INTRODUCTION
Mr. B a 65 year-old man with long history of diabetes mellitus and hypertension has been diagnosed with atrial fibrilation. Dr. L appropriately suggests that Mr. B should be anti-coagulated with warfarin. "Warfarin will reduce your annual risk of stroke by about 60%..... Bleeding is the main side effect but fatal bleeding stays well below 1% per year." Dr. L states.
Mr. B agrees to take warfarin. Two weeks after their conversation, Dr. L receives a phone call from Mr. B: " I am going to stop warfarin. My son who is a medical student tells me that my risk of stroke will be reduced by only 3% every year and risk of bleeding in my head increases by almost 200%."
For an informed consent, patients must be impartially informed about the advantages and disadvantages of the preventative, diagnostic or therapeutic options. In addition, patients should be able to comprehend these options and their outcomes to reflect and enact their individual values on the potential beneficial and harmful events.
Providing patients with unbiased information leads to truthful risk perceptions.
Several Randomized Controlled Trials (RCTs) have shown that patients who receive
decision aides with detailed description of outcome probabilities are more likely
to have accurate risk perception especially if they are presented quantitatively
(O’Connor et al., 2009).
In general, two formats are used to describe the risk reduction in the medical literature: (1) Relative Risk Reduction (RRR) and (2) absolute risk reduction (ARR). The goal of this manuscript is to explain how to calculate RRR and ARR with an example on a risk-reducing drug and further I will elucidate if there is any evidence that use of RRR can manipulate the risk perception among the patients and physicians.
How to calculate and interpret the absolute and relative risk measures:
In primary prevention, RCTs (Hart et al., 1999),
the rate of stroke among patients with atrial fibrillation who were not anticoagulated
has been estimated to be approximately 4.6% per year. Rate of stroke in patients
who received an adjusted dose of warfarin (i.e. international normalized ratio,
2.0-3.0) decreased to 2.0% per year. The rates of intracranial hemorrhage in
warfarin and placebo arms were 0.3% and 0.1% per year, respectively.
Absolute Risk Reduction (ARR) is calculated by subtracting the event rate in the intervention arm from the placebo arm. In our example, the ARR equals 4.6-2.0% = 2.6% per year. Therefore, warfarin therapy reduces the annual risk of stroke by 2.6% in patients with atrial fibrillation.
With the same concept, absolute risk increase is calculated by subtracting the harmful event rate in the intervention arm from the placebo arm, which in our example is 0.3-0.1% = 0.2% per year. Hence, warfarin therapy increases the annual risk of stroke by 0.2% in patients with atrial fibrillation.
Relative Risk Reduction (RRR) is another conventional measure to report risk probabilities in medical literature. It is calculated by dividing the ARR by the baseline risk (i.e. event rate in the placebo arm). In our example the RRR per year is:
This means that warfarin therapy, compared to the baseline risk of stroke in
patients with atrial fibrillation, reduces the annual risk of stroke by 52%.
Unfortunately, in medical literature and pharmaceutical promotions “comparison
with the baseline risk” is rarely mentioned, making it almost impossible
to differentiate relative versus absolute risks.
Relative risk increase is rarely used to make treatment decisions as it produces overstated percentages due to rarity of adverse events. In our example, compared with the baseline risk of stroke in patients with atrial fibrillation, warfarin therapy increases the annual risk of intracranial hemorrhage by:
As a matter of fairness it is reasonable to address the adverse effects of
a treatment in Relative risk increase if the therapeutic effect has been presented
by RRR.
Does framing the data in RRR alter the perception of therapeutic effectiveness
in patients? Griffith et al. (2009) recruited
113 participants between the age of 30 and 75 without a history of stroke, heart
attack or congestive heart failure. Through a conjoint analysis, participants
were given series of pairwise hypothetical interventions for heart disease prevention
and were asked to choose their preference. Interventions had various attributes
including ability to reduce heart attacks, side effects, ease of use and cost.
“Ability to reduce heart attacks” was presented in RRR or ARR formats.
Participants were randomized to receive the RRR or ARR version of the questionnaire.
Irrespective to age and education level, those in the RRR arm were significantly
more likely to consider the “ability to reduce heart attacks” as the
most important attribute (59 vs. 33%; p<0.01).
When data presented in RRR which is typically a significant percentage, participants
downplay other attributes of the test. Similar results have been reported from
other studies regarding the persuasiveness of RRR (Berry
et al., 2006; Gyrd-Hansen et al., 2003;
Hembroff et al., 2004; Misselbrook
and Armstrong, 2001).
Does framing the data in RRR alter the perception of therapeutic effectiveness
in physicians? In Helsinki Heart RCT (Frick et al.,
1987), after five years of treatment with gemfibrozil, 2.73% of patients
in the treatment arm experienced a cardiac event comparing to 4.14% in the placebo
arm. Without mentioning the name of the trial or the medication, Bobbio
et al. (1994) summarized the results of Helsinki Heart study in various
formats and distributed it among 148 physicians. Physicians’ willingness
to prescribe the drug was 77% when the data was presented in terms of RRR while
24% were willing to prescribe the drug when data was expressed in terms ARR
(p<0.001). Influence of RRR on physician’s perception of treatment benefits
has been reported in several other trials (Bucher et
al., 1994; Cranney and Walley, 1996; Forrow
et al., 1992; Naylor et al., 1992).
CONCLUSION
Exploitation of "information framing" is well-recognized in marketing (McGettigan
et al., 1999) and mass media (Entman, 2007).
Perception of probabilities and outcomes predictably shifts when the same problem
is framed in different ways (Tversky and Kahneman, 1981).
As for medical interventions when the results are presented in RRR rather than ARR, it appears that the enthusiasm for the intervention increases and both physicians and patients downplay other attributes of the test.
In our vignette, both Dr. L nor Mr. B’s son were truthful about the scientific data that they provided to Mr. B. However, neither of them presented the data in a neutral manner and without preconception. Dr. L used RRR to emphasize on the therapeutic effects of warfarin while Mr. B’s son used an opposite approach to persuade his father to stop the medication.
Taken together, the persuasive influence of RRR on decision making suggests that the benefits and the harms of the interventions to be communicated by ARR. This includes medical literature, pharmaceutical company promotions, patient education pamphlets, media reports and discussions between the physicians and patients. This concept should be reflected in the curriculum development of medical schools, schools of public health and continuing medical education (CME) programs.
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