Food and Drug Administration, HHS.
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.
Submit either electronic or written comments on the collection of information by August 16, 2010.
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.Start Further Info
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.End Further Info End Preamble Start Supplemental 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 (§ 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. 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 Start Printed Page 34143an “intended use” statement. In a content analysis of DTC advertising, 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.
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, (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.
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|
|Placebo||High||• 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|
|Start Printed Page 34144|
|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|
|Extra High Efficacy||• 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|
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 Start Printed Page 34145this mixed approach 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 practitioners 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. 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:
|21 CFR Section||No. of Respondents||Annual Frequency per Response||Total Annual Responses||Hours per Response||Total Hours|
|Physician survey-main study||600||1||600||.333||200|
|Consumer experiment-main study||2,500||1||2,500||.25||625|
|1 There are no capital costs or operating and maintenance costs associated with this collection of information.|
Dated: June 9, 2010.
Acting Assistant Commissioner for Policy.
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.Back to Citation
3. Woloshin, S., L. Schwartz, “Direct to Consumer Advertisements for Prescription Drugs: What Are Americans Being Told,” Lancet, 358, 1141-46, (2001).Back to Citation
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).Back to Citation
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.Back to Citation
7. Including internists, general practitioners, and family practitioners.Back to Citation
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.Back to Citation
[FR Doc. 2010-14445 Filed 6-15-10; 8:45 am]
BILLING CODE 4160-01-S