Download Clinical Endpoints Brochure - HER2 Positive Breast Cancer

Clinical Endpoints in
Breast Cancer
AN OVERVIEW OF TRIAL DESIGN,
ANALYSIS, AND CLINICAL ENDPOINTS
2
Why We Need
Clinical Trials
Table of Contents
A Guide for Oncology Professionals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Why We Need Clinical Trials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Who Conducts Clinical Trials? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Trial Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Endpoints in Breast Cancer Clinical Trials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
Summary of Common Endpoints in Breast Cancer Trials . . . . . . . . . . . . . . . . . . . . . . 17
Interpreting Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
3
Why We Need
Clinical Trials
An Overview for Oncology Professionals
This brochure is designed to provide an overview of clinical trial endpoints from the perspective of an
investigator designing a clinical trial. Much of the information applies to clinical trials in general, but the
focus wherever possible is on trials in breast cancer. The main topics are as follows:
What are the key
elements of trial design,
and why do they matter?
What endpoints (outcomes) are typically
measured in breast
cancer trials? What
are the advantages
and limitations of
different endpoints?
How do investigators interpret
and report trial
results?
Why We Need Clinical Trials
Although less than 5% of patients with cancer are enrolled in clinical trials,1 these trials are an important
step between basic cancer research and clinical practice. Clinical trials support evidence-based medicine by
answering specific questions that may lead to improvements in patient care.
From a drug-development perspective, clinical trials are important for evaluating the efficacy and safety of
new therapies. Trials in each phase of development provide critical information (see figure).
Clinical Trials’ Purpose by Phase2,3
PHASE
PURPOSE
NUMBER OF PARTICIPANTS
1
Initial trial of a drug in humans for dosing, safety, and early efficacy information
fewer than 100*
2
Subsequent trial of a drug’s safety and efficacy in a particular disease setting
up to several hundred*
3
Larger trial comparing a drug with best available therapy to confirm efficacy and safety;
often used for US Food and Drug Administration (FDA) drug approval
hundreds to thousands*
4
Trial conducted after FDA approval to gain additional information about the drug’s
risks and benefits
up to thousands*
* The patient numbers cited here apply to clinical trials in general. Patient numbers in breast cancer trials may be smaller.
4
Who Conducts Clinical Trials?
Many people working in different organizations and locations can be involved in conducting a clinical trial.
Here is a summary of the roles of these companies and individuals in a typical cancer therapy trial.4,5
Trial Design
Sponsor. A sponsor is a person or organization—such as a pharmaceutical company or government
agency—that decides to start a clinical trial and takes overall responsibility for it. Although sponsors do not
actually conduct the trial, they have the following general responsibilities under federal law:
•Selecting qualified investigators
•Providing the information investigators need to conduct the trial
•Ensuring proper monitoring of the trial and compliance with protocols
•Informing investigators and the FDA when significant drug risks are identified
Contract research organization. A sponsor may choose to transfer some or all of its responsibilities to a
contract research organization, or CRO. Once this transfer occurs, the CRO is subject to the same federal
regulations that a sponsor would be.
Investigator. This is the person who actually conducts the trial and directs the administration of drugs to
trial participants. If a team of individuals conducts the trial, the person leading the team may be called the
principal investigator. Investigators are responsible for the following:
•Ensuring the trial is conducted according to a formal plan and relevant laws
•Protecting the rights, safety, and welfare of participants
•Controlling the drugs used in the trial
Research coordinator. Research coordinators work under the supervision of an investigator to perform many
of the daily activities involved in the trial. Some of their main responsibilities are as follows:
•Screening, enrolling, and educating participants
•Obtaining participants’ informed consent
•Coordinating study visits and follow-up care
•Maintaining documents
•Reporting adverse events
5
Trial Design
Well-designed clinical trials generate meaningful results. Following are key decisions investigators must
make in designing a trial.
