TABLE OF CONTENTS
I.
INTRODUCTION
II.
IDENTIFYING STUDIES FOr INCLUsion IN THE
CLINICAL STUDIES SECTION
A. Studies To Include in the Clinical
Studies
Section
B. Studies Not To Include in the
Clinical Studies
Section
III.
Describing Studies in the Clinical
Studies Section
A. General
Principles
B. Describing the Study
Design
C. Summarizing Study
Findings
D. Presenting Data for Different Types of
Outcomes
E.
Implied Claims and Advertising and
Promotional Considerations
F.
Updating the Clinical Studies
Section
APPENDIX
INTRODUCTION
GRAPHS
TABLES
Guidance for Industry
Clinical Studies Section of Labeling for Prescription Drug
and Biological Products — Content and Format
This
guidance represents the Food and Drug Administration's (FDA's)
current thinking on this topic. It does not create or confer
any rights for or on any person and does not operate to bind FDA
or the public. You can use an alternative approach if the
approach satisfies the requirements of the applicable statutes
and regulations. If you want to discuss an alternative
approach, contact the FDA staff responsible for implementing
this guidance. If you cannot identify the appropriate FDA
staff, call the appropriate number listed on the title page of
this guidance.
This guidance is intended to assist
applicants in deciding (1) what studies should be included in the
CLINICAL STUDIES section of prescription drug
labeling, (2) how to describe individual studies, and (3) how to
present study data, including presentation of data in graphs and
tables. This guidance is intended to make the CLINICAL STUDIES
section of labeling, as described in the final rule amending the
requirements for the content and format of labeling for human
prescription drug and biological products (21 CFR 201.56 and
201.57),
more useful, and to promote consistency in the content and format
of the section across drug product classes and within drug classes
and indications. This guidance also calls attention to the
advertising and promotional implications of data and statements
contained in the CLINICAL STUDIES section.
The
principal objective of labeling is to provide the information that
is most useful to prescribers in treating their patients. In some
cases, making the information in the CLINICAL STUDIES
section of labeling more useful to prescribers could warrant
significant departures from past labeling practices.
FDA's guidance documents, including this
guidance, do not establish legally enforceable responsibilities.
Instead, guidances describe the Agency's current thinking on a
topic and should be viewed only as recommendations, unless
specific regulatory or statutory requirements are cited. The use
of the word should in Agency guidances means that something
is suggested or recommended, but not required.
The CLINICAL STUDIES section of labeling must
discuss those clinical studies that facilitate an understanding of
how to use the drug safely and effectively (21 CFR
201.57(c)(15)). This is usually accomplished by providing
concise, accurate summaries of information from studies concerning
a drug’s effectiveness (and sometimes safety) that practitioners
consider important to clinical decision making. Generally, this
should include information from the adequate and well-controlled
studies that demonstrate the effectiveness of the drug for its
approved indication. This section of the labeling is not intended
to describe all available effectiveness data. Additional studies
that reach the same conclusion should be omitted or described
briefly without detail. If there are multiple studies that address
the same effectiveness issue, the subset selected for presentation
should ordinarily reflect the overall conclusions derived from the
database as a whole (e.g., not suggest a larger treatment effect
than the database as a whole).
The following are the types of
adequate and well-controlled studies
that should usually be included in the CLINICAL STUDIES section.
1.
Clinical studies that provide primary support for
effectiveness
2.
Clinical studies that provide other important information
about a drug’s effectiveness not furnished by the studies that
provide primary support for effectiveness, such as:
·
Studies that suggest differential effects in
population subsets (e.g., women vs. men, presence or absence of
concomitant illness or medications)
·
Studies that suggest lack of effectiveness in a
clinical situation or lack of effect on a particular endpoint
where the drug might have been expected to work
·
Studies that provide information relevant to dose
selection or adjustment (e.g., dose-response studies or studies in
nonresponders to a particular dose)
·
Studies that provide information about the nature
and size of the treatment effect, particularly where the effect is
small
3.
Clinical studies that prospectively evaluate an important
safety endpoint
The following are the types of
studies that should usually not be included in the CLINICAL
STUDIES section, unless they also meet one of the factors in II.A
(above). If an exception is made, the limitations of the study
and the reasons for inclusion should be stated.
1.
Clinical studies with results that imply effectiveness for
an unapproved indication, use, or dosing regimen
2.
Active control clinical studies that imply comparative
effectiveness or safety claims not supported by substantial
evidence
3.
Studies that are not adequate and well-controlled within
the meaning of 21 CFR 314.126.
1. Focus on Effectiveness Data
The primary
objective of the CLINICAL STUDIES section is to summarize (1) the
evidence supporting effectiveness in the subjects who were
studied, (2) the critical design aspects of the studies, including
the populations studied and endpoints measured, and (3) the
important limitations of the available evidence. Ordinarily,
safety data are described in the ADVERSE REACTIONS section.
However, in some cases it may be appropriate to present important
information about safety in the CLINICAL STUDIES section (e.g., if
the safety data are best understood when presented with a detailed
study description or in the context of effectiveness results).
The section should also include safety data from controlled
studies specifically designed to evaluate a safety endpoint. If
safety data are presented in the CLINICAL STUDIES section, they
must be cross-referenced in the ADVERSE REACTIONS section and
other sections, as appropriate (21 CFR 201.57(c)(15)(ii)).
2. Amount of Detail
In
general, the amount of detail needed to provide a useful
description of a study and its results will depend on the
indication, the trial design, the understanding
of the drug or drug class, and the
extent to which the information adds to an understanding of the
clinical effects of the drug and how the drug should be used. The
amount of detail appropriate for a given study or dataset is
inevitably a matter of judgment, but some general principles can
be described.
Ordinarily, applicants should include more detail when:
·
The study responses
measured are of critical health importance. In most cases, such
responses would be direct measures of a meaningful clinical
outcome (e.g., mortality, stroke, acute myocardial infarction
rates, fracture rates, symptom alleviation, or functional
improvement), but could also include effects on important
surrogate endpoints (e.g., cholesterol or hemoglobin A1c).
·
The study results
demonstrate that a new agent offers a clear advantage over
existing therapy (see section III.A.4 for a discussion of
comparative claims).
·
The study results
represent a significant advance in the treatment of a disease or
condition, or provide important information about a drug’s
activities relative to its therapeutic class.
·
The study enrolled a
very specific population or used a very specific concomitant
regimen, and the results may not be applicable to other
populations.
·
The study results are
not what would be expected for that drug class and indication —for
example, when the study results demonstrate a particularly
marginal response or a response for which the clinical meaning or
implications are unclear.
·
The study uses an
unfamiliar endpoint (e.g., a novel surrogate endpoint), or there
are important limitations and uncertainties associated with an
endpoint.
Applicants should
include less detail when:
·
The new drug appears
to have effects that are typical of its class.
·
The magnitude of the
effect on clinical endpoints measured in the study is not readily
translatable into effects in clinical practice. For example,
exercise testing in a study of heart failure can demonstrate
effectiveness, but does not translate to a quantifiable clinical
outcome. Similarly, changes in HAM-D scores can be used to
demonstrate effectiveness of an antidepressant, but the results
for a given study are population- and probably site-specific, and
thus, do not necessarily translate to a numerically similar
outcome in clinical practice.
In
these cases, it could be useful to describe the study in general
terms (e.g., population, duration, endpoints measured, and
qualitative outcome) without providing detailed results.
3. Endpoints
The CLINICAL STUDIES
section should present those endpoints that establish the
effectiveness of the drug or show the limitations of
effectiveness. This includes endpoints the Agency has accepted as
evidence of effectiveness, or closely related endpoints that may
be more easily understood. When it would be informative, the
CLINICAL STUDIES section can also discuss other endpoints shown to
be affected by the drug and endpoints that might have been
expected to be influenced by the drug, but were not.
·
Composite Endpoints:
In general, the results for all components of a composite endpoint
should be presented. Presentation of all components reveals which
components are driving the result and which components may be
unaffected, or even adversely affected, by treatment with the
drug. When there is a range of effects on the components of a
composite endpoint, selectively presenting only a single component
of the composite endpoint, or presenting only the change in the
composite endpoint, can be misleading. In most cases, discussion
of a component of a composite endpoint should be only descriptive
(i.e., not be presented with statistical analyses) unless the
component has been assessed as a separate endpoint with a
prospectively defined hypothesis and analysis plan.
·
Primary and Secondary Endpoints: The terms
primary endpoint and secondary endpoint are
used so variably that they are rarely helpful. The appropriate
inquiry is whether there is a well-documented, statistically and
clinically meaningful effect on a prospectively defined endpoint,
not whether the endpoint was identified as primary or secondary.
·
Closely Related Endpoints: If two or more
endpoints are closely related and convey essentially the same
information, only one should generally be presented.
4. Comparative Data
If
the effectiveness of a drug can be determined by comparison to
placebo, data comparing the effects of the drug to an active
comparator should generally not be included in labeling unless the
data are adequate to support an explicit comparative claim (either
a superiority or similar effectiveness claim). For example, when
describing a clinical trial with three treatment arms (study drug,
active control, and placebo) in which the comparison of study drug
to placebo yields important effectiveness information and the
active control was present only to confirm assay sensitivity, the
identity of the active control and the results from that arm
should be omitted if those data are not adequate to support a
comparative claim and are not otherwise important to a clinician’s
understanding of the drug’s effect.
If
effectiveness can be determined only by comparison to an active
control (superiority or non-inferiority trial) and the identity of
the active comparator is important to a clinician’s understanding
of the drug’s effects, the active control data and identity of the
comparator should be included in labeling. In such cases, the
labeling should make clear that no comparative claim has been
established (if it has not been) and should disclose any
limitations of the comparative data (e.g., if the comparator was
administered in a suboptimal or unapproved regimen).
An
explicit claim of superior or similar effectiveness must be
supported by substantial evidence (21 CFR 201.56(a)(3)).
For superiority claims, such evidence would include adequate and
well-controlled trials designed to establish superiority of one
treatment over another. For claims of similar effectiveness, such
evidence would include adequate and well-controlled trials
designed to demonstrate that one treatment is not inferior to
another and that the difference between the two is not clinically
significant. Thus, the non-inferiority margin used would have to
be smaller than the margin needed to merely establish
effectiveness. For example, a non-inferiority trial designed to
show that a new drug has at least 50 percent of the effect of the
active control can provide adequate evidence of effectiveness, but
a 50 percent non-inferiority margin would ordinarily be too large
to support a claim of similar effectiveness. For each type of
trial, the active control should be used at an appropriate dose
and regimen, generally the highest recommended dose, and in an
appropriate patient population.
The following
elements are recommended when describing the study design.
1. Major Design Characteristics
The major design
characteristics should be identified, including level of blinding
(e.g., double-blinded, partially blinded, open-label), type of
controls (e.g., placebo, active, historical), duration of the
study, method of allocation to treatment groups (e.g.,
randomization), and use of a run-in period to identify potential
responders or eliminate placebo responders from subsequent phases
of the study. Often, many of these factors can be summarized in a
phrase such as “randomized, double-blind, placebo-controlled
study.”
2. Treatment Arms
The dose, regimens,
and any titration procedure should be identified for each trial
arm.
3.
Concomitant Therapy
Information about
concomitant therapies should be included to the extent it helps to
understand the use of the study drug or its effects.
4. Study Population
The description of
the study population should identify those characteristics that
are important for understanding how to interpret and apply the
study results. The description thus should identify important
inclusion and exclusion criteria, the demographic characteristics
of the studied population, baseline values of any clinically
relevant variables important for understanding the treatment
effect, and other characteristics of the population that have
important implications for the extent to which results can be
generalized. For example, the description should discuss
enrollment factors that exclude subjects prone to adverse effects,
the age distribution of the study population, a baseline value
that results in a study population that is more or less sick than
usual, or a study population enriched by a study design that
eliminates nonresponders.
5. Critical Endpoints
Endpoints critical to establishing effectiveness should be
identified, and those that are not commonly understood should be
defined.
When including a
detailed summary of study findings (see section III.A.2 for a
discussion of when more detail is important), the following
elements should be addressed to the extent they contribute to
practitioners’ understanding of drug effectiveness.
1.
Disposition of Subjects
It is generally
recommended that the discussion of disposition of subjects include
the following:
·
The number of subjects enrolled
·
The number of subjects completing the study
·
The number of subjects discontinuing the study and
the reasons for discontinuation
·
For a study with a run-in period or other distinct
phases, the number of subjects entering each phase and the number
of subjects not progressing to the next phase
2.
Treatment Effect
It is recommended
that the summary of findings describe the clinical outcome of the
treatment relative to the comparator (e.g., placebo or active).
·
Absolute vs. Relative Difference: When
presenting differences between study group and comparator, it is
important to present the absolute difference between treatment
groups for the endpoint measured, as well as the relative
difference (e.g., relative risk reduction or hazard ratio). For
example, if mortality is 6 percent in one study arm and 8 percent
in the other, the absolute difference (2 percent) should be
presented along with the 25 percent relative risk reduction.
·
Group Results and Individual Subject Data:
In most cases, the treatment effect is presented as a mean or
median result accompanied by a measure of uncertainty or
distribution of results for the treated groups. However,
providing individual subject data for all treatment groups can be
a useful alternative for describing the clinical effect of a
drug. This can be done by including a graphical presentation of
the distribution or cumulative distribution of responses among
individual subjects (see Appendix for examples of graphical
methods for presenting individual subject data). Individual data
can also be presented as categorical outcomes (e.g., the
proportion of patients reaching a prospectively defined goal, such
as systolic blood pressure of 120 mmHg).
·
Combined Data: In certain situations,
analyses of data combined from multiple effectiveness studies can
be useful for estimating the treatment effect. These analyses
should be included only when they are scientifically appropriate
and better characterize the treatment effect. Meta-analytic
graphs (see Appendix) can be useful for displaying confidence
intervals from several studies.
·
Uncertainty of Treatment Effect: A
confidence interval and a p-value provide complementary
information, and both should usually be provided when describing
uncertainty of the treatment effect. A confidence interval
provides a better numerical description of the uncertainty of the
treatment effect and provides some information about its size. A
p-value better conveys the strength of the finding (i.e., how
likely it is that the observed treatment effect is a chance
finding). However, it is generally better not to use a p‑value
alone.
3. Describing Results Within Treatment Groups
In controlled
trials, the change from baseline in a treatment group is usually
not by itself informative. The comparison of the change from
baseline between treatment groups is critical for
understanding the treatment effect. Therefore, results for both
the study drug and comparator should almost always be presented
because the magnitude of the treatment effect is conveyed by the
comparison. Presentation of results for both study drug and
comparator is especially important for studies with large effects
in the placebo group, where presentation of results uncorrected
for the placebo group response can be highly misleading. When
results from active control arms are discussed, a comparative
claim should not be implied where one is not supported. The
relevant statistical comparisons are those comparing the groups,
not the comparison of the treated and baseline value within a
group.
For continuous data,
the presentation of results within a treatment group should
include, where appropriate, information about the variability of
individual subject responses within the treatment group. This
variability can be described with standard deviations and
illustrated with box plots (see Appendix for examples of graphical
methods for presenting results within treatment groups).
4. Demographic and Other Subgroups
The CLINICAL STUDIES
section should include a summary statement about the results of
required explorations of treatment effects in age, gender, and
racial subgroups (21 CFR 314.50(d)(5)(v)). The summary statement
should report the findings of analyses that had a reasonable
ability to detect subgroup differences and should note when
analyses were not useful because of inadequate sample size. The
following are examples of appropriate summary statements.
·
The database was not large enough to assess whether
there were differences in effects in age, gender, or race
subgroups.
·
Examination of age and gender subgroups did not
identify differences in response to (study drug) among these
subgroups. There were too few African-American subjects to
adequately assess differences in effects in that population.
·
Examination of age and gender subgroups suggested a
larger treatment effect in women (possibly resulting from the
larger mg/kg dose in women), but no age-related differences.
There were too few African-American subjects to adequately assess
differences in effects in that population.
Compelling results
from analyses of other subgroups of established interest should
also be presented, with a caution statement, where appropriate,
about the inherent risks of unplanned subgroup analyses.
Data on outcomes of treatment should
be presented only if the outcome is of clinical significance.
1.
Categorical Outcomes (e.g., success or failure)
For categorical outcomes, the number (or percentage) of
outcomes for randomized subjects should be shown. For example,
the total sample size for the treatment group, the number of
successes, the number of failures, and the number of unknown
status should be provided. Where informative, those subjects
whose outcome status is unknown can be further differentiated by
including the number who dropped out due to adverse events, the
number who were lost to follow-up, or any other pertinent
distinction. If only percentages are reported, the denominator
should be included.
2.
Continuous Variables
For continuous variables, measures of central tendency (e.g.,
mean, median), accompanied by a measure of distribution, are the
usual methods for presenting data. When means or medians are
used, the number of subjects remaining in the study at each time
point should be provided. Because means or medians, even when
accompanied by descriptions of variability, may not adequately
convey the variability of responses, it might be useful to display
individual responses (e.g., by graphical representation of the
cumulative distribution of responses — see Appendix). It is
important to include the baseline value when reporting any change
(either numerical or percent change) from that baseline.
3.
Time-to-Event Endpoints
When time-to-event
endpoints (e.g., mortality) are used, median or mean survival
alone is not usually an adequate descriptor. Survival curves (or
event-free survival curves) and hazard ratios are often effective
ways to display such data. Data can also be summarized at
specific times (e.g., prevalence at 3, 6, 9, 12 months) or at
specific event frequency (e.g., time to 25 percent, 50 percent,
and 75 percent prevalence of events). The number of subjects
evaluated at a given interval or frequency should be specified.
Note again the need to convey both absolute and relative
difference (see III.C.2).
4.
Graphs or Tables
Graphs and/or tables
are often more effective than text alone in communicating study
results, and one or the other should be used when presenting study
results in the CLINICAL STUDIES section. See the Appendix for
guidance on the use of graphs and tables in the CLINICAL STUDIES
section of labeling.
The CLINICAL STUDIES
section must not suggest or imply indications, uses or dosing
regimens not stated in the INDICATIONS AND USAGE or DOSAGE AND
ADMINISTRATION section (21 CFR 201.57(c)(15)(i)). Words or
phrases that lack a commonly understood meaning (e.g., imprecise
quantitative terms), are not easily defined, are vague,
misleading, or promotional in tone should be avoided. Examples
include large or small (instead, use actual size or
amount), well-designed (instead, provide specifics about
the study design), extensively studied (instead, provide
specifics about the database), rapid (instead, specify
change/unit time), trend (instead, provide specifics about
the outcome), potent (instead, give the size of the
effect), pivotal study (instead, describe as major
effectiveness study), and highly significant (instead,
provide the confidence interval).
Advertising and
promotion make frequent use of statements or data appearing in the
CLINICAL STUDIES section. Sponsors are reminded that any claim of
effectiveness made in prescription drug promotion, including
comparative effectiveness, must be supported by substantial
evidence (21 CFR 201.56(a)(3)) or substantial clinical experience
(see e.g., 21 CFR 202.1(e)(6)(i)).
The
CLINICAL STUDIES section
must be updated when new information becomes available (21 CFR
201.56(a)(2)) that causes the labeling to become inaccurate, false
or misleading. Such outdated information must be promptly revised
or deleted.
A cumulative
distribution plot shows the percentage of subjects with a change
value equal to or less than the value on the x-axis. These
distributions can be graphed using connected points, bars, or
steps. A cumulative distribution plot may need a footnote and
additional text in the body of the label describing how to read the
graph. For example, the following text could accompany the graph
shown above: “Approximately 50% of the patients in each group had a
decrease of at least 2 mg/dL at endpoint.”
