1. ClinicalTrials.gov Results Reporting from the Ground Up
[Presenter Name and contact Info]

2. Purpose of Template Presentation
This presentation was compiled by a team from several CTSA institutions. The presentation can be modified as necessary for your individual institution. You may choose to use the presentation in its entirety or utilize individual sections as needed.
This presentation addresses Results Reporting. CTSA has compiled other template presentations on Overview of ClinicalTrials.gov and how to input Registration information into the database that you can draw from as well.
Please note: Results reporting for Terminated Studies is not included in this presentation. For assistance with terminated studies see:
This slide set was created in 2013 and updated in May 2015.

3. Outline Introduction The Four Results Modules
Results Reporting Requirement
Preparing for Results Reporting
The Four Results Modules
Participant Flow
Baseline Characteristics
Outcome Measures
Adverse Events
ClinicalTrials.gov Review Process
Additional Resources

4. FDAAA Results Requirement Refresher
Required for:
FDAAA “Applicable Clinical Trials” that
study drugs, biologics, and devices that are approved, licensed, or cleared by FDA (for any use).
When:
Within 12 months of Primary Completion Date (the final data collection for the primary endpoint)
If product not approved by Primary Completion Date but is approved later, then results due 30 days after approval
Delays are possible, primarily for manufacturer or under limited special circumstances
Pending publication is NOT considered a good cause for delay
Slides on FDAAA “Applicable Clinical Trial” determination can be found in the CTSA’s slides on Registration.
The Primary Completion Date may be well before the PI thinks the study is over. There may be additional follow-up that continues for years – but FDAAA requires results data submitted within a year of the final data collection for the primary endpoint. That means getting to work on analysis and reporting quickly.
Acceptable delays MAY (but not automatically) be granted if:
-Trial reached Primary Completion Date before the drug, biologic, or device is initially approved, licensed, or cleared by FDA for any use.
-You request an extension for a “good cause”
Refer to

5. How are Results Reported?
Tables are constructed by data providers
“Stand alone” tables - must be meaningful to people who are not already familiar with the study.
No narrative conclusions
Columns are study arms
Rows are measures
Type of measure determines specific design of cells

7. Preparing for Results Reporting
Accurate Registration Entry is Essential for Results Reporting
Be sure your registration is as accurate and complete before entering results. Registration inaccuracies will be replicated in the results reporting module as some fields auto populate.
If outcomes in registration were copied directly from protocol “Aims”, as described for NIH grant applications, they may be too general for use in results reporting and should be fixed in registration to carry over more directly into Results Reporting.

8. Preparing for Results Reporting
TIP: Populating the “Detailed Description” field in your Registration record may assist in the reader’s understanding of the study and will make your Quality Assurance review more effective. Remember, the ultimate goal is clarity for the public.
TIP: If time allows, release your registration one final time to the ClinicalTrials.gov QA review team to ensure you have addressed any errors before inputting results.

9. Preparing for Results Reporting
Different Modules have Different Structures.
The ClinicalTrials.gov PRS system software is frequently updated to improve ease of use. Changes in functionality and design of data entry fields are common.
See the “What’s New” link on the main menu to learn about updates to the system

10. Preparing for Results Reporting
If you are new to Results Reporting, these general resources will help you prepare:
How to Submit Your Results homepage
Basic Results Data Elements Definitions
PRS User Guide
Located on Main Menu in database
10 minute webinars for each results module
Helpful Hints (with common study designs examples)

11. Module 1: Participant Flow

12. FDAAA: Participant Flow Definition
“A table…, including the number of patients who dropped out of the clinical trial and the number of patients excluded from the analysis, if any.”
FDAAA[Sec. 282(j)(3)(c)(i)],
The Participant Flow description. It will describe data such as # subjects enrolled, completed, terminated, lost to follow-up etc.

13. Participant Flow Purpose
Provide information about the study design by documenting the “flow” of participants through different stages of the study.
The module should account for all enrolled participants, and make it clear which participants were analyzed.
See ClinicalTrials.gov Participant Flow Module Presentation, Rebecca J. Williams, PharmD, MPH, at .html

14. Participant Flow Data Elements
Recruitment Details
Milestones
Pre-assignment Details
Milestone Title
Arm/Group*
STARTED Data*
Title
COMPLETED Data*
Description
Reason Not Completed
Period Title(s)*
Type (e.g., Death)
“Overall Study” (default) if single period
Data
This is an overview of the data elements within the Participant Flow.
Explain unfamiliar terms such as:
Recruitment details: Brief description of recruitment process (i.e., dates of recruitment process, types of locations (medical center) to provide any needed context
Pre-assignment details: Description of any significant events/approaches for study (i.e.. Wash-out, run-in) following participant enrollment but prior to group assignment. That is, provide an explanation of why enrolled subjects were dropped, excluded, etc.
While not all elements are required, all elements are encouraged to ensure the participant flow is understandable to someone who was not familiar with the study.
*Required by ClinicalTrials.gov
For definitions of these elements, see the Basic Results Data Elements Definitions:

15. Optional sections but add if it would help public understand the study better on
Participant Flow
The descriptive information for Participant flow. The background information including Recruitment Details and Pre-assignment Details as well as the descriptions of each arm in the study.
See ClinicalTrials.gov Participant Flow Module Presentation, Rebecca J. Williams, PharmD, MPH, at .html

16. Participant Flow Structure
Tabular Format
Arms/Groups – pre-populated from Protocol Section.
Period(s) – Represent different stages of study.
Milestones – Specific events/time points when # of subjects reported. Must have STARTED and COMPLETED.
Example: If your study only has one period than you would provide the title of “Overall Study” to the period and only one Participant Flow table would be needed for your record.
This is an example of a basic Participant Flow table for parallel design study (For examples of other study designs, see ClinicalTrials.gov’s Helpful Hints: Basic Results at
Tabular Format
Table showing progress of research participants through each stage of trial.
Arms
Arms/groups of study. “Copied” from Protocol section, but may be modified.
Periods
Table may consist of single or multiple periods, to represent different stages of the trial (e.g. “double-blind period”, “open-label period”).
Milestones
Specific events or times points when the # of numbers of participants are reported.
Each Period must include two milestones: Number STARTED and Number COMPLETED. Additional milestones are optional.

17. Participant Flow Structure (Multiple Periods)
EXAMPLE: If your study has 3 different periods, you would create 3 tables and provide a descriptive title for each.
STARTED & COMPLETED are required milestones. You can add others milestones to show specific events when the # of participants was reported.
You will track the # of participants that do not complete the period and provide a reason why.
Example adapted from ClinicalTrials.gov‘s Basic Results Helpful Hints, p.13 at

18. Participant Flow – What is wrong with this?
For the 1st period, there is no explanation of why some subjects did not complete the period.
In the 2nd period, the # of subjects that started does not match the # that finished the 1st period. This may be a data error. Or if there was a washout period between the two periods, you may want to add that as a separate period and explain what happened to the subjects that dropped out.
Period: First Intervention
Arm A: Drug Bupropion, then placebo
Arm B: Placebo, then Drug Bupropion
STARTED 92 95
COMPLETED 88
NOT COMPLETED 4
Period: Second Intervention
Arm A: Placebo, then Drug Bupropion
Arm B: Drug Bupropion, then placebo
STARTED 88 93
COMPLETED
NOT COMPLETED

19. Get Organized Using the Simple Form
Use one form for each period in your study to gather your data for the Participant Flow module.
One helpful tool to use to get organized before inputting results is to use the simple form. For Participant flow, each sheet of paper represents 1 period (which will be organized as 1 table within the database). Print out as many simple forms as you have periods.
Source:

20. Results Overview
Your result’s “homebase”. Here is there is overview of all 4 results modules.
On the left you have the option to view a more detailed overview. To view this for Participant flow, click on “expand section”.
This Results Section page is your home base for inputting results. You can access the 4 Results modules from here.
Click on “edit” next to Participant Flow to edit that module.

21. Participant Flow – Edit Mode
Within “edit mode”, you can scroll up and down to edit various parts of the Participant Flow. The screen is only partially shown in this snapshot.

22. Edit Mode – Edit Arm/Group
In edit mode, you can edit the Arm/Group as needed. For example, you can add an arm/group, delete an arm/group or edit the title and description of the arm/group.

23. Edit Mode – Edit Arm/Group Description
After clicking on the “edit” button to update the arm/group title and description, a text box pops up. Here is a snapshot of Arm A text box. Edit as needed and click on “OK” to save changes.

24. Edit Mode – Edit the Period
Always click on “save” at the bottom of the page!
Note: there is a button at the bottom of the page to “add a period” if needed.
Here you can edit information about the Period such as Period Title, # of participants that started and completed the period. You can also note the # that did not complete the period and why.

25. Edit Mode – Reason Not Completed
Within the Period, use the dropdown box when selecting a reason why a subject did not complete a period. There is an “other” option to select if the reason isn’t listed.

26. Edit Mode – Reason Not Completed
If you select “other”, then a blank field appears where you would explain why a subject dropped out.

27. Edit Mode – Simple but important!
At the bottom of each page in edit mode:
Save: Saves your work and brings you back to the “Results Overview page.”
Cancel: Does not save changes and brings you back to the “Results Overview page.”
A friendly reminder: Don’t forget to save.

28. Participant Flow – Quick Tips
Number of participants “started” should match “Enrollment, Actual” in protocol section
Pre-Assignment Details can be used to explain any discrepancies in Enrollment, Actual and total number of participants Started.
Specific Periods to reflect study design and to account for # of participants starting and completing each Period
Use of Milestones to convey key events
For example, number who received intervention
Reasons for non-completion
See

29. Module 2: Baseline Characteristics

30. Baseline Characteristics
“A table of demographic and baseline data for the entire trial population and for each arm or comparison group.” Note that only baseline measures for Age and Gender are required; all other baseline measures are optional.
explaining FDAAA Sec. 282(j)(3)(c)(i)

31. Description of Baseline Characteristics Module
Table of demographic and baseline data for the entire trial population and for each arm or comparison group
Accommodates different data types:
Continuous: measure of central tendency (e.g., mean) and measure of dispersion (e.g., standard deviation)
Categorical: for each category – (1) a count or (2) measure of central tendency and measure of dispersion

32. Get organized using the Templates
As with the Participant Flow, the template sheets might helpful to gather your data. This one is only for the default criteria, but there are others for Gender, Race, Ethnicity, Region, and Study Specific Measures downloadable from

33. If it’s in Table 1, it probably belongs in Baseline Characteristics
These will become Default measures
Much of the data you need will come from Table 1, if an article has been published. If not, that still may be a good way to ask your PI for the data you will need, “What would you put in Table 1, if you were publishing this trial’s results?” If s/he can articulate those fields, you can use those “simple templates to ask your data manager to run the reports necessary to fill out the templates, and the ClinicalTrials.gov baseline characteristics module.
These will become User Specified Baseline Measures

34. ClinicalTrials.gov Format
“Default” Required Measures
NCT

35. Default Baseline Characteristics
Age and Gender are Required Characteristics by default, however, best practice would include other relevant information.
Choose and display characteristics that are most applicable to your study.
Region defines “nation”, not states or regions within the U.S.
Is there a benefit to showing age in both ways? (That is, age can be expressed as either categories or as mean and standard deviation). Sometimes there is; however both ways are not required.
Even if a trial never included gender data collection, the baseline measure of gender will still need to be in the table. One approach is to use Gender, Customized and to specify a category of “Unknown” or “Gender data not collected”. The Baseline Measure Description can be used to explain why “unknown” (e.g., not collected as part of the study protocol).

36. ClinicalTrials.gov Format
Here is the way the user specified criteria will look if they are all represented by “participant”. If the units of measure are something more variable, you are more likely to have medians with standard deviations represented.

37. User-Specified Baseline Characteristics
Do include all meaningful elements that make your study understandable/ useful to others, both demographic and clinical measures, such as baseline values of outcome measures or prior and concurrent treatment characteristics.
Make sure units and scales are labeled, and understandable – (e.g. what the range of a scale is and what it means. If it’s a well-known scale, within the discipline, refer to it by name and give a citation, if necessary.)
Use Table 1, if there is a published article or draft.
If there is no article from which to work, consult with PI.
Example of a citation of a scale:
Quebec Task Force (QTF) Classification of Spinal
Disorders consists of 8 classes ranging from
Class 0 (no pain) to Class 7(spinal Stenosis)

38. Post Baseline Characteristics

39. Baseline Overview
Then use the Edit or Delete to edit each “Default Measure” to edit it or “delete” that measure. If you want to “Add Baseline Measures” highlighted texts will open up a new baseline measure which, once saved, will show up like all of the default measures and can be subsequently modified or deleted. Modify allows you to describe Title, description, measure type, measure of dispersion and unit of measure. Edit – over on the left, allows you to list the different characteristics and put in the actual data.
From Baseline Overview you can edit (fill in) or delete default measures, or you can add additional baseline study specific measures.

40. Edit Baseline Measure
If the measure states what you intended, you can go ahead, and add the data, as here.
OR you can Edit the Baseline Measure Description. Make sure you click Save to save your data. Note too, you could Add a Category (which could be a subset, or could be more like a period.)

41. Baseline doesn’t always mean only at the beginning of the study
More than one period or time point can be considered “baseline” in studies which follow more complicated protocols:
Crossover
Dose escalation
Factorial
Multiple Period
That is, not every one of these designs would require posting multiple baselines, but there may be times when the responsible party feels that to have a clear understanding of the findings of the study, it helps to show how baseline characteristics differed between one portion of the study and another.