Patient Population
Trial Design
When deciding whom to enroll in a clinical trial, investigators aim to include patients who may benefit
from the intervention being tested.6 They also select a population that will allow results of the trial to be
generalized to patients in clinical practice. In general, the more diverse the trial population, the more
relevant the results may be to the wider, “real-world” population.7
To meet these goals, investigators define inclusion and exclusion criteria that determine whether individual
patients are eligible for a trial. Inclusion and exclusion criteria can be demographic characteristics or
disease- and treatment-related characteristics.7
EXAMPLES OF INCLUSION CRITERIA:
EXAMPLES OF EXCLUSION CRITERIA:
•Gender
•Drug intolerance
•Age
•History of certain medical conditions
•Type and stage of cancer
•Previous treatment with certain drugs
Treatments and Controls
In most phase 3 and some phase 2 trials, the treatment being investigated is compared with a “control”
intervention to assess any difference in effect (hence the term controlled trials). The control may be a
placebo (if no effective therapies are available for the disease being studied) or a standard treatment—one
in wide use and considered effective at the time the trial is designed.8
Oncology trials rarely use placebos as controls, as doing so may be unethical. However, with standard
treatment as the control, if a trial takes a long time to complete (some can take years), the standard treatment
may no longer be in wide use by the time the trial results are reported, making the results less relevant.
6
If the objective of a trial is to show that the experimental treatment is more effective than the control,
then the trial is considered to have a “superiority” design. If the trial’s objective is simply to show that the
experimental treatment is about as effective as the control (not substantially worse), then the trial is said to
have a “noninferiority” design.9
Endpoints
Efficacy and safety in clinical trials are assessed by measuring certain outcomes, or endpoints, that investigators
specify before the trial starts.8 These may include clinical endpoints, such as overall survival, as well as surrogate
endpoints, which are expected to predict a clinical outcome.10
The primary endpoint is the key measure by which clinical benefit is assessed, and it influences the number
of patients needed for the trial.11 Secondary endpoints are other outcomes that provide additional, potentially
valuable information.6 Some studies have more than one primary endpoint (coprimary endpoints), and many
studies have several secondary endpoints.
A third type of endpoint, exploratory endpoints, may be used to analyze results for the purpose of generating
hypotheses that can be explored in future trials. Unlike primary and secondary endpoints, exploratory endpoints
are often not prespecified.12
Can the trial
be conducted in a
reasonable time
frame?
SELECTING THE
PRIMARY ENDPOINT:
QUESTIONS INVESTIGATORS ASK
Some endpoints require
What
longer follow-up than
others, lengthening the
is the most clinically
time required to complete
meaningful measure of benefit
trials and obtain
that
could guide treatment decisions
meaningful results.13
in this disease state
and patient population?
What is the current
standard of care?
Can a sufficient
number of patients be
recruited to complete
the trial?
Some endpoints need larger
trials in order to demonstrate
statistically significant
differences between arms,
potentially making recruitment
difficult.13
Because endpoints are such an important part of trial design, they are covered in detail in a special section starting
on page 10. See that section for descriptions of the most common endpoints used in breast cancer clinical trials.
7
Sample Size
Sample size is the number of patients participating in the trial. Determining the sample size is an important
step in trial design because sample size influences the power of a trial—the probability that the data will
demonstrate efficacy or inefficacy. The more patients included in a trial, the greater its power to detect
differences between the treatment and the control.14
Randomization
Phase 3 trials and some phase 2 trials use randomization to assign patients to treatment groups. This
ensures that patients have an equal, random chance of being assigned to any group, and it helps create
groups that are comparable at baseline. This way, if the groups have different results, the difference can
be attributed to the treatments patients received and not the choice of which group they were assigned to.
Randomization is a way to reduce bias.7
Some randomized trials use a process called stratification to “presort” patients by characteristics that could
influence results (eg, extent of disease). This creates groups that are comparable in terms of patients’
prognosis and allows investigators to examine the effect of the experimental treatment in these subgroups.
Random assignment to treatments then occurs within the stratified groups.7
Control
group
RANDOMIZATION
Investigational
group
STRATIFICATION
Control
group
RANDOMIZATION
Investigational
group
8
WHAT IS A CROSSOVER DESIGN?
In a crossover study design, patients begin in one study arm but switch treatments partway through
the trial, allowing for the comparison of treatments within the study group.2
•A washout period is sometimes used between treatments to minimize effects of the first treatment
extending into the second treatment period.15
In oncology clinical trials, patients sometimes cross over to another arm of the trial upon disease
progression. Crossover in those trials is usually not intended to compare treatments but to provide
patients with an alternative if the first treatment fails.16
Endpoints in
Breast Cancer Trials
Blinding
Blinding means ensuring that patients, investigators, or both are unaware of which patients are receiving
the experimental treatment and which are receiving the control. If only the patients are unaware, the trial
is called single-blinded. If investigators are also unaware, the trial is called double-blinded. Blinding helps
prevent influence caused by knowledge of treatment assignments.7
9
Endpoints in Breast Cancer Clinical Trials
Typically, new breast cancer therapies are investigated first in patients with metastatic breast cancer
(MBC).17 Trials in patients with early breast cancer (EBC) often come later. Endpoints in breast cancer
clinical trials may be specified as primary or secondary endpoints (see discussion on page 7). Commonly
used endpoints are defined in this section, along with advantages and limitations that investigators might
consider in choosing the endpoints in a trial.
Overall Survival
Endpoints in
Breast Cancer Trials
Overall survival (OS) is the time from randomization or study enrollment until death from any cause.18
ADVANTAGES FOR CLINICAL TRIAL DESIGN
LIMITATIONS
•OS is a universally accepted measure of
benefit.18
•OS is often more difficult to demonstrate in
earlier lines of therapy because multiple lines
of treatment after the experimental treatment
may confound the OS results, making it more
difficult to determine how the experimental
treatment contributed to patient outcomes.19-21
•OS is easily and precisely measured.18
•Of all the clinical endpoints, it is the most
reliable and least subject to investigator bias.18
–– Some studies are designed to allow patients
in the control arm to “cross over” and
receive the experimental treatment if their
disease progresses. This may also confound
the overall effect of the drug being studied.18
•Compared with other endpoints, OS often
requires larger patient populations and longer
follow-up times to show statistically significant
differences between groups, depending on the
disease state and event rate.18,22,23
•OS events include deaths unrelated to cancer.18
10
Progression-Free Survival
Progression-free survival (PFS) is the time from randomization or trial enrollment until disease progression or
death from any cause.18 It is often used as a surrogate endpoint for OS.19
ADVANTAGES FOR CLINICAL TRIAL DESIGN
LIMITATIONS
•PFS is a clinically valid endpoint that reflects
tumor growth.13,18 It is based on fairly objective
and quantitative assessments.18
•Validation of PFS as a surrogate for OS can be
difficult in some disease settings.18
•Depending on the disease state and event
rate, PFS typically requires smaller trials and
shorter follow-up times than OS, allowing faster
completion of trials.18
•PFS is not confounded by crossover or by
the administration of subsequent therapies
following disease progression; PFS measures
only the effect of the treatment being
investigated.18,19
•Measurement of PFS may be subject to
investigator bias.18
•The definition of PFS may vary among clinical
trials.18
•Measuring PFS requires frequent tumor
assessments and balanced timing of
assessment among treatment arms.18
•Study designs may include review by an
independent review committee (IRC) or an
independent review facility (IRF) to ensure
the objectivity of PFS results and remove the
possibility of investigator bias. PFS results may be
reported as being based on IRC or IRF review.18
11
Event-Free Survival
Event-free survival (EFS) is the time from study entry to disease progression, local or distant disease
recurrence, death, or discontinuation of treatment for any reason (eg, toxicity, patient preference, or initiation
of a new treatment in the absence of documented progression).25 This endpoint is not generally used in
breast cancer trials.
ADVANTAGES FOR CLINICAL TRIAL DESIGN
LIMITATIONS
•EFS may be useful in evaluating highly toxic
therapies.25
•Initiation of subsequent therapy is subjective,
and regulatory agencies generally discourage
the use of an EFS endpoint because it
combines data on efficacy, toxicity, and patient
withdrawal.25
Disease-Free Survival
Disease-free survival (DFS) is the time from randomization or trial enrollment until tumor recurrence or
death from any cause. The most frequent use of this endpoint is in the adjuvant setting after definitive
surgery or radiotherapy.18
ADVANTAGES FOR CLINICAL TRIAL DESIGN
LIMITATIONS
•Smaller sample size
•Not statistically validated as a surrogate for OS
in all settings18
18
•Shorter follow-up times compared with OS18
•Useful in situations where survival may be
prolonged18
•Not precisely measured and therefore subject
to assessment bias, particularly in open-label
studies18
•Sometimes complicated to define, particularly
when deaths are noted without prior tumorprogression documentation, creating variability
in DFS among studies18,26
12
Response Rate
Response rate (RR) represents the objective tumor response to treatment in a clinical study. Parameters for
tumor size reduction and minimum response time are clearly outlined in the protocol to ensure consistency
across all treatment groups. Measurements are taken before and throughout the study to determine RR.18
Although RR is not recognized as a valid surrogate endpoint for survival, it does reflect a change in tumor
size and is therefore considered a direct measure of treatment efficacy. Because it provides immediate
evidence that the treatment is having a positive effect, it may be combined with other surrogate endpoints to
measure efficacy.18
RR actually comprises several distinct endpoints, including complete response, partial response, progressive
disease, and stable disease (see table).
Response-Related Endpoints27
ENDPOINT
DEFINITION ACCORDING TO THE RESPONSE EVALUATION CRITERIA IN
SOLID TUMORS (RECIST) VERSION 1.1*
Complete response
Disappearance of all target lesions and reduction in lymph node size
Partial response
At least a 30% decrease in the size of all target lesions in relation to the lesion
size observed at baseline
Progressive
disease
At least a 20% increase in the size of all target lesions or the appearance of 1 or
more new lesions in relation to the lesion size and number observed at baseline
Stable disease
Neither sufficient shrinkage to qualify as a partial response nor sufficient
increase to qualify as progressive disease
* RECIST guidelines were updated to version 1.1 in 2008 for further clarification and to accommodate newer imaging technologies.
Clinical trials that began prior to the update used RECIST version 1.0 to measure RR.
13
Response-related endpoints are often used in combination to assess clinical benefit in a given population.
For example, clinical benefit rate is the percentage of patients with a complete or partial response or
with stable disease for a minimum period of time.28 The objective RR includes patients with a confirmed
complete or partial response (at least 2 consecutive responses).18
ADVANTAGES FOR CLINICAL TRIAL DESIGN
LIMITATIONS
•Can be assessed in single-arm trials, which may
be used when there is no available treatment
for comparison18
•Not a comprehensive measure of drug activity18
•Does not always include a time/duration
component
•May use a smaller population and can be
assessed earlier than survival18
•Attributable directly to the drug, not the natural
history of the disease18
Duration of Response
Duration of response (DoR) is the time from documentation of tumor response to disease progression or
death from any cause in patients who have a confirmed response.27
ADVANTAGES FOR CLINICAL TRIAL DESIGN
LIMITATIONS
•Because DoR is based on tumor assessments,
it is considered a direct measure of treatment
duration and efficacy and adds a level of detail
to the objective RR.27
•DoR is not a comprehensive measure of
drug activity.
•DoR is relevant to clinical practice because it
gives an indication of the durability of response
in a patient population.
•It can be assessed in single-arm trials.18
•It can be measured in a smaller patient
population and assessed earlier than OS.
14
Two less commonly used endpoints in cancer trials are time to progression (TTP) and time to treatment
failure (TTF).
Time to Progression
TTP is the time from randomization until objective tumor progression.18 It is similar to PFS but does not
include deaths. TTP is an uncommon endpoint.
Time to Treatment Failure
TTF is the time from randomization until discontinuation of treatment for any reason, including disease
progression, treatment toxicity, and death.18 TTF is an uncommon endpoint.
Summary of Endpoints
15
Pathological Complete Response (Surrogate Endpoint, Neoadjuvant Setting)
Pathological complete response (pCR) is a surrogate endpoint used in trials of neoadjuvant treatment. pCR
indicates tumor response to systemic therapy. It can be thought of as the disappearance of pathology in tissue
samples examined after neoadjuvant therapy. It does not, however, mean the cancer has been cured.17
Definitions of pCR may vary among clinical trials, but most incorporate the standard American Joint
Committee on Cancer (AJCC) TNM (tumor, node, metastasis) pathologic staging system.17
Because definitions vary with regard to nodal status and in situ disease, FDA recognizes 2 pCR definitions
for use in neoadjuvant clinical trials17:
•No trace of invasive disease in breast or nodes; remaining in situ disease permitted (ypT0/Tis ypN0)
Summary of Endpoints
•No trace of invasive disease in breast or nodes (ypT0 ypN0)
16
ADVANTAGES FOR CLINICAL TRIAL DESIGN
LIMITATIONS
•pCR can be measured relatively quickly (several
months after the start of a trial).17
•Differing pCR definitions can make it difficult to
interpret studies.17
•pCR may be used as a surrogate endpoint
to support FDA accelerated approval in the
neoadjuvant setting.17
•pCR may not be able to predict long-term
outcomes (survival).17
•For FDA approval of a drug, endpoints such as
OS or EFS must also be examined, either in the
same trial or in a different trial.17
Summary of Common Endpoints in Breast Cancer Trials
COMMON ENDPOINTS IN BREAST CANCER CLINICAL TRIALS
•Overall survival
•Progression-free survival
•Event-free survival
•Disease-free survival
•Response rate
•Duration of response
•Time to progression
•Time to treatment failure
•Pathological complete response (surrogate endpoint used in neoadjuvant trials)
Interpreting Results
17
Interpreting Results
After statisticians analyze the data collected in a clinical trial, results can be reported. Following are some
terms and types of analyses commonly found in reported trial results.
Confidence Interval
The numerical value of a reported outcome or difference in outcome between treatment groups is only
an estimate of the actual value in a broader population. A confidence interval (CI) reported along with the
estimate shows the range within which the true value is likely to fall, indicating how precise the estimate is.
A narrow interval is more precise.14,29
A CI comes with a percentage—usually 95%—that tells how certain investigators are that the true value lies
within the interval given.29
EXAMPLE:
If the median OS in a treatment group is reported as “12.4 months (95% CI, 9.9-15.2),” it loosely
means there is a 95% chance that the population median OS (if the study were repeated many times
with different patients) is between 9.9 and 15.2 months.
P Value
A P value reported with an outcome is the probability that the results occurred due to chance rather than a
true difference in the treatments being compared. The smaller the P value, the more likely that the result is
statistically significant.7
Interpreting Results
EXAMPLE:
A P value of 0.05 means the probability that the results are due to chance is 5%.
Common cutoffs for statistical significance are 5% and 1%, meaning results with P values below the cutoff
are considered statistically significant, and results with P values above the cutoff are not.
18
Risk
REPORTS OF CLINICAL TRIAL RESULTS MAY MENTION SEVERAL KINDS OF RISK,
EACH OF WHICH HAS A DIFFERENT MEANING.
ABSOLUTE RISK
The numerical chance of
something happening, such as a
patient’s chance of breast cancer
recurrence30
RELATIVE RISK
The comparison between groups; it
is the risk in one group (typically
the treatment group) stated as a
percentage of the risk in another
group (typically the control group)30
ABSOLUTE RISK REDUCTION
This refers to the difference
between the absolute risk of an
event in one group and the
absolute risk of that event in
another group.30
RELATIVE RISK REDUCTION
This refers to how much the
relative risk is reduced in the
treatment group, calculated as 1
minus the relative risk.30
In the example below,
In the example below,
In the example below,
In the example below,
Absolute risk for
patients in the
treatment group
= 40
%
Risk in the
%
treatment group 40
Risk in the
control group
= 67%
60%
60% – 40% = 20%
the relative risk for patients
in the treatment group is 67% of
the control group’s risk
1 – 0.67 = 0.33
0.33 or
33%
the absolute risk
reduction is 20%
Data on risk reduction should be interpreted carefully.
EXAMPLE
TREATMENT
GROUP:
PATIENTS
100
PATIENTS WITH RECURRENCE
PATIENTS WITHOUT RECURRENCE
PATIENTS WITH RECURRENCE
PATIENTS WITHOUT RECURRENCE
40
60
CONTROL
GROUP
PATIENTS
100
60
40
19
Hazard Ratio
The hazard ratio (HR) is the relative risk of experiencing the event being measured (eg, disease
progression) in one trial arm compared with the other over the entire time period of the trial. An HR of
1 indicates equal risk in both trial arms. An HR of less than 1 indicates a reduced risk in one of the trial
arms. An HR of greater than 1 indicates an increased risk. The HR measures the effect over the time of
the treatment analysis. Sometimes it is used to assess benefit when medians have not been reached (eg,
in interim analyses).31
•HRs can be used to calculate the reduction in risk of an outcome.14
–– For example, an HR for OS of 0.53 indicates there is a 1 – HR, or 47%, reduction in the risk of
death in one arm compared with the other.
•HRs can also be used to calculate overall improvement in an outcome measure (eg, PFS or OS) by
using the formula (1 – HR)/HR.
–– For example, if the HR for OS is 0.53, overall improvement in OS would be (1 – 0.53)/0.53, or 89%.
•The HR is typically reported with a 95% CI.
Median Value
This is the true midpoint. It can also be considered the 50th percentile.14 Median values are often used
to describe PFS or OS duration in clinical trials. For example, assuming all patients are included in the
analysis, median PFS is the point in time when 50% (half) of patients in a treatment arm have had disease
progression or died and half are alive with no disease progression. Only at this point can median PFS be
measured. Before then, the HR may be used to describe benefit, as it estimates the risk of an event (in this
case, disease progression or death) regardless of whether a median time point has been reached.
Intention to Treat
Many phase 3 trials use a method of data analysis called intention to treat (ITT). This method includes in the
efficacy analysis every person randomized to a treatment arm at the start of the trial, regardless of whether
they actually completed treatment or even received treatment. An ITT analysis may cause efficacy to be
understated, but it helps prevent biased results.7
20
Adverse-Event Grades
To standardize the reporting of adverse reactions in clinical trials, the National Cancer Institute (NCI) has
developed Common Terminology Criteria for Adverse Events (CTCAE). The criteria were most recently
updated in June 2010 (version 4.03). Clinical trials begun earlier than this date may use earlier versions to
report adverse reactions.
Using the NCI-CTCAE, adverse reactions are reported by grade (level of severity) on a scale of 1 to 5
(see figure).
NCI-CTCAE Grades32
GRADE
DEGREE OF SEVERITY
1
Mild, with no or mild symptoms; no intervention required
2
Moderate; minimal intervention indicated; some limitation of activities
3
Severe but not life threatening; hospitalization required; limitation of patient’s ability to care for
himself/herself
4
Life threatening; urgent intervention required
5
Death related to adverse event
21
Subgroup Analyses
After a clinical trial is completed, analyses of patient subgroups within the overall patient population may be
performed in order to provide more detailed information, such as33
•How the experimental treatment works in patients who share a particular relevant characteristic, such as
age or extent of disease
•Whether the benefit seen in the patient population as a whole is maintained across diverse patient types or
is derived from only a subgroup of patients
Subgroup analyses may be specified before any data are examined (prospective analysis) or may occur,
unplanned, after a first analysis of the data (retrospective analysis). Because they cannot be influenced by
the data, prospective analyses may be considered more reliable. Performing too many subgroup analyses of
either type, however, can increase the chance of false-positive findings.33
It is important to note that most clinical trials are not statistically designed to show significant benefit in each
patient subgroup, and there is a chance that the subgroups are not equally balanced and could therefore
show results that are confounded by other baseline characteristics. Thus, subgroup analyses are often
considered exploratory, whether prespecified or not.
