Transcript It is a busy day in your practice and you are sitting at

The Pharmaceutical Promotional
Literature
A User’s Guide
Case
It is a busy day in your practice and you are
sitting at your desk, legs up, leafing through a
recent issue of Diversion, The Magazine for
Physicians at Leisure. You come across an ad
for Plavix, which states that this medication
reduces the risk of cardiovascular events by
9% compared to aspirin. You wonder if you
should be switching all your patients to Plavix.
TM
TM
Promotional spending on prescription drugs,
l996-2003
Promotional expenditures ($ billions)
30
24.9
25
21
17.8
20
15.7
13.9
12.5
15
11
9
10
5
0
1996
Source: IMS Health
1997
1998
1999
2000
2001
2002
2003
Promotional spending on prescription drugs, 2003
Detailing to
doctors 21.3%
$5.3 billion
DTC ads 12.85%
$3.2billion
Source: IMS Health
Samples 66%
billion $16.4
Total spending: $24.9 billion
But isn’t all this advertising and
promotion a good thing? Isn’t it
an important way for doctors to
learn about new products?
Scientific versus commercial sources of influence
• Telephone questionnaire of 85 randomly
selected internists in Boston area
• Questioned about two classes of drugs:
– Propoxyphene analgesics
– Cerebral and peripheral vasodilators.
Am J Med 1982;273:4
Scientific versus Commercial Sources of Influence
100%
80%
68%
62%
60%
40%
20%
4%
4%
0%
Scientific papers
Very important
Am J Med 1982;273:4
Drug ads
Minimally important
Scientific versus Commercial Sources of Influence
% of physicians
100%
80%
71%
60%
49%
32%
40%
20%
0%
Impaired cerebral
blood flow major
cause of dementia
Am J Med 1982;273:4
Vasodilators useful Propoxyphene more
in managing
potent than aspirin
"confused geriatric
patients"
Pharmaceutical Advertisements in Leading Medical
Journals: Experts’ Assessments
• “Peer review” of all ads from 10 journals during
January, 1990.
• 109 advertisements were analyzed by 113 experienced
physician peer reviewers and 54 clinical pharmacists.
• 71% of reviewers had received money from the drug
industry within the past 2 years; 53% had received
more than $5000.
Ann Int Med 1992;116:912
Pharmaceutical Advertisements in Leading Medical
Journals: Experts’ Assessments
FDA regulations specify that ads are false, lacking in fair
balance, or otherwise misleading if:
• They make claims about relative safety and efficacy or
about the populations in which the drug is useful that
are not supported by the current literature.
• Use literature or references inappropriately to support
claims in the advertisement.
• Use statistics erroneously.
• Use headlines, sub-headlines, or pictorial or other
graphic material in way that is misleading.
Ann Int Med 1992;116:912
Pharmaceutical Advertisements in Leading Medical
Journals: Experts’ Assessments
100
92
80
57
60
40
44
30
20
0
Disagreed
with DOC
claim
Ad would Little or no
Not in
lead to
educational compliance
proper
value
with 1 or
prescribing
more FDA
criteria
Ann Int Med 1992;116:912
The Quantity and Quality of Scientific Graphs in
Pharmaceutical Advertisements
• Review of all pharmaceutical ads in from 10
leading American journals in 1999.
• 498 unique advertisements (3,185 total).
• 74 unique graphs
JGIM 2003;18:294-297
The Quantity and Quality of Scientific Graphs in
Pharmaceutical Advertisements
• 36% of graphs contained “numeric distortion.”
• 66% of graphs contained “chart junk.”
• 54% reported intermediate outcomes.
JGIM 2003;18:294-297
Are the risk reductions relative or absolute?
Dead Alive
Therapy
8
92
100
Placebo
12
88
100
Dead Alive
Therapy
8
92
100
Placebo
12
88
100
Risk (Rx) = 8/100 = 8%
Risk (Pl) = 12/100 =12%
Dead Alive
Therapy
8
92
100
Placebo
12
88
100
Relative Risk(RR) = Risk (Rx)/ Risk (Pl) = .08/.12 = .67
Relative Risk Reduction (RRR) = 1 - RR = 1- .67 = .33
or 33%
Dead Alive
Therapy
8
92
100
Placebo
12
88
100
Absolute Risk Reduction (ARR) = Risk (Pl) - Risk (Rx)
= .12 - .08 = .04 or 4%
Number Needed to Treat (NNT):
Number of patients needed to
treat to prevent one outcome
NNT = 1/ARR
NNT = 1/ARR
ARR = 4%
NNT = 1/.04 = 25
Completeness of reporting trial results: effect
on physicians’ willingness to prescribe
• Questionnaire concerning Helsinki Heart Study.
• 148 Italian physicians completed questionnaire.
Results of HHS:
• Cardiac events in treatment group: 2.73%
• Cardiac events in placebo group: 4.14%
Lancet 1994. 343; 1209
Completeness of reporting trial results: effect
on physicians’ willingness to prescribe
•
•
•
•
•
ARR = 1.41 %
RRR = 34%
NNT = 71
Difference in event free rates (97.3% vs 95.9%)
RR of cardiac events - RI deaths = 6%
Lancet 1994. 343; 1209
Completeness of reporting trial results: effect
on physicians’ willingness to prescribe
“You are in doubt whether to start drug treatment
to reduce serum cholesterol of one of your
patients. We will gave you 5 statements derived
from 5 different randomized trials recently
published in leading medical journals. On the
basis of each statement you should indicate how
likely you are to prescribe each drug for your
patient. Assume that the dosage is the same for
each treatment.”
Lancet 1994. 343; 1209
Completeness of reporting trial results: effect
on physicians’ willingness to prescribe
Likelihood of prescribing:
• Drug “A” (RRR) =
• Drug “B” (ARR) =
• Drug “C” (% event free) =
• Drug “D” (NNT) =
• Drug “E” (complete) =
77%
24%
37%
34%
28%
P < 0.001 for RRR vs other measures
Lancet 1994. 343; 1209
Are the results statistically significant?
Are they clinically significant?
Are the graphs telling the truth?
Are the graphs telling the truth?
• Does the size of the effect shown equal
the size of the effect in the data?
Tufte’s Lie Factor:
Size of effect shown in graphic
Size of effect in data
Are the graphs telling the truth?
• Does the size of the effect shown equal
the size of the effect in the data?
• Is only a small percentage of the possible
event rate displayed?
Are the graphs telling the truth?
• Does the size of the effect shown equal
the size of the effect in the data?
• Is only a small percentage of the possible
event rate displayed?
• Does the y-axis start at zero?
Are the graphs telling the truth?
• Does the size of the effect shown equal
the size of the effect in the data?
• Is only a small percentage of the possible
event rate displayed?
• Does the y-axis start at zero?
• Is the survival curve longer than the
study?
Are the references “real?”
Is Cal Ripken in the ad?
(Appeal to celebrity)
Logical Fallacies in Pharmaceutical Promotion
Argumentum ad populum
Appeal to popularity
J Gen Intern Med 1994;9:563-7
Logical Fallacies in Pharmaceutical Promotion
Argumentum ad verecundiam
Appeal to authority
J Gen Intern Med 1994;9:563-7
Logical Fallacies in Pharmaceutical Promotion
Argumentum ad celebritam
Appeal to celebrity
Logical Fallacies in Pharmaceutical Promotion
Fallacy of ignoratio elenchi
(or fallacy of irrelevant conclusions,
or fallacy of ignoring the issue
or the non-sequitur)
J Gen Intern Med 1994;9:563-7
Logical Fallacies in Pharmaceutical Promotion
Appeal to emotion
Check-list
• Are the risks relative or absolute?
Check-list
• Are the risks relative or absolute?
Relative.
Absolute = 0.9%
Check-list
• Are the risks relative or absolute? Relative
• Is the result statistically significant?
Check-list
• Are the risks relative or absolute?
• Is the result statistically significant?
Yes, marginally.
P = .045
95% CI (0.3% to 16.5%)
Check-list
• Are the risks relative or absolute? Relative
• Is the result statistically significant? Yes
• Is the result clinically significant?
Check-list
• Are the risks relative or absolute? Relative
• Is the result statistically significant? Yes
• Is the result clinically significant?
No
NNT = 1/ARR =1/.009 =111
95%CI (57 - 2500)
Check-list
•
•
•
•
Are the risks relative or absolute? Relative
Is the result statistically significant? Yes
Is the result clinically significant? No
Does the size of the effect shown equal the
size of the effect in the data?
Check-list
•
•
•
•
Are the risks relative or absolute? Relative
Is the result statistically significant? Yes
Is the result clinically significant? No
Does the size of the effect shown equal the
size of the effect in the data? No
Check-list
•
•
•
•
Are the risks relative or absolute? Relative
Is the result statistically significant? Yes
Is the result clinically significant? No
Does the size of the effect shown equal the
size of the effect in the data? No
• Are the references "real?”
Check-list
•
•
•
•
Are the risks relative or absolute? Relative
Is the result statistically significant? Yes
Is the result clinically significant? No
Does the size of the effect shown equal the
size of the effect in the data? No
• Are the references "real?”
Yes, the “CAPRIE” study, The Lancet, Vol. 348,
November 16,1996.
Check-list
•
•
•
•
Are the risks relative or absolute? Relative
Is the result statistically significant? Yes
Is the result clinically significant? No
Does the size of the effect shown equal the
size of the effect in the data? No
• Are the references "real?” Yes
• Is Cal Ripken in the ad?
Check-list
•
•
•
•
Are the risks relative or absolute? Relative
Is the result statistically significant? Yes
Is the result clinically significant? No
Does the size of the effect shown equal the
size of the effect in the data? No
• Are the references "real?” Yes
• Is Cal Ripken in the ad? No, thankfully.
Conclusions
• Pharmaceutical ads are often inaccurate,
biased, and misleading.
• They misuse statistics and graphics, over-state
results, and employ fallacious reasoning.
• They should not be used to guide clinical
decisions.
• Keep your patients on aspirin!
A few sources of prescribing information
• Medical Letter (http://www.medicalletter.com)
• Prescriber’s Letter
(http://www.prescribersletter.com)
• Therapeutics Initiative (http://www.ti.ubc.ca)
• Drug and Therapeutics Bulletin (UK)
(http://www.dtb.org.uk/idtb)