42. Example of Multiple Baselines shown
Reporting Groups
Description
Sorafenib
(Nexavar,
BAY )
Inpatient dose escalation of sorafenib from 400 mg orally twice daily (bid) for the first cycle, 600 mg bid for the second cycle and 800 mg bid until disease progression, unacceptable toxicity or withdrawal of consent. Each cycle is 28 days. Dose reductions due to toxicities were allowed.
Reporting Groups
Description
Sorafenib
(Nexavar,
BAY
Inpatient dose escalation of sorafenib from 400 mg orally twice daily (bid) for the first cycle, 600 mg bid for the second cycle and 800 mg bid until disease progression, unacceptable toxicity or withdrawal of consent. Each cycle is 28 days. Dose reductions due to toxicities were allowed.
Cycle 1 (28 Days)
Sorafenib (Nexavar, BAY )
STARTED 83
COMPLETED 52
Not Completed 31
Baseline Measures
Sorafenib (Nexavar, BAY
Number of Participants 83
Age Continuous
[units: years]
Median (Full Range)
Cycle 1 (n=83)
61 (33 to 80)
Cycle 2 (n=52)
63 (33 to 72)
Cycle 3 (n=44)
55 (33 to 72)
Cycle 2 (28 Days)
Sorafenib (Nexavar, BAY )
STARTED 52
COMPLETED 44
Not Completed 8
This slide, coming from the Train-the-Trainer workshop slides, shows using “Categories” for multiple baseline measures of age, as the baseline for different cycles of the trial. You can see, in it, that the population of participants in the study is diminishing at each of the cycles, and therefore the median age is changing as well. By using “categories” the results reporter could show those three populations more clearly than by using one baseline.
Cycle 3 (28 Days)
Sorafenib (Nexavar, BAY )
STARTED 44
COMPLETED 33
Not Completed 11
From supplemental slide provided at Train-the-Trainer workshops; courtesy of ClinicalTrials.gov.

43. Using Categories for Multiple Periods/ Multiple Baselines
Note how when another Category is added, it needs a title as well as data. Remember to save!

44. Important Quality Checks
Review record to ensure:
Categories do not overlap and all categories are presented
Range and direction of scores in baseline characteristics description are explained
Terms are understandable to the general public. Use footnotes if necessary to describe a score.

45. Module 3: Outcome Measures & Statistical Analyses
This module provides some high level guidance on entering outcome measures, and provides examples of outcome measures for a parallel design study.

46. FDAAA*: Outcome Measures
“…a table of values for each of the primary and secondary outcome measures for each arm of the clinical trial…including the results of scientifically appropriate tests of the statistical significance of such outcome measures.”
[Sec. 282(j)(3)(C)(ii)]
*Food and Drug Administration Amendments Act of 2007

47. Outcome Measures Purpose
The Outcome Measures module displays the results and associated statistical analyses for each prespecified primary and secondary outcome measure. Other outcome measures may also be included.
See ClinicalTrials.gov Outcome Measures and Statistical Analyses Module Presentation, Deborah A. Zarin, M.D. at

48. Outcome Measures – Data Elements
To set up table
Arm/Group title* and Description
Number of Participants Analyzed*
To Describe specific Outcome Measures
Outcome Measure Title*
Outcome Measure Description
Unit of Measure*
Outcome Measure Time Frame*
Measure Type (e.g., mean, median)*
Measure of Dispersion/Precision (e.g., Standard Deviation)*
Data*
This slide lists the data elements associated with the outcome measures module. Items with a red star are required by ClinicalTrials.gov.
*Required by ClinicalTrials.gov

49. Outcome Measures Data Elements
Outcome Measure Type*
Options
Primary
Secondary
Other Pre-specified
Post-hoc
Outcome Measure Reporting Status*
Outcome Measure Safety Issue? (Y/N)
Primary or secondary outcome measures are copied from protocol section. If you need to add other outcome measures, you can add them here. (Note: outcome measures must be specific, measurable, and have a specific time frame in which they are measured. The following slides will cover this topic in greater detail.)
Status: indicates whether results have been posted on the pubic ClinicalTrials.gov webpage yet. Remember that each record is required to have “posted” data for at least one outcome measure. (Also remember posted results has its own tab on the public ClinicalTrials.gov webpage)
Here is the excerpt from FDAAA on which outcomes measures are required:
*Required by ClinicalTrials.gov

50. Field = Part of Outcome Measure Title
Field = Timeframe
This is a framework for thinking about specificity of the outcome measure described. Along the left, you can see that for any level of specificity, a specific time frame is necessary. Then going from top to bottom, you can see increasing levels of specificity. The highest level is the domain, and in this case we’re going to report a measure about anxiety. That is not very specific though. The next measure is level two and is designed to say what specifically was used to measure anxiety and in this case the Hamilton Anxiety Rating Scale was used. The third is the specific metric, which is what was measured in the individual participants in each arm of the trial. For this example, we are going to look at change from baseline. Finally, the question is how are the data across participants in each arm aggregated? In this case it was a categorical measure, and the category chosen was the proportion of subjects in each arm with a decrease of greater than or equal to 50 percent. As you move down the diagram, you are getting more and more specific. It is extremely important that when registering the outcome measures and reporting the results that the information be entered with as much specificity as possible.
Field = Part of Outcome Measure Title
Draft Outcome Measure Title: Proportion of Participants with Decrease in Anxiety ≥ 50% on the Hamilton Anxiety Rating Scale

