Download Analyze This? Supporting Clinical Decisions Graphically When Not Enough Data is Available A Study Case: Challenges in NCI CTCAE Version 4 Grading

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Analyze This?
Supporting Clinical Decisions Graphically When Not Enough Data is Available
A Study Case: Challenges in NCI CTCAE Version 4 Grading
Sheila Dayog, Genentech, a Member of the Roche Group, South San Francisco, CA
ABSTRACT
Working with laboratory clinical data is challenging enough, but another challenge has arisen when applying the
updated National Cancer Institute Common Terminology Criteria, Version 4.0 for Adverse Events (NCI CTCAE).
Version 4.0 incorporates stronger clinical observation into the some of the laboratory grading descriptions, thus
removing straight forward range-based numeric algorithms. Additionally, these observations can present themselves
a number of ways and the task of programmatic laboratory grade assignment whilst considering these assessments
offers challenges. Potential for inconsistent grading exists, possibly leading to incorrect clinical data interpretation.
This paper will discuss these challenges, offering the use of SAS® graphics data visualization to assist in identifying
any discordant relationships between laboratory grade assignments and the adverse event grades that occur
throughout the conduct of an oncology clinical trial.
INTRODUCTION
An adverse event (AE) is described by the Common Terminology Criteria as “any unfavorable and unintended sign
(including an abnormal laboratory finding), symptom, or disease temporally associated with the use of a medical
treatment or procedure that may or may not be considered related to the medical treatment or procedure.” Generally
speaking, the collection of adverse events is required during the conduct of all phases of an oncology clinical trial.
In phase I trials, commonly referred to as “first-in-man” studies, the primary endpoint is entirely based on evaluating
adverse events. These events are supported by laboratory evidence in determining a recommended safe dose and
the decision is dependent upon the proper evaluation of toxicity levels. As drug development passes from early
phase into later-stage development, the overall safety assessments continue to be closely monitored. One of the
methods for measuring these assessments is to characterize severity by applying a grading scale developed by the
Common Toxicity Criteria by the US National Cancer Institute (NCI CTC). The severity scale ranges from a “mild”
event to “death”, categorized 1 thru 5 accordingly.
NCI CTCAE VERSION 4.0 CLINICAL DATA CHALLENGES
Uncertainty of laboratory grading surfaced when version 4.0 criteria required investigator clinical assessment as input
into the overall grade determination. Dependencies upon clinical assessments found in multiple data sources like
physical examinations, concomitant medications, adverse events, vital signs, and laboratory results makes
programmatic approaches challenging, subject to varying sponsor approaches and inconsistency in overall severity
categorization. Interrelating events amongst these data domains is tricky, dependent upon many factors like the
overall data collection, the reconciling of the assessment dates within a defined visit window, or the unfortunate
consideration of free-text fields which may contain relevant information.
The Cancer Therapy Evaluation Program (CTEP) within the NCI reviewed each CTCAE v4.0 term for which the
grading scale included a quantitative component. Guidance was put forth, identifying 26 events where investigator
input is required. An example of Anemia guidance is listed below, highlighting the areas difficult to programmatically
consider.
CTCAE
v4.0
Term
Anemia
Grade 1
Grade 2
Grade 3
Hemoglobin
(Hgb) <LLN
- 10.0 g/dL;
<LLN - 6.2
mmol/L;
<LLN - 100
g/L
Hgb <10.0 8.0 g/dL;
<6.2 - 4.9
mmol/L;
<100 - 80g/L
Hgb <8.0
g/dL; <4.9
mmol/L; <80
g/L;
transfusion
indicated
Grade 4
Lifethreatening
consequences;
urgent
intervention
indicated
CTCAE v4.0 AE Term Definition
A disorder characterized by an reduction in the
amount of hemoglobin in 100 ml of blood. Signs
and symptoms of anemia may include pallor of
the skin and mucous membranes, shortness of
breath, palpitations of the heart, soft systolic
murmurs, lethargy, and fatigability.
Figure 1. CTEP Guidance: CTCAE v4.0 Grading Scales with Numeric Component
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In noting the highlighted text above, difficulties can occur in relating the partial criteria of “transfusion indicated” in the
concomitant medications data collection, for example. Additionally, general signs and symptoms of “pallor of the skin
and mucous membranes, lethargy, and fatigability” may or may not be collected in the physical examination data.
“Palpitations of the heart” could be recorded in the vital signs collection as tachycardia, cardiac arrhythmia, or in the
form of an abnormal ECG assessment. These general characterizations can be easily assessed by the on-site
investigator for which all can factor into the overall assignment of grade 4. Applying programmatic algorithms,
however, to include these assessments is very difficult. Noted in the above criterion for grade 4, there is simply no
numeric algorithm in which to measure the test result. Furthermore, when studying a fairly sick subject population, it
is difficult to programmatically ascertain whether the reported assessments are or are not related to the actual
adverse event in question.
Awareness of these challenges alert programmers to the fact that grading discrepancies exist. Solutions are difficult
and are highly dependent upon the overall setup of the data collection and overall reporting. In exploring these
challenges, graphical displays can be useful in quickly identifying where gaps exist. While solutions to this problem
are not discussed, the simple identification of areas requiring further scrutiny of the data to better support clinical
decision making can be supported.
GRAPHIC ILLUSTRATION OF LABORATORY DISCORDANCE
All graphics displayed were generated using the SAS® 9.2 ODS Graphics Designer to produce quick and easy
results. Additionally, SAS® Graph Template Language (GTL) template code was created, enabling a programmer to
reproduce the code outside of the designer interface, allowing for simple reusability.
Firstly, let us consider the previous NCI CTCAE Version 3.0 grading scale where clear numeric algorithms were
straightforward in application. There are some discrepancies easily noted in the Hemoglobin results for Anemia, but
by in large, there is very little discordance between investigator assigned grades and the programmatically calculated
grades from the sponsor.
These panel graphics were created by utilizing the “add column” function within the Graphics Designer. Other
components offering ease of use include drop-and-drag functionality to allow overlay of four plots in total.
Figure 2. Illustration of minimal discordance using version 3.0 where clinical input was not required.
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Next, let us view Hemoglobin results from a protocol mandating the version 4.0 grading scale. This example
illustrates strong discordance between the investigative sites who conducts the clinical evaluation of the patient,
versus the programmatic laboratory grading assignments from the sponsoring organization.
It is not difficult to identify these discrepancies and in fact, all cases assessed by the sponsor were assigned to grade
1. The investigator reported a very different picture, with only two events being reported as a grade 1. The most
extreme case is that of the “Life-threatening” grade 4 investigator finding, unable to be replicated by laboratory results
alone.
Figure 3. Illustration of notable discordance using version 4.0 where clinical input was required.
Now that clear discrepancies have been identified, the subject that had the two-point grading difference was quickly
identified and further examined.
Referring back to the adverse event grading guidance for Anemia (Figure 1.), scrutiny of the clinical assessment data
resulted in the following:
•
Vital signs: The subject did not present with any abnormal vitals signs (e.g., shortness of breath or any
indication of heart palpitations).
•
Concomitant medications or interventional therapy: The subject did receive a blood transfusion; however the
reported transfusion administration date fell just outside of the protocol-defined amount of time for which
assessments can be considered “related” to the particular adverse event in question.
•
Life-threatening consequences or urgent interventions: Hospitalization was the action taken in response to
this particular event, as indicated in the adverse event data domain. This information may qualify for grade 4
criterion of “urgent intervention indicated”. As this particular data point was not part of the programming
algorithm, the resulting sponsor defined “mild” grade 1 differed greatly from the investigators “life-threatening”
grade 4 finding. Furthermore, as one may recall from the CTEP guidance on Anemia, it provided no numeric
component for grade 4 categorization. In this case, grade 4 laboratory results measuring Hemoglobin make for
unlikely sponsor-defined replication of the investigator grade assignment.
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CONCLUSION
Safety data collection is a key component in drug development. Without proper safety assessments and reporting,
drug development cannot move forward, ultimately affecting the approval of a safe and efficacious therapeutic.
During Phase I clinical trials, dose limiting toxicities are the primary endpoints which reflect the side effects during
treatment that are severe enough to prevent an increase in dosage or even halt study drug administration. Decisionmaking to dose escalate are entirely dependent upon the analysis of these safety events. Subsequent maximum
tolerated doses are determined which identify safe dosing levels for later-stage development. Without accurate and
proper interpretation, clinical decision-making is jeopardized. In recognizing real potential for grading differences,
sponsors should be more vigilant in data review. Graphical illustration offers a tool to assist decision making, at the
very least, identifying trends where further investigation is warranted.
REFERENCES
National Cancer Institute. Common Terminology Criteria for Adverse Events (CTCAE) Version 4.0
http://evs.nci.nih.gov/ftp1/CTCAE/CTCAE_4.03_2010-06-14_QuickReference_5x7.pdf
National Cancer Institute. CTEP Guidance: CTCAE v4.0 Grading Scales with Numeric Component
http://evs.nci.nih.gov/ftp1/CTCAE/About.html
Rodriguez, Robert N. 2008. "Getting Started with ODS Statistical Graphics in SAS 9.2.” Proceedings of the SAS
Global Forum 2008 Conference. Cary, NC: SAS Institute Inc. (Paper 305-2008)
ACKNOWLEDGMENTS
Many thanks to Mario Widel and Xiangyun Wang for guidance and encouragement.
RECOMMENDED READING
Kuhfeld, Warren. 2010. Statistical Graphics in SAS®: An Introduction to the Graph Template Language and the
Statistical Graphics Procedures. Cary, NC: SAS Institute, Inc.
CONTACT INFORMATION
Your comments and questions are valued and encouraged. Contact the author at:
Sheila Dayog
Genentech, A Member of the Roche Group
1 DNA Way
South San Francisco, CA 94080
[email protected]
SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS
Institute Inc. in the USA and other countries. ® indicates USA registration.
Other brand and product names are trademarks of their respective companies.
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