An EvidenceBased Medicine Approach to Antihyperglycemic
Therapy in Diabetes to Overcome Overtreatment
Anil N Makam MD MAS12 and Oanh K Nguyen MD MAS12
1Division of General Internal Medicine UT Southwestern Medical Center
2Division of Outcomes & Health Services Research UT Southwestern Medical Center
Abstract
Overtreatment is pervasive in medicine and leads to potential patient harms and excessive costs in
healthcare Although evidencebased medicine (EBM) is often derided as practice by rote
algorithmic medicine the appropriate application of key EBM principles in clinical decision
making is fundamental to preventing overtreatment and promoting highvalue individualized
patientcentered care Specifically this article discusses the importance of 1) using absolute rather
than relative estimates of benefits to inform treatment decisions 2) considering the time horizon to
benefit of treatments 3) balancing potential harms and benefits and 4) using shared decision
making by physicians to incorporate the patient’s values and preferences into treatment decisions
Here we illustrate the application of these principles to considering the decision of whether or not
to recommend intensive glycemic control to patients in order to minimize microvascular and
cardiovascular complications in type 2 diabetes mellitus Through this lens this example will
illustrate how an EBM approach can be used to individualize glycemic goals and prevent
overtreatment and can serve as a template for applying EBM to inform treatment decisions for
other conditions to optimize health and individualize patient care
Keywords
Diabetes Mellitus EvidenceBased Medicine Medical Overuse Diabetes Complications Clinical
DecisionMaking Review [Publication Type]
INTRODUCTION WHAT IS OVERTREATMENT
Overtreatment is defined by the Institute of Medicine as the use of a treatment even when the
potential harms exceed the possible benefits1 Overtreatment is pervasive in medicine and is
not limited to a single therapeutic category2 Overuse which encompasses both overtesting
and overtreatment accounts for nearly 20 of the estimated 750 billion of wasteful
spending in health care in the United States3 Additionally many physicians in the US
recognize that their own patients are receiving too much medical care that is potentially
Correspondence to Anil N Makam MD MAS 5323 Harry Hines Blvd Dallas TX 753909169 (t) 2146483272 (f) 2146483232
AnilMakam@UTSouthwesternedu
DISCLOSURES
None
HHS Public Access
Author manuscript
Circulation Author manuscript available in PMC 2018 January 10
Published in final edited form as
Circulation 2017 January 10 135(2) 180–195 doi101161CIRCULATIONAHA116022622
Author Manuscript Author Manuscript Author Manuscript Author Manuscriptharmful In a nationally representative survey 42 of US primary care physicians thought
their patients were receiving too much care in their own practices4 Even more were
concerned about overly aggressive practice styles among medical subspecialists (61)4
Despite the potential for harm the enormous costs and increasing awareness overtreatment
nonetheless remains prevalent due to many systemlevel factors including financial
incentives malpractice concerns performance metrics practice culture and time
constraints3–14 Although legal policy and health system reforms are needed frontline
action in parallel by individual physicians is also critical to addressing the epidemic of
overtreatment Applying the principles of evidencebased medicine (EBM) to the clinical
decision making process is a key strategy that physicians can use both at the bedside and in
guideline development and policy decisions to prevent overtreatment in their immediate
spheres of influence This review article will outline an EBM framework to guide clinical
decision making to enable individualized medical treatment decisions concordant with the
aims of patientcentered and personalized healthcare increasing areas of national
priority15 16
WHAT IS EVIDENCEBASED MEDICINE
In the words of the late David Sackett a founding father of evidencebased medicine EBM
is the conscientious explicit and judicious use of current best evidence in making
decisions about the care of individual patients [emphasis added]17 The practice of EBM
does not consist of universal rote application of clinical guidelines Rather EBM requires
physicians to assess and understand what the best available evidence is use his or her
clinical judgment to apply this knowledge to the treatment of individual patients and do so
in the context of the patient’s values and preferences (Figure 1) Thus the practice of EBM
is not cookbook’ medicine but is a complex and nuanced approach requiring mastery of
three separate but overlapping domains of knowledge
There are two key reasons why practicing EBM is not synonymous with the delivery of
algorithmic cookbook’ medicine First many recommendations and guidelines are poorly
substantiated by current evidence and as such should not be broadly disseminated and
indiscriminately applied18 For example among the American College of Cardiology (ACC)
and the American Heart Association (AHA) practice guidelines issued between 1984 and
2008 only 11 of the 2711 recommendations were classified as level of evidence A (ie
supported by multiple randomized trials or a metaanalysis)19 Furthermore among the
1305 class I ACCAHA guideline recommendations which indicate general consensus that
a particular health care service is useful and effective only 19 have level of evidence A19
As such approximately 20 of class I ACCAHA guideline recommendations were
downgraded reversed or omitted within a decade suggesting questionable durability in the
absence of strong evidence20 The proliferation of recommendations based on a weak or
nonexistent evidence base is not only an issue for practice guidelines but is a phenomenon
observed among popular online evidencebased’ resources For example approximately
twothirds of the 9400 graded recommendations in UpToDate are supported by weak
evidence (ie absence of clinical trials or robust observational studies)18
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptThe second and more compelling reason why EBM is not synonymous with cookbook’
medicine is that even for recommendations based on strong levels of evidence decisions in
clinical practice are still ultimately value judgements – ie decisions ultimately hinge on the
physician’s and patient’s assessment of whether or not a treatment is actually worth it after
considering the potential harms and benefits enumerated in the scientific literature17 18
Science can be used to inform clinical decisions but cannot definitively inform value
judgements since the significance of potential benefits and harms of a therapy are in the eye
of the beholder and will differ across individuals Thus the EBM triad requires a bottomup
approach that incorporates the best available evidence with both the physician’s expertise
and judgement and the patient’s values and preferences
AN EBM APPROACH TO OVERCOMING OVERTREATMENT AND
PERSONALIZING THERAPEUTIC DECISIONS
Distilled to its simplest form an EBM approach provides guidance for making the best
therapeutic decision for an individual patient through the understanding and application of
four key principles
1 Absolute estimates of benefit What are the absolute (and not relative) benefits
of a particular therapy for patientcentered outcomes
2 Time horizon to benefit How long must a patient be on a particular therapy in
order to reap the potential benefit compared to their current life expectancy
3 Balance of benefits versus harms Do the potential absolute benefits outweigh
the potential harms of therapy for the specific patient under consideration
4 Shared decision making Is the decision to treat consistent with the patient’s
values and preferences
Case Example Should Physicians Recommend Intensive Glycemic Control in Patients
With Type 2 Diabetes Mellitus
To illustrate how EBM principles should be applied to clinical decision making we present
the case example of considering whether to recommend intensive glycemic control in
patients with type 2 diabetes mellitus (henceforth referred to as diabetes’) to reduce
microvascular and cardiovascular complications While using an EBM approach is not
unique to specific diseases diabetes is an ideal disease model to illustrate how an EBM
approach can prevent the harms of overtreatment because 1) diabetes is highly prevalent21
2) the strategy of intensive glycemic control has been thoroughly investigated and there is a
large body of evidence available on the benefits and harms of this treatment strategy 3) the
decision to pursue glycemic control is influenced less by external factors (ie financial
incentives and malpractice concerns) and more by physicians’ clinical decision making
compared to other conditions (eg percutaneous coronary intervention for stable
angina)22 23 and 4) applying an EBM approach to the treatment of hyperglycemia in type 2
diabetes highlights the discordance between the current prevailing paradigm of treatment
versus what is actually supported by the best available current evidence
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptASSESSING THE ABSOLUTE ESTIMATES OF TREATMENT BENEFIT FOR
PATIENTCENTERED OUTCOMES
To understand why absolute estimates of benefit are the preferred measure of treatment
efficacy it is first necessary to understand the limitations of relative risks Imagine a
hypothetical trial assessing the benefit of drug X versus placebo in preventing myocardial
infarction over a oneyear treatment period If the outcome occurs in 10 of individuals on
drug X (risk 1) versus 15 taking placebo (risk 2) the relative risk (RR) of a myocardial
infarction for individuals prescribed drug X is 067 (risk 1risk 2) and the corresponding
relative risk reduction (RRR) is 33 (100*(1RR)) In this example the absolute risk
reduction (ARR) for myocardial infarction among individuals treated with drug X is 5
(risk 2–risk 1) and the number needed to treat (NNT) is 20 (1ARR) For this same
hypothetical trial if the risk of myocardial infarction for those prescribed drug X is only 1
and the risk in the placebo group is only 15 the RR remains a deceptively impressive
067 but the ARR is now only 05 and the NNT is 200 indicating a minimally effective
therapy Thus reports of the RR or RRR do not provide physicians any information on the
magnitude of treatment benefit Relying on these measures alone makes it impossible to
assess the clinical relevance of the treatment and may lead to erroneously inflated estimates
about the potential benefit
In contrast absolute estimates of treatment benefit in the form of ARR or NNT more
accurately convey the treatment effect size and potential clinical significance of treatment In
the hypothetical trial above a NNT of 20 means that one would need to treat 20 individuals
(with characteristics within the parameters of the trial’s inclusion and exclusion criteria)
with drug X for one year to prevent one additional myocardial infarction compared to
placebo Notably a NNT of 20 also implies that for every 20 people treated with drug X on
average 19 people derive no benefit with respect to preventing a myocardial infarction
compared to being prescribed placebo over this time period While both the ARR and NNT
are valid measures to convey the absolute benefit of therapy the NNT more clearly
illustrates that the benefits of treatment are not shared equally by every individual in the
treatment group and that most individuals in this example will not derive any benefit after
one year of therapy even for what many would consider a clinically meaningful effect size
There are important limitations to the interpretation and application of absolute risks First
absolute risks are estimated at the population level As the evolutionary biologist Stephen
Jay Gould astutely stated in his essay The Median isn’t the Message variation is the hard
reality not a set of imperfect measures for a central tendency24 Thus ARR and NNT
convey average estimates of benefit in a group and cannot predict the potential benefit for
an individual patient Physicians must therefore also consider an individual’s risk profile for
the outcome of interest based on established risk factors Assessing the potential benefits
(and harms) of treatment in the context of individuals’ risks is essential to the optimal
selection of individuals for treatment Second treating individuals who are either healthier
or sicker than those included in studies can significantly alter the harmbenefit profile of a
therapy25 This phenomenon commonly referred to as indication drift can markedly reduce
the effectiveness of therapies Lastly absolute measures of risk (as well as relative risks) are
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Author Manuscript Author Manuscript Author Manuscript Author Manuscriptestimated only for specific durations of time on treatment and as such do not capture the
full effect of time26 Consequently ARR and NNT provide limited information to guide
treatment decisions beyond the duration reported in clinical studies Despite these
limitations the absolute risk is essential to understanding the magnitude of potential benefit
and is the first step in deciding whether the treatment is valuable for an individual patient
What are the estimated benefits of intensive glycemic control in type 2 diabetes
Large Relative Benefits in Preventing (Mostly Surrogate) Outcomes—Intensive
glycemic control is defined in randomized controlled trials as treatment strategies resulting
in a hemoglobin A1c (HbA1c) value between 64–70 and conventional glycemic control is
defined as treatment strategies resulting in a modestly higher HbA1c between 79 and
8427–31 The relative benefits of intensive versus conventional glycemic control in
diabetes are summarized in Table 1 In the landmark UKPDS trial the relative benefits of 10
years of intensive glycemic control for individuals with newly diagnosed diabetes were only
demonstrated for intermediate markers of microvascular complications (ie progression of
retinopathy on eye exam loss of reflexes or change in biothesiometer readings and
microalbuminuria) but not for actual meaningful clinical manifestations of microvascular
disease (ie vision loss symptomatic neuropathy amputation or endstage renal disease
requiring dialysis)27 Other trials have similarly failed to show improvement in these more
clinically meaningful endpoints32 33
The evidence for the relative benefits of intensive glycemic control for preventing
cardiovascular disease is even less well substantiated Although the benefits for reducing
surrogate microvascular outcomes have been consistently observed in trials31 34 the 15
relative risk reduction for the cardiovascular outcome of nonfatal myocardial infarction
(MI) has not been consistently observed Although three of the four landmark trials on
intensive glycemic control (UKPDS VADT and ADVANCE) did not show a statistically
significant reduction in nonfatal MIs27–30 35 the results of a metaanalysis more clearly
supported this 15 relative reduction31 However it should be noted that intensive glycemic
control has not been shown in parallel to also reduce cardiovascular diseasespecific
mortality (RR 111 95 CI 086–143) or allcause mortality (RR 104 95 CI 091–
119) calling into question the reliability and significance of the reduced risk in nonfatal
MIs31 Additionally intensive glycemic control does not reduce the risk of strokes36 Thus
while diabetes remains a strong prognostic marker for cardiovascular disease achieving
intensive glycemic control does not modify the risk of cardiovascular disease
Of note two recent multicenter diabetes outcomes trials of empagliflozin and liraglutide
demonstrated clinically significant reductions in both cardiovascular diseasespecific and all
cause mortality37 38 While potentially representing important advances in the therapy of
type 2 diabetes the observed mortality reduction in these trials was likely not mediated
through the mechanism of intensive glycemic control for several reasons First while not
explicitly designed to test the effect of intensive glycemic control there was only a modest
reduction in HbA1c of 04 compared to approximately 1 reduction achieved in other
trials none of which showed reductions in cardiovascular or allcause mortality31 37 38
Second the modest37 to nonexistent reductions38 in large vessel atheroscleroticmediated
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Author Manuscript Author Manuscript Author Manuscript Author Manuscriptcardiovascular outcomes (MIs and strokes) were disproportionately smaller in magnitude
than the observed reduction in cardiovascular diseasespecific mortality in these trials These
results suggest that these medications may be working through mechanisms other than
preventing the progression of atherosclerosis which is the implicated causal pathway
between hyperglycemia of diabetes and cardiovascular diseasespecific mortality39 Lastly
the improvement in cardiovascular mortality in both of these trials emerged far earlier than
expected (within the first 3 months for empagliflozin and 6 months for liraglutide) given the
natural history of the progression of atherosclerosis due to hyperglycemia39 Taken together
these trials suggest that the reductions in mortality observed with these medications are not
attributed to intensive glycemic control but rather are due to medicationspecific effects on
other unidentified mechanistic pathways
Modest Absolute Benefits of Intensive Glycemic Control for Diabetes—There is
no direct evidence of an absolute benefit of intensive glycemic control on patientcentered
outcomes such as clinically apparent microvascular disease or mortality despite several well
conducted clinical trials with up to 15 years of followup33 Consequently to estimate the
absolute benefits of glycemic control we must rely instead on simulation studies that model
the potential benefits of glycemic control on clinical outcomes extrapolating the observed
effects on intermediate outcomes from landmark trials over a much longer timespan than is
feasible in those trials This approach represents the best available evidence regarding the
absolute benefits of intensive glycemic control with respect to clinically relevant outcomes
that patients and physicians care about To this end Vijan and colleagues developed a
Markov simulation model to estimate the absolute benefits of intensive glycemic control
using simulated individuals with characteristics based on adults with diabetes sampled in the
National Health and Nutrition Examination Study (NHANES) a nationally representative
population survey in the US40 The authors modeled the risk of progression from the onset
of asymptomatic diabetes to intermediate microvascular outcomes and the cardiovascular
outcome of nonfatal MI using the relative risk reductions with intensive glycemic control
observed in clinical trials (Table 1) The authors then estimated the likelihood of progression
from these intermediate outcomes to endstage complications (eg visual loss amputation
endstage renal disease) and death using findings from other randomized controlled trials
and US populationbased observational studies41–46
Using this model the authors simulated two treatment scenarios commonly encountered in
clinical practice to estimate the absolute benefits of intensive glycemic control on clinically
apparent microvascular and cardiovascular complications of diