Agency Information Collection Activities; Proposed Collection; Comment Request; Study of Clinical Efficacy Information in Professional Labeling and Direct-to-Consumer Print Advertisements for Prescription Drugs, 34142-34146 [2010-14445]
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34142
Federal Register / Vol. 75, No. 115 / Wednesday, June 16, 2010 / Notices
National Vaccine Plan and updates from
other Working Groups. If there is a
change in meeting dates this
information will be posted on the NVAC
Web site (https://www.hhs.gov/nvpo/
nvac/) as soon as the pertinent
information becomes available.
For these special meetings, members
of the public are invited to attend by
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phone number. The call-in number will
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of the public the opportunity to provide
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available. Public comment will be
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to the meeting.
Dated: June 1, 2010.
Bruce Gellin,
Deputy Assistant Secretary for Health,
Director, National Vaccine Program Office,
Executive Secretary, NVAC.
[FR Doc. 2010–14472 Filed 6–15–10; 8:45 am]
BILLING CODE 4150–44–P
DEPARTMENT OF HEALTH AND
HUMAN SERVICES
Food and Drug Administration
[Docket No. FDA–2010–N–0266]
Agency Information Collection
Activities; Proposed Collection;
Comment Request; Study of Clinical
Efficacy Information in Professional
Labeling and Direct-to-Consumer Print
Advertisements for Prescription Drugs
AGENCY:
Food and Drug Administration,
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HHS.
ACTION:
Notice.
SUMMARY: The Food and Drug
Administration (FDA) is announcing an
opportunity for public comment on the
proposed collection of certain
information by the agency. Under the
Paperwork Reduction Act of 1995 (the
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PRA), Federal agencies are required to
publish notice in the Federal Register
concerning each proposed collection of
information, and to allow 60 days for
public comment in response to the
notice. This notice solicits comments on
the Study of Clinical Efficacy
Information in Professional Labeling
and Direct-to-Consumer (DTC) Print
Advertisements for Prescription Drugs.
This study is designed to investigate
efficacy and effectiveness information of
prescription drugs as conveyed to
healthcare providers through approved
labeling and to consumers through print
advertisements.
DATES: Submit either electronic or
written comments on the collection of
information by August 16, 2010.
ADDRESSES: Submit electronic
comments on the collection of
information to https://
www.regulations.gov. Submit written
comments on the collection of
information to the Division of Dockets
Management (HFA–305), Food and Drug
Administration, 5630 Fishers Lane, rm.
1061, Rockville, MD 20852. All
comments should be identified with the
docket number found in brackets in the
heading of this document.
FOR FURTHER INFORMATION CONTACT:
Elizabeth Berbakos, Office of
Information Management, Food and
Drug Administration, 1350 Piccard Dr.,
PI50–400B, Rockville, MD 20850, 301–
796–3792,
Elizabeth.Berbakos@fda.hhs.gov.
SUPPLEMENTARY INFORMATION: Under the
PRA (44 U.S.C. 3501–3520), Federal
agencies must obtain approval from the
Office of Management and Budget
(OMB) for each collection of
information they conduct or sponsor.
‘‘Collection of information’’ is defined in
44 U.S.C. 3502(3) and 5 CFR 1320.3(c)
and includes agency requests or
requirements that members of the public
submit reports, keep records, or provide
information to a third party. Section
3506(c)(2)(A) of the PRA (44 U.S.C.
3506(c)(2)(A)) requires Federal agencies
to provide a 60-day notice in the
Federal Register concerning each
proposed collection of information
before submitting the collection to OMB
for approval. To comply with this
requirement, FDA is publishing notice
of the proposed collection of
information set forth in this document.
With respect to the following
collection of information, FDA invites
comments on these topics: (1) Whether
the proposed collection of information
is necessary for the proper performance
of FDA’s functions, including whether
the information will have practical
utility; (2) the accuracy of FDA’s
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estimate of the burden of the proposed
collection of information, including the
validity of the methodology and
assumptions used; (3) ways to enhance
the quality, utility, and clarity of the
information to be collected; and (4)
ways to minimize the burden of the
collection of information on
respondents, including through the use
of automated collection techniques,
when appropriate, and other forms of
information technology.
Study of Clinical Efficacy Information
in Professional Labeling and Direct-toConsumer (DTC) Print Advertisements
for Prescription Drugs—New
FDA regulations require that an
advertisement that makes claims about
a prescription drug include a ‘‘fair
balance’’ of information about the
benefits and risks of the advertised
product, in terms of both content and
presentation (§ 202.1(e)(5(ii) (21 CFR
202.1(e)(5)(ii)). In past research, FDA
has focused primarily on the risk
component of the risk-benefit ratio. In
the interest of thoroughly exploring the
issue of fair balance, however, the
presentation of effectiveness, or benefit,
information is equally important.
The act requires that manufacturers,
packers, and distributors (sponsors) who
advertise prescription human and
animal drugs, including biological
products for humans, disclose in
advertisements certain information
about the advertised product’s uses and
risks.1 By its nature, the presentation of
this risk information is likely to evoke
active tradeoffs by consumers, i.e.,
comparisons with the perceived risks of
not taking treatment, and comparisons
with the perceived benefits of taking a
treatment.2 Because FDA has an interest
in fostering safe and proper use of
prescription drugs, an activity that
engages both risks and benefits, an
indepth understanding of consumers’
processing of this information is central
to this regulatory task.
Research and guidance to sponsors on
how to present benefit and efficacy
information in prescription drug
advertisements is limited. For example,
‘‘benefit claims,’’ broadly defined,
appearing in advertisements are often
presented in general language that does
not inform patients of the likelihood of
efficacy and are often simply variants of
1 For prescription drugs and biologics, the act
requires advertisements to contain ‘‘information in
brief summary relating to side effects,
contraindications, and effectiveness’’ (21 CFR
202.1(e)(1)).
2 See Schwartz, L., S. Woloshin, W. Black, et al.,
‘‘The Role of Numeracy in Understanding the
Benefit of Screening Mammography,’’ Annals of
Internal Medicine, 127(11), 966–72, 1997.
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an ‘‘intended use’’ statement. In a
content analysis of DTC advertising,3
the researchers classified the
‘‘promotional techniques’’ used in the
advertisements. Emotional appeals were
observed in 67 percent of the ads while
vague and qualitative benefit
terminology was found in 87 percent of
the ads. Only 9 percent contained data.
For risk information, however, half the
advertisements used data to describe
side-effects, typically with lists of sideeffects that generally occurred
infrequently.
FDA regulations require that
prescription drug advertisements that
make (promotional) claims about a
product also include risk information in
a ‘‘balanced’’ manner (§ 202.1(e)(5)(ii)),
both in terms of the content and
presentation of the information. This
balance applies to both the front (a.k.a.
‘‘display’’) page of an advertisement, as
well as the brief summary page.
However, beyond the ‘‘balance’’
requirement limited guidance and
research exists to direct or encourage
sponsors to present benefit claims that
are informative, specific, and reflect
clinical effectiveness data.
The purpose of this project is to: (1)
Understand how physicians process
clinical efficacy information and how
they interpret approved product label
information,4 (2) determine physician
preferences for alternative presentations
of clinical efficacy information in DTC
advertising, and (3) examine how
different presentations of clinical
efficacy information in DTC advertising
affect consumers’ perceptions of efficacy
and safety. Specifically, we are
interested in how physicians and
consumers make risk/benefit
assessments and particularly, how
consumers make such judgments in
response to variations in the efficacy
presentations in the ‘‘display’’ (first)
page of a DTC print ad. A particular
concern is whether certain presentations
cause consumers to form skewed
perceptions or unfounded risk/benefit
tradeoffs. Therefore, we will investigate
to what extent consumers, when
provided with efficacy information,
form perceptions that correspond with
clinically-based physicians’ assessments
of the benefits, risks, and benefit/risk
tradeoffs of the same drugs. These
studies will inform FDA’s thinking
regarding how manufacturers may
provide useful and non-misleading
efficacy information in DTC print
advertisements.
Design Overview
This study will be conducted in two
concurrent, independent parts. The first
part will involve 2,500 consumers in an
experimental examination of variations
of the display page of print DTC ads for
two fictitious drugs, closely
approximating existing drugs for
overactive bladder (OAB) and benign
prostatic hyperplasia (BPH). In the
second part, 600 general practitioners
will review and evaluate a fictitious
‘‘approved’’ label for the same
conditions. This design will allow us to
compare consumers’ perceptions of
efficacy with a more objective measure
of the true efficacy of the drug as
measured by physician perceptions of
clinical efficacy from labeling.
Consumer Experiment. In this part of
the study, women who have been
diagnosed with or are at risk for OAB
(self-designated based on relevant
symptoms) will be recruited and will
view one version of a DTC ad for a drug
to treat OAB. Men who have been
diagnosed with or are at risk for BPH
(self-designated based on relevant
symptoms) will be recruited and will
view one version of a DTC ad for a drug
to treat BPH. Although the two
conditions are somewhat specific to
gender (men can suffer from OAB but it
is much more prevalent in women), they
share many of the same symptoms and
characteristics. These medical
conditions afford us the ability to
maintain various realistic manipulations
of placebo level and type of claim, as
explained in the following paragraphs.
The graphical elements and
construction of the two ads will be
comparable yet still realistic.
Consumers will be randomly assigned
to see 1 of 12 DTC print ads within their
respective medical condition and will
answer questions about the effectiveness
and safety of the fictitious drug
advertised in them. These 12
experimental conditions will be created
by examining three independent
variables in the following manner: Type
of claim (2 levels: treatment,
prevention), placebo rate (3 levels: high,
low, none), and framing (2 levels: single,
mixed). Please note that the numbers
describing efficacy seen in the table are
for illustration only. Actual numbers
used will be determined by pretesting.
Treatment Claim Study
Prevention Claim Study
Frame
Frame
Single
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Placebo
High
Mixed
Single
Mixed
• 30/100 on Drug X reduced urinary frequency and urgency
• 20/100 without Drug
X reduced urinary frequency and urgency
• 30/100 on Drug X reduced urinary frequency and urgency;
70/100 saw no improvement
• 20/100 without Drug
X reduced urinary frequency and urgency;
80/100 saw no improvement
• Diagnosed with bladder cancer on Drug
X: 4/100
• Diagnosed with bladder cancer without
Drug X: 5/100
• Diagnosed with bladder cancer on Drug
X: 4/100; Not diagnosed with bladder
cancer on Drug X:
96/100
• Diagnosed with bladder cancer without
Drug X: 5/100; Not
diagnosed with bladder cancer without
Drug X: 95/100
3 Woloshin, S., L. Schwartz, ‘‘Direct to Consumer
Advertisements for Prescription Drugs: What Are
Americans Being Told,’’ Lancet, 358, 1141–46,
(2001).
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4 As part of this effort, a qualitative mental
models procedure was completed that helped us
determine how physicians think about the efficacy
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of potential pharmaceutical options (OMB control
no. 0910–0649).
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Treatment Claim Study
Prevention Claim Study
Frame
Frame
Single
Mixed
Single
Mixed
Low
• 30/100 on Drug X reduced urinary frequency and urgency
• 3/100 without Drug X
reduced urinary frequency and urgency
• 30/100 on Drug X reduced urinary frequency and urgency;
70/100 saw no improvement
• 3/100 without Drug X
reduced urinary frequency and urgency;
97/100 saw no improvement
• Diagnosed with bladder cancer on Drug
X: 4/100
• Diagnosed with bladder cancer without
Drug X: 9/100
• Diagnosed with bladder cancer on Drug
X: 4/100; Not diagnosed with bladder
cancer on Drug X:
96/100
• Diagnosed with bladder cancer without
Drug X: 9/100; Not
diagnosed with bladder cancer without
Drug X: 91/100
None
• 30/100 on Drug X reduced urinary frequency and urgency
• 3/100 without Drug X
reduced urinary frequency and urgency;
70/100 saw no improvement
• Diagnosed with bladder cancer on Drug
X: 4/100
• Diagnosed with bladder cancer on Drug
X: 4/100; Not diagnosed with bladder
cancer on Drug X:
96/100
• Diagnosed with bladder cancer on Drug
X: 4/100
• Diagnosed with bladder cancer without
Drug X: 15/100
• Diagnosed with bladder cancer on Drug
X: 4/100; Not diagnosed with bladder
cancer on Drug X:
96/100
• Diagnosed with bladder cancer without
Drug X: 15/100; Not
diagnosed with bladder cancer without
Drug X: 85/100
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Extra High Efficacy
We will investigate variations of
numerical presentation in two different
types of claims: Treatment and
prevention. Treatment claims usually
involve symptoms that may be
alleviated by taking a given prescription
drug. This type of claim is directly
observable and somewhat testable by
patients. If bothersome symptoms do
not go away, a patient can return to the
healthcare provider with this
information and pursue additional
options for treatment. In general, drugs
that treat symptoms typically show
substantial percentages of people who
experience relief.
Prevention claims are important but
due to their long-term nature,
potentially harder to communicate. A
drug that prevents a negative future
event may not alleviate any symptoms
at all. Patients may feel no benefit from
the drug and must trust their healthcare
provider and the data, as much as they
can process it, that the drug is providing
a positive benefit for them. The nature
of these claims is such that the event
being prevented is relatively rare, and
thus the numbers used to describe them
are often very small. For example, a
cholesterol drug that reduces the risk of
heart attack from 3 out of 100 to 2 out
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of 100 may not seem objectively large,
but has enormous consequences for
millions of people and the healthcare
system in general. We chose to test this
type of claim to determine whether
consumers are sensitive to the
magnitude of the benefit in these
clinically meaningful but objectively
small and usually asymptomatic
outcomes. While we will examine the
current issues in both treatment and
prevention claims, we do not intend to
make comparisons between the two.
The second variable of interest is
communication of a placebo rate. Three
levels will be examined. In addition to
testing a control condition with no
placebo information, we will utilize a
high and low placebo rate to better
understand if and how consumers use
placebo information. We see three
possibilities: (1) People use placebo
numbers correctly, such that the low
placebo group demonstrates higher
perceived efficacy than the high placebo
group, (2) people use the placebo
numbers as a peripheral cue to mean
‘‘science’’ so there are no differences
between high and low placebo groups
on perceived efficacy but both are
higher than the no placebo group and
(3) people do not find the numbers
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meaningful or cannot process them, so
the high and low groups do not differ
from one another and they do not differ
from the no placebo group. In an
attempt to make our claims as realistic
as possible, we will maintain fairly low
rates of prevention in the prevention
conditions. For this reason, in addition
to the 12 cells in the table previously
illustrated in this document, we will
also have an additional control cell in
which the effectiveness rates are quite
high—higher than could reasonably be
expected but high enough to be
objectively noticeable (e.g., risk of
bladder cancer on Drug X, 4/100; risk of
bladder cancer on placebo, 15/100).
This additional condition will provide
confidence that our research
manipulations are operating as we
expect.
Finally, we will examine the addition
of mixed framing to the traditional use
of a single positive frame in a DTC ad.
Mixed framing provides the number of
people who benefited and the number of
people who did not benefit, whereas
positive framing provides only the
number of people who benefited. Only
a few studies have actually measured
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this mixed approach5 although risk
communication guides recommend the
use of mixed framing to create more
accurate perceptions.6 Although a
completely balanced design would also
include a negative framing condition
(which would provide only the number
of people who did not benefit), we feel
it is unrealistic to create an ad that
would suggest, for example, that ‘‘Drug
X did not work for 70% of people in
clinical trials,’’ so we have chosen not to
include negative framing in our
investigation.
In this part of the project, we are most
interested in consumers’ perceived
efficacy and safety, which we can then
compare with ratings physicians will
provide based on the prescribing
information, described in the next
section. We will also ask consumers
questions to measure their accuracy
with regard to claims, their recall of the
information in the ad, and demographic
questions that may influence their
responses, such as knowledge about
their medical condition and their level
of numeracy.
Physician Study. Six hundred general
practitioners7 will participate in an
Internet survey lasting no longer than 20
minutes. They will complete two tasks
during this time. In the first task, they
will evaluate a prescription drug label
(also known as the prescribing
information, written for healthcare
practitioners) for one of the two
fictitious drugs described in the
consumer study located in the following
paragraphs. To provide a match for the
variations of information in the DTC ads
the consumers will observe, physicians
will be randomly assigned to see
prescribing information that varies in
terms of claim type, placebo rates in
clinical trials, and the medical
condition the drug treats (OAB or BPH).
As part of this task, we will obtain
timing and sequence information on
which sections of the label physicians
examine. This will enable us to have a
deeper understanding of physicians’
processing of the prescribing
information. We are not aware of
existing literature on this topic.
Additionally, physicians will answer
questions about the efficacy and safety
of the drug and quantitative questions
about the benefit shown in the clinical
studies (as described in the label). These
questions have been designed such that
they can be reasonably compared with
the responses of consumers who will
answer the same questions after viewing
a corresponding DTC ad.
In the second task, physicians will see
four versions of a print DTC ad for a
fictitious product for high cholesterol
and will rank the ads in order of how
representative of the clinical data as the
physicians know it the ads are and how
useful they believe the ads would be for
their patients.8 The four versions will be
selected to mirror the versions of the
OAB/BPH drug that consumers will see
in the consumer experiment (i.e., low
placebo, frame).
Thus, this research will provide us
with a rich data set in order to address
several questions: (1) How physicians
process clinical efficacy information
and how they use approved product
label information, (2) how physicians’
interpretations of clinical efficacy
information relate to their preferences
for alternative DTC ad presentations,
and (3) which variations of information
in DTC ads bring consumers closer to or
farther away from the conclusions of the
physicians regarding the same drugs.
The total respondent sample for this
data collection is 3,400. We estimate the
response burden to be 20 minutes in the
first part and 15 minutes in the second
part, for a burden of 906 hours.
The response burden chart is listed
below.
FDA estimates the burden of this
collection of information as follows:
TABLE 1.—ESTIMATED ANNUAL REPORTING BURDEN1
No. of
Respondents
21 CFR Section
Annual Frequency
per Response
Total Annual
Responses
Hours per
Response
Total Hours
Physician survey-pretest
100
1
100
.333
33
Physician survey-main study
600
1
600
.333
200
Consumer experiment-pretest
200
1
200
.25
50
Consumer experiment-main study
2,500
1
2,500
.25
625
Total
3,400
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1 There
908
are no capital costs or operating and maintenance costs associated with this collection of information.
5 For a literature review, see Moxey, A., D.
O’Connell, P. McGettigan, et al., ‘‘Describing
Treatment Effects to Patients: How They Are
Expressed Makes a Difference,’’ Journal of General
Internal Medicine, 18, 948–959, 2003.
6 Fagerlin, A., P.A. Ubel, D.M. Smith, et al.,
‘‘Making Numbers Matter: Present and Future
Research in Risk Communication,’’ American
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Journal of Health Behavior, 31, S47–S56, 2007;
Schwartz, L.M., S. Woloshin, H.G. Welch, ‘‘Risk
Communication in Clinical Practice: Putting Cancer
in Context’’, Monograph of the National Cancer
Institute, 25, 124–133, 1999.
7 Including internists, general practitioners, and
family practitioners.
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8 To reduce burden, the physician sample will be
split in this task, so that half of the physicians see
the four ad versions with treatment claims and the
other half see the four ad versions with prevention
claims. Type of claim is described in greater detail
in the consumer experiment section.
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Dated: June 9, 2010.
Leslie Kux,
Acting Assistant Commissioner for Policy.
[FR Doc. 2010–14445 Filed 6–15–10; 8:45 am]
BILLING CODE 4160–01–S
DEPARTMENT OF HEALTH AND
HUMAN SERVICES
National Institutes of Health
Proposed Collection; Comment
Request Resource for the Collection
and Evaluation of Human Tissues and
Cells From Donors With an
Epidemiology Profile (NCI)
SUMMARY: In compliance with the
requirement of Section 3506(c) (2)(A) of
the Paperwork Reduction Act of 1995,
for opportunity for public comment on
proposed data collection projects, the
National Cancer Institute (NCI), the
National Institutes of Health (NIH) will
publish periodic summaries of proposed
projects to be submitted to the Office of
Management and Budget (OMB) for
review and approval.
Proposed Collection: Title: Resource
for the Collection and Evaluation of
Human Tissues and Cells From Donors
With an Epidemiology Profile (NCI).
Type of Information Collection Request:
New. Need and Use of Information
Collection: Under the auspices of three
NCI IRB-approved protocols and
instruments, the Laboratory of Human
Carcinogenesis conducts case-control
studies to investigate the relations
between biomarkers, the environment,
and human cancer. Human subjects
recruited from the general population
are needed as controls (Population
Controls) for bio-specimens and
personal histories (social, occupational
and health) that serve as references for
the significance of the frequency and
prevalence of bio-markers found in
cancer patients and thought to be
important in the development,
progression, and/or response to
treatment of the malignant growths in
cancer patients. The questionnaires will
be used to obtain the personal histories
to compare to the life styles and
exposures and the biospecimens will
serve as controls for the assay results
obtained from cancer patients. The
collection of information and specimens
from the cancer cases received NIH
Clinical Exemption (Request #2009–09–
002) on October 28, 2009. Frequency of
Response: Once. Affected Public: Adult
and senior members of the licensed
driver population in Baltimore,
Maryland and eleven nearby counties,
including the Eastern Shore. Type of
Respondents: Responders will be
English speaking, male and female,
Caucasian, African-American and
Asian. The total annual reporting
burden is estimated to be 692 (see table
below). There are no Capital Costs,
Operating Costs, and/or Maintenance
Costs to report.
TABLE 1—ESTIMATES OF ANNUAL BURDEN HOURS
Type of
respondents
Survey instrument
Adults (40–79 years old) ................
Telephone Screener (Attachment
16).
Main Questionnaire (Attachment 6)
Prostate Supplemental Questionnaire (Attachment 7).
Liver Supplement (Attachment 8) ..
Refusal Questionnaire Form (Attachment 21).
1700
225
125
.........................................................
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Request for Comments: Written
comments and/or suggestions from the
public and affected agencies should
address one or more of the following
points: (1) Evaluate whether the
proposed collection of information is
necessary for the proper performance of
the function of the agency, including
whether the information will have
practical utility; (2) Evaluate the
accuracy of the agency’s estimate of the
burden of the proposed collection of
information, including the validity of
the methodology and assumptions used;
(3) Enhance the quality, utility, and
clarity of the information to be
collected; and (4) Minimize the burden
of the collection of information on those
who are to respond, including the use
of appropriate automated, electronic,
mechanical, or other technological
collection techniques or other forms of
information technology.
FOR FURTHER INFORMATION CONTACT:
To
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1
1
10/60
(0.17)
60/60 (1)
30/60 (0.5)
225
63
1
1
30/60 (0.5)
2/60 (0.03)
113
8
2500
........................
............................
692
proposed project or to obtain a copy of
the data collection plans and
instruments, contact Glenwood E.
Trivers or Elise Bowman, Center for
Cancer Research, NCI, NIH, 37 Convent
Drive, Room 3060–C or 3060–A,
Building 37, Bethesda, Maryland
30893–4258 or call non-toll-free number
301–496–2094 or 301–496–2090 or email your request, including your
address to triversg@mail.nih.gov or
bowmane@mail.nih.gov.
Comments Due Date: Comments
regarding this information collection are
best assured of having their full effect if
received within 60 days of the date of
this publication.
Dated: June 9, 2010.
Vivian Horovitch-Kelley,
NCI Project Clearance Liaison, National
Institutes of Health.
[FR Doc. 2010–14546 Filed 6–15–10; 8:45 am]
BILLING CODE 4140–01–P
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Annual
burden hours
225
225
request more information on the
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Frequency of
response
Average time per
response
(minutes/hour)
1
Totals .......................................
Number of
respondents
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DEPARTMENT OF HEALTH AND
HUMAN SERVICES
Centers for Disease Control and
Prevention
Draft Guideline for the Prevention and
Control of Norovirus Gastroenteritis
Outbreaks in Healthcare Settings
AGENCY: Centers for Disease Control and
Prevention (CDC), Department of Health
and Human Services (DHHS).
ACTION: Notice of availability and
request for public comment.
SUMMARY: This notice is a request for
review of and comment on the Draft
Guideline for the Prevention and
Control of Norovirus Gastroenteritis
Outbreaks in Healthcare Settings,
available on the following Web site:
https://www.cdc.gov/publiccomments/.
This document is for use by infection
prevention staff, healthcare
epidemiologists, healthcare
administrators, nurses, other healthcare
E:\FR\FM\16JNN1.SGM
16JNN1
Agencies
[Federal Register Volume 75, Number 115 (Wednesday, June 16, 2010)]
[Notices]
[Pages 34142-34146]
From the Federal Register Online via the Government Printing Office [www.gpo.gov]
[FR Doc No: 2010-14445]
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DEPARTMENT OF HEALTH AND HUMAN SERVICES
Food and Drug Administration
[Docket No. FDA-2010-N-0266]
Agency Information Collection Activities; Proposed Collection;
Comment Request; Study of Clinical Efficacy Information in Professional
Labeling and Direct-to-Consumer Print Advertisements for Prescription
Drugs
AGENCY: Food and Drug Administration, HHS.
ACTION: Notice.
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SUMMARY: The Food and Drug Administration (FDA) is announcing an
opportunity for public comment on the proposed collection of certain
information by the agency. Under the Paperwork Reduction Act of 1995
(the PRA), Federal agencies are required to publish notice in the
Federal Register concerning each proposed collection of information,
and to allow 60 days for public comment in response to the notice. This
notice solicits comments on the Study of Clinical Efficacy Information
in Professional Labeling and Direct-to-Consumer (DTC) Print
Advertisements for Prescription Drugs. This study is designed to
investigate efficacy and effectiveness information of prescription
drugs as conveyed to healthcare providers through approved labeling and
to consumers through print advertisements.
DATES: Submit either electronic or written comments on the collection
of information by August 16, 2010.
ADDRESSES: Submit electronic comments on the collection of information
to https://www.regulations.gov. Submit written comments on the
collection of information to the Division of Dockets Management (HFA-
305), Food and Drug Administration, 5630 Fishers Lane, rm. 1061,
Rockville, MD 20852. All comments should be identified with the docket
number found in brackets in the heading of this document.
FOR FURTHER INFORMATION CONTACT: Elizabeth Berbakos, Office of
Information Management, Food and Drug Administration, 1350 Piccard Dr.,
PI50-400B, Rockville, MD 20850, 301-796-3792,
Elizabeth.Berbakos@fda.hhs.gov.
SUPPLEMENTARY INFORMATION: Under the PRA (44 U.S.C. 3501-3520), Federal
agencies must obtain approval from the Office of Management and Budget
(OMB) for each collection of information they conduct or sponsor.