51. Outcome Measure Outcome measure information:
Please be specific as possible.
Title: include the name of the specific measure. Avoid using verbs, that is, do not put “To determine…”
Time Frame: must have a time point at which the outcome is assessed for the specific metric used (hours, days, weeks, years) Hint: specify which study day it is measured - do not use “until the end of study or death”.
Description: describes what will be measured, not why it is measured. If the outcome measure is a questionnaire or scale, provide the range and what low or high scores mean.
Safety Issue: Is this outcome measure assessing a safety issue?
This slide shows the data fields that must be entered for an outcome measure. If the outcome measure in the protocol is framed as a hypothesis, including a verb, re-write the outcome measure into a specific measure. (Hint: Look in the statistical section of the protocol to find more specific outcome measures.)
If the Outcome measure is using a scale, the name of the scale should be provided in the Outcome Measure Title. The range and direction of scores (0=worst, 10=best) are provided in the Outcome Measure Description. The Unit of Measure is “units on a scale,” if no other unit was used.
If the Outcome Measure expresses a change, specify two time points in the Time Frame (e.g., week 0 and week 52).
For more information on this topic, please refer to “ClinicalTrials.gov Review of Protocol Submissions,” especially the section on Outcome Measures and Outcome Measures time frames on p

52. Example of an Outcome Measure What is wrong with this?
The top example is too vague and not specific enough. The bottom example is a better example of how an outcome measure should be expressed. Before this Outcome Measure is complete, you should describe the Dysphagia Questionnaire in Description box, that is, the range and direction of scores. The criteria used to define “complete response to dysphagia” should be described in the Outcome Measure Description (this may be the specific score achieved on the dysphagia questionnaire).

53. Example of an Outcome Measure What is wrong with this?
The top example is too vague and not specific enough. The bottom example is a better example of how an outcome measure should be expressed. If appropriate, describe how a complete histologic response was determined.

54. Get Organized Using the Simple Form
As you start to prepare to enter your data, you may find the Outcome Measure Template helpful as a worksheet to plan data entry. This template and others are available at
Where to get information for the module: Protocol (study design, methods, statistical section); manuscript or published journal article (abstract, methods, results [text and tables], statistics section). Note: sometimes p values can be in figures or in figure legends. If a manuscript or article has not been written yet, you might have to work from data tables from the statistician.
Use one simple form for each Outcome Measure you are entering into the database.

55. Outcome Measures – Journal Article Format
This is an example of how outcome measures are displayed in journal articles. This data cannot be entered into ClinicalTrials as one outcome measure, it would require several outcome measures to capture all of the data. (Note: ClinicalTrials.gov cannot display graphs such as Kaplan-Meier curves, or box and whisker plots. You must obtain the numeric data to enter the outcome measure.)
Pappas PG, Chetchotisakd P, Larsen RA et al. Clin Infect Dis. 2009
© 2009 Infectious Diseases
Society of America
Journal articles have similar information to ClinicalTrials.gov, just presented in a different format!

56. Outcome Measures – ClinicalTrials.gov Format, Public View
This is an example of how a completed outcome measure would look (public view on as compared to a journal article presentation.
NCT

57. ClinicalTrials.gov Format (cont.), Public View
This is an continued example of how a completed outcome measure would look, note that the data are presented in a table. It is not possible at this time to present data as graphs, box and whisker plots, etc.
NCT

58. Data Elements – Statistical Analyses*
Although the data element of statistical analyses is “optional”, depending on the study protocol and statistical analysis plan it may be “required”.
Ideally, every protocol should have a statistical analysis plan (SAP). Therefore, what analyses were planned should be reported in ClinicalTrials.gov. However, not all fields will be required; this is dependent on the statistical test involved. To determine what statistical tests were performed, review the statistical methods section in the protocol, the SAP, and the journal article, if available, or speak to the study statistician. P-values and other statistical tests can be found in the results tables in the journal article.
For non-statisticians, a good reference book is:
Lang, Thomas A, and Secic, Michelle. How to Report Statististics in Medicine: Annotated Guidelines for Authors, Editors, and Reviewers. Philadelphia: American College of Physicians, 2006.
*The law requires scientifically appropriate tests of statistical significance.
Basic Results Data Elements Definitions:

59. Go to Outcome Overview to Add Statistical Analysis
To enter the statistical analysis, return to outcome measure screen view, and click on “Add Statistical Analysis.”

60. Add Outcome Statistical Analysis
Generally you must check at least 2 groups, or you can check all groups if appropriate (omnibus analysis). If you get error messages, enter the required data and then save (“OK” button at bottom of screen) and the error messages will disappear.

61. Add Outcome Statistical Analysis
Choose the statistical test from the drop-down box.
In the next set of boxes, complete the fields appropriate for the statistical test. (Note: If only a p-value is being entered as shown in this example, you only need to enter the p-value and the statistical test of hypothesis. You do not need to enter an estimated value for p-values, this is for other statistical tests.) It is ok to enter a non-statistically significant p-value. If a statistician is available, get one to help you.

62. Completed Outcome Measure and Statistical Analysis
This slide shows a completed outcome measure and the associated statistical analysis.

63. Outcome Measures and Statistical Analyses – Quick Tips
Results, including study or outcome conclusions, are not provided in narrative form.
The Title and Description are comprehensible and descriptive (e.g., Arm A, B, C is not informative).
For measures obtained using a scale:
Name of scale is provided in “Measure Title.”
Range and direction of scores (0 = worst; 10 = best) are indicated in “Measure Description.”
“Unit of Measure” is “units on a scale” if no other unit.
See

64. Module 4: Adverse Events

65. Description of the Adverse Events Reporting Module
The Adverse Events Module is a summary of results for SAEs and AEs that are collected during the study
Data should be tracked and reported in accordance with the procedures for data collection as defined in the protocol
Adverse Events are reported as summary data at the end of the study
SAEs and AEs are presented in separate tabular format
Not “real time” adverse event reporting while the study is ongoing
Use the Adverse Events Reporting Additional Description to provide information on analysis population, methods of event data collection and other details
The statute requires adverse event reporting regardless of relatedness for any event that occurs in more than 5% of the participants in at least one arm, even if the protocol does not require this data collection. If there are differences in statutory requirement and what was done in protocol, this can be explained in the Adverse Events Reporting Additional Description.

66. Adverse Events Reporting
Adverse Event (AE)
“Unfavorable changes in health, including abnormal laboratory findings, that occur in trial participants during the clinical trial or within a specified period following the trial. Two types of adverse event data are to be reported: "Serious" and "Other (Not Including Serious)" adverse events.”

67. Adverse Events Reporting
Serious Adverse Events (SAEs)
A table of all anticipated and unanticipated serious adverse events grouped by organ system, with number and frequency of such events in each arm of the trial
Other Adverse Events (AEs)
A table of anticipated and unanticipated adverse events that exceed 5% within any arm of the trial, grouped by organ system, with number and frequency of such events in each arm of the trial.

68. Adverse Event Reporting
Adverse Events are entered by 2 modes
Manual entry directly into the PRS browser based interface
Download and Upload link
Use the predefined Adverse Events Simple form for preparation
Simple form (template) is helpful in organizing results entry
Data is segmented and compiled by
Frequency of Event
Total Number of events
Number of events (deaths, myocardial infarction, fever, etc.)
Number events per participant
Frequency of events Total Number Affected by Any Serious Adverse Event* (per arm/group): Overall number of participants affected by one or more Serious Adverse Events. Total Number of Participants at Risk for Serious Adverse Event* (or Number of Participants at Risk for each Serious Adverse Event Term required) (per arm/group) : Overall number of participants included in the assessment of serious adverse events during the trial (i.e., the denominator for calculating frequency of serious adverse events)

69. Getting Organized Using the Serious Adverse Events Template

70. Using the Other Adverse Events Template
Getting Organized
Using the Other Adverse Events Template

71. Adverse Events
Frequency Threshold for Reporting Other (Not Including Serious) Adverse Event
The frequency of Other (Not Including Serious) Adverse Events that, when exceeded within any arm or comparison group, are reported in the results database for all arms or comparison groups. The number must be less than or equal to the allowed maximum (5%), and must not include any symbols (e.g., >= , %). Expressed as a percentage. For example, a threshold of 5 percent indicates that all Other (Not Including Serious) Adverse Events with a frequency greater than 5 percent within at least one arm or comparison group are reported.
Total Number Affected by any Other (Not Including Serious) Adverse Event above the Frequency Threshold
Overall number of participants affected by one or more Other (Not Including Serious) Adverse Events above the specified Frequency Threshold (e.g., 5%).

