
[Federal Register: June 16, 2010 (Volume 75, Number 115)]
[Notices]               
[Page 34142-34146]
From the Federal Register Online via GPO Access [wais.access.gpo.gov]
[DOCID:fr16jn10-71]                         

-----------------------------------------------------------------------

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.

-----------------------------------------------------------------------

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 http://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.
---------------------------------------------------------------------------

    \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.
---------------------------------------------------------------------------

    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.
---------------------------------------------------------------------------

    \3\ Woloshin, S., L. Schwartz, ``Direct to Consumer 
Advertisements for Prescription Drugs: What Are Americans Being 
Told,'' Lancet, 358, 1141-46, (2001).
---------------------------------------------------------------------------

    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.
---------------------------------------------------------------------------

    \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).
---------------------------------------------------------------------------

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                       Mixed                                Single                       Mixed
--------------------------------------------------------------------------------------------------------------------------------------------------------
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
---------------------------------------------------------------------------------------          -------------------------------------------------------
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
--------------------------------------------------------------------------------------------------------------------------------------------------------

    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.
---------------------------------------------------------------------------

    \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.
---------------------------------------------------------------------------

    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).
---------------------------------------------------------------------------

    \7\ Including internists, general practitioners, and family 
practitioners.
---------------------------------------------------------------------------

    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).
---------------------------------------------------------------------------

    \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.
---------------------------------------------------------------------------

    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\
----------------------------------------------------------------------------------------------------------------
                              No. of       Annual Frequency    Total Annual        Hours per
     21 CFR Section         Respondents      per Response        Responses         Response         Total Hours
----------------------------------------------------------------------------------------------------------------
Physician survey-pretest             100                   1             100                .333              33
----------------------------------------------------------------------------------------------------------------
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
----------------------------------------------------------------------------------------------------------------
Total                              3,400  ..................  ..............  ..................             908
----------------------------------------------------------------------------------------------------------------
\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

