENAM Trade Name DetectPRO

4 ABC DI PCR01 4 LOTNUM Lot Number 20160202013

5 ABC DI PCR02 1 DEVTYPE Device Type RT-qPCR kit

6 ABC DI PCR02 2 MANUF Manufacturer Acme

7 ABC DI PCR02 3 TRADENAM Trade Name DetectPRO

8 ABC DI PCR02 4 LOTNUM Lot Number 20161101004



7 Vital Signs and Urine Output Example 1

The following example represents collection of baseline vital signs upon admission and summary daily assessments thereafter. The daily assessment shows abnormal values and rates them as "LOWEST" or

"HIGHEST" for each 24-hour period. The value of "HIGHEST" or "LOWEST" is dependent upon the range of normal limits and the direction of the abnormal values. The value is stored in the VSCOLSRT variable.

Rows 1-6: Show baseline vital signs upon admission (i.e., systolic and diastolic blood pressure, heart rate, respiratory rate, temperature, oxygen saturation). The non-standard variable VSN2SCAL reflects that the

"SpO2 Scale 1" from the National Early Warning Score 2 (NEWS2) Scale was the appropriate scale to be used in scoring this result in calculating the subject's NEWS2 total score.

Rows 7-13: Show the most abnormal vital signs for the 24-hour period of 2020-03-10, day 4 in this study. The subject was in prone position at the time of the measurement. The lowest blood pressure for the 24-

hour period occurred at 08:15; it was 70/36 with an MAP 47 mmHg. The highest temperature, highest heart rate, highest respiratory rate and lowest saturation also occurred at different times throughout

the 24-hour period. The LNKID variable is used to show the connection of LOWEST urine output that occurred at 0800.

vs.xpt Row STUDYID DOMAIN USUBJID VSSEQ VSLNKID VSTESTCD VSTEST VSCAT VSSCAT VSPOS VSORRES VSORRESU VSSTRESC VSSTRESN VSSTRESU VSLOC VSCSTATE VSBLFL VISITNUM VISIT VISITDY VSDTC VSDY VSEVLINT VSCOLSRT VSO2SRC VSN2SCAL

1 CVD-2 VS 200 1 SYSBP Systolic Blood Pressure

ADMISSION SITTING 120 mmHg 120 120 mmHg CONSCIOUS Y 1 1 1 2020-03-07T08:00

1

2 CVD-2 VS 200 2 DIABP Diastolic Blood

Pressure

ADMISSION SITTING 80 mmHg 80 80 mmHg CONSCIOUS Y 1 1 1 2020-03-

07T08:00

1

3 CVD-2 VS 200 3 HR Heart Rate ADMISSION SITTING 72 beats/min 72 72 beats/min CONSCIOUS Y 1 1 1 2020-03-07T08:00

1

4 CVD-2 VS 200 4 RESP Respiratory Rate ADMISSION SITTING 26 breaths/min 26 26 breaths/min CONSCIOUS Y 1 1 1 2020-03-07T08:00

1

5 CVD-2 VS 200 5 TEMP Temperature ADMISSION SITTING 41.0 C 41.0 41.0 C CONSCIOUS Y 1 1 1 2020-03-07T08:00

1

6 CVD-2 VS 200 6 OXYSAT Oxygen Saturation ADMISSION SITTING 93 % 93 93 % CONSCIOUS Y 1 1 1 2020-03-07T08:00

1 ROOM AIR SPO2 SCALE 1

7 CVD-2 VS 200 7 CPLRFLT Capillary Refill Time ADMISSION SITTING 1 sec 1 1 sec FINGERNAIL CONSCIOUS Y 1 1 1 2020-03-

07T08:00

1

8 CVD-2 VS 200 8 A SYSBP Systolic Blood Pressure

DAILY PRONE 70 mmHg 70 70 mmHg UNCONSCIOUS 4 4 4 2020-03-10T08:15

4 -PT24H LOWEST

9 CVD-2 VS 200 9 A DIABP Diastolic Blood Pressure


4 -PT24H LOWEST

10 CVD-2 VS 200 10 A MAP Mean Arterial Pressure


4 -PT24H LOWEST

11 CVD-2 VS 200 11 A HR Heart Rate DAILY PRONE 126 beats/min 126 126 beats/min UNCONSCIOUS 4 4 4 2020-03-10T22:18

4 -PT24H HIGHEST

12 CVD-2 VS 200 12 A RESP Respiratory Rate DAILY PRONE 28 breaths/min 28 28 breaths/min UNCONSCIOUS 4 4 4 2020-03-

10T17:00

4 -PT24H HIGHEST

13 CVD-2 VS 200 13 A TEMP Temperature DAILY PRONE 38.6 C 38.6 38.6 C UNCONSCIOUS 4 4 4 2020-03-10T05:14

4 -PT24H HIGHEST

14 CVD-2 VS 200 14 A OXYSAT Oxygen Saturation DAILY PRONE 88 % 88 88 % UNCONSCIOUS 4 4 4 2020-03-10T13:05

4 -PT24H LOWEST OXYGEN THERAPY

15 CVD-2 VS 200 15 A CPLRFLT Capillary Refill Time DAILY PRONE 4 sec 4 4 sec STERNUM UNCONSCIOUS 4 4 4 2020-03-07T21:00

4 -PT24H HIGHEST



VS NSV Metadata

Variable Label Type Role Codelist Origin

VSCOLSRT Collected Summary Result Type text Non-standard Record Qualifier CRF

VSO2SRC Oxygen Source text Non-standard Record Qualifier CRF

VSN2SCAL NEWS2 Oxygen Saturation Scale Used text Non-standard Record Qualifier SPO2 SCALE 1, SPO2 SCALE 2 CRF

The Laboratory Test Results (LB) domain was used to show the urine output.

Row 1: Shows the amount of urine collected for the 24-hour period for day 4 of the study (2020-03-10T11:59).

Row 2: Shows the lowest hourly urine output in the 24-hour period for day 4 of the study. LBCOLSRT was used to denote the urine output was the LOWEST in the 24-hour period.

lb.xpt

Row STUDYID DOMAIN USUBJID LBSEQ LBLNKID LBTESTCD LBTEST LBORRES LBORRESU LBORNRLO LBORNRHI LBSTRESC LBSTRESN LBSTRESU LBLOINC LBSPEC VISITNUM VISIT VISITDY LBDTC LBDY LBCOLSRT

1 CVD-2 LB 200 1 A FLUIDOUT Fluid Output

150 mL/day 150 150 mL/day 9192-6 URINE 1 1 4 2020-03-10T11:59

4

2 CVD-2 LB 200 2 A FLUIDOUT Fluid Output

10 mL/h 10 10 mL/h 9188-4 URINE 1 1 4 2020-03-10T08:00

4 LOWEST

LB NSV Metadata

Variable Label Type Role Codelist Origin

LBCOLSRT Collected Summary Result Type text Non-standard Record Qualifier CRF



8 Concomitant Medications Example 1

In COVID-19 studies, sponsors may be interested in collecting data on medication use, such as anti-malarial medications. This example shows data for subjects who were asked about their medication

use. CMEVLINT is used to indicate that only medications in the last 7 days were of interest.

Rows 1-2: Show the subject took an "ANTI-MALARIA MEDICATION" within 7 days before the study start.

Row 3: Shows the subject did not use an "ANTIVIRAL AGENT" within 7 days before the study start.

Rows 4-5: Show the subject took a "CORTICOSTEROID" within 7 days before the study start.

Row 6: Shows the subject did not take an "ANTIBIOTIC" within 7 days before the study start.

Row 7: Shows the subject did not use an "ANTIFUNGAL AGENT" within 7 days before the study start.

cm.xpt

Row STUDYID DOMAIN USUBJID CMSEQ CMTRT CMCAT CMPRESP CMOCCUR CMDOSE CMDOSU CMDOSFRQ CMROUTE CMDTC CMSTDTC CMENDTC CMSTRF CMEVLINT

1 CVD-18 CM 180 1 ANTI-MALARIA MEDICATION

ANTI-MALARIA MEDICATION

Y Y 2020-04-08

BEFORE -P7D

2 CVD-18 CM 180 2 HYDROXYCHLOROQUINE ANTI-MALARIA MEDICATION

400 mg QD ORAL 2020-04-02

2020-04-06

3 CVD-18 CM 180 3 ANTIVIRAL AGENT ANTIVIRAL AGENT Y N 2020-04-08

BEFORE -P7D

4 CVD-18 CM 180 4 CORTICOSTEROID CORTICOSTEROID Y Y 2020-04-08

BEFORE -P7D

5 CVD-18 CM 180 5 PREDNISONE CORTICOSTEROID 125 mg Q6H INTRAVENOUS 2020-04-07

2020-04-07

6 CVD-18 CM 180 6 ANTIBIOTIC ANTIBIOTIC Y N 2020-04-08

BEFORE -P7D

7 CVD-18 CM 180 7 ANTIFUNGAL AGENT ANTIFUNGAL AGENT Y N 2020-04-08

BEFORE -P7D



9 Respiratory Findings

9.1 Imaging

In some instances, imaging (chest radiographs, computed tomography (CT) scans) may be performed on suspected COVID-19 subjects for screening, diagnosis,

and management of the virus.[5]

Example 1

This example illustrates pre-specified procedures for chest x-rays and chest CT scans collected for 2 subjects in the Procedures (PR) domain. Findings from these

imaging procedures are represented in the Respiratory System Findings (RE) domain.

Rows 1-2: Show that pre-specified procedures for chest x-ray and chest CT scan were collected for the subject. The subject had a chest x-ray but not a CT

scan.

Rows 3-4: Show pre-specified procedures for chest x-ray and chest CT scan were collected for the subject. This subject had both a chest x-ray and a CT scan

of the chest performed.

pr.xpt

Row STUDYID DOMAIN USUBJID PRSEQ PRTRT PRPRESP PROCCUR PRLOC VISITNUM VISIT PRDTC PRSTDTC

1 COVID1901 PR COVID1901-01 1 X-RAY Y Y CHEST 5 DAY 5 2020-04-07 2020-04-07

2 COVID1901 PR COVID1901-01 2 CT SCAN Y N CHEST 5 DAY 5 2020-04-07

3 COVID1901 PR COVID1901-02 1 X-RAY Y Y CHEST 7 DAY 7 2020-04-09 2020-04-09

4 COVID1901 PR COVID1901-02 2 CT SCAN Y Y CHEST 7 DAY 7 2020-04-09 2020-04-09

As noted, these imaging findings are shown in the RE domain. In this study, the sponsor was interested in whether the findings were normal or abnormal, so a

test of "Interpretation" was used. The non-standard variable (NSV) RECLSIG was used to note whether the findings were clinically significant.

Row 1: Shows the chest x-ray was normal for subject COVID1901-01.

Row 2: Shows the chest x-ray performed on subject COVID1901-02 was not evaluable.

Row 3: Shows that subject COVID1901-02 had an abnormal chest CT, and the imaging reviewer deemed this to be a clinically significant finding (as

indicated in the NSV RECLSIG).

re.xpt

Row STUDYID DOMAIN USUBJID SPDEVID RESEQ RETESTCD RETEST REORRES RESTRESC RELOC REMETHOD VISITNUM VISIT REDTC RECLSIG

1 COVID1901 RE COVID1901-01

ABC006 1 INTP Interpretation Normal NORMAL LUNG X-RAY 5 DAY 5

2020-04-07

N


ABC010 1 INTP Interpretation Not evaluable

NOT EVALUABLE

LUNG X-RAY 7 DAY 7

2020-04-09


ABC010 2 INTP Interpretation Abnormal ABNORMAL LUNG CT SCAN 7 DAY 7

2020-04-09

Y



RE NSV Metadata

Variable Label Type Role Origin

RECLSIG Clinically Significant text Non-standard Result Qualifier CRF

Example 2

This example illustrates 2 pre-specified imaging findings (i.e., infiltrates, pneumonia) in the RE domain, collected for 1 subject on 2 different visits.

Rows 1-2: Show that there was no sign of pneumonia or infiltrates on day 3 by imaging.

Rows 3-4: Show that by day 7 the subject had developed signs of both pneumonia and infiltrates on imaging.

re.xpt

Row STUDYID DOMAIN USUBJID RESEQ RETESTCD RETEST REORRES RESTRESC RELOC REMETHOD VISITNUM VISIT REDTC

1 ABC001 RE ABC001-01 1 PNEUMIND Pneumonia Indicator N N CHEST X-RAY 2 DAY 3 2020-03-21

2 ABC001 RE ABC001-01 2 INFLTIND Infiltrates Indicator N N CHEST CT SCAN 2 DAY 3 2020-03-21

3 ABC001 RE ABC001-01 3 PNEUMIND Pneumonia Indicator Y Y CHEST X-RAY 3 DAY 7 2020-03-25

4 ABC001 RE ABC001-01 4 INFLTIND Infiltrates Indicator Y Y CHEST CT SCAN 3 DAY 7 2020-03-25

9.2 Pulmonary Function Tests

Pulmonary function tests will probably not be planned assessments for acute phases of COVID-19, but may be useful in studies to assess possible long-term

after-effects of infection. Pulmonary function tests are discussed in the Asthma Therapeutic Area User Guide (TAUG-Asthma;

https://www.cdisc.org/standards/therapeutic-areas/asthma) and the Chronic Obstructive Pulmonary Disease Therapeutic Area User Guide (TAUG-COPD;

https://www.cdisc.org/standards/therapeutic-areas/copd). Pulmonary function tests are represented in the RE domain; CDISC controlled terminology includes

codelists for multiple test names and codes.

https://www.cdisc.org/standards/therapeutic-areas/asthma

https://www.cdisc.org/standards/therapeutic-areas/copd



10 Cardiac Events/Findings The topic of electrocardiograms (EKGs) and measuring QT intervals may be of interest in some treatments currently

under study for COVID-19.[6] Drug-induced QT prolongation has long served as a surrogate indicator for increased

risk of drug-associated arrhythmia. However, the relationship between QT prolongation and risk of arrhythmia is

imperfect and complex.[7] Refer to the QT Studies Therapeutic Area User Guide

(https://www.cdisc.org/standards/therapeutic-areas/qt-studies) if this aspect is of interest for the study requirements.

https://www.cdisc.org/standards/therapeutic-areas/qt-studies



11 Hospitalization Information about hospitalization events is represented in the Healthcare Encounters (HO) domain.

Example 1

This example includes the HODECOD variable. An extensible codelist has been developed for HODECOD. The

indication for hospitalization and discharge outcome are shown in the NSVs INDC and DISOUT, respectively. The

NSV DISOUT uses the published DISCHDX codelist.

Row 1: Shows the subject was hospitalized due to COVID-19 and was discharged to self-care at home.

Row 2: Shows the subject was admitted to an intensive care unit due to COVID-19 and did not survive.

ho.xpt

Row STUDYID DOMAIN USUBJID HOSEQ HOTERM HODECOD HOSTDTC HOENDTC HOINDC HODISOUT

1 CVD-20 HO 200 1 HOSPITAL HOSPITAL STAY 2020-04-01

2020-04-08

COVID-19

HOME, SELF CARE

2 CVD-20 HO 201 1 INTENSIVE CARE UNIT

INTENSIVE CARE UNIT STAY

2020-04-02

2020-04-14

COVID-19

EXPIRED

HO NSV Metadata


HOINDC Indication text Non-standard Record Qualifier CRF

HODISOUT Discharge Outcome text DISCHDX Non-standard Record Qualifier CRF



12 Procedures Some COVID-19 patients may require assisted ventilation therapy (also known as mechanical ventilation therapy)

or renal treatment. These treatments—along with underlying comorbidities such as older age, hypertension, diabetes,

cardiovascular disease, chronic lung disease, and cancer—may play a role in the survival of patients with COVID-

19. Understanding the treatments used may provide insight into future treatment. In their 2020 article, Vincent and

Taccone[8] provided a decision tree for the possible paths to death and recovery in patients who require respiratory

support.

A focus of interest is the different types of assistance for oxygen therapy. Non-invasive ventilation (NIV) such as

continuous positive airway pressure (CPAP) and bilevel positive airway pressure (BIPAP) helps the patient breathe by taking in pressurized air through a mask attached to a small machine. The use of NIV treatments may reduce the

need for invasive treatments such as mechanical ventilation. As respiratory decompensation progresses, the patient

may require intubation, in which an endotracheal tube (ETT) is inserted through the mouth into the airway so the

patient can be placed on a ventilator to help with breathing. Some studies have shown that, for patients with severe

respiratory illness, prone positioning treatments while on mechanical ventilation when applied for at least 12 hours

daily is likely to reduce mortality.[9] Extracorporeal membrane oxygenation (ECMO) has been shown in some

studies of severe acute respiratory failure to rescue lung injury, improve oxygen levels, and reduce kidney

damage.[10] The ECMO machine pumps blood from the patient's body through tubes to an artificial lung, which

adds oxygen to it and removes carbon dioxide and then sends the blood back to the patient with the same force as

the heart. These treatments have been used for patients with COVID-19.[10]

12.1 Assisted Ventilation and Oxygen Treatments

Oxygen therapy treatments provide respiratory assistance and include invasive and non-invasive mechanical

ventilation. When required for the treatment of COVID-19, this is represented in the Procedures (PR) domain.

Example 1

The following example shows how to represent this information for a subject receiving these treatments in a

hospital. For this study, the sponsor was only interested in whether these procedures occurred during hospitalization

and the length of time a subject was on mechanical ventilation, not other treatments. If the start and end date of the

invasive mechanical ventilation was not available, the PRDUR variable would be used and could be populated with

count of DAYS (example not shown). This could be linked to the hospitalization record via RELREC (example not

shown). The Sponsor Device Identifier (SPDEVID) is used in the Procedures (PR) and Concomitant Medication

(CM) examples to link to the Device Identifiers (DI) dataset. MedDRA was used as the coding list for the

PRDECOD variable.

Row 1: Shows a pre-specified question asking whether the subject has received high-flow nasal cannula

oxygen therapy during hospitalization.

Rows 2-4: Show pre-specified questions asking whether the subject has received non-invasive mechanical

ventilation during hospitalization (includes oxygen therapy). If the answer is yes, the next 2 pre-

specified questions specify what types of non-invasive mechanical ventilation treatments were used:

CPAP ventilation and/or BIPAP ventilation.

Rows 5-6: Show pre-specified questions asking whether the subject has received invasive mechanical ventilation

during the hospitalization (includes oxygen therapy). If the answer is yes, the start and end date of the

mechanical ventilation is collected, and whether the subject received the treatment using "Prone"

positioning (a treatment called prone mechanical ventilation). The PRPOS variable for body position

was not used because the positioning is part of the treatment aim for prone mechanical ventilation.

Row 7: Shows a pre-specified question asking whether the subject has had a tracheostomy procedure during

hospitalization.

Row 8: Shows a pre-specified question asking whether the subject has received ECMO treatment during

hospitalization.



pr.xpt

Row STUDYID DOMAIN USUBJID SPDEVID PRSEQ PRTRT PRDECOD PRCAT PRPRESP PROCCUR PRSTDTC PRENDTC PREVINTX

1 CVD-12 PR 201 HFNC 1 High-flow Nasal Cannula Oxygen Therapy

HIGH-FLOW NASAL CANNULA OXYGEN THERAPY

Y Y DURING HOSPITALIZATION

2 CVD-12 PR 201 2 Non-Invasive Ventilation NON-INVASIVE MECHANICAL VENTILATION

NON-INVASIVE MECHANICAL VENTILATION


3 CVD-12 PR 201 CPAP 3 Continuous Positive Airway pressure

CONTINUOUS POSITIVE AIRWAY PRESSURE VENTILATION



4 CVD-12 PR 201 BIPAP 4 Bilevel Positive Airway Pressure

BILEVEL POSITIVE AIRWAY PRESSURE VENTILATION


Y N DURING HOSPITALIZATION

5 CVD-12 PR 201 VENTDV 5 Mechanical Ventilation MECHANICAL VENTILATION INVASIVE MECHANICAL VENTILATION

Y Y 2020-03-07T23:45

2020-03-12T09:15

DURING HOSPITALIZATION

6 CVD-12 PR 201 VENTDV 6 Prone Ventilation MECHANICAL VENTILATION INVASIVE MECHANICAL VENTILATION


7 CVD-12 PR 201 7 Tracheostomy TRACHEOSTOMY Y N DURING HOSPITALIZATION

8 CVD-12 PR 201 ECMODV 8 Extracoroporeal Membrane Oxygenation

EXTRACORPOREAL MEMBRANE OXYGENATION

LIFE SUPPORT/HEMODYNAMIC SUPPORT


Details for the 3 subjects who received oxygen therapy are shown in the following table. The device used to deliver the oxygen therapy is represented in the DI domain. SPDEVID was included because the sponsor

was interested in the device used for administering oxygen.

cm.xpt

Row STUDYID DOMAIN SPDEVID USUBJID CMSEQ CMTRT CMINDC CMDOSE CMDOSU CMDOSFRQ CMROUTE CMSTDTC CMENDTC

1 CVD-12 CM NC 201 1 OXYGEN THERAPY SHORTNESS OF BREATH 2 L/min CONTINUOUS RESPIRATORY (INHALATION) 2020-03-07T17:45 2020-03-07T18:45

2 CVD-12 CM MASK 201 2 OXYGEN THERAPY SHORTNESS OF BREATH 10 L/min CONTINUOUS RESPIRATORY (INHALATION) 2020-03-07T21:16 2020-03-07T22:30

3 CVD-12 CM HFOM 201 3 OXYGEN THERAPY SHORTNESS OF BREATH 12 L/min CONTINUOUS RESPIRATORY (INHALATION) 2020-03-07T22:31 2020-03-07T23:45

4 CVD-12 CM VENTDV 201 4 OXYGEN THERAPY HYPOXIA 100 % CONTINUOUS ENDOTRACHEAL 2020-03-07T23:45 2020-03-15T09:19

5 CVD-12 CM VENTDV 201 5 OXYGEN THERAPY HYPOXIA 50 % CONTINUOUS TRANSTRACHEAL 2020-03-15T09:20

6 CVD-12 CM MASK 202 1 OXYGEN THERAPY SHORTNESS OF BREATH 10 L/min CONTINUOUS RESPIRATORY (INHALATION) 2020-03-21T09:20 2020-03-24T17:20

7 CVD-12 CM HFOM 203 1 OXYGEN THERAPY SHORTNESS OF BREATH 10 L/min CONTINUOUS RESPIRATORY (INHALATION) 2020-03-22T09:20 2020-03-26T07:20

In this particular study, the sponsor was interested in the model for the non-invasive ventilation devices, the ventilator, and the ECMO device. The DI domain provides a mechanism for identifying devices that appear

in other domains.

di.xpt


1 CVD-12 DI NC 1 DEVTYPE Device Type NASAL CANNULA

2 CVD-12 DI HFNC 1 DEVTYPE Device Type HIGH FLOW NASAL CANNULA

3 CVD-12 DI HFNC 2 MODEL Model FLOWRITENC

4 CVD-12 DI FM 1 DEVTYPE Device Type OXYGEN DELIVERY FACE MASK

5 CVD-12 DI HFOM 1 DEVTYPE Device Type HIGH FLOW OXYGEN MASK DELIVERY SYSTEM




6 CVD-12 DI CPAP 1 DEVTYPE Device Type CPAP MACHINE

7 CVD-12 DI CPAP 2 MODEL Device Type BREATHWELL CPAP MACHINE

8 CVD-12 DI BIPAP 1 DEVTYPE Device Type BIPAP MACHINE

9 CVD-12 DI BIPAP 2 MODEL Device Type TWICETHEBREATH BIPAP MACHINE

10 CVD-12 DI VENTDV 1 DEVTYPE Device Type VENTILATOR MACHINE

11 CVD-12 DI VENTDV 2 MODEL Model WEHELPYOUBREATHE

12 CVD-12 DI ECMODV 1 DEVTYPE Device Type ECMO - EXTRACORPOREAL MEMBRANE OXYGENATION MACHINE

13 CVD-12 DI ECMODV 2 MODEL Model PERFUSEBETTER

12.2 Renal Treatment

Example 1

In this example, all subjects were asked whether they received renal treatment during hospitalization for COVID-19.

Row 1: Shows the subject underwent renal treatment during hospitalization, which was ongoing.

Row 2: Shows the subject did not undergo renal treatment during hospitalization.

pr.xpt

Row STUDYID DOMAIN USUBJID PRSEQ PRTRT PRPRESP PROCCUR PRDTC PRSTDTC PRENDTC PRENRTPT PREVINTX

1 CVD-12 PR 120 1 RENAL TREATMENT Y Y 2020-03-15 2020-03-15 ONGOING DURING HOSPITALIZATION

2 CVD-12 PR 121 1 RENAL TREATMENT Y N 2020-03-15 DURING HOSPITALIZATION



13 Vaccines The CDISC Vaccines Therapeutic Area User Guide (TAUG-Vax; https://www.cdisc.org/standards/therapeutic-

areas/vaccines/) was developed with FDA participation. The FDA technical specification Submitting Study Datasets

for Vaccines to the Office of Vaccines Research and Review[11] refers to the TAUG-Vaccines.

The TAUG-Vaccines includes a number of known issues. Some information which has become available since

publication is relevant in resolving some of those known issues and other points.

• One known issue discusses the appropriateness of the value "TREATMENT" in the epoch codelist for

vaccine studies. The definition of this term has been updated as suggested in the known issue to read, "A

period in a clinical study during which subjects receive investigational product." This means that

"TREATMENT" is an appropriate value in the EPOCH variable for vaccine studies.

• Some of the known issues refer to the supplemental qualifier --COLSRT (Collected Summary Result

Type). This variable is included as a standard variable in the drafts of the SDTM v2.0 and the SDTMIG

v3.4 developed for release in November 2020. This variable would still be represented as a supplemental

qualifier in submissions based on currently published versions of the standards, but can be used with

increased confidence because it is very likely to become a standard variable.

• One known issue is whether reactogenicity events that meet criteria for reporting as adverse events should

be reported in both the Clinical Events (CE) and Adverse Events (AE) domains. The FDA technical

specification[11] says (p. 3) that "if a reactogenicity event should happen to continue beyond the

assessment interval, it should also be represented in the AE domain," which seems to answer this question

for submissions to the FDA.

• One known issue discusses CESTDTC and CEENDTC in global Clinical Events (CE) reactogenicity

records; examples in the TAUG-Vaccines assume that these dates are collected. The FDA technical

specification (p. 2) says that "if an event occurred, the clinical event start day/date (CESTDY/CESTDTC)

and end day/date (CEENDY/CEENDTC) of the reactogenicity event should be collected and included in

the dataset."

• The TAUG-Vaccines discusses data collection approaches for reactogenicity data (i.e., flat model, nested

model, highly nested model). The FDA expresses a preference for the flat model in the technical

specification:[11]

We prefer that the Vaccine TAUG “flat model” be utilized, i.e., that data for each day be included,

even if a subject never experienced a particular event. However, the “nested model,” which

includes only a summary record for a particular event if a subject never experienced that event,

may be necessary for large trials with significant amounts of data. Sponsors should discuss which

model is appropriate with their review team prior to beginning their clinical trial. (p. 2)

• One of the known issues in the TAUG-Vaccines concerns cases where an investigator's assessment of

severity is different from a subject's. Although the known issue says there is no agreed-upon solution, there

are in fact solutions described within the SDTMIG, as illustrated in the following examples.

https://www.cdisc.org/standards/therapeutic-areas/vaccines/

https://www.cdisc.org/standards/therapeutic-areas/vaccines/



Example 1

In this example, symptom severity is assessed for events as a whole. In this record, severity is recorded as "MILD". The variable --EVAL is a findings domain variable so is not present in this events domain. All data

in an events record is assumed to be provided by the investigator.

ce.xpt

Row STUDYID DOMAIN USUBJID CESEQ CETERM CEDECOD CECAT CESCAT CEPRESP CEOCCUR CESTAT CEREASND CESEV CESTDTC CEENDTC CESTDY CEENDY

1 ABC123 CE 101 1 VOMITING Vomiting REACTOGENICITY SYSTEMIC Y Y MILD 2020-04-01 2020-04-02 1 2

The subject also provided an evaluation of severity of the event, and the investigator provided the reason why their evaluations of severity differed. Both of these items were recorded as supplemental qualifiers.

This example represents non-standard variables (NSVs) in a separate supplemental qualifiers domain since the QEVAL variable is needed.

Row 1: Shows the assessment of severity by the study subject.

Row 2: Shows the reason the investigator's assessment of severity differed from the study subject's.

suppce.xpt

Row STUDYID RDOMAIN USUBJID IDVAR IDVARVAL QNAM QLABEL QVAL QORIG QEVAL

1 ABC123 CE 101 CESEQ 1 CESEV1 Severity/Intensity 1 MODERATE CRF STUDY SUBJECT

2 ABC123 CE 101 CESEQ 1 CEDIFFRS Reason Investigator Changed Assessment Subject's verbal description was of mild vomiting. CRF INVESTIGATOR

Example 2

In the study in this example, subjects kept a diary assessing the severity of symptoms. The diary results were discussed with the investigator, who could agree or disagree with the subject's assessment of symptom

severity. Because these assessments were for time periods within the event rather than for the event as a whole, they were represented as findings about the event. In this example, assessments by the investigator and

the subject differed, so were represented in 2 different evaluators as 2 separate FA records.

Row 1: Shows the investigator's evaluation of vomiting severity. The NSV FADIFFRS was used for the reason the investigator's assessment was different from the subject's assessment.

Row 2: Shows the study subject's evaluation of vomiting severity.

face.xpt

Row STUDYID DOMAIN USUBJID FASEQ FATESTCD FATEST FAOBJ FACAT FASCAT FAORRES FASTRESC FASTAT FAREASND FABLFL FAEVAL FADTC FADY FADIFFRS

1 COVIDABC FA 101 1 SEV Severity/Intensity VOMITING REACTOGENICITY SYSTEMIC MILD MILD INVESTIGATOR 20200-04-01

1 Subject's verbal description was of mild vomiting

2 COVIDABC FA 101 2 SEV Severity/Intensity VOMITING REACTOGENICITY SYSTEMIC MODERATE MODERATE STUDY SUBJECT

20200-04-01

1

FACE NSV Metadata


FADIFFRS Reason Investigator Changed Assessment text Non-standard Record Qualifier CRF



14 Questionnaires, Ratings, and Scales Questionnaires, ratings, and scales (QRS) are maintained as stand-alone guides on the CDISC website

at https://www.cdisc.org/foundational/qrs. Supplements may or may not be finalized at the time of publication of

this interim user guide, and depend on copyright approval where applicable. CDISC cannot produce supplements for

copyrighted instruments without the express permission of the copyright holder.

New measurement tools are implemented on an ongoing basis by the CDISC QRS Terminology and Standards

Development subteams. The following table lists the instruments that are being pursued as potential supplements as

part of the development work for this interim user guide. Sponsors should refer to the the CDISC website

(https://www.cdisc.org/foundational/qrs) if an instrument of interest in COVID-19 research studies is not included, as it may have been developed for another therapeutic area. See CDISC COP 001

(at https://www.cdisc.org/about/bylaws) for details on implementing or requesting development of standards for

SDTM-based submissions.

Full Name and Abbreviation

Copyright Permission Status

Supplement Status

RSCAT RSTESTCD/RSTEST

National Early Warning Score 2 (NEWS2)

Granted Supplement in progress

NEWS2 NEWS109/NEWS1-NEWS Total (see supplement for additional RSTESTCD/RSTEST terminology)

Richmond Agitation-Sedation Scale (RASS)

To be requested RASS RASS0101/RASS01-Score

Riker Sedation-Agitation Scale (SAS)

To be requested SAS SAS0101/SAS01-Score

Some sponsors may calculate the scores for the individual items as well as the total score for the NEWS2 instrument

in ADaM. There are some items that may need to be collected and represented in SDTM.

The NEWS2 consciousness score can be represented in SDTM using RSTESTCD = "NEWS107"/RSTEST =

"NEWS1-Consciousness". The possible responses on the CRF include "Alert", "Confusion", "V", "P", or "U". After

consulting with subject matter experts and the NEWS2 phone application, it was determined that the most

meaningful data would be to represent these as "Alert", "New Confusion", "Verbal Responsive", "Pain Responsive",

or "Unresponsive". The mapping strategy is included in the following tables.

RSTESTCD RSTEST

NEWS107 NEWS1-Consciousness

RSORRES RSSTRESC RSSTRESN

Alert 0 0

New Confusion 3 3

Verbal Responsive

3 3

Pain Responsive

3 3

Unresponsive 3 3

Sponsors may also wish to collect information on the oxygen saturation scale used; see Vital Signs and Urine Output

for an example representing this information as an NSV in VS.

14.1 Clinical Global Impression and Sponsor-created

Instruments

The Clinical Global Impression (CGI)—sometimes also called the Clinical Global Assessment (CGA)—and the

Patient Global Impression (PGI) are scales used to assess the severity, change, or improvement of a disease

condition. CDISC supplements for both CGI and PGI are available at https://www.cdisc.org/foundational/qrs.

As with any standard instruments, the CGI and PGI should be used as intended and not adapted. Some sponsors'

disease-specific assessment instruments may be thought to apply to CGI or PGI concepts. However, when these

https://www.cdisc.org/foundational/qrs


https://www.cdisc.org/about/bylaws




require different item terminology or detailed disease-specific responses they may represent substantially different

scientific concepts than those in the CGI and PGI standard instruments.

For sponsor-developed scales, the best practice is to follow the guidance provided in the QRS Naming Rules

document (available at https://www.cdisc.org/foundational/qrs) for the values of --TESTCD, --TEST, and --CAT.




15 Appendices

Appendix A: Non-standard Variables (NSVs)

The following table lists the non-standard variables (NSVs) used in this document and provides their parent domain

and variable-level metadata.

Parent Domain

Variable Label SAS Data Type

XML Data Type

Codelist/Controlled Terms

Role

ER ERCNTRY Country Char text ISO 3166-1 alpha-3 Non-Standard Record Qualifier

ER ERREGION Geographical Region Char text ISO 3166-2 Non-Standard Record Qualifier

FA FADIFFRS Reason Investigator Changed Assessment

Char text Non-Standard Record Qualifier

FA RNGVALLO Range Value Low Num float Non-Standard Record Qualifier

FA RNGTXTLO Range Text Low Char text Non-Standard Record Qualifier

FA RNGVALHI Range Value High Num float Non-Standard Record Qualifier

FA RNGTXTHI Range Text High Char text Non-Standard Record Qualifier

HO HOINDC Indication Char text Non-Standard Record Qualifier

HO HODISOUT Discharge Outcome Char text DISCHDX Non-Standard Record Qualifier

LB LBCOLSRT Collected Summary Result Type


RE RECLSIG Clinically Significant Char text Non-Standard Record Qualifier

VS VSCOLSRT Collected Summary Result Type


VS VSN2SCAL NEWS2 Oxygen Saturation Scale Used

Char text SPO2 SCALE 1, SPO2 SCALE 2

Non-Standard Record Qualifier

VS VSO2SRC Oxygen Source Char text Non-Standard Record Qualifier



Appendix B: Glossary and Abbreviations

aCRF Annotated case report form

ADaM Analysis Data Model

ADaMIG ADaM Implementation Guide

BPAP Bilevel positive airway pressure

CDASH Clinical Data Acquisition Standards Harmonization Project

CDASHIG CDASH Implementation Guide

CDISC Clinical Data Interchange Standards Consortium

CGA Clinical Global Assessment (scale)

CGI Clinical Global Impression (scale)

Controlled Terminology A finite set of values that represent the only allowed values for a data item. These values may be codes, text, or numeric. A codelist is one type of controlled terminology.

CPAP Continuous positive airway pressure

CRF Case report form (sometimes called a case record form). A printed, optical, or electronic document designed to record all required information to be reported to the sponsor for each trial subject.

CSR Clinical study report

CT Computed tomography (scan)

Domain A collection of observations with a topic-specific commonality about a subject.

ECMO Extracorporeal membrane oxygenation

EDC Electronic data collection

EKG Electrocardiogram

ETT Endotracheal tube

FDA (US) Food & Drug Administration

FiO2 Fraction of inspired oxygen

Foundational Standards Used to refer to the suite of CDISC standards that describe the clinical study protocol (Protocol), design (Study Design), data collection (CDASH), laboratory work (Lab), analysis (ADaM), and data tabulation (SDTM and SEND). See http://www.cdisc.org/ for more information on each of these clinical data standards.

GI Gastrointestinal

HIV Human immunodeficiency virus

IgG Immunoglobulin G

IgM Immunoglobulin M

MedDRA Medical Dictionary for Regulatory Activities

MERS Middle East respiratory syndrome

NIH (US) National Institutes of Health

NIV Non-invasive ventilation

NSV Non-standard variable

Oxygen therapy Respiratory assistance treatments, including invasive and non-invasive mechanical ventilation

PCR Polymerase chain reaction

PGI Patient Global Impression (scale)

PPE Personal protective equipment

Prone mechanical ventilation

Mechanical ventilation using prone positioning; the positioning is a part of the treatment

QRS Questionnaires, ratings, and scales

RNA Ribonucleic acid

SARS Severe acute respiratory syndrome

http://www.cdisc.org/



SDTM Study Data Tabulation Model

SDTMIG SDTM Implementation Guide

Slice Data about an event that represents assessment at a period of time within an event

Snapshot Data about an event that represents assessment at a point in time

Subject A participant in a study

TAUG Therapeutic area user guide

VAS Visual analog scale(s)

WHO World Health Organization

Zoonotic transmission Transmission of a disease from infected animals to humans



Appendix C: References

1. Centers for Disease Control and Prevention. Coronavirus disease 2019 (COVID-19): people who are at higher

risk for severe illness. https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/people-at-higher-

risk.html. Accessed April 17, 2020.

2. Johns Hopkins Medicine. Coronavirus and COVID-19: who is at higher risk?

https://www.hopkinsmedicine.org/health/conditions-and-diseases/coronavirus/coronavirus-and-covid19-who-is-

at-higher-risk. Accessed April 17, 2020.

3. Centers for Disease Control and Prevention. Coronavirus disease 2019 (COVID-19): if you have animals.

https://www.cdc.gov/coronavirus/2019-ncov/daily-life-

coping/animals.html?CDC_AA_refVal=https%3A%2F%2Fwww.cdc.gov%2Fcoronavirus%2F2019-

ncov%2Fprepare%2Fanimals.html. Accessed April 7, 2020.

4. Pan X, Chen D, Xia Y, et al. Viral load of SARS-CoV-2 in clinical samples. Lancet, 2020;20(4):411-412.

doi:10.1016/ S1473-3099(20)30113-4

5. American College of Radiology. ACR recommendations for the use of chest radiography and computed

tomography (CT) for suspected COVID-19 infection. https://www.acr.org/Advocacy-and-Economics/ACR-

Position-Statements/Recommendations-for-Chest-Radiography-and-CT-for-Suspected-COVID19-Infection.

Accessed April 17, 2020.

6. Guatret P, Lagier J, Parola P, et al. Hydroxychloroquine and azithromycin as a treatment of COVID-19: results

of an open-label non-randomized clinical trial. Int J Antimicrob Agents. 2020.

doi:10.1016/j.ijantimicag.2020.105949. Published March 20, 2020. Accessed April 2, 2020.

7. Simpson TF, Kovacs RJ, Stecker EC. Ventricular arrhythmia risk due to hydroxychloroquine-azithromycin

treatment for COVID-19. Cardiology Magazine. https://www.acc.org/latest-in-

cardiology/articles/2020/03/27/14/00/ventricular-arrhythmia-risk-due-to-hydroxychloroquine-azithromycin-

treatment-for-covid-19. Published March 29, 2020. Accessed April 2, 2020.

8. Vincent JL, Taccone FS. Understanding pathways to death in patients with COVID-19. Lancent Respir Med.

2020. doi:10.1016/S2213-2600(20)30165-X. Published April 6, 2020. Accessed April 8, 2020.

9. Munshi L, Del Sorbo L, Adhikari NKJ, et al. Prone position for acute respiratory distress syndrome. A

systematic review and meta-analysis. Ann Am Thorac Soc. 2017;14(suppl 4):S280-S288.

doi:10.1513/AnnalsATS.201704-343OT

10. Phua J, Weng L, Ling L, et al. Intensive care management of coronavirus disease 2019 (COVID-19): challenges

and recommendations. Lancet Respir Med. 2020. doi:10.1016/S2213-2600(20)30161-2. Published April 6,

2020. Accessed April 8, 2020.

11. US Department of Health and Human Services, Food and Drug Administration. Submitting study datasets for

vaccines to the Office of Vaccine Research and Review. Guidance for industry. Technical specifications

document. https://www.fda.gov/media/112581/download. Revised December 2019. Accessed April 6, 2020.

https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/people-at-higher-risk.html

https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/people-at-higher-risk.html

https://www.hopkinsmedicine.org/health/conditions-and-diseases/coronavirus/coronavirus-and-covid19-who-is-at-higher-risk

https://www.hopkinsmedicine.org/health/conditions-and-diseases/coronavirus/coronavirus-and-covid19-who-is-at-higher-risk

https://www.cdc.gov/coronavirus/2019-ncov/daily-life-coping/animals.html?CDC_AA_refVal=https%3A%2F%2Fwww.cdc.gov%2Fcoronavirus%2F2019-ncov%2Fprepare%2Fanimals.html



https://doi.org/10.1016/S1473-3099(20)30113-4

https://www.acr.org/Advocacy-and-Economics/ACR-Position-Statements/Recommendations-for-Chest-Radiography-and-CT-for-Suspected-COVID19-Infection

https://www.acr.org/Advocacy-and-Economics/ACR-Position-Statements/Recommendations-for-Chest-Radiography-and-CT-for-Suspected-COVID19-Infection

https://doi.org/10.1016/j.ijantimicag.2020.105949

https://www.acc.org/latest-in-cardiology/articles/2020/03/27/14/00/ventricular-arrhythmia-risk-due-to-hydroxychloroquine-azithromycin-treatment-for-covid-19



https://doi.org/10.1016/S2213-2600(20)30165-X

https://doi.org/10.1513/AnnalsATS.201704-343OT

https://doi.org/10.1016/S2213-2600(20)30161-2

https://www.fda.gov/media/112581/download



Appendix D: Representations and Warranties, Limitations of

Liability, and Disclaimers

CDISC Patent Disclaimers

It is possible that implementation of and compliance with this standard may require use of subject matter covered by

patent rights. By publication of this standard, no position is taken with respect to the existence or validity of any

claim or of any patent rights in connection therewith. CDISC, including the CDISC Board of Directors, shall not be

responsible for identifying patent claims for which a license may be required in order to implement this standard or

for conducting inquiries into the legal validity or scope of those patents or patent claims that are brought to its

attention.

Representations and Warranties

“CDISC grants open public use of this User Guide (or Final Standards) under CDISC’s copyright.”

Each Participant in the development of this standard shall be deemed to represent, warrant, and covenant, at the time

of a Contribution by such Participant (or by its Representative), that to the best of its knowledge and ability: (a) it

holds or has the right to grant all relevant licenses to any of its Contributions in all jurisdictions or territories in

which it holds relevant intellectual property rights; (b) there are no limits to the Participant’s ability to make the

grants, acknowledgments, and agreements herein; and (c) the Contribution does not subject any Contribution, Draft

Standard, Final Standard, or implementations thereof, in whole or in part, to licensing obligations with additional

restrictions or requirements inconsistent with those set forth in this Policy, or that would require any such

Contribution, Final Standard, or implementation, in whole or in part, to be either: (i) disclosed or distributed in

source code form; (ii) licensed for the purpose of making derivative works (other than as set forth in Section 4.2 of

the CDISC Intellectual Property Policy (“the Policy”)); or (iii) distributed at no charge, except as set forth in

Sections 3, 5.1, and 4.2 of the Policy. If a Participant has knowledge that a Contribution made by any Participant or

any other party may subject any Contribution, Draft Standard, Final Standard, or implementation, in whole or in

part, to one or more of the licensing obligations listed in Section 9.3, such Participant shall give prompt notice of the

same to the CDISC President who shall promptly notify all Participants.

No Other Warranties/Disclaimers. ALL PARTICIPANTS ACKNOWLEDGE THAT, EXCEPT AS PROVIDED

UNDER SECTION 9.3 OF THE CDISC INTELLECTUAL PROPERTY POLICY, ALL DRAFT STANDARDS

AND FINAL STANDARDS, AND ALL CONTRIBUTIONS TO FINAL STANDARDS AND DRAFT

STANDARDS, ARE PROVIDED “AS IS” WITH NO WARRANTIES WHATSOEVER, WHETHER EXPRESS,

IMPLIED, STATUTORY, OR OTHERWISE, AND THE PARTICIPANTS, REPRESENTATIVES, THE CDISC

PRESIDENT, THE CDISC BOARD OF DIRECTORS, AND CDISC EXPRESSLY DISCLAIM ANY

WARRANTY OF MERCHANTABILITY, NONINFRINGEMENT, FITNESS FOR ANY PARTICULAR OR

INTENDED PURPOSE, OR ANY OTHER WARRANTY OTHERWISE ARISING OUT OF ANY PROPOSAL,

FINAL STANDARDS OR DRAFT STANDARDS, OR CONTRIBUTION.

Limitation of Liability

IN NO EVENT WILL CDISC OR ANY OF ITS CONSTITUENT PARTS (INCLUDING, BUT NOT LIMITED

TO, THE CDISC BOARD OF DIRECTORS, THE CDISC PRESIDENT, CDISC STAFF, AND CDISC

MEMBERS) BE LIABLE TO ANY OTHER PERSON OR ENTITY FOR ANY LOSS OF PROFITS, LOSS OF

USE, DIRECT, INDIRECT, INCIDENTAL, CONSEQUENTIAL, OR SPECIAL DAMAGES, WHETHER

UNDER CONTRACT, TORT, WARRANTY, OR OTHERWISE, ARISING IN ANY WAY OUT OF THIS

POLICY OR ANY RELATED AGREEMENT, WHETHER OR NOT SUCH PARTY HAD ADVANCE NOTICE

OF THE POSSIBILITY OF SUCH DAMAGES.

Note: The CDISC Intellectual Property Policy can be found at:

http://www.cdisc.org/system/files/all/article/application/pdf/cdisc_20ip_20policy_final.pdf.

http://www.cdisc.org/system/files/all/article/application/pdf/cdisc_20ip_20policy_final.pdf

Documents

Interim User Guide for COVID-19 - balramchauhan