72. Manual Entry of Adverse Events
Click Edit Results to access Adverse Events Module

73. Manual Entry of Adverse Events
Within Edit Results, Click Edit to access Adverse Events Module

74. Manual Entry of Adverse Events
Click Edit to enter Time Frame, Source and Assessment Type Information
Click Add here to build the Serious Event List
Click Edit here to enter SAE Totals

75. Manual Entry of Adverse Events
Enter Adverse Event Terms etc. * denotes required fields

76. Manual Entry of Adverse Events
Click Edit to enter results for each event
Entering Events is not required
A Note will appear when Events is left blank.
When results are availble, please enter Events

77. Downloading/Uploading Adverse Events
Click “Download or Upload Adverse Events” Link

78. Download Adverse Events Template
Download produces a Tab Delimited file that can be opened in a spreadsheet program. Upload accepts a properly formatted Tab Delimited file that you supply and loads the content into the specified Adverse Events table.
Open the file using a spreadsheet program such as Excel. (If you open the file with a program like Wordpad, you can use cut/paste to transfer the content into the spreadsheet.)
Do not change the names or placement of column headers in the file or the upload feature in the PRS will not work.
If the contents are for the Serious Adverse Event table, then column one (adverseEventType) of every row must contain the word "Serious".
If the contents are for the Other (Not Including Serious) Adverse Event table, then column one (adverseEventType) of every row must contain the word "Other".
Rows may be added below the headers and existing rows (not header rows) may be deleted or changed.
Add Adverse Event Terms and related information as rows in the spreadsheet with one row per term.
Save the file as "Text (Tab Delimited)"

79. Sample AE Template Download
Note adverseEventType row must contain “Other” for each row (or “Serious” for SAE)
Headers must not be changed
Add, delete, edit existing rows and when complete, save file as text (tab delimited)

80. Upload Adverse Events Upload the file
Select your completed Spreadsheet using Browse and select Open
Select Adverse Event Type (Serious or Other)
Select the file format (Excel Workbook or Excel )
Select the green Upload button
The upload feature is quite sensitive to the format of the file. The download file serves as a guide to the proper format.
The upload feature does not allow you to change Arm/Groups (i.e., columns). Your upload will be rejected if the columns in your file do not match the order and content exactly as specified in the template.
By changing the rows in the file, you can effectively add, delete, or modify the information about each adverse event.
The entire contents of the adverse event table in the PRS will be replaced by the contents of the upload file.

81. Serious Adverse Events (Public site view)

82. Other Adverse Events (Public site view)

83. Important Quality Checks
The Total Number of Participants at Risk should be equal to the Total Number of participants Started. (Refer to the Participant Flow)
Adverse Events Reporting Additional Description can be used to explain the Analysis Population (any discrepancies in total number of participants Started Participant Flow).
The number of Events is not required when entering Adverse Events, however a Note will occur for each results entry field that is left blank. You are not required to address Notes in order to submit your record to ClinicalTrials.gov.
Adverse Events results are reported as a summary at the end of the study , not real-time while the study is ongoing.
Be consistent when entering event names for AEs (for example Anemia, angina) Enter either all lower case or upper case letters. Adverse event names will appear in the case as they are entered.
Corrections for text fields in the AE module must be corrected using Modify under event.
When using the Download or Upload Adverse Events link, the upload will be rejected if the columns in your file do not match the order and content in the PRS.
Frequency of events Total Number Affected by Any Serious Adverse Event* (per arm/group): Overall number of participants affected by one or more Serious Adverse Events. Total Number of Participants at Risk for Serious Adverse Event* (or Number of Participants at Risk for each Serious Adverse Event Term required) (per arm/group) : Overall number of participants included in the assessment of serious adverse events during the trial (i.e., the denominator for calculating frequency of serious adverse events)

84. ADDRESSING QA COMMENTS

85. ClinicalTrials.gov PRS QA Process
When data entry is complete, the Responsible Party approves and releases the registration record.
After the registration record is released, the ClinicalTrials.gov QA staff performs a manual review of the record for consistency and quality. (See Protocol/Results Review criteria).
The Quality Review focuses on logic, internal consistency, apparent validity, meaningful entries, and formatting.

86. ClinicalTrials.gov PRS QA Process
If QA identifies issues requiring attention, comments are noted and the study record is reset to “In Progress” by ClinicalTrials.gov.
The record owner and RP will receive notifications from ClinicalTrials.gov regarding review comments and current record status.
Identified issues must be addressed, and the Responsible Party must approve, and re-release the record.
If the record passes ClinicalTrials.gov QA, it is Released for publishing on the ClincalTrials.gov website.

87. ClinicalTrials.gov PRS Results Data Flow
Data Provider Inputs Results Data. RP “approves” & “releases” data to ClinicalTrials.gov.
ClinicalTrials.gov conducts QA review of data within 30 days.
APPROVES: ClinicalTrials.gov posts data on public website.
RESETS to “in-progress”: ClinicalTrials.gov provides PRS comments to Data Provider.

