Submitting Patient-
Reported Outcome Data in 
Cancer Clinical Trials 
 
Guidance for Industry 
Technical Specifications Document 
 
 
 
For questions regarding this technical specifications document, contact 
CDER at cder-edata@fda.hhs.gov. 
 
 
 
 
 
 
 
 
 
U.S. Department of Health and Human Services 
Food and Drug Administration 
Center for Drug Evaluation and Research (CDER) 
Oncology Center of Excellence (OCE) 
 
 
November 2023 
Technical Specifications Document 
   
Revision History 
 
Date  Version  Summary of Revisions 
November 2023  1.0  Initial Version 
     
     
     
 
 
  Contains Nonbinding Recommendations 
TABLE OF CONTENTS 
 
 
1.0  Introduction ........................................................................................................................ 1 
1.1.  Purpose ............................................................................................................................ 1 
1.2.  Scope ................................................................................................................................ 2 
1.3.  Relationship to Other Documents ................................................................................. 2 
2.0  Relevant Acronyms ............................................................................................................ 3 
3.0  Overview of Dataset Specifications .................................................................................. 4 
3.1  SDTM Specifications ...................................................................................................... 4 
3.1.1  Questionnaires Dataset ........................................................................................... 4 
3.1.2  Trial Summary Dataset .......................................................................................... 7 
3.2  ADaM Specifications ...................................................................................................... 8 
3.2.1  General Considerations .......................................................................................... 8 
3.2.2  Handling of Missing PRO Data and Intercurrent Events ................................. 11 
3.2.3  ADQS Dataset Structure ...................................................................................... 13 
4.0  Specifications for Tables and Figures ............................................................................ 16 
4.1  Patient Disposition........................................................................................................ 16 
4.1.1  Clinical Benefit ...................................................................................................... 16 
4.1.2  Safety and Tolerability ......................................................................................... 17 
4.2  PRO Data Completeness .............................................................................................. 18 
4.2.1  Available Data Rate (Clinical Benefit) ................................................................ 18 
4.2.2  Completion Rate (Safety and Tolerability)......................................................... 18 
4.3  Distributions ................................................................................................................. 19 
4.3.1  Distribution of Responses ..................................................................................... 20 
4.3.2  Distribution of Change in Responses from Baseline .......................................... 20 
4.4  Incidence of Healthcare Utilization ............................................................................ 21 
5.0  Appendix ........................................................................................................................... 22 
5.1  Example SDTM Questionnaires Dataset.................................................................... 22 
5.2  Example ADaM Questionnaires Analysis Dataset .................................................... 24 
5.3  Example Tables and Figures ....................................................................................... 27 
5.3.1  Patient Disposition when Evaluating Clinical Benefit ....................................... 27 
5.3.2  Patient Disposition when Informing Safety and Tolerability ........................... 29 
5.3.3  Available Data Rate for Clinical Benefit ............................................................ 31 
5.3.4  Completion Rate for Safety and Tolerability ..................................................... 33 
5.3.5  Distribution of Responses ..................................................................................... 35 
5.3.6  Distribution of Change in Responses from Baseline .......................................... 39 
5.3.7  Incidence of Healthcare Utilization ..................................................................... 43 
 
 
 
 
 
 
 
 
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TABLE OF TABLES 
 
Table 1. Specifications for a Subset of QS Variables ................................................................. 5 
Table 2. Recommended QS Representation of Missing PRO Data .......................................... 6 
Table A1. Example Schedule of Assessments ........................................................................... 22 
Table A2. Subset of Sample QS Dataset ................................................................................... 23 
Table A3. (Part 1) Subset of Sample ADQS Dataset ............................................................... 25 
Table A4. Patient Disposition when Evaluating Clinical Benefit (Denominator = 
Randomized Population) ............................................................................................................ 27 
 Figure A1. Patient Disposition when Evaluating Clinical Benefit (Denominator = 
Randomized Population) ............................................................................................................ 28 
Table A5. Patient Disposition when Informing the Evaluation of Safety and Tolerability 
(Denominator = Safety Population) ........................................................................................... 29 
 Table A6. Available Data Rate for Clinical Benefit (Denominator = Randomized 
Population)................................................................................................................................... 31 
Table A7. Completion Rate for Safety and Tolerability (Denominator = PRO Expected 
Population)................................................................................................................................... 33 
Table A8. Distribution of Categorical Responses for Item 1 (Safety and Tolerability 
Example) ...................................................................................................................................... 35 
Table A9. Summary Statistics for Item 2 with Continuous Response Options (Safety and 
Tolerability Example) ................................................................................................................. 37 
Table A10. Distribution of Change in Response Categories from Baseline for Item 1 (Safety 
and Tolerability Example) ......................................................................................................... 39 
Table A11. Change from Baseline for Item 2 with Continuous Response Options (Safety 
and Tolerability Example) ......................................................................................................... 41 
Table A12. Incidence of Healthcare Utilization (Safety and Tolerability Example where 
Denominator = PRO Expected) ................................................................................................. 43 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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TABLE OF FIGURES 
 
Figure A1. Patient Disposition when Evaluating Clinical Benefit (Denominator = 
Randomized Population) ............................................................................................................ 28 
Figure A2. Patient Disposition when Informing the Evaluation of Safety and Tolerability 
(Denominator = Safety Population) ........................................................................................... 30 
Figure A3. Available Data Rate for Clinical Benefit (Denominator = Randomized 
Population)................................................................................................................................... 32 
Figure A4. Completion Rate for Safety and Tolerability (Denominator = PRO Expected 
Population)................................................................................................................................... 34 
Figure A5. Distribution of Categorical Responses for Item 1 (Safety and Tolerability 
Example where Denominator = PRO Completed) ................................................................... 36 
Figure A6. Descriptive Means for Item 2 with Continuous Response Options (Safety and 
Tolerability Example for Physical Functioning)  ..................................................................... 38 
Figure A7. Distribution of Change in Response Categories from Baseline for Item 1 (Safety 
and Tolerability Example where Denominator = PRO Completed) ...................................... 40 
Figure A8. Change from Baseline for Item 2 with Continuous Response Options (Safety 
and Tolerability Example)  ........................................................................................................ 42 
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Submitting Patient-Reported Outcome Data  
in Cancer Clinical Trials 
 
Guidance for Industry 
Technical Specifications Document1
 
 
This guidance represents the current thinking of the Food and Drug Administration (FDA or Agency) on 
this topic. It does not establish any rights for any person and is not binding on FDA or the public. You  
can use an alternative approach if it satisfies the requirements of the applicable statutes and regulations. 
To discuss an alternative approach, contact the FDA office responsible for this guidance as listed on the 
title page.  
 
 
 
 
1.0  INTRODUCTION 
 
1.1.  Purpose 
 
This document provides technical specifications for submitting patient-reported outcome (PRO) 
data collected in cancer clinical trials to support a marketing application for a medical product in 
oncology, where a PRO is a type of clinical outcome assessment (COA) used to collect patient 
experience data.2 The FDA Patient-Focused Drug Development (PFDD) Glossary defines a PRO 
as a measurement based on a report that comes directly from the patient (i.e., study subject) 
about the status of a patient's health condition without interpretation of the patients response by 
a clinician or anyone else, where a PRO can be measured by self-report or by interview, provided 
that the interviewer records only the patients response.3 This technical specifications document 
supplements FDAs draft guidance for industry Core Patient-Reported Outcomes in Cancer 
Clinical Trials (June 2021)4 and the PFDD Guidance series.5 
 
 
 
1 This guidance has been prepared by the Office of Biostatistics in the Center for Drug Evaluation and Research at 
the Food and Drug Administration. You may submit comments on this guidance at any time. Submit comments to 
Docket No. FDA-2018-D-1216 (available at https://www.regulations.gov/docket?D=FDA-2018-D-1216) (see the 
instructions for submitting comments in the docket). 
2 21st Century Cures Act section 3001. More information on patient experience data within section 3001 is available 
at: https://www.congress.gov/114/plaws/publ255/PLAW-114publ255.pdf. 
3 More information is available at FDAs PFDD Glossary web page: https://www.fda.gov/drugs/development-
approval-process-drugs/patient-focused-drug-development-glossary and at the FDA-NIH BEST web page: 
https://www.ncbi.nlm.nih.gov/books/NBK338448/def-item/glossary.patientreported-outcome/.  
4 When final, this guidance will represent the FDAs current thinking on this topic. For the most recent version of a 
guidance, check the FDA guidance web page at https://www.fda.gov/RegulatoryInformation/Guidances/default.htm.  
5 More information is available at FDAs PFDD Guidance web page: https://www.fda.gov/drugs/development-
approval-process-drugs/fda-patient-focused-drug-development-guidance-series-enhancing-incorporation-patients-
voice-medical. 
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1.2.  Scope 
 
This document provides specifications for the submission of Clinical Data Interchange Standards 
Consortium (CDISC) Study Data Tabulation Model (SDTM) and Analysis Data Model (ADaM) 
datasets and specifications for recommended tables and figures. These technical specifications 
aim to provide general guidelines for (1) standardized dataset content and structure and (2) 
recommended tables and figures to facilitate FDA review of the marketing application that the 
submitted data and analysis outputs are intended to support. The SDTM and ADaM 
specifications outlined in section 3.0 Overview of Dataset Specifications are not prescriptive and 
do not include an exhaustive list of all datasets, variables, and controlled terminologies to be 
submitted for FDA review. Further, the recommended tables and figures do not comprise all 
information needed to support FDA review of a marketing application. The dataset specifications 
and specifications for tables and figures are pursuant to discussions with FDA and may vary by 
clinical drug development program and clinical trial therein. These specifications are intended to 
be applicable to any PRO data used to inform the evaluation of (1) safety and tolerability or (2) 
clinical benefit in randomized studies (i.e., improvement in disease symptoms) within a cancer 
clinical trial. 
 
This document does not pertain to submissions needed to support FDA review of the PRO 
measure itself or the proposed interpretation and use of scores generated by the PRO measure 
within the context of a specific clinical trial. Agreement on the PRO measure(s) used to collect 
study data and analyses of the resulting PRO data should be discussed with FDA as early as 
possible in a medical product development program, for example, prior to trial initiation. 
Sponsors are strongly encouraged to use the resources described in section 1.3 Relationships to 
Other Documents and to seek Agency input for confirmation and clarification as needed. 
Sponsors should consult with the Agency to determine which requested displays defined in 
section 4.0 Specifications for Tables and Figures apply to the PRO measure used within the 
marketing application. Lastly, although this guidance focuses on PRO measures, some of these 
recommendations may be relevant to other COAs (i.e., clinician-reported, observer-reported, and 
performance outcome measures) in cancer clinical trials.  
 
1.3.  Relationship to Other Documents  
 
These technical specifications have been drafted in accordance with the business rules and 
assumptions outlined in the CDISC SDTM,6 the SDTM Implementation Guide (SDTMIG),7 the 
ADaM8, and the ADaM Implementation Guide (ADaMIG). As new versions of the models and 
implementation guides become available, these technical specifications may be updated 
accordingly to maintain alignment. In addition, the FDA Study Data Technical Conformance 
Guide (sdTCG)9 provides general specifications and recommendations for submitting datasets 
 
6 More information is available at CDISCs SDTM web page: https://cdisc.org/standards/foundational/sdtm. 
7 More information is available at CDISCs SDTMIG web page: https://cdisc.org/standards/foundational/sdtmig. 
8 More information is available at CDISCs ADaM web page: https://cdisc.org/standards/foundational/adam. 
9 More information is available at FDAs Study Data Standards Resources web page: 
https://www.fda.gov/industry/fda-resources-data-standards/study-data-standards-resources. 
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using the SDTM and ADaM standards. Sponsors should review the FDA Data Standards 
Catalog10 to ensure data submissions follow FDA-supported standards. 
 