A subgroup analysis can be graphically represented as a forest plot, which shows the relative sizes of the
subgroups being evaluated, the magnitude of benefit in each subgroup, and the CI for each subgroup. The
following figure explains how to read a forest plot.
Regression Analysis
A regression analysis is a statistical modeling technique that evaluates the relationship between 2 or more
variables in a clinical trial.14 For example, a regression analysis might show how age, sex, and treatment
affect PFS in a trial.
22
Reading a Forest Plot
1
2
3
4
0
1.0
FAVORS EXPERIMENTAL ARM
2.0
FAVORS CONTROL ARM
Data are for illustrative purposes only.
1 The beginning and end of the purple line indicate the lower and upper limits of the CI, respectively.
2 Placement of the plot indicates the HR point estimate; the size of the plot indicates the relative size of
the patient subgroup.
3 The HR falls to the left of 1, indicating a favorable result for the experimental arm relative to the control
arm. The large block indicates a relatively large subgroup of patients. The narrow CI indicates a relatively
precise HR estimate.
4 Although the HR appears to favor the experimental arm, the small size of the block indicates a relatively
small subgroup, and the large CI indicates a relatively low level of precision.
23
Time-to-Event Analyses
Many endpoints used in breast cancer trials measure the time until occurrence of an event, such as disease
progression, recurrence, or death. For survival endpoints (eg, OS and DFS), data are often reported graphically
with a Kaplan-Meier curve, which shows events over time.14
•Kaplan-Meier curves may become unreliable when the number of patients available for analysis at particular
time points becomes small.34
•While the following example illustrates PFS, the same principle can be applied to OS.
Reading a Kaplan-Meier Curve
100
1 14-month median follow-up
9
8
PROGRESSION-FREE SURVIVAL, %
80
5
4
60
50
40
7
10
3
P < 0.01
HR = 0.76 (95% CI, 0.64-0.88)
6
11
20
2
Investigational arm
Control arm
0
0
10
12
PATIENTS
AT RISK
24
20
30
86
59
0
0
TIME, MONTHS
400
399
225
164
Data are for illustrative purposes only.
1 Median follow-up is the duration of time for which 50% of the population has been followed.
2 An HR of < 1 indicates reduced risk in the investigational arm.
3 The 95% CI of the HR. Lower limit = 0.64; upper limit = 0.88.
4 Median PFS in control arm = 15.6 months.
5 Median PFS in experimental arm = 20.3 months.
6 Time difference between median PFS points (20.3 months – 15.6 months = 4.7 months).
7 The P value indicates a high level of statistical significance.
8 Shading indicates the differences in PFS between the 2 study groups for the entire time period
(reported as the HR).
9 An early separation of the curve shows a rapid response in the treatment arm vs the control arm.
10 A maintained separation of the curve shows duration of benefit over time.
11 The steep drop in the curve could be due to the small number of patients available for analysis. For
example, this curve represents only 17 patients over 28 months.
12 Patients at risk: the number of patients who have not had a progression event and whose follow-up
extends at least that far into the curve. The number at risk also helps you determine the reliability of
the curve at that time point (especially toward the end of the curve).
25
References
1. Keller JK, Bowman J, Lee JA, et al. Poor access to clinical
trials among newly diagnosed adult cancer patients in the
community—1999–2004. Commun Oncol. 2007;4:695-700.
2. The FDA’s drug review process: ensuring drugs are safe
and effective. US Food and Drug Administration website.
http://www.fda.gov/drugs/resourcesforyou/consumers/
ucm143534.htm. Updated November 6, 2014. Accessed
November 18, 2015.
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