88. Accessing PRS Review Comments
Records with PRS Comments may be accessed using the “PRS Review Comments” link from the Records drop down box.

89. Accessing PRS Review Comments

90. Accessing PRS Review Comments
Click the Edit Link

91. ClinicalTrials.gov PRS Review Comments
Each comment is logged under
related module
Comments are highlighted in Pink
At the top of the list of comment, you can choose to show only those sections with comments. As there currently is no direct link from the comments back to the problem areas, it is recommended to print a copy of the comments to refer to when correcting the record. Please note that sometimes one comment may refer to multiple corrections needed in the record.

92. ClinicalTrials.gov PRS QA Comments
Common Areas for QA Comments:
General
Expand acronyms and abbreviations
Review for spelling errors
Proper formatting
Content
Brief title is in lay language and includes condition and interventions evaluated in this study
Review for internal consistency
Check overall recruiting status and compare it to the study start date, the primary completion date, and the study completion date listed

93. ClinicalTrials.gov PRS QA Comments
Outcome Measures
Enter what is being measured, not why it is being measured
General terms as “safety,” “tolerability,” or “feasibility” are not sufficient
Time frame, must be specific
“At Follow up” or “end of study” is not specific
Most outcome measures have one time point
Each unique combination outcome measure and time frame should be entered separately
Time frame for change of outcome measure
Time frames indicate time period over which change occurred– generally two points should be entered
Time-to-event should include a time over which the event will be assessed
When entering data into ClinicalTrials.gov
Enter arms and interventions
Specify each study arm first
Specify each intervention
Assign each intervention to one or more study arms

94. Sample QA Comment Examples
Please note that the Primary Outcome Measure is vague. The following is a definition for Primary Outcome Measure: "Specific key measurement(s) or observation(s) used to measure the effect of experimental variables in a study, or for observational studies, to describe patterns of diseases or traits or associations with exposures, risk factors or treatment." Please modify the Primary Outcome Measure, as appropriate, and re-release the record
The Outcome Measure is reporting a change. Please provide complete information:
Specify relevant time points (e.g., baseline and 48 weeks) in the Time Frame.
Specify change calculation details in Outcome Measure Description if more than two time points.

95. Sample QA Comment Examples continued
The Time Frame provided is not specific. The Time Frame should specify the specific time point(s) at which the outcome measure was assessed and for which data are presented. (e.g.,"up to 2 weeks"). An average time period may also be acceptable.
The Measure includes a scale. Please complete the scale information:
Specify Full Scale Name and Construct (i.e., indicate what the scale measures if not clear from name).
Include all scale ranges (i.e., minimum and maximum scores) required to interpret any values in the data table. For example, if the *total* score is reported, the *total* range should be provided. If subscale scores are reported, the range for each subscale should be provided.
For each scale range provided, specify which values are considered to be a better or worse outcome (i.e., For the minimum and maximum values in the range, do higher values represent a better or worse outcome?)
Use "Units on a scale”

96. Sample QA Comment Examples continued
Please review entire record and expand all acronyms and abbreviations (and include acronym in parentheses) at least the first time used in *both* the Protocol and Results section. The Spelling link at the top of the "Edit Protocol Record" page can be used to help locate and spell out unexpanded acronyms. (e.g., "INR")
The Enrollment number in the protocol section conflicts with the number of participants Started in the Participant Flow module. Please verify and correct either or both of these data elements, or otherwise explain the apparent discrepancy in Pre-Assignment Details, as appropriate (e.g., if 12 participants were excluded for the given criteria, please make this explicit).
Number of Participants Analyzed is not consistent with numbers provided in any of the rows in the Participant Flow Module. Please verify numbers and/or explain the discrepancy in Analysis Population Description, as appropriate.

97. QA Comment- Quick Tips QA Comments can be accessed from
the Main Menu “QA Review Comments”
link or within the record by clicking
To locate the specific issues noted in the PRS Review Comments, use the Expand Selection link
When addressing QA Comments regarding the number of participants in any section, start with the Participant Flow and take a systematic approach through the modules to make certain all participants are accounted for including the Enrollment Number from the Protocol Section.
If you ever have questions on QA comments, you may contact your institutional contact and/or for assistance.

98. This slide set was made possible by a collaboration of CTSA organizations (Mayo Clinic, Partners, University of Michigan Medical School, Duke University) and the National Library of Medicine.   
The Clinical and Translational Science Awards Program (CTSA) is part of the Roadmap Initiative, Re-Engineering the Clinical Research Enterprise and is funded by the National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH).