Sunday, September 09, 2012

Adverse Event Collections for Screening Failures

In the last issue, I stated that a more accurate definition of Screening Failures may be as following “Potential subjects who were screened for the study participation, but were not enrolled (randomized or dosed) for the study”

Once we know the definition of the screening failures, the next question is about the data collection for screening subjects in clinical trials. How much data should we collect for screening failures? Should AE be collected and entered into the clinical database? for screening failures, should SAE be reported to regulatory agency and should SAE narratives be written?


I have a question related to the collecting and recording of screening failure adverse events during clinical trials. I work for a data management group of a medium sized pharma company. Currently we collect and database all AEs that occur to screening failures in our clinical trials.
On further research I have not been able to find any regulation or guidance document that requires this. Can you tell me what the FDA position is on this?
Should we
1) Record and database all AEs for screening failures?
2) Not record and database AEs for screening failures?
Clinical Site Quality Control
3) Not record or database and put systems in place that can detect an unusually large number of AEs in a specific site for screening failures.


I'm not sure what you mean by "screening failure adverse events." Are you referring to an intercurrent illness or condition that occurs between the time that the subject was enrolled but before randomization that leads to the subject being considered a screening failure? If so, we do not consider these to be adverse events; because the subject has not yet received any study drug, it would not be "associated" with the use of the test article. Nevertheless, because the intercurrent illness or condition affects the subject's eligibility for the study, it should still be recorded by the study site and reported to the sponsor. The clinical investigator should also ensure that the subject receives appropriate medical care, either by providing it directly or by referring the subject back to the subject's primary care physician.

The answer above was not all accurate. During the screening period, subjects were exposed to the screening procedures which could cause adverse events; subjects could have emotional changes / nervousness / anxiety just because of the study participation;  subjects could be asked to change their regular treatment/medication to meet the inclusion /  exclusion criteria that in turn could cause side effects (such as withdrawal effect). Therefore, it is very possible for subjects to develop adverse events during the screening period. In other words, adverse events can be reported for screening failure subjects even though the subject has not yet received any study drug.

Different situations for adverse event collections can be listed in the table blow:

All Subjects Screened
Eligible for study participation
Screening failures
Adverse events during the screening period starting from ICF signing
Non treatment-emergent adverse events
Non treatment emergent adverse events
Adverse events reported after the first dose of the study drug
Treatment-emergent adverse events
Statistical analysis
Non-treatment emergent and treatment emergent adverse events are summarized separately
Not included in statistical analysis since screening failures are not included in safety population

From the table above, we can see the followings:

1. For subjects who are eventually randomized and receive the study medication, all adverse events need to be captured and recorded in the clinical database starting from the informed consent signing. By comparing the AE onset date/time with the first dose date/time, the AEs can be separated as non-treatment emergent AEs and treatment emergent AEs.
For this group of subjects, it is accurate to say that any AE occurred after the informed consent signing should be recorded.

2. For screening failures, whether or not the AEs reported during the screening period should be recorded in the clinical database is up for debating.

  • Some companies do not record any data into the clinical database for screening failures. All information about the screening failures are maintained in a screening log.
  • Some companies record only the key information into the clinical database for screening failures. The key information may be demographics, reason for screening failures
  • Some companies choose extreme conservative way and record all available information for screening failures in the clinical database.

Unfortunately, there is no clear regulatory guidance on what information (especially adverse events) should be recorded into the clinical database for screening failures. The languages from In ICH E3 (STRUCTURE AND CONTENT OF CLINICAL STUDY REPORTS), seems to suggest that for screening failures, only information needed may be the reason for screening failures (and adverse event could be one of the reasons for screening failure).

The most extreme (or conservative) situation could be that in a study, the SAE narratives would be written for all subjects including the screening failures. In order to have sufficient information for SAE narrative writing for screening failures, all details about SAE and the ancillary information (physical example, medical history, vital signs, laboratory, …) would need to be collected. A lot of time and efforts would be spent on the data collection, but the collected data would not be very useful or at least not relevant to the purpose of the study since in the end, the screening failures would be excluded from the safety population for the safety analysis. This practice of collecting almost every detail about the screening failures is not wrong, but is not an efficient way for conducting the clinical trials.

Nowadays, the industry trend is moving toward to being compliant with CDISC standards (SDTM, aDaM). There seems to be a lot of confusions about whether or not data for screening failures should be included in the database and if so, where to include. The following weblinks from CDISC Public Discussion Forum show the confusions.

 To summarize, for screening failures, the best way for data collection may be to collect only the demographic information and the reason for screening failures in clinical database. The reason for screening failure should include a category of “AE” since subject can be screening failure due to AE (or precisely non-treatment emergent AE) during the screening period. The details about the AE / SAEs for screen failure subjects are not necessary to be entered into the clinical database.

Thursday, September 06, 2012

Definition of Screening Failures in Clinical Trials

In all clinical trials, the typical process starts with a screening period. The screening period starts with the signing of the informed consent. During the screening period, inclusion/exclusion criteria for the study participation will be checked / tested. Subjects who meet all inclusion criteria and do not meet any exclusion criterion will be eligible to be randomized (in randomized trial) or to be dosed (in non-randomized trial). Those who are not eligible for randomization or dosing will be considered as ‘screening failures”.

It seems to be a straightforward concept. However, there could be confusions if there are subjects who are not randomized or dosed due to other reasons (for example consent withdrawal, family relocation, death during the screening period,…). These situations may not be part of the inclusion/exclusion criteria, but still cause the subjects not to be randomized or dosed.

What is the definition of “screening failures”? Will screening failures only refer to subjects who do not meet the inclusion/exclusion criteria?

In the most recent version of CDISC Clinical Research Glossary, the term Screening (of Subjects) is defined as “A process of active consideration of potential subjects for enrollment in a trial’ and the term Screen Failure is defined as “Potential subject who did not meet one or more criteria required for participation in a trial.” This definition of Screening Failure is accurate only if all other situations (such as consent withdrawal, lost to follow up,…) are part of the inclusion/exclusion criteria.

In ICH E3 (STRUCTURE AND CONTENT OF CLINICAL STUDY REPORTS), while no definition of Screening Failures are provided, it has the following statement and the example flow chart.

“…It may also be relevant to provide the number of patients screened for inclusion and a breakdown of the reasons for excluding patients during screening, if this could help clarify the appropriate patient population for eventual drug use.”

The annex IV b above implied that there could be multiple reasons for screening failures and inclusion/exclusion criteria would just be one of these reasons.

For example, in a clinical trial, we could have a case report form to ask the reasons for screening failures and we could have the following list of reasons:

Primary reason for screening failure:
  • Adverse Event
  • Patient Non-compliance
  • Consent Withdrawn
  • Inclusion/exclusion criteria not met
  • Lost to follow-up
  • Death
  • Other

Therefore, a more accurate definition of Screening Failures may be as following “Potential subjects who were screened for the study participation, but were not enrolled (randomized or dosed) for the study”

INSET statement in SAS Procedures

Recently, I find out how convenient to include some summaries statistics in a statistical graph with a statement called INSET. An INSET statement places a box or table of summary statistics, called an inset, directly in a graph created with a CDFPLOT, HISTOGRAM, PPPLOT, PROBPLOT, or QQPLOT statement. INSET statement is available in many SAS procedures (Proc Univeriate, Proc Boxplot, Proc Lifereg,...).
If we run the following program in SAS, the INSET statement used in Proc Univariate will place a box on the left corner of the CDF graph to indicate the mean and standard deviation.
data Cord;
label Strength="Breaking Strength (psi)";
input Strength @@;
6.94 6.97 7.11 6.95 7.12 6.70 7.13 7.34 6.90 6.83
7.06 6.89 7.28 6.93 7.05 7.00 7.04 7.21 7.08 7.01
7.05 7.11 7.03 6.98 7.04 7.08 6.87 6.81 7.11 6.74
6.95 7.05 6.98 6.94 7.06 7.12 7.19 7.12 7.01 6.84
6.91 6.89 7.23 6.98 6.93 6.83 6.99 7.00 6.97 7.01
title 'Cumulative Distribution Function of Breaking Strength';
proc univariate data=Cord noprint;
histogram strength /normal;
cdf Strength / normal;
inset normal(mu sigma);
 The following are more examples of using INSET statements:

Monday, September 03, 2012

Free Lectures on Statistics and Medical Research

Now that we are in the internet era, the learning is not limited to be in the school. There are great resources on the web. The elite universities now post their video lectures for the public.

One great resource for mathematics/statistics and varriety of other topics is which features the lectures from Universities such as Harvard, MIT, Yale, Stanford,... For statistics,  there are six classes listed. Unfortunately, there is no topic specifically to the biostatistics. Another resource is open course which currently listed 500 free online courses from top universities.

For biostatistics, while there is no video lectures, there are recorded lectures in mp3 format. For example, there are five biostatistics classes listed at
For topics in medical research (not necessarily clinical trials), there are more resources available.