In addition, sponsors should reference the following:  
 
  Draft guidance for industry Core Patient-Reported Outcomes in Cancer Clinical Trials (June 
2021)11 
 
  FDA PFDD Guidance series12 
 
  Guidance for industry E9(R1) Statistical Principles for Clinical Trials Addendum: Estimands 
and Sensitivity Analysis in Clinical Trials (May 2021) 
 
  CDISC Controlled Terminology13 
 
  CDISC Questionnaires, Ratings and Scales (QRS) Supplements and CDISC QRS Resources, 
which includes QRS Naming and Business Rules14  
 
 
2.0  RELEVANT ACRONYMS 
 
Abbreviation  Description 
ADaM  Analysis Data Model 
ADaMIG  Analysis Data Model Implementation Guide 
ADRG  Analysis Data Reviewers Guide 
AE  Adverse Event 
BEST  Biomarkers, EndpointS, and other Tools 
BDS  Basic Data Structure 
CAT  Computerized Adaptive Testing 
CDISC  Clinical Data Interchange Standards Consortium 
CDER  Center for Drug Evaluation and Research 
COA  Clinical Outcome Assessment 
CRF  Case Report Form 
cSDRG  Clinical Study Data Reviewers Guide 
CSR  Clinical Study Report 
FDA  Food and Drug Administration 
INV  Investigator 
IRC  Independent Review Committee 
NCI EVS  National Cancer Institute Enterprise Vocabulary Services 
NIH  National Institutes of Health 
 
10 More information is available at FDAs Study Data Standards Resources web page: 
https://www.fda.gov/industry/fda-resources-data-standards/study-data-standards-resources. 
11 When final, this guidance will represent the FDAs current thinking on this topic. 
12 More information is available at FDAs PFDD Guidance series web page: 
https://www.fda.gov/drugs/development-approval-process-drugs/fda-patient-focused-drug-development-guidance-
series-enhancing-incorporation-patients-voice-medical. 
13 More information is available at NCIs web page: https://datascience.cancer.gov/resources/cancer-
vocabulary/cdisc-terminology. 
14 More information is available at CDISCs QRS web page: https://cdisc.org/standards/foundational/qrs. 
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Abbreviation  Description 
PFDD  Patient-Focused Drug Development 
PRO  Patient-Reported Outcome 
QRS  Questionnaires, Ratings and Scales 
SAP  Statistical Analysis Plan 
sdTCG  Study Data Technical Conformance Guide 
SDTM  Study Data Tabulation Model 
SDTMIG  Study Data Tabulation Model Implementation Guide 
Setting International Standards in Analyzing Patient-Reported Outcomes and Quality of Life 
SISAQOL 
Endpoints 
 
     
3.0  OVERVIEW OF DATASET SPECIFICATIONS 
 
Dataset specifications detail the CDISC datasets that are used to support PRO data tabulation and 
analyses in cancer clinical trials. Sponsors should implement the CDISC SDTM standard when 
submitting clinical tabulation data and the CDISC ADaM standard when submitting analysis 
data. This section supplements existing guidance by providing specifications for submitting PRO 
data collected in cancer clinical trials but does not cover all data to be submitted for a clinical 
trial. As documented in the FDA sdTCG,15 both SDTM and ADaM datasets should be 
accompanied by informative metadata provided in a compliant data definition file (i.e., Define-
XML) and are expected to be accompanied by a Clinical Study Data Reviewers Guide (cSDRG) 
and an Analysis Data Reviewers Guide (ADRG), respectively. Standard CDISC Controlled 
Terminology16 developed and maintained by CDISC, and National Cancer Institute Enterprise 
Vocabulary Services (NCI EVS) should be used where applicable, and codelists may be 
extensible by adding controlled terminology that is not previously defined. Sponsor-extended 
codelists and use of alternate (e.g., non-CDISC or sponsor-defined) terminologies should be 
indicated in the study metadata (e.g., Define-XML file, cSDRG). In addition, software programs 
used to create ADaM datasets and analyze PRO data should be submitted with the marketing 
application for FDA review.  
 
3.1  SDTM Specifications   
 
This section details the SDTM specifications for (1) PRO data submitted within the 
Questionnaires (QS) dataset and (2) the Trial Summary (TS) dataset.  
 
3.1.1  Questionnaires Dataset 
 
PRO data should be tabulated using the SDTM QS domain specifications. For select measures, 
CDISC publishes QRS Supplements17 that provide guidance on representing named COA 
measures in the SDTM. CDISC also provides submission values within the controlled 
terminology related to named COA measures. These resources should be consulted for guidance 
on a PRO measure, in addition to the guidance provided in the SDTM and SDTMIG. 
 
15 More information is available at FDAs Study Data Standards Resources web page: 
https://www.fda.gov/industry/fda-resources-data-standards/study-data-standards-resources. 
16 More information is available at NCIs web page: https://datascience.cancer.gov/resources/cancer-
vocabulary/cdisc-terminology. 
17 More information is available at CDISCs QRS web page: https://cdisc.org/standards/foundational/qrs. 
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3.1.1.1 General Considerations 
 
The QS dataset tabulates the PRO data as collected for individual patients at distinct assessment 
timepoints. The subset of standard QS variables in Table 1 is included to clarify how variables 
should be completed for PRO measures used in oncology studies to foster consistency and 
standardization across industry. An example QS dataset is provided in Appendix 5.1. 
 
Table 1. Specifications for a Subset of QS Variables 
Variable  Variable 
Type  Comments 
Name  Label 
QSCAT  Category of  Char  The measure name and version number should be provided within 
Question  QSCAT. Controlled Terminology should be implemented if 
applicable; if not, QSCAT should be constructed according to CDISC 
QRS Naming and Business Rules. The most common name that the 
measure is known by should be used, which can either be the 
complete name of the measure or an acronym. 
QSTESTCD  Question  Char  A topic variable for QS and short name for the value in QSTEST. 
Short Name  Controlled Terminology should be implemented if applicable; if not, 
construct according to CDISC QRS Naming and Business Rules. 
QSTESTCD should begin with a short code for the PRO measure 
followed by the item number (e.g., ABC01). In the case where item 
numbers are absent, sequential numbers starting with 01 should be 
used and can be shortened to 1 to accommodate the eight-character 
limit for values of QSTESTCD. 
QSTEST  Question  Char  This is the name of the item or, if applicable, the source data 
Name  summary score18 used to obtain the measurement or finding. QSTEST 
should start with a short code for the measure followed by a hyphen 
and a brief description. Controlled Terminology should be 
implemented if applicable; if not, construct according to CDISC QRS 
Naming and Business Rules. If QSTEST is > 40 characters in length, 
put meaningful text in QSTEST and describe the full-text in the study 
metadata (e.g., the annotated Case Report Form (CRF), the cSDRG, 
or the Define-XML). 
 
For each patient and assessment timepoint where the PRO measure is 
planned to be administered per the protocol-defined schedule of 
assessments, a record should be provided for each item or source data 
summary score within the measure, including records for measures 
not administered to the patient (See section 3.1.1.2 Handling of 
Missing PRO Data and section 3.1.1.3 Handling of PRO Data Not 
Collected due to Skip Logic or Computerized Adaptive Testing). 
QSSTAT  Completion  Char  This is populated as NOT DONE when an item score (response) or 
Status  source data summary score is empty/null. QSSTAT is empty/null if a 
value exists in QSORRES. 
QSREASND  Reason Not  Char  This is used in conjunction with QSSTAT when QSSTAT = NOT 
Performed  DONE to describe why an item score or source data summary score 
is empty/null (See section 3.1.1.2 Handling of Missing PRO Data and 
section 3.1.1.3 Handling of PRO Data Not Collected due to Skip 
Logic or Computerized Adaptive Testing). 
 
18 Source data summary scores are summary scores (e.g., total scores, subscale scores) that are source data (e.g., 
data reported within a CRF) and are submitted in the QS dataset. 
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Additional Considerations: 
 
Additional source data captured should be submitted either as additional rows with relevant 
QSTEST and QSTESTCD values within the QS dataset or within a Supplemental Questionnaires 
(SUPPQS) dataset. Additional content is dependent on the PRO measure administered, and if 
needed for analysis, should be copied into the applicable ADaM dataset. Example content 
captured within SUPPQS for each patient and assessment timepoint includes: 
 
  Data Collection Mode: The mode of data collection used in the administration of the PRO 
measure, if differing from the protocol and/or varying across patients, assessment timepoints, 
or sites (e.g., clinical trial site, home). Examples of data collection mode may include paper-
based administration, handheld electronic device, computer web-based application, or 
telephone-based administration. 
 
  Data Collector: In cases where the measure is not self-administered (i.e., not independently 
completed by the patient without any assistance), the individual administering the PRO 
measure to the patient (e.g., caregiver, study staff member) by reading items to the patient 
and/or recording the patients responses. 
 
  Language: The language in which the measure was administered to the patient. 
 
3.1.1.2 Handling of Missing PRO Data 
 
Understanding the reasons for and prevalence of missing PRO data are critical to support FDA 
review and regulatory decision-making. Missing PRO data should be represented within the QS 
dataset with the reason for missingness captured under Reason Not Performed (QSREASND). 
The QS dataset should include one record per item per PRO measure per patient per assessment 
timepoint, regardless of whether an item response is missing. When applicable, the QS dataset 
should also include one row per source data summary score per PRO measure per patient per 
assessment timepoint, regardless of whether the source data summary score is missing. Table 2 
provides scenario-specific recommendations for displaying PRO data that are missing at a 
planned (i.e., per protocol) assessment timepoint. Appendix 5.1 demonstrates scenarios for 
representing missing data within the QS dataset. CDISC QRS Supplements19 provide additional 
guidance on modeling missing data for named COA measures in SDTM datasets, including the 
modeling of timing variables. 
 
Table 2. Recommended QS Representation of Missing PRO Data 
Scenario  Recommended Representation in QS Dataset 
The patient did not respond to an  The row for the missing item response should include: 
item administered within a PRO   QSSTAT = NOT DONE 
measure.   QSREASND contains the reason the patient did not respond if 
known/collected. Otherwise, QSREASND is empty/null. 
A source data summary score cannot  The row for the missing source data summary score should include: 
be calculated per the scoring   QSSTAT = NOT DONE  
algorithm based on the available item 
 
19 More information is available at CDISCs QRS web page: https://cdisc.org/standards/foundational/qrs. 
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Scenario  Recommended Representation in QS Dataset 
responses (e.g., due to insufficient   QSREASND is populated if known/collected (e.g., QSREASND = 
item response data).  NOT CALCULABLE). Otherwise, QSREASND is empty/null. 
 
 
 
The patient was not administered the  The row for each missing item response and source data summary score 
PRO measure either at an onsite visit  within the measure should include: 
attended by the patient or at a   QSSTAT = NOT DONE 
planned (per protocol) offsite PRO   QSREASND contains the reason the measure was not administered if 
assessment timepoint.  known/collected. Examples include, but are not limited to, patient was 
physically unable to complete the PRO measure due to adverse event, 
patient refusal, patient did not provide, study site failed to administer or 
other site staff error, or technological problems with a PRO 
administered electronically. 
The patient did not attend an onsite  The row for each missing item response and source data summary score 
visit and the PRO measure is only  within the measure should include: 
administered onsite.   QSSTAT = NOT DONE 
 QSREASND contains the reason the patient did not attend the visit if 
known/collected. Examples include, but are not limited to, patient was 
unable to attend a scheduled trial visit due to hospitalization. 
 
3.1.1.3 Handling of PRO Data Not Collected due to Use of Skip Logic or 
Computerized Adaptive Testing 
 
Separate from missing data, PRO data may not be collected from the patient due to the use of 
skip logic or computerized adaptive testing to administer PRO items. When implemented, skip 
logic may be created based on the response to certain items. When the patient is not administered 
an item within a PRO measure due to the use of skip logic, the representation in the QS dataset 
should follow the guidance provided in the sdTCG.  
 
Computerized adaptive testing (CAT) refers to a sequential form of individual testing 
administered by a computer in which successive items in the measure are selected for 
administration based primarily on the items psychometric properties and content in relation to 
the patients responses to previous items.20 When the patient was not administered an item from 
an item bank (i.e., the total set of items from which a subset is selected for the patient during 
adaptive testing) for a PRO measure due to the use of CAT, a row for each remaining 
unadministered item within the item bank should not be included within the QS dataset. Rather, 
only the administered items for CAT-administered measures should be submitted within the QS 
dataset.  
 
3.1.2  Trial Summary Dataset 
 
Data related to the trial summary should be stored in the TS dataset. Of particular interest to 
FDA is the frequency with which these technical specifications are used to create and submit 
 
20 American Educational Research Association, American Psychological Association, National Council on 
Measurement in Education, 2014, The Standards for Educational and Psychological Testing, Washington (DC): 
American Educational Research Association Publications. 
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trial data. Per the FDA sdTCG, sponsors may include the following parameter and associated 
value in the TS dataset to indicate that these technical specifications were used for the study: 
 
  TSPARAMCD = FDATCHSP 
  TSPARAM = FDA Tech Spec 
  TSVAL = Oncology PROs Technical Specifications Guidance v1.0 
 
3.2  ADaM Specifications 
 
This section provides specifications for the ADaM dataset containing analysis-ready PRO data 
(referenced in this document as the ADQS dataset), which are derived from PRO data in the 
SDTM QS dataset discussed in section 3.1.1 Questionnaires (QS) Dataset in conjunction with 
other SDTM and ADaM data. 
 
3.2.1  General Considerations 
 
The ADQS dataset described in this section follows the ADaM Basic Data Structure (BDS). In 
addition to variables for treatment assignment, stratification, subgrouping, and other covariates 
needed for analysis, the ADQS dataset should contain all individual item scores and summary 
scores (e.g., subscale scores, total scores, other composite or index scores). Table 3 contains 
specifications for a subset of ADQS variables, some of which are standard variables (included 
here to clarify how they should be completed for PRO measures used in oncology studies to 
foster consistency and standardization across industry as well as traceability) and some of which 
are newly defined. Table 3 does not include all ADQS variables to be submitted, such as timing 
and treatment variables. An example ADQS dataset is provided in Appendix 5.2. 
 
Table 3. Specifications for a Subset of ADQS Variables 
Variable 
Variable Label  Type  Comments 
Name 
PARCATy  Parameter  Char  PARCAT1: The measure name(s) and version(s) should be 
Category y  provided within PARCAT1 for each item and summary score 
provided in PARAM to differentiate between PRO measures 
administered during the study. The measure name may match 
the value stored in the variable QS.QSCAT from the input 
SDTM QS dataset. 
Additional PARCATy variables: As demonstrated within 
section 3.2.3 ADQS Dataset Structure, the recommended 
number of PARCATy variables and their corresponding values 
differ based on the PRO measure and the number of summary 
scores calculated. 
PARAM  Parameter  Char  The description of the analysis parameter (e.g., individual item 
or summary score). The value of PARAM may match the value 
stored in QS.QSTEST for parameters existing in the input 
SDTM QS dataset. Individual parameters are needed for each 
summary score. Documentation for derived parameters should 
be provided in submitted study metadata (e.g., the Define-XML 
file and the ADRG). 
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Variable 
Variable Label  Type  Comments 
Name 
PARAMCD  Parameter Code  Char  The short name of the analysis parameter in PARAM. The value 
of PARAMCD may match the values stored in QS.QSTESTCD 
for parameters existing in the input SDTM QS dataset. 
AVAL /  Analysis Value /   Num/  The analysis value for each parameter described by PARAM. 
AVALC  Analysis Value (C)  Char  For parameters existing in the input SDTM QS dataset, 
quantitative values used for analysis and captured in AVAL may 
be copied from QS.QSSTRESN, and qualitative values used for 
analysis and captured in AVALC may be copied from 
QS.QSSTRESC. In some cases, it is acceptable to populate 
AVAL for qualitative values. Reference the ADaMIG for details 
around populating AVAL and AVALC. Study metadata should 
describe how the analysis value is calculated for derived 
parameters. 
DTYPE  Derivation Type  Char  Analysis value derivation method. DTYPE must be populated 
with the algorithm or statistical method used when AVAL or 
AVALC has been imputed or derived differently than the other 
analysis values within the parameter. Reference the ADaMIG 
for details around the submission of DTYPE. This document 
utilizes phantom records (i.e., where DTYPE = PHANTOM) 
to represent missing item scores or summary scores such that 
each patient has the same number of observations (See section 
3.2.2 Handling of Missing PRO Data and Intercurrent Events 
and the examples within Appendix 5.2). Based on the study 
attributes, alternate DTYPE values may be used to handle 
missing data depending on the imputation method(s) 
implemented. When imputation is performed, imputation rules 
are included in the studys Statistical Analysis Plan (SAP). 
Imputation methods are not specified within this document for 
oncology PROs. 
ONTRTFL  On Treatment  Char  A character indicator variable to specify whether the 
Record Flag  observation occurred while the patient was on treatment. This 
flag is strongly recommended within the ADQS dataset to 
denote whether the patient was on treatment during 
administration of the PRO measure at a given assessment 
timepoint. 
ONTRxxFL  On Treatment in  Char  For multi-period studies, a character indicator variable to 
Period xx Record  specify whether the observation occurred while the patient was 
Flag  on treatment for period xx. This flag is strongly recommended 
within the ADQS dataset when multiple periods exist to denote 
whether the patient was on treatment during administration of 
the PRO measure at a given assessment timepoint within period 
xx. 
SCBLFL  Screening Used as  Char  When applicable to include, an indicator variable to specify 
Baseline Flag  when the baseline record (i.e., the record where ABLFL = Y) 
is sourced from a Screening assessment timepoint(s) rather than 
from a prespecified baseline assessment timepoint. Clear 
documentation defining the PRO Baseline score should be 
provided within the study metadata. 
PROEXPFL  PRO Expected  Char  An indicator variable to specify whether the PRO parameter 
Flag  (e.g., the individual item or summary score reported within a 
row) corresponds to a planned (per protocol) PRO assessment 
timepoint. The type of PRO objective (e.g., clinical benefit vs. 
safety and tolerability) affects whether PROEXPFL is populated 
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Variable 
Variable Label  Type  Comments 
Name 
at a given assessment timepoint (e.g., if PRO data are used to 
evaluate clinical benefit, patients who discontinue from 
treatment may be expected to take the PRO measure and 
PROEXPFL = Y. ) (See section 4.0 Specifications for Tables 
and Figures and the examples within Appendix 5.2). If PRO 
objectives for both (1) clinical benefit and (2) safety and 
tolerability are present within the same trial, two PRO Expected 
Flag variables should be submitted within the ADQS dataset 
(e.g., PROEX1FL and PROEX2FL) with definitions for each 
variable provided within the study metadata.  
PROSCMFL  PRO Score  Char  An indicator variable to specify whether the PRO item score or 
Completed Flag  summary score is populated at a planned (per protocol) PRO 
assessment timepoint (i.e., where AVAL or AVALC is not 
empty/null). For example, the indicator value is null for any 
item within the PRO measure where a response is not provided 
by the patient. 
AREASND  Analysis Reason  Char  Describes the reason for missing PRO data. It is recommended 
Not Performed  that AREASND is populated for records where item score or 
summary score is missing (i.e., where AVAL or AVALC is 
empty/null). The value of AREASND should match the value 
stored in QS.QSREASND when QSREASND is populated in 
the input SDTM QS dataset. When QS.QSREASND is not 
populated, AREASND is populated by another source, when 
available. For example, if the PRO data are used to evaluate 
clinical benefit, AREASND may be populated for phantom 
records using DS.DSDECOD or ADSL.DCTREASP for a 
patient who died or discontinued from treatment, or using 
DM.ACTARM for patients who were randomized but not 
treated (See section 3.2.2 Handling of Missing PRO Data and 
Intercurrent Events and the examples within Appendix 5.2). 
Variables in ADQS copied from the ADaM ADSL Dataset or Other Datasets 
FPDDT  First Progressive  Num  Date of first progression. Null if no progression occurred for the 
Disease Date  patient throughout the study. FDA understands that the 
interpretation of progression outcomes can differ between 
independent review committees (IRCs) and site investigators 
(INV). If progression is evaluated by both an IRC and an INV, 
then two First Progressive Disease Date variables are 
recommended for submission (e.g., FPDIRCDT = First 
Progressive Disease as Assessed by IRC Date and FPDINVDT 
= First Progressive Disease as Assessed by INV Date). The 
date(s) should align with the study rules outlined in the study 
protocol and the SAP. The interpretation used for the primary 
analysis should be clearly defined within the study metadata. 
DTHDT  Date of Death  Num  Date of patients death. 
EOSDT  End of Study Date  Num  Date patient ended the study.  
EOSSTT  End of Study  Char  The patients status as of the end of study or data cutoff. 
Status  Examples: COMPLETED, DISCONTINUED, ONGOING. 
DCSREAS  Reason for  Char  Reason for a patients discontinuation from study, if applicable. 
Discontinuation  Null for patients who completed the study.  
from Study 
EOTDT  Date of Treatment  Num  Date the patient discontinued from treatment. May equal 
Discontinuation  EOSDT. 
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Variable 
Variable Label  Type  Comments 
Name 
EOTSTT  End of Treatment  Char  The patients status as of the end of treatment or data cutoff. 
Status  Examples: COMPLETED, DISCONTINUED, ONGOING. 
DCTREAS  Reason for  Char  Reason for a patients discontinuation of treatment, if 
Discontinuation of  applicable. This variable represents discontinuation of treatment 
Treatment  in the overall study and not discontinuation of treatment within 
individual treatment periods; reference the ADaMIG for period-
specific discontinuation variables. 
 
TRTDURD  Total Treatment  Num  Total treatment duration as measured in days. 
Duration (Days) 
TRxxDURD  Treatment Duration  Num  For multi-period studies, treatment duration for period xx as 
in Period xx (Days)  measured in days. 
RANDDT  Date of  Num  Date of patients randomization. 
Randomization 
RANDFL  Randomized  Char  Indicates whether the patient is included in the randomized 
Population Flag  population. 
SAFFL  Safety Population  Char  Indicates whether the patient is included in the safety 
Flag  population. 
ITTFL  Intent-To-Treat  Char  Indicates whether the patient is included in the intent-to-treat 
Population Flag  population. 
Variables in ADQS copied from input SDTM QS Dataset 
QSSEQ  Sequence Number  Num  Sponsors should include any SDTM variables in the ADQS 
VISIT  Visit Name  Char  dataset needed to provide traceability to the source SDTM QS 
VISITNUM  Visit Number  Num  dataset. 
QSSTAT  Completion Status  Char  Sponsors should include SDTM variables that provide 
QSREASND  Reason Not  Char  explanations for missing item scores or missing source data 
Performed  summary scores. See Comments for QSSTAT and QSREASND 
provided in Table 1. Specifications for a Subset of QS 
Variables. 
 
3.2.2  Handling of Missing PRO Data and Intercurrent Events 
 
As discussed in SDTM section 3.1.1.2 Handling of Missing PRO Data and section 3.1.1.3 
Handling of PRO Data Not Collected due to Skip Logic or Computerized Adaptive Testing, 
understanding the reasons for and prevalence of missing PRO data or PRO data not collected, as 
well as intercurrent events21 occurring during the study, are critical to support FDA review and 
regulatory decision-making. Approaches to represent missing data and intercurrent events within 
the ADQS dataset are provided in section 3.2.2.1 Approaches to Represent Missing Data and 
Intercurrent Events and scenarios to represent missing PRO data and intercurrent events within 
the ADQS dataset are provided in section 3.2.2.2 Scenarios to Represent Missing Data and 
Intercurrent Events which further depend on the PRO objective (i.e., clinical benefit vs. safety 
and tolerability). When provided, the reason for missing PRO data should be distributed across 
all rows for each item score and summary score within the missing PRO measure at each planned 
(per protocol) PRO assessment timepoint. The example provided in Appendix 5.2 illustrates the 
 
21 See the guidance for industry E9(R1) Statistical Principles for Clinical Trials Addendum: Estimands and 
Sensitivity Analysis in Clinical Trials (May 2021). For the most recent version of a guidance, check the FDA 
guidance web page at https://www.fda.gov/RegulatoryInformation/Guidances/default.htm. 
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representation of missing data, and the tables and figures requested by the Agency to analyze 
missing data are specified within section 4.0 Specifications for Tables and Figures. 
 
3.2.2.1 Approaches to Represent Missing Data and Intercurrent Events 
 
Approaches to represent missing PRO data within the ADQS dataset include: 
 
  Copying records from the SDTM QS dataset, where QS.QSSTAT = NOT DONE and 
QS.QSREASND is populated with the reason the item(s) and/or summary score(s) are 
missing, or 
 
  Deriving new phantom records in the ADQS dataset (e.g., where DTYPE = PHANTOM).  
 
When QS.QSREASND is populated within the SDTM QS dataset for a record, the value should 
be copied into the ADQS dataset within QSREASND. ADQS.AREASND should be populated in 
the ADQS dataset to indicate the reason the item score or summary score was not done when 
reason is available, including for phantom records. QS.QSSTAT and QS.QSREASND are null 
for phantom records derived in the ADQS dataset, and phantom records should only be derived 
when the row representing the missing item score or source data summary score (if applicable) 
does not exist in the SDTM QS dataset. When phantom records are derived in the ADQS dataset 
for an entire PRO measure, a row should be derived for each item and summary score within the 
PRO measure, with the reason populated in ADQS.AREASND (if known) and distributed across 
all rows. 
 
3.2.2.2 Scenarios to Represent Missing Data and Intercurrent Events 
 
When the PRO objective is to evaluate clinical benefit, rows should be represented in the ADQS 
dataset for each item score and summary score within the PRO measure for all randomized 
patients at each planned (per protocol) PRO assessment timepoint, regardless of whether the item 
score or summary score has a value populated. PRO data may be collected for patients after 
intercurrent events such as treatment discontinuation due to disease progression or due to adverse 
event (AE), which is further described within section 4.0 Specifications for Tables and Figures. 
Intercurrent events include events occurring after treatment initiation that affect either the 
interpretation or the existence of the measurements associated with the clinical question of 
interest. Intercurrent events should be addressed when describing the clinical question of interest 
to precisely define the treatment effect that is to be estimated.22 If records are not tabulated in 
the QS dataset at each PRO assessment timepoint for the patient, including PRO assessment 
timepoints after an intercurrent event, including a terminal intercurrent event such as death, then 
these records should be derived as phantom records in the ADQS dataset. Since rows are 
represented for all randomized patients, records are also derived for patients who were 
randomized but not treated. 
 
 
22 See the guidance for industry E9(R1) Statistical Principles for Clinical Trials Addendum: Estimands and 
Sensitivity Analysis in Clinical Trials (May 2021).  
 
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When the PRO objective is to inform the evaluation of safety and tolerability, rows are only 
represented in the ADQS dataset for each item score and summary score within the PRO 
measure for patients where the PRO is expected to be completed at the planned (per protocol) 
PRO assessment timepoints, including rows for patients who are on therapy throughout the study 
and rows for patients at assessment timepoints prior to treatment discontinuation or death. The 
number of PRO assessments to be administered after a patient discontinues treatment should be 
carefully considered and minimized to reduce patient burden. Rationale regarding the number of 
PRO assessments to be administered should be provided, given that the administration of PRO 
measures beyond treatment discontinuation can be challenging in cancer clinical trials. Sponsors 
are strongly encouraged to consult with the Agency to make appropriate determinations. Rows 
would not be created in the ADQS dataset for assessment timepoints after a patients death or for 
any PRO assessment timepoints for randomized but not treated patients. When rows are created 
in the ADQS dataset for the applicable patients and assessment timepoints when informing the 
evaluation of safety and tolerability, rows should be created for each item score and summary 
score within the PRO measure, regardless of whether the item score or summary score has a 
value populated. 
 
Regardless of PRO objective, if a patient pauses treatment and does not have records included in 
the QS dataset, these records should be derived as phantom records in the ADQS dataset. In 
addition, there are certain scenarios regardless of PRO objective where the PRO measure is not 
administered to a patient, and missing data rows do not need to be created for the patient in the 
ADQS dataset such as when the PRO measure is not available in the patients language. 
 
3.2.3  ADQS Dataset Structure  
 
Example dataset structures are described below for PRO measures where individual item scores 
are used to calculate at least one summary score and where item scores are analyzed individually. 
 
3.2.3.1 Dataset Structure for PRO Measures Where Summary Scores 
are Calculated  
 
The preferred dataset structure for PRO measures where individual item scores are used to 
calculate summary scores includes the consistent use of parameter category variables (e.g., 
PARCAT1, PARCAT2) to allow for the easy identification of each measure, score, and item. 
The scenarios below within Tables 4-7 illustrate how categorical variables are recommended for 
use based on the complexity of relationships between items, subscales, and higher-level scales 
within the PRO measure. 
 
As described within Table 3: Specifications for a Subset of ADQS Variables, PARCAT1 reports 
the PRO measure name and version. PARCAT2 is created within the ADQS dataset for PRO 
measures where summary scores are calculated to indicate whether PARAM represents an item 
or a summary score, where the summary score calculated is dependent on the instrument scoring 
manual. Example terminology values for PARCAT2 include, but are not limited to, ITEM, 
SUBSCALE SCORE, SCALE SCORE, RAW SCORE, TOTAL SCORE, COMPOSITE 
SCORE, and INDEX SCORE. The number of additional PARCATy variables within the 
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ADQS dataset depends on the summary scores to be calculated based on the intended use of the 
PRO measure as described in the protocol, SAP, and instrument scoring manual. 
 
Scenario 1 within Table 4 represents a simple scenario where items within a two-item measure 
are used to compute a single total score. 
 
Table 4. ADQS Dataset Structure for Scenario 1 
PARCAT1  PARCAT2  PARAM 
Measure Name and Version  ITEM  Item 1 
Measure Name and Version  ITEM  Item 2 
Measure Name and Version  TOTAL SCORE  Total Score 
 
Scenario 2 within Table 5 represents a scenario where multiple scores are calculated, and each 
scale score is calculated from distinct, mutually exclusive item score(s). PARCAT3 reports the 
scale to which each item contributes.  
 
Table 5. ADQS Dataset Structure for Scenario 2 
PARCAT1  PARCAT2  PARCAT3  PARAM 
Measure Name and Version  ITEM  Scale Score 1  Item 1 
Measure Name and Version  ITEM  Scale Score 1  Item 2 
Measure Name and Version  ITEM  Scale Score 1  Item 3 
Measure Name and Version  ITEM  Scale Score 2  Item 4 
Measure Name and Version  ITEM  Scale Score 2  Item 5 
Measure Name and Version  ITEM  Scale Score 3  Item 6 
Measure Name and Version  SCALE SCORE  Scale Score 1  Scale Score 1 
Measure Name and Version  SCALE SCORE  Scale Score 2  Scale Score 2 
Measure Name and Version  SCALE SCORE  Scale Score 3  Scale Score 3 
 
Scenario 3 within Table 6 represents a scenario where (1) multiple subscale scores are 
calculated, and each subscale score is calculated from distinct, mutually exclusive item score(s), 
and (2) multiple scale scores are calculated, and each scale score is calculated from distinct, 
mutually exclusive subscale score(s). PARCAT3 reports the subscale to which an item 
contributes, and PARCAT4 reports the scale to which a subscale contributes. 
 
Table 6. ADQS Dataset Structure for Scenario 3 
PARCAT1  PARCAT2  PARCAT3  PARCAT4  PARAM 
Measure Name and Version  ITEM  Subscale Score 1  Scale Score A  Item 1 
Measure Name and Version  ITEM  Subscale Score 1  Scale Score A  Item 2 
Measure Name and Version  ITEM  Subscale Score 1  Scale Score A  Item 3 
Measure Name and Version  ITEM  Subscale Score 2  Scale Score A  Item 4 
Measure Name and Version  ITEM  Subscale Score 2  Scale Score A  Item 5 
Measure Name and Version  ITEM  Subscale Score 3  Scale Score B  Item 6 
Measure Name and Version  SUBSCALE SCORE  Subscale Score 1  Scale Score A  Subscale Score 1 
Measure Name and Version  SUBSCALE SCORE  Subscale Score 2  Scale Score A  Subscale Score 2 
Measure Name and Version  SUBSCALE SCORE  Subscale Score 3  Scale Score B  Subscale Score 3 
Measure Name and Version  SCALE SCORE    Scale Score A  Scale Score A 
Measure Name and Version  SCALE SCORE    Scale Score B  Scale Score B 
 
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Scenario 4 within Table 7 represents a scenario where (1) multiple subscale scores are 
calculated, and each subscale is calculated from distinct, mutually exclusive item score(s), and 
(2) multiple scale scores are calculated. However, in this scenario, a single subscale score can 
contribute to multiple scale scores. PARCAT3 reports the subscale to which an item contributes 
and separate categorical variables (i.e., PARCAT4 and PARCAT5) report the individual scale to 
which a subscale contributes. Similarly, if an item can contribute to multiple subscales, a 
separate PARCATy is needed for each subscale (not pictured). 
 
Table 7. ADQS Dataset Structure for Scenario 4 
PARCAT1  PARCAT2  PARCAT3  PARCAT4  PARCAT5  PARAM 
Measure Name  Subscale 
ITEM  Scale Score A  Scale Score B  Item 1 
and Version  Score 1 
Measure Name  Subscale 
ITEM  Scale Score A  Scale Score B  Item 2 
and Version  Score 1 
Measure Name  Subscale 
ITEM  Scale Score A  Scale Score B  Item 3 
and Version  Score 1 
Measure Name  Subscale 
ITEM  Scale Score A  Scale Score B  Item 4 
and Version  Score 2 
Measure Name  Subscale 
ITEM  Scale Score A  Scale Score B  Item 5 
and Version  Score 2 
Measure Name  Subscale 
ITEM  Scale Score A    Item 6 
and Version  Score 3 
Measure Name  SUBSCALE  Subscale 
Scale Score A  Scale Score B  Subscale Score 1 
and Version  SCORE  Score 1 
Measure Name  SUBSCALE  Subscale 
Scale Score A  Scale Score B  Subscale Score 2 
and Version  SCORE  Score 2 
Measure Name  SUBSCALE  Subscale 
Scale Score A    Subscale Score 3 
and Version  SCORE  Score 3 
Measure Name 
SCALE SCORE    Scale Score A    Scale Score A 
and Version 
Measure Name 
SCALE SCORE      Scale Score B  Scale Score B 
and Version 
 
3.2.3.2 Dataset Structure for PRO Measures Where Summary Scores 
are Not Calculated  
 
The preferred dataset structure when summary scores are not calculated and item scores are 
analyzed individually include PRO measures that analyze attributes of symptomatic AEs, where 
AEs are selected from an item library prior to trial initiation. Scenario 5 within Table 8 
represents the consistent use of parameter category variables to allow for the easy identification 
of the measure, symptoms (e.g., rash, headache), and attributes (e.g., presence, severity, 
frequency) within an example PRO measure. PARCAT2 reports the stand-alone symptom and 
PARCAT3 reports the stand-alone attribute. PARAM is a compliant, stand-alone analysis 
variable. CDISC Controlled Terminology is implemented when available for the PRO measure. 
 
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Table 8. ADQS Dataset Structure for Scenario 5 
PARCAT1  PARCAT2  PARCAT3  PARAM 
Measure Name and Version  Symptom 1  Attribute 1  Symptom 1 Attribute 1 
Measure Name and Version  Symptom 2  Attribute 2  Symptom 2 Attribute 2 
Measure Name and Version  Symptom 2  Attribute 3  Symptom 2 Attribute 3 
Measure Name and Version  Symptom 3  Attribute 1  Symptom 3 Attribute 1 
 
 
4.0  SPECIFICATIONS FOR TABLES AND FIGURES 
 
In addition to the sponsors  prespecified tables and figures presenting analyses of PRO data, the 
Agency strongly recommends the following tables and figures based on PRO data be provided 
within the Clinical Study Report (CSR) to facilitate the evaluation of the PRO measure in cancer 
clinical trials. Sponsors should also provide an executive summary of clinical interpretation of 
the most critical PRO results informing risk(s) and benefit(s) within the CSR. Examples of the 
requested tables and figures are shown in Appendix 5.3 which are partitioned by treatment arm 
and assessment timepoint. Analysis visits (ADQS.AVISIT) should be assigned from SDTM 
visits (QS.VISIT) based on windowing rules in the studys SAP. It is possible that not all records 
are assigned an AVISIT (e.g., records for unscheduled visits), and these records are excluded 
from the requested tables and figures. In the examples, counts and percentages are provided 
within the requested tables and percentages are provided within the requested bar charts. 
 
4.1  Patient Disposition 
 
Provide a table and bar chart summarizing cumulative patient disposition. Whether a PRO 
measure is expected to be completed for a patient differs based on the PRO objective as 
described in sections 4.1.1 and 4.1.2 (i.e., when PRO data are used to evaluate clinical benefit vs. 
safety and tolerability). 
 
4.1.1  Clinical Benefit 
 
When the PRO objective is clinical benefit, the percentage for each disposition category should 
be calculated using the randomized population as the fixed denominator. The PRO measure is 
expected to be completed by the patient for the following:  
 
  Patients who are on therapy. 
  Patients who discontinued from treatment due to disease progression, AE, or other reason as 
specified in the protocol.  
  Patients who were randomized but not treated. 
  Patients who paused treatment. 
 
When the PRO measure is expected to be completed at a PRO assessment timepoint, the PRO 
Expected Flag (PROEXPFL) equals Y as defined in Table 3: Specifications for a Subset of 
ADQS Variables.  
 
Conversely, the PRO measure is not expected to be completed by the patient for the following:  
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  PRO assessment timepoints after death for patients who died. 
  Translation of the PRO measure is not available in the patients language (affects all PRO 
assessment timepoints). 
 
When the PRO measure is not expected to be completed at a PRO assessment timepoint, the 
PRO Expected Flag (PROEXPFL) is null.  
 
An example table and bar chart illustrating the structure and inputs for the table and figure, 
including the preferred categories, are provided in Appendix 5.3.1. Within the table and figure, 
the three recommended categories for treatment discontinuation include treatment 
discontinuation due to disease progression, treatment discontinuation due to AE, and all other 
reasons for treatment discontinuation. In addition, an Other category within PRO Not Expected 
groups patients who were not expected to complete the PRO measure at a designated assessment 
timepoint for reasons other than patient death (e.g., the translation of the PRO measure is not 
available in the patient's language). 
 
4.1.2  Safety and Tolerability 
 
When the PRO objective is safety and tolerability, the percentage for disposition categories 
should be calculated using the safety population as the fixed denominator. The PRO measure is 
expected to be completed for patients who are either on therapy or paused treatment at a given 
PRO assessment timepoint, which are totaled within a PRO Expected column. When the PRO 
measure is expected to be completed by the patient at a PRO assessment timepoint, the PRO 
Expected Flag (PROEXPFL) equals Y as defined in Table 3: Specifications for a Subset of 
ADQS Variables.  
 
Conversely, the PRO measure is not expected to be completed by the patient for reasons 
including:  
 
  PRO assessment timepoints after death for patients who died. 
  Patients who were randomized but not treated (affects all PRO assessment timepoints). 
  Translation of the PRO measure is not available in the patients language (affects all PRO 
assessment timepoints). 
 
In some cases, PRO assessment timepoints may be less frequent or stop after treatment 
discontinuation for patients who discontinued from treatment due to disease progression, AE, or 
other reason.  Expectations for when PRO assessments will be collected should be planned in 
advance with FDA. See Section 3.2.2.2. 
 
When the PRO measure is not expected to be completed at a PRO assessment timepoint, the 
PRO Expected Flag (PROEXPFL) is null. An example table and bar chart illustrating the 
structure and inputs, including the preferred categories, are provided in Appendix 5.3.2. Within 
the table and figure, the three recommended categories for treatment discontinuation include 
treatment discontinuation due to disease progression, treatment discontinuation due to AE, and 
all other reasons for treatment discontinuation. In addition, an Other category within PRO Not 
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Expected groups patients who were not expected to complete the PRO measure at a designated 
assessment timepoint for reasons other than patient death or treatment discontinuation. 
 
4.2  PRO Data Completeness 
 
Provide a table and data visualization summarizing PRO data completeness.23 The denominator 
used to evaluate data completeness differs based on the PRO objective (i.e., when PRO data are 
used to inform the evaluation of clinical benefit vs. safety and tolerability) as described in 
sections 4.2.1 and 4.2.2. The numerator (referenced as the PRO Completed column in Table A6 
and Table A7) is the number of patients submitting a completed PRO measure at the designated 
PRO assessment timepoint and does not differ based on PRO objective. Sponsors should defer to 
the instructions provided within the instrument scoring manual to determine what constitutes a 
complete PRO measure (i.e., number of items needed for completion to produce a reliable 
score). When not provided within the instrument scoring manual, sponsors should provide 
rationale for the number of responses necessary to constitute a complete PRO measure. 
 
Within the tables, counts and percentages of patients who did not complete the PRO measure 
(referenced as Reason for PRO Not Completed in Table A6 and Table A7) should be calculated 
with the accompanying reasons for missing observations based on collected data. If reasons are 
unknown or not collected, a separate column should be provided to report the affected count and 
percentage. The example tables contain possible reasons for noncompletion and should be 
modified to represent the reported reasons collected within the clinical trial (See section 3.1.1.2 
Handling of Missing PRO Data for example reasons for noncompletion). If both clinical benefit 
as well as safety and tolerability PRO objectives are specified within a single trial, the sponsor 
should submit the requested tables and data visualizations for both available data rate and 
completion rate as described below. 
 
4.2.1  Available Data Rate (Clinical Benefit) 
 
When PRO data are used to evaluate clinical benefit, the available data rate should be calculated 
where the randomized population is used as a fixed denominator. The table and data 
visualization should be provided based on available data rate (1) at the PRO instrument level and 
(2) for the concept(s) evaluated by the PRO measure (e.g., single item score or a summary score 
such as subscale score or total score). When the concept measured is a summary score (e.g., 
physical functioning), the table and data visualization should be provided for both the summary 
score and for each individual item score that contributes to the summary score. An example table 
and bar chart illustrating the structure and inputs are provided in Appendix 5.3.3, with 
percentages provided for each category within the bar chart. Reasons for treatment 
discontinuation are included in the table and figure as described in the table footnotes. 
 
4.2.2  Completion Rate (Safety and Tolerability) 
 
When PRO data are used to inform the evaluation of safety and tolerability, the completion rate 
should be calculated where the denominator is the number of patients expected to complete the 
PRO measure at the designated PRO assessment timepoint as described in section 4.1.2 Patient 
 
23More information is available at SISAQOLs web page: https://www.sisaqol-imi.org/.  
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Disposition for Safety and Tolerability (i.e., where PRO Expected Flag (PROEXPFL) equals Y 
as defined in Table 3: Specifications for a Subset of ADQS Variables). Thus, the denominator 
can decrease throughout an oncology trial based on attrition over time. The table and data 
visualization should be provided at the PRO instrument level based on completion rate. The 
sponsor should consult with the Agency to determine additional tables and data visualizations to 
provide for individual items (including patient-reported symptomatic adverse events) and/or 
summary scores. An example table and bar chart illustrating the structure and inputs are provided 
in Appendix 5.3.4, with percentages provided for each category within the bar chart. Reasons for 
treatment discontinuation may be excluded as reasons for PRO noncompletion in the table and 
figure as described in the table footnotes. 
 
4.3  Distributions 
 
Provide a table and data visualization summarizing the distribution of responses and the 
distribution of change in responses from baseline. When the PRO measure is used to inform the 
evaluation of safety and tolerability, the sponsor should consult with the Agency to determine the 
tables and data visualizations to provide for individual items (including patient-reported 
symptomatic adverse events) and/or summary scores. When the PRO measure is to evaluate 
clinical benefit, the table and data visualization should be provided for the concept(s) evaluated 
by the PRO measure (e.g., single item score, subscale score, total score). When the concept 
measured is a summary score (e.g., physical functioning), the table and data visualization should 
be provided for both the summary score and for each individual item score that contributes to the 
summary score. 
 
Within the table, counts and percentages should be provided for PRO Completed and PRO Not 
Completed. Additional columns within the table depends on PRO objective; when the PRO 
objective is safety and tolerability, the count and percentage for PRO Expected should be 
provided. When the PRO objective is clinical benefit, the count and percentage for the 
randomized population should be provided. When the PRO objective is safety and tolerability, 
the denominator used to determine the percentage for PRO Completed and PRO Not Completed 
is the number of patients expected to complete the PRO measure at the designated PRO 
assessment timepoint as described in section 4.1.2 Patient Disposition for Safety and Tolerability 
(i.e., where PRO Expected Flag (PROEXPFL) equals Y as defined in Table 3: Specifications 
for a Subset of ADQS Variables). When the PRO objective is clinical benefit, the denominator 
used to determine the percentage for PRO Completed and PRO Not Completed is the 
randomized population.  
 
When the concept measured has categorical response options with binary or ordinal outcomes, 
counts and percentages within the table for the response categories or change in response 
categories should be provided where the denominator used to determine the percentage for each 
category is PRO Completed (i.e., where PRO Score Completed Flag (PROSCMFL) equals Y as 
defined in Table 3: Specifications for a Subset of ADQS Variables). When the concept measured 
has continuous response options, summary statistics should be provided and are calculated based 
on PRO Completed. 
 
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Within the data visualization, counts for PRO Completed and PRO Not Completed should be 
provided below the figure as shown in the examples within the appendices. In addition, if the 
PRO objective is safety and tolerability, counts for PRO Expected should be provided; if the 
PRO objective is clinical benefit, counts for the randomized population should be provided. The 
type of data visualization provided further depends on the response options for the PRO measure. 
A bar chart should be provided when the concept measured has categorical response options with 
binary or ordinal outcomes. When the concept measured has continuous response options, a line 
graph should be provided. For example, a line graph with descriptive means may be provided 
when the PRO objective is safety and tolerability objective. The sponsor may consult with the 
Agency to discuss alternative data visualizations (e.g., density curves, box plots) to provide when 
continuous data are captured. Within the line graph, standard error bars with jittering should be 
provided as well as labels to indicate improving/worsening or higher/lower functioning, 
depending on the concept measured. 
 
4.3.1  Distribution of Responses 
 
When the concept measured has categorical response options with a binary or ordinal outcome, 
the distribution of responses in the table and bar chart should include all possible response 
options for the item or summary score with the percentage provided for each category within the 
bar chart. Within Appendix 5.3.5, an example table is provided in Table A8 and a bar chart is 
provided in Figure A5 for a single item for a safety and tolerability PRO objective.  
 
When the concept measured has continuous response options, the distribution of responses in the 
table and line graph should represent a summary statistic (e.g., the mean score) over time. An 
example table is provided in Table A9, and a line graph is provided in Figure A6 for a single 
item showing descriptive means for a safety and tolerability PRO objective.  
 
4.3.2  Distribution of Change in Responses from Baseline 
 
When the concept measured includes categorical response options with a binary or ordinal 
outcome, the distribution of change in response categories for the table and bar chart should 
include all possible scenarios (e.g., improving, no change, worsening) based on the number of 
response categories for the item or summary score with the percentage provided for each change 
category within the bar chart. Within Appendix 5.3.6, an example table is provided in Table A10 
and a bar chart is provided in Figure A7 for a single item for a safety and tolerability PRO 
objective. Labels for No Change or Improving and Worsening should be provided in the bar 
chart as shown in the example. 
 
When the concept measured has continuous response options, the distribution of change in 
responses from baseline in the table and line graph should represent a summary statistic (e.g., 
mean) change from baseline over time. An example table is provided in Table A11 and a line 
graph is provided in Figure A8 for a single item showing descriptive mean change from baseline 
for a safety and tolerability PRO objective. 
 
 
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4.4  Incidence of Healthcare Utilization 
 
Provide a table summarizing the incidence of healthcare utilization, including emergency 
department visits, hospitalizations, supportive care medications, supportive care procedures, and 
other relevant interventions depending on the study. Each supportive care medication and 
supportive care procedure should be represented as a separate column within the table. The 
denominator used to determine the percentage for each intervention depends on PRO objective. 
When the PRO objective is safety and tolerability, the denominator is the number of patients 
expected to complete the PRO measure at the designated PRO assessment timepoint as described 
in section 4.1.2 Patient Disposition for Safety and Tolerability (i.e., where PRO Expected Flag 
(PROEXPFL) equals Y as defined in Table 3: Specifications for a Subset of ADQS Variables). 
When the PRO objective is clinical benefit, the denominator is the randomized population. In 
addition to columns for healthcare utilization interventions, columns are provided for 
Randomized Patients and PRO Expected.  
 
An example table illustrating the structure and inputs is provided in Appendix 5.3.7. The table 
contains example healthcare utilization values for supportive procedures and supportive 
medications, but the table should be modified to represent the intervention within the study. The 
sponsor may consult with the Agency to determine the appropriate supportive care medications 
and supportive care procedures to provide (e.g., growth factors, steroids, and transfusions depend 
on the cancer type and may not always be relevant).
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5.0 APPENDIX 
 
Table A1 represents an example schedule of assessments within the study protocol (not pictured) for Study A, where the patient-
reported outcome (PRO) data are used to evaluate clinical benefit. Study A is referenced in the example Questionnaires (QS) dataset 
in Appendix 5.1 and the example Questionnaires Analysis Dataset (ADQS) in Appendix 5.2. As shown in Table A1, the PRO measure 
is administered initially onsite at the Screening visit and subsequently onsite on Day 1 of each of three cycles, where Cycle 1 Day 1 
represents the Baseline visit. The example PRO measure administered to patients in Study A is a two-item measure, where answers to 
both items are used to calculate total score according to the instrument scoring manual (not pictured). The total score is not collected 
as source data and is calculated in the Analysis Data Model (ADaM) ADQS dataset. Note the numeric values provided in 
QS.QSORRES within Table A2 and ADQS.AVAL within Table A3 are provided for illustrative purposes only. 
 
3 Table A1. Example Schedule of Assessments 
Visit 
       Activity  Cycles 1 through 3 (Cycle Length = 21 Days) 
Screening 
Day 1  Day 8  Day 15 
PRO Measure  X  X     
 
5.1  Example SDTM Questionnaires Dataset 
 
Table A2 shows an example of tabulated data using the QS domain specifications. Where the PRO measure was not completed as 
expected, Table A2 shows a subset of variables to be submitted within the QS dataset and illustrates how missing PRO assessment 
timepoints are represented. Scenarios displayed in Table A2 include: 
 
  Patient 1 only responded to one of two items in the PRO measure at the Cycle 1 Day 1 visit.  
 
o  Row 3 shows QSSTAT = NOT DONE and null QSREASND since reason for the missing item is not captured within the 
administered PRO measure.  
 
  Patient 1 attended the onsite Cycle 3 Day 1 visit but refused to take the PRO measure. When the PRO measure is not administered, 
rows are created for each item.  
 
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o  Rows 7 through 8 show null QSORRES, QSSTAT = NOT DONE, and QSREASND = PATIENT REFUSAL, where 
PATIENT REFUSAL is captured on the CRF. Given the onsite visit was attended, Date/Time of Finding (QSDTC) is 
populated.  
 
  Patient 2 was unable to attend the onsite Cycle 1 Day 1 visit due to hospitalization; thus, the PRO measure was not administered. 
In this scenario, rows are created for each item.     
 
o  Rows 11 through 12 show null QSORRES, QSSTAT = NOT DONE, and QSREASND = HOSPITALIZATION. To 
indicate the onsite visit was not attended by Patient 2, QSDTC is set to null. 
  
  Patient 2 died after the Cycle 1 Day 1 visit. Thus, no visit data are available in the QS dataset for the remaining visits. Since the 
PRO data are used to evaluate clinical benefit, the remaining visits are omitted from the QS dataset and derived as phantom 
records in the ADQS dataset shown in Appendix 5.2. 
 
4 Table A2. Subset of Sample QS Dataset 
Row  USUBJID  VISIT  QSCAT  QSTEST  QSTESTCD  QSORRES  QSSTAT  QSREASND  QSDTC 
Measure Name and 
1  A_100_1  SCREENING  I01-Item 1  I01  3      2022-02-01 
Version 
Measure Name and 
2  A_100_1  SCREENING  I01-Item 2  I02  5      2022-02-01 
Version 
Measure Name and 
3  A_100_1  CYCLE 1 DAY 1  I01-Item 1  I01    NOT DONE    2022-02-22 
Version 
Measure Name and 
4  A_100_1  CYCLE 1 DAY 1  I01-Item 2  I02  4      2022-02-22 
Version 
Measure Name and 
5  A_100_1  CYCLE 2 DAY 1  I01-Item 1  I01  2      2022-03-15 
Version 
Measure Name and 
6  A_100_1  CYCLE 2 DAY 1  I01-Item 2  I02  4      2022-03-15 
Version 
Measure Name and 
7  A_100_1  CYCLE 3 DAY 1  I01-Item 1  I01    NOT DONE  PATIENT REFUSAL  2022-04-05 
Version 
Measure Name and 
8  A_100_1  CYCLE 3 DAY 1  I01-Item 2  I02    NOT DONE  PATIENT REFUSAL  2022-04-05 
Version 
Measure Name and 
9  A_100_2  SCREENING  I01-Item 1  I01  4      2022-03-14 
Version 
Measure Name and 
10  A_100_2  SCREENING  I01-Item 2  I02  5      2022-03-14 
Version 
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Row  USUBJID  VISIT  QSCAT  QSTEST  QSTESTCD  QSORRES  QSSTAT  QSREASND  QSDTC 
Measure Name and 
11  A_100_2  CYCLE 1 DAY 1  I01-Item 1  I01    NOT DONE  HOSPITALIZATION   
Version 
Measure Name and 
12  A_100_2  CYCLE 1 DAY 1  I01-Item 2  I02    NOT DONE  HOSPITALIZATION   
Version 
 
5.2  Example ADaM Questionnaires Analysis Dataset  
 
Table A3 shows an example ADQS dataset for the same patients and scenario descriptions as those provided in Appendix 5.1. Note 
that this table only shows a subset of variables to be submitted in the ADQS dataset; additional variables, such as population flags and 
treatment variables, are not provided as these depend on individual study needs. In this example, total score is calculated for each 
patient and analysis visit (i.e., where PARAM = Total Score) since scores are not captured within the SDTM QS dataset. Scenarios 
displayed in Table A3 include: 
 
  Patient 1 only responded to one of two items at the Baseline visit. Thus, per the scoring manual, Total Score is incalculable in the 
ADQS dataset. 
 
o  Row 6 reports Total Score and shows AREASND = NOT CALCULABLE. QSSTAT and QSREASND are null since 
records for PARAM = Total Score are created in the ADQS dataset. 
 
o  Rows 4 through 6 report ONTRTFL = Y since the patient was on treatment during the Baseline visit and PROEXPFL = Y 
since the patient was expected to complete the PRO measure at the Baseline visit. PROSCMFL = Y in Row 5 since only 
Item 2 had a response provided by the patient. 
 
  Patient 1 attended the Cycle 3 Day 1 visit but refused to take the PRO measure.  
 
o  Row 12 reports Total Score and shows AREASND = PATIENT REFUSAL as reported within QS.QSREASND for the 
individual items in Rows 10 and 11. 
 
o  Rows 10 through 12 report ONTRTFL = Y since the patient was on treatment and PROEXPFL = Y since the patient was 
expected to complete the PRO measure at the visit. PROSCMFL is null for all rows since the measure was not completed. 
 
  Patient 2 was unable to attend the Baseline visit due to hospitalization. 
 
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o  Row 18 reports Total Score and shows AREASND = HOSPITALIZATION as reported within QS.QSREASND for the 
individual items in Rows 16 and 17. 
 
o  Rows 16 through 18 report null ONTRTFL since the patient was not on treatment but PROEXPFL = Y since the patient was 
still expected to complete the PRO measure at the visit. PROSCMFL is null for all rows since the measure was not completed. 
 
  Patient 2 died after the Baseline visit. Since the PRO data are used to evaluate clinical benefit, phantom records are derived in the 
ADQS dataset for all items and summary scores for the missing analysis visits at Cycle 2 Day 1 and Cycle 3 Day 1. These missing 
visits are derived as phantom records in the ADaM dataset with DTYPE = PHANTOM and AREASND = DEATH, where, in 
this example, AREASND is populated from ADSL.DCTREAS. Note that QSSTAT and QSREAND are null. For phantom 
records, AVISIT is populated to represent the visit number for the missing visit. Given the patient died, ONTRTFL, PROEXPFL, 
and PROSCMFL are null. 
 
5 Table A3. (Part 1) Subset of Sample ADQS Dataset 
Row  USUBJID  VISIT  AVISIT  PARCAT1  PARAM  PARAMCD  AVAL  QSSTAT 
1  A_100_1  SCREENING  SCREENING  Measure Name and Version  I01-Item 1  I01  3   
2  A_100_1  SCREENING  SCREENING  Measure Name and Version  I01-Item 2  I02  5   
3  A_100_1  SCREENING  SCREENING  Measure Name and Version  Total Score  TS  8   
4  A_100_1  CYCLE 1 DAY 1  BASELINE  Measure Name and Version  I01-Item 1  I01    NOT DONE 
5  A_100_1  CYCLE 1 DAY 1  BASELINE  Measure Name and Version  I01-Item 2  I02  4   
6  A_100_1  CYCLE 1 DAY 1  BASELINE  Measure Name and Version  Total Score  TS     
7  A_100_1  CYCLE 2 DAY 1  CYCLE 2 DAY 1  Measure Name and Version  I01-Item 1  I01  2   
8  A_100_1  CYCLE 2 DAY 1  CYCLE 2 DAY 1  Measure Name and Version  I01-Item 2  I02  4   
9  A_100_1  CYCLE 2 DAY 1  CYCLE 2 DAY 1  Measure Name and Version  Total Score  TS  6   
10  A_100_1  CYCLE 3 DAY 1  CYCLE 3 DAY 1  Measure Name and Version  I01-Item 1  I01    NOT DONE 
11  A_100_1  CYCLE 3 DAY 1  CYCLE 3 DAY 1  Measure Name and Version  I01-Item 2  I02    NOT DONE 
12  A_100_1  CYCLE 3 DAY 1  CYCLE 3 DAY 1  Measure Name and Version  Total Score  TS     
13  A_100_2  SCREENING  SCREENING  Measure Name and Version  I01-Item 1  I01  4   
14  A_100_2  SCREENING  SCREENING  Measure Name and Version  I01-Item 2  I02  5   
15  A_100_2  SCREENING  SCREENING  Measure Name and Version  Total Score  TS  9   
16  A_100_2  CYCLE 1 DAY 1  BASELINE  Measure Name and Version  I01-Item 1  I01    NOT DONE 
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Row  USUBJID  VISIT  AVISIT  PARCAT1  PARAM  PARAMCD  AVAL  QSSTAT 
17  A_100_2  CYCLE 1 DAY 1  BASELINE  Measure Name and Version  I01-Item 2  I02    NOT DONE 
18  A_100_2  CYCLE 1 DAY 1  BASELINE  Measure Name and Version  Total Score  TS     
19  A_100_2  CYCLE 2 DAY 1  CYCLE 2 DAY 1  Measure Name and Version  I01-Item 1  I01     
20  A_100_2  CYCLE 2 DAY 1  CYCLE 2 DAY 1  Measure Name and Version  I01-Item 2  I02     
21  A_100_2  CYCLE 2 DAY 1  CYCLE 2 DAY 1  Measure Name and Version  Total Score  TS     
22  A_100_2  CYCLE 3 DAY 1  CYCLE 3 DAY 1  Measure Name and Version  I01-Item 1  I01     
23  A_100_2  CYCLE 3 DAY 1  CYCLE 3 DAY 1  Measure Name and Version  I01-Item 2  I02     
24  A_100_2  CYCLE 3 DAY 1  CYCLE 3 DAY 1  Measure Name and Version  Total Score  TS     
 
Table A3. (Part 2) Subset of Sample ADQS Dataset 
Row  QSREASND  DTYPE  AREASND  DCTREAS  PROEXPFL  PROSCMFL  ONTRTFL 
1          Y  Y   
2          Y  Y   
3          Y  Y   
4          Y    Y 
5          Y  Y  Y 
6      NOT CALCULABLE    Y    Y 
7          Y  Y  Y 
8          Y  Y  Y 
9          Y  Y  Y 
10  PATIENT REFUSAL    PATIENT REFUSAL    Y    Y 
11  PATIENT REFUSAL    PATIENT REFUSAL    Y    Y 
12      PATIENT REFUSAL    Y    Y 
13          Y  Y   
14          Y  Y   
15          Y  Y   
16  HOSPITALIZATION    HOSPITALIZATION    Y     
17  HOSPITALIZATION    HOSPITALIZATION    Y     
18      HOSPITALIZATION    Y     
19    PHANTOM  DEATH  DEATH       
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Row  QSREASND  DTYPE  AREASND  DCTREAS  PROEXPFL  PROSCMFL  ONTRTFL 
20    PHANTOM  DEATH  DEATH       
21    PHANTOM  DEATH  DEATH       
22    PHANTOM  DEATH  DEATH       
23    PHANTOM  DEATH  DEATH       
24    PHANTOM  DEATH  DEATH       
 
5.3  Example Tables and Figures 
 
5.3.1  Patient Disposition when Evaluating Clinical Benefit 
 
6 Table A4. Patient Disposition when Evaluating Clinical Benefit (Denominator = Randomized Population)1 
PRO Expected2  PRO Not Expected 
Treatment  Treatment  
Treatment 
Analysis  Treatment  Randomized  Patients On  Discontinuation:  Discontinuation: 
Discontinuation:   Death,   Other,3  
Visit  Arm  Patients (N)  Therapy,   Disease   Adverse  
Other Reasons,   n (%)  n (%) 
n (%)  Progression,   Event (AE),  
n (%) 
n (%)  n (%) 
Control  600  600 (100.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%) 
Baseline 
Treatment  602  602 (100.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%) 
Cycle 2  Control  600  564 (94.0%)  16 (2.7%)  15 (2.5%)  0 (0.0%)  5 (0.8%)  0 (0.0%) 
Day 1  Treatment  602  572 (95.0%)  10 (1.7%)  13 (2.2%)  0 (0.0%)  7 (1.2%)  0 (0.0%) 
Cycle 3  Control  600  525 (87.5%)  30 (5.0%)  26 (4.3%)  6 (1.0%)  13 (2.2%)  0 (0.0%) 
Day 1  Treatment  602  542 (90.0%)  23 (3.8%)  21 (3.5%)  0 (0.0%)  16 (2.7%)  0 (0.0%) 
 
1 Denominator used to calculate percentages is the number of randomized patients. 
2 When PRO data are used to evaluate clinical benefit, the PRO measure is generally expected to be completed for patients who both did not discontinue 
treatment and who discontinued treatment for reasons other than death. Columns under PRO Expected includes patients who both completed and did not 
complete the PRO measure (e.g., the patient did not attend an onsite visit, the patient did not complete the PRO measure at the attended onsite visit or at a 
prespecified offsite assessment timepoint, the patient partially completed the PRO measure resulting in incalculable summary scores). 
3 The Other column groups patients not expected to complete the PRO measure at a designated assessment timepoint for reasons other than patient death (e.g., 
the translation of the PRO measure is not available in the patient's language). 
 
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Figure A1. Patient Disposition when Evaluating Clinical Benefit (Denominator = Randomized Population)  
 
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5.3.2  Patient Disposition when Informing Safety and Tolerability 
 
7Table A5. Patient Disposition when Informing the Evaluation of Safety and Tolerability (Denominator = Safety Population)4 
PRO Not Expected 
Safety  PRO  Treatment  Treatment  Treatment 
Analysis  Treatment  Randomized 
Population  Expected,5   Death, n  Discontinuation:  Discontinuation:  Discontinuation:  Other,6  
Visit  Arm  Population (N) 
(N)  n (%)  (%)  Disease   Adverse   Other Reasons,   n (%) 
Progression, n (%)  Event, n (%)  n (%) 
Control  600  600  600 (100.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%) 
Baseline 
Treatment  602  602  602 (100.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%) 
Cycle 2  Control  600  600  564 (94.0%)  5 (0.8%)  16 (2.7%)  15 (2.5%)  0 (0.0%)  0 (0.0%) 
Day 1  Treatment  602  602  572 (95.0%)  7 (1.2%)  10 (1.7%)  13 (2.2%)  0 (0.0%)  0 (0.0%) 
Cycle 3  Control  600  600  525 (87.5%)  13 (2.2%)  30 (5.0%)  26 (4.3%)  6 (1.0%)  0 (0.0%) 
Day 1  Treatment  602  602  542 (90.0%)  16 (2.7%)  23 (3.8%)  21 (3.5%)  0 (0.0%)  0 (0.0%) 
   
 
4 Denominator used to calculate percentages is the number of patients in the safety population. 
5 When PRO data are used to inform the evaluation of safety and tolerability, the PRO measure may not be expected to be completed after a patient discontinues 
from treatment as shown in the table. Thus, the PRO Expected column excludes patients who discontinued from treatment. The PRO Expected column is 
determined where PRO Expected Flag (PROEXPFL) equals Y and includes patients who both completed and did not complete the PRO measure (e.g., the 
patient did not attend an onsite visit, the patient did not complete the PRO measure at the attended onsite visit or at a prespecified offsite assessment timepoint, 
the patient partially completed the PRO measure resulting in incalculable summary scores).  
6 The Other column groups patients who were not expected to complete the PRO measure at a designated assessment timepoint for reasons other than treatment 
discontinuation or patient death (e.g., the translation of the PRO measure is not available in the patient's language). 
 
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Figure A2. Patient Disposition when Informing the Evaluation of Safety and Tolerability (Denominator = Safety Population)  
 
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5.3.3  Available Data Rate for Clinical Benefit 
 
8 Table A6. Available Data Rate for Clinical Benefit (Denominator = Randomized Population)7 
Reason for PRO Not Completed,9 n (%) 
PRO Not 
9  PRO  Completed8  Patient Unable to  Patient Unable to 
Treatment  Randomized  Reason 
Analysis  Completed,   (excluding  Complete due to  Complete due to  Patient  Device  Death, n (%) 
Arm  Patients (N)  Unknown,10 
Visit  n (%)  Death),  Disease   Adverse   Refusal  Failure 
n (%) 
n (%)  Progression  Event (AE) 
Control  600  600 (100.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%) 
Baseline 
Treatment  602  602 (100.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%) 
Cycle 2  Control  600  556 (92.7%)  39 (6.5%)  8 (1.3%)  25 (4.2%)   6 (1.0%)  0 (0.0%)  0 (0.0%)  5 (0.8%) 
Day 1  Treatment  602  551 (91.5%)  44 (7.3%)  3 (0.5%)  36 (6.0%)  5 (0.8%)  0 (0.0%)  0 (0.0%)  7 (1.2%) 
Cycle 3  Control  600  542 (90.3%)  45 (7.5%)  14 (2.3%)  26 (4.3%)  0 (0.0%)  5 (0.8%)  0 (0.0%)  13 (2.2%) 
Day 1  Treatment  602  539 (89.5%)  47 (7.8%)  10 (1.7%)  32 (5.3%)  5 (0.8%)  0 (0.0%)  0 (0.0%)  16 (2.7%) 
 
   
 
7 Denominator used to calculate percentages is the number of randomized patients. 
8 The PRO Not Completed column is calculated where PROEXPFL = Y and PROSCMFL is null; thus, death is excluded from the counts and percentages and 
is provided as a standalone column. 
9 When PRO data are used to evaluate clinical benefit, reasons for PRO Not Completed are based on collected data from QS.QSREASND within the study. All 
reasons for noncompletion collected during the study should be included. Counts can include patients who were on therapy and who discontinued; thus, counts in 
Table A6 may be larger than counts in Table A7 given that patients complete the PRO measure after treatment discontinuation when evaluating clinical benefit. 
10 Unknown reasons, if present, should be tabulated within the separate Reason Unknown column.  
 
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Figure A3. Available Data Rate for Clinical Benefit (Denominator = Randomized Population) 
 
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5.3.4  Completion Rate for Safety and Tolerability 
 
10 Table A7. Completion Rate for Safety and Tolerability (Denominator = PRO Expected Population)11 
Reason for PRO Not Completed,13 n (%) 
PRO 
Analysis Visit  Treatment  Expected12  PRO  PRO Not  Patient  Patient Unable  Device  Reason 
Arm  Completed, n (%)  Completed, n (%)  to Complete  Unknown,14  
(N)  Refusal  Failure 
due to AE  n (%) 
Control  600  600 (100.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%) 
Baseline 
Treatment  602  602 (100.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%) 
Control  564  542 (96.1%)  22 (3.9%)  6 (1.1%)  16 (2.8%)  0 (0.0%)  0 (0.0%) 
Cycle 2 Day 1 
Treatment  572  536 (93.7%)  36 (6.3%)  5 (0.9%)  31 (5.4%)  0 (0.0%)  0 (0.0%) 
Control  525  510 (97.1%)  15 (2.9%)  0 (0.0%)  10 (1.9%)  5 (1.0%)  0 (0.0%) 
Cycle 3 Day 1 
Treatment  542  516 (95.2%)  26 (4.8%)  5 (0.9%)  21 (3.9%)  0 (0.0%)  0 (0.0%) 
   
 
11 Denominator used to calculate percentages is PRO Expected. 
12 When PRO data are used to inform the evaluation of safety and tolerability, the PRO measure may not be expected to be completed after a patient discontinues 
from treatment as shown in the table. The PRO Expected column excludes patients who discontinued from treatment and is determined where PRO Expected 
Flag (PROEXPFL) equals Y. 
13 Reasons for PRO Not Completed are based on collected data within the study and represent reasons the PRO measure was not completed when the patient did 
not discontinue from treatment. All reasons for noncompletion collected during the study should be included.  
14 Unknown reasons, if present, should be tabulated within the separate Reason Unknown column. 
 
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Figure A4. Completion Rate for Safety and Tolerability (Denominator = PRO Expected Population) 
 
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5.3.5  Distribution of Responses 
 
11Table A8. Distribution of Categorical Responses for Item 1 (Safety and Tolerability Example)15 
PRO  PRO  PRO Not  Response Categories,17 n (%) 
Analysis Visit  Treatment Arm 
Expected16  Completed, n (%)  Completed, n (%)  Not at all  A little  Quite a bit  Very much 
Control  600  600 (100.0%)  0 (0.0%)  332 (55.3%)  220 (36.7%)  31 (5.2%)  17 (2.8%) 
Baseline 
Treatment  602  602 (100.0%)  0 (0.0%)  313 (52.0%)  228 (37.9%)  38 (6.3%)  23 (3.8%) 
Control  564  542 (96.1%)  22 (3.9%)  299 (55.2%)  188 (34.7%)  34 (6.3%)  21 (3.9%) 
Cycle 2 Day 1 
Treatment  572  536 (93.7%)  36 (6.3%)  268 (50.0%)  199 (37.1%)  41 (7.6%)  28 (5.2%) 
Control  525  510 (97.1%)  15 (2.9%)  225 (44.1%)  189 (37.1%)  63 (12.4%)  33 (6.5%) 
Cycle 3 Day 1 
Treatment  542  516 (95.2%)  26 (4.8%)  203 (39.3%)  193 (37.4%)  71 (13.8%)  49 (9.5%) 
   
 
15 Denominator used to calculate percentages for PRO Completed and PRO Not Completed is PRO Expected. Denominator used to calculate percentages for 
each response category is PRO Completed. 
16 When PRO data are used to inform the evaluation of safety and tolerability, the PRO measure may not be expected to be completed after a patient discontinues 
from treatment as shown in the table. The PRO Expected column excludes patients who discontinued from treatment and is determined where PRO Expected 
Flag (PROEXPFL) equals Y. 
17 The example response categories represent the response options for the item. 
 
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Figure A5. Distribution of Categorical Responses for Item 1 (Safety and Tolerability Example where Denominator = PRO 
Completed) 
 
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12 Table A9. Summary Statistics for Item 2 with Continuous Response Options (Safety and Tolerability Example)18 
Analysis Visit    Control  Treatment 
PRO Expected19 (N)  600  602 
PRO Not Completed, n (%)  0 (0.0%)  0 (0.0%) 
PRO Completed, n (%)  600 (100.0%)  602 (100.0%) 
Summary Statistics20 
   Mean  2.1  1.0 
Baseline 
   Standard Deviation   1.8  0.9 
   Standard Error  0.07  0.04 
   Median  2.1  1.0 
   Minimum  0.0  0.0 
   Maximum  4.1  2.0 
PRO Expected (N)  564  572 
PRO Not Completed, n (%)  22 (3.9%)  36 (6.3%) 
PRO Completed, n (%)  542 (96.1%)  536 (93.7%) 
Summary Statistics 
   Mean  7.1  5.1 
Cycle 2 Day 1 
   Standard Deviation   4.6  3.7 
   Standard Error  0.19  0.15 
   Median  7.2  5.1 
   Minimum  0.3  0.2 
   Maximum  11.8  9.8 
PRO Expected (N)  525  542 
PRO Not Completed, n (%)  15 (2.9%)  26 (4.8%) 
PRO Completed, n (%)  510 (97.1%)  516 (95.2%) 
Summary Statistics 
Cycle 3 Day 1     Mean  6.2  3.9 
   Standard Deviation   5.2  2.7 
   Standard Error  0.23  0.12 
   Median  6.6  3.8 
   Minimum  0.1  0.0 
 
18 Denominator used to calculate percentages for PRO Completed and PRO Not Completed is PRO Expected. 
19 When PRO data are used to inform the evaluation of safety and tolerability, the PRO measure may not be expected to be completed after a patient discontinues 
from treatment as shown in the table. The PRO Expected column excludes patients who discontinued from treatment and is determined where PRO Expected 
Flag (PROEXPFL) equals Y. 
20 Summary Statistics are calculated based on PRO Completed. 
 
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   Maximum  11.4  10.0 
Figure A6. Descriptive Means for Item 2 with Continuous Response Options (Safety and Tolerability Example for Physical 
Functioning)21,22 
 
 
21 The Higher Functioning and Lower Functioning labels are provided as examples for physical functioning. Labels provided within the figure should 
accurately represent the concept being measured. 
22 Error bars based on a 95% confidence internal for the mean are represented within the line plot. 
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5.3.6  Distribution of Change in Responses from Baseline 
 
13 Table A10. Distribution of Change in Response Categories from Baseline for Item 1 (Safety and Tolerability Example)23 
Change in Response Categories,25 n (%) 
PRO  PRO Not 
Analysis  Treatment  PRO 
Visit  Arm  Expected24 Completed, Completed,  Improving Improving Improving  No  Worsening Worsening Worsening 
n (%)  n (%)  1  2  3  Change  1  2  3 
542  303  132 
Control  564  22 (3.9%)  38 (7.0%)  11 (2.0%)  3 (0.6%)  38 (7.0%)  17 (3.1%) 
(96.1%)  (55.9%)  (24.4%) 
Cycle 2 
Day 1 
536  296  141 
Treatment  572  36 (6.3%)  33 (6.2%)  14 (2.6%)  6 (1.1%)  32 (6.0%)  14 (2.6%) 
(93.7%)  (55.2%)  (26.3%) 
510  261  126 
Control  525  15 (2.9%)  50 (9.8%)  24 (4.7%)  10 (2.0%)  29 (5.7%)  10 (2.0%) 
(97.1%)  (51.2%)  (24.7%) 
Cycle 3 
Day 1 
516  261  123 
Treatment  542  26 (4.8%)  44 (8.5%)  28 (5.4%)  11 (2.1%)  39 (7.6%)  10 (1.9%) 
(95.2%)  (50.6%)  (23.8%) 
   
 
23 Denominator used to calculate percentages for PRO Completed and PRO Not Completed is PRO Expected. Denominator used to calculate percentages for 
each change in response category is PRO Completed. 
24 When PRO data are used to inform the evaluation of safety and tolerability, the PRO measure may not be expected to be completed after a patient discontinues 
from treatment as shown in the table. The PRO Expected column excludes patients who discontinued from treatment and is determined where PRO Expected 
Flag (PROEXPFL) equals Y. 
25 The example response categories represent the response options for the item. 
 
39 
  Contains Nonbinding Recommendations 
Figure A7. Distribution of Change in Response Categories from Baseline for Item 1 (Safety and Tolerability Example where 
Denominator = PRO Completed) 
 
   
40 
  Contains Nonbinding Recommendations 
14 Table A11. Change from Baseline for Item 2 with Continuous Response Options (Safety and Tolerability Example)26 
Analysis Visit    Treatment  Control 
PRO Expected27 (N)  564  572 
PRO Not Completed, n (%)  22 (3.9%)  36 (6.3%) 
PRO Completed, n (%)  542 (96.1%)  536 (93.7%) 
Summary Statistics28 
   Mean  4.9  4.5 
Cycle 2 Day 1 
   Standard Deviation   4.0  1.7 
   Standard Error  0.17  0.19 
   Median  5.0  4.2 
   Minimum  -1.1  -1.3 
   Maximum  10.3  9.0 
PRO Expected1 (N)  525  542 
PRO Not Completed, n (%)  15 (2.9%)  26 (4.8%) 
PRO Completed, n (%)  510 (97.1%)  516 (95.2%) 
Summary Statistics 
   Mean  4.1  2.9 
Cycle 3 Day 1 
   Standard Deviation   5.7  5.6 
   Standard Error  0.25  0.24 
   Median  4.2  2.9 
   Minimum  -1.6  -1.4 
   Maximum  8.0  8.5 
   
 
26 Denominator used to calculate percentages for PRO Completed and PRO Not Completed is PRO Expected. 
27 When PRO data are used to inform the evaluation of safety and tolerability, the PRO measure may not be expected to be completed after a patient discontinues 
from treatment as shown in the table. The PRO Expected column excludes patients who discontinued from treatment and is determined where PRO Expected 
Flag (PROEXPFL) equals Y. 
28 Summary Statistics are calculated based on PRO Completed. 
41 
  Contains Nonbinding Recommendations 
Figure A8. Change from Baseline for Item 2 with Continuous Response Options (Safety and Tolerability Example)29 30 
 
 
29 The Improving and Worsening labels are provided as examples within the figure. Labels of directionality should align with what is provided in the scoring 
manual for the PRO measure used. 
30 Error bars based on a 95% confidence internal for the mean are represented within the line plot. 
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  Contains Nonbinding Recommendations 
5.3.7  Incidence of Healthcare Utilization 
 
15 Table A12. Incidence of Healthcare Utilization (Safety and Tolerability Example where Denominator = PRO Expected)31 
Healthcare Utilization Intervention, n (%) 
Supportive Care   Supportive Care  
PRO 
Analysis  Treatment  Randomized  Expected32  Emergency   Medications   Procedures   Other  
Visit  Arm  Patients  Department   Hospitalizations  Opiates  (e.g., Steroids,   (e.g., Palliative:  
(N)  (Describe) 
(ED) Visits  Transfusions,   Hospice,  
Growth Factors)  Nephrostomy) 
Control  600  600  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%) 
Baseline 
Treatment  602  602  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%)  0 (0.0%) 
Cycle 2 Day  Control  600  564  5 (0.9%)  2 (0.4%)  0 (0.0%)  0 (0.0%)  3 (0.5%)  0 (0.0%) 
1  Treatment  602  572  5 (0.9%)  3 (0.5%)  0 (0.0%)  1 (0.2%)  1 (0.2%)  0 (0.0%) 
Cycle 3 Day  Control  600  525  7 (1.3%)  5 (1.0%)  0 (0.0%)  0 (0.0%)  3 (0.6%)  0 (0.0%) 
1  Treatment  602  542  7 (1.3%)  3 (0.6%)  0 (0.0%)  2 (0.4%)  5 (0.9%)  0 (0.0%) 
 
 
31 Denominator used to calculate percentages is PRO Expected. 
32 When PRO data are used to inform the evaluation of safety and tolerability, the PRO measure may not be expected to be completed after a patient discontinues 
from treatment as shown in the table. The PRO Expected column excludes patients who discontinued from treatment and is determined where PRO Expected 
Flag (PROEXPFL) equals Y. 
 
43