``Collection of information'' is defined in 44 U.S.C. 3502(3) and 5 CFR
1320.3(c) and includes agency requests or requirements that members of
the public submit reports, keep records, or provide information to a
third party. Section 3506(c)(2)(A) of the PRA (44 U.S.C. 3506(c)(2)(A))
requires Federal agencies to provide a 60-day notice in the Federal
Register concerning each proposed collection of information before
submitting the collection to OMB for approval. To comply with this
requirement, FDA is publishing notice of the proposed collection of
information set forth in this document.
With respect to the following collection of information, FDA
invites comments on these topics: (1) Whether the proposed collection
of information is necessary for the proper performance of FDA's
functions, including whether the information will have practical
utility; (2) the accuracy of FDA's estimate of the burden of the
proposed collection of information, including the validity of the
methodology and assumptions used; (3) ways to enhance the quality,
utility, and clarity of the information to be collected; and (4) ways
to minimize the burden of the collection of information on respondents,
including through the use of automated collection techniques, when
appropriate, and other forms of information technology.
Study of Clinical Efficacy Information in Professional Labeling and
Direct-to-Consumer (DTC) Print Advertisements for Prescription Drugs--
New
FDA regulations require that an advertisement that makes claims
about a prescription drug include a ``fair balance'' of information
about the benefits and risks of the advertised product, in terms of
both content and presentation (Sec. 202.1(e)(5(ii) (21 CFR
202.1(e)(5)(ii)). In past research, FDA has focused primarily on the
risk component of the risk-benefit ratio. In the interest of thoroughly
exploring the issue of fair balance, however, the presentation of
effectiveness, or benefit, information is equally important.
The act requires that manufacturers, packers, and distributors
(sponsors) who advertise prescription human and animal drugs, including
biological products for humans, disclose in advertisements certain
information about the advertised product's uses and risks.\1\ By its
nature, the presentation of this risk information is likely to evoke
active tradeoffs by consumers, i.e., comparisons with the perceived
risks of not taking treatment, and comparisons with the perceived
benefits of taking a treatment.\2\ Because FDA has an interest in
fostering safe and proper use of prescription drugs, an activity that
engages both risks and benefits, an indepth understanding of consumers'
processing of this information is central to this regulatory task.
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\1\ For prescription drugs and biologics, the act requires
advertisements to contain ``information in brief summary relating to
side effects, contraindications, and effectiveness'' (21 CFR
202.1(e)(1)).
\2\ See Schwartz, L., S. Woloshin, W. Black, et al., ``The Role
of Numeracy in Understanding the Benefit of Screening Mammography,''
Annals of Internal Medicine, 127(11), 966-72, 1997.
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Research and guidance to sponsors on how to present benefit and
efficacy information in prescription drug advertisements is limited.
For example, ``benefit claims,'' broadly defined, appearing in
advertisements are often presented in general language that does not
inform patients of the likelihood of efficacy and are often simply
variants of
[[Page 34143]]
an ``intended use'' statement. In a content analysis of DTC
advertising,\3\ the researchers classified the ``promotional
techniques'' used in the advertisements. Emotional appeals were
observed in 67 percent of the ads while vague and qualitative benefit
terminology was found in 87 percent of the ads. Only 9 percent
contained data. For risk information, however, half the advertisements
used data to describe side-effects, typically with lists of side-
effects that generally occurred infrequently.
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\3\ Woloshin, S., L. Schwartz, ``Direct to Consumer
Advertisements for Prescription Drugs: What Are Americans Being
Told,'' Lancet, 358, 1141-46, (2001).
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FDA regulations require that prescription drug advertisements that
make (promotional) claims about a product also include risk information
in a ``balanced'' manner (Sec. 202.1(e)(5)(ii)), both in terms of the
content and presentation of the information. This balance applies to
both the front (a.k.a. ``display'') page of an advertisement, as well
as the brief summary page. However, beyond the ``balance'' requirement
limited guidance and research exists to direct or encourage sponsors to
present benefit claims that are informative, specific, and reflect
clinical effectiveness data.
The purpose of this project is to: (1) Understand how physicians
process clinical efficacy information and how they interpret approved
product label information,\4\ (2) determine physician preferences for
alternative presentations of clinical efficacy information in DTC
advertising, and (3) examine how different presentations of clinical
efficacy information in DTC advertising affect consumers' perceptions
of efficacy and safety. Specifically, we are interested in how
physicians and consumers make risk/benefit assessments and
particularly, how consumers make such judgments in response to
variations in the efficacy presentations in the ``display'' (first)
page of a DTC print ad. A particular concern is whether certain
presentations cause consumers to form skewed perceptions or unfounded
risk/benefit tradeoffs. Therefore, we will investigate to what extent
consumers, when provided with efficacy information, form perceptions
that correspond with clinically-based physicians' assessments of the
benefits, risks, and benefit/risk tradeoffs of the same drugs. These
studies will inform FDA's thinking regarding how manufacturers may
provide useful and non-misleading efficacy information in DTC print
advertisements.
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\4\ As part of this effort, a qualitative mental models
procedure was completed that helped us determine how physicians
think about the efficacy of potential pharmaceutical options (OMB
control no. 0910-0649).
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Design Overview
This study will be conducted in two concurrent, independent parts.
The first part will involve 2,500 consumers in an experimental
examination of variations of the display page of print DTC ads for two
fictitious drugs, closely approximating existing drugs for overactive
bladder (OAB) and benign prostatic hyperplasia (BPH). In the second
part, 600 general practitioners will review and evaluate a fictitious
``approved'' label for the same conditions. This design will allow us
to compare consumers' perceptions of efficacy with a more objective
measure of the true efficacy of the drug as measured by physician
perceptions of clinical efficacy from labeling.
Consumer Experiment. In this part of the study, women who have been
diagnosed with or are at risk for OAB (self-designated based on
relevant symptoms) will be recruited and will view one version of a DTC
ad for a drug to treat OAB. Men who have been diagnosed with or are at
risk for BPH (self-designated based on relevant symptoms) will be
recruited and will view one version of a DTC ad for a drug to treat
BPH. Although the two conditions are somewhat specific to gender (men
can suffer from OAB but it is much more prevalent in women), they share
many of the same symptoms and characteristics. These medical conditions
afford us the ability to maintain various realistic manipulations of
placebo level and type of claim, as explained in the following
paragraphs. The graphical elements and construction of the two ads will
be comparable yet still realistic.
Consumers will be randomly assigned to see 1 of 12 DTC print ads
within their respective medical condition and will answer questions
about the effectiveness and safety of the fictitious drug advertised in
them. These 12 experimental conditions will be created by examining
three independent variables in the following manner: Type of claim (2
levels: treatment, prevention), placebo rate (3 levels: high, low,
none), and framing (2 levels: single, mixed). Please note that the
numbers describing efficacy seen in the table are for illustration
only. Actual numbers used will be determined by pretesting.
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Treatment Claim Study Prevention Claim Study
-------------------------------------------------------- -------------------------------------------------------
Frame Frame
-------------------------------------------------------- -------------------------------------------------------
Single Mixed Single Mixed
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Placebo High 30/100 on Drug X 30/100 on Drug X ........ Diagnosed with Diagnosed with
reduced urinary frequency reduced urinary frequency bladder cancer on Drug X: bladder cancer on Drug X:
and urgency and urgency; 70/100 saw 4/100 4/100; Not diagnosed with
20/100 without no improvement Diagnosed with bladder cancer on Drug X:
Drug X reduced urinary 20/100 without bladder cancer without 96/100
frequency and urgency Drug X reduced urinary Drug X: 5/100 Diagnosed with
frequency and urgency; 80/ bladder cancer without
100 saw no improvement Drug X: 5/100; Not
diagnosed with bladder
cancer without Drug X: 95/
100
-------------------------------------------------------- -------------------------------------------------------
[[Page 34144]]
Low 30/100 on Drug X 30/100 on Drug X ........ Diagnosed with Diagnosed with
reduced urinary frequency reduced urinary frequency bladder cancer on Drug X: bladder cancer on Drug X:
and urgency and urgency; 70/100 saw 4/100 4/100; Not diagnosed with
3/100 without no improvement Diagnosed with bladder cancer on Drug X:
Drug X reduced urinary 3/100 without bladder cancer without 96/100
frequency and urgency Drug X reduced urinary Drug X: 9/100 Diagnosed with
frequency and urgency; 97/ bladder cancer without
100 saw no improvement Drug X: 9/100; Not
diagnosed with bladder
cancer without Drug X: 91/
100
-------------------------------------------------------- -------------------------------------------------------
None 30/100 on Drug X 3/100 without ........ Diagnosed with Diagnosed with
reduced urinary frequency Drug X reduced urinary bladder cancer on Drug X: bladder cancer on Drug X:
and urgency frequency and urgency; 70/ 4/100 4/100; Not diagnosed with
100 saw no improvement bladder cancer on Drug X:
96/100
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Extra High Efficacy ........ Diagnosed with Diagnosed with
bladder cancer on Drug X: bladder cancer on Drug X:
4/100 4/100; Not diagnosed with
Diagnosed with bladder cancer on Drug X:
bladder cancer without 96/100
Drug X: 15/100 Diagnosed with
bladder cancer without
Drug X: 15/100; Not
diagnosed with bladder
cancer without Drug X: 85/
100
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We will investigate variations of numerical presentation in two
different types of claims: Treatment and prevention. Treatment claims
usually involve symptoms that may be alleviated by taking a given
prescription drug. This type of claim is directly observable and
somewhat testable by patients. If bothersome symptoms do not go away, a
patient can return to the healthcare provider with this information and
pursue additional options for treatment. In general, drugs that treat
symptoms typically show substantial percentages of people who
experience relief.
Prevention claims are important but due to their long-term nature,
potentially harder to communicate. A drug that prevents a negative
future event may not alleviate any symptoms at all. Patients may feel
no benefit from the drug and must trust their healthcare provider and
the data, as much as they can process it, that the drug is providing a
positive benefit for them. The nature of these claims is such that the
event being prevented is relatively rare, and thus the numbers used to
describe them are often very small. For example, a cholesterol drug
that reduces the risk of heart attack from 3 out of 100 to 2 out of 100
may not seem objectively large, but has enormous consequences for
millions of people and the healthcare system in general. We chose to
test this type of claim to determine whether consumers are sensitive to
the magnitude of the benefit in these clinically meaningful but
objectively small and usually asymptomatic outcomes. While we will
examine the current issues in both treatment and prevention claims, we
do not intend to make comparisons between the two.
The second variable of interest is communication of a placebo rate.
Three levels will be examined. In addition to testing a control
condition with no placebo information, we will utilize a high and low
placebo rate to better understand if and how consumers use placebo
information. We see three possibilities: (1) People use placebo numbers
correctly, such that the low placebo group demonstrates higher
perceived efficacy than the high placebo group, (2) people use the
placebo numbers as a peripheral cue to mean ``science'' so there are no
differences between high and low placebo groups on perceived efficacy
but both are higher than the no placebo group and (3) people do not
find the numbers meaningful or cannot process them, so the high and low
groups do not differ from one another and they do not differ from the
no placebo group. In an attempt to make our claims as realistic as
possible, we will maintain fairly low rates of prevention in the
prevention conditions. For this reason, in addition to the 12 cells in
the table previously illustrated in this document, we will also have an
additional control cell in which the effectiveness rates are quite
high--higher than could reasonably be expected but high enough to be
objectively noticeable (e.g., risk of bladder cancer on Drug X, 4/100;
risk of bladder cancer on placebo, 15/100). This additional condition
will provide confidence that our research manipulations are operating
as we expect.
Finally, we will examine the addition of mixed framing to the
traditional use of a single positive frame in a DTC ad. Mixed framing
provides the number of people who benefited and the number of people
who did not benefit, whereas positive framing provides only the number
of people who benefited. Only a few studies have actually measured
[[Page 34145]]
this mixed approach\5\ although risk communication guides recommend the
use of mixed framing to create more accurate perceptions.\6\ Although a
completely balanced design would also include a negative framing
condition (which would provide only the number of people who did not
benefit), we feel it is unrealistic to create an ad that would suggest,
for example, that ``Drug X did not work for 70% of people in clinical
trials,'' so we have chosen not to include negative framing in our
investigation.
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\5\ For a literature review, see Moxey, A., D. O'Connell, P.
McGettigan, et al., ``Describing Treatment Effects to Patients: How
They Are Expressed Makes a Difference,'' Journal of General Internal
Medicine, 18, 948-959, 2003.
\6\ Fagerlin, A., P.A. Ubel, D.M. Smith, et al., ``Making
Numbers Matter: Present and Future Research in Risk Communication,''
American Journal of Health Behavior, 31, S47-S56, 2007; Schwartz,
L.M., S. Woloshin, H.G. Welch, ``Risk Communication in Clinical
Practice: Putting Cancer in Context'', Monograph of the National
Cancer Institute, 25, 124-133, 1999.
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In this part of the project, we are most interested in consumers'
perceived efficacy and safety, which we can then compare with ratings
physicians will provide based on the prescribing information, described
in the next section. We will also ask consumers questions to measure
their accuracy with regard to claims, their recall of the information
in the ad, and demographic questions that may influence their
responses, such as knowledge about their medical condition and their
level of numeracy.
Physician Study. Six hundred general practitioners\7\ will
participate in an Internet survey lasting no longer than 20 minutes.
They will complete two tasks during this time. In the first task, they
will evaluate a prescription drug label (also known as the prescribing
information, written for healthcare practitioners) for one of the two
fictitious drugs described in the consumer study located in the
following paragraphs. To provide a match for the variations of
information in the DTC ads the consumers will observe, physicians will
be randomly assigned to see prescribing information that varies in
terms of claim type, placebo rates in clinical trials, and the medical
condition the drug treats (OAB or BPH).
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\7\ Including internists, general practitioners, and family
practitioners.
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As part of this task, we will obtain timing and sequence
information on which sections of the label physicians examine. This
will enable us to have a deeper understanding of physicians' processing
of the prescribing information. We are not aware of existing literature
on this topic. Additionally, physicians will answer questions about the
efficacy and safety of the drug and quantitative questions about the
benefit shown in the clinical studies (as described in the label).
These questions have been designed such that they can be reasonably
compared with the responses of consumers who will answer the same
questions after viewing a corresponding DTC ad.
In the second task, physicians will see four versions of a print
DTC ad for a fictitious product for high cholesterol and will rank the
ads in order of how representative of the clinical data as the
physicians know it the ads are and how useful they believe the ads
would be for their patients.\8\ The four versions will be selected to
mirror the versions of the OAB/BPH drug that consumers will see in the
consumer experiment (i.e., low placebo, frame).
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\8\ To reduce burden, the physician sample will be split in this
task, so that half of the physicians see the four ad versions with
treatment claims and the other half see the four ad versions with
prevention claims. Type of claim is described in greater detail in
the consumer experiment section.
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Thus, this research will provide us with a rich data set in order
to address several questions: (1) How physicians process clinical
efficacy information and how they use approved product label
information, (2) how physicians' interpretations of clinical efficacy
information relate to their preferences for alternative DTC ad
presentations, and (3) which variations of information in DTC ads bring
consumers closer to or farther away from the conclusions of the
physicians regarding the same drugs.
The total respondent sample for this data collection is 3,400. We
estimate the response burden to be 20 minutes in the first part and 15
minutes in the second part, for a burden of 906 hours.
The response burden chart is listed below.
FDA estimates the burden of this collection of information as
follows:
Table 1.--Estimated Annual Reporting Burden\1\
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No. of Annual Frequency Total Annual Hours per
21 CFR Section Respondents per Response Responses Response Total Hours
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Physician survey-pretest 100 1 100 .333 33
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Physician survey-main 600 1 600 .333 200
study
----------------------------------------------------------------------------------------------------------------
Consumer experiment- 200 1 200 .25 50
pretest
----------------------------------------------------------------------------------------------------------------
Consumer experiment-main 2,500 1 2,500 .25 625
study
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Total 3,400 .................. .............. .................. 908
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\1\ There are no capital costs or operating and maintenance costs associated with this collection of
information.
[[Page 34146]]
Dated: June 9, 2010.
Leslie Kux,
Acting Assistant Commissioner for Policy.
[FR Doc. 2010-14445 Filed 6-15-10; 8:45 am]
BILLING CODE 4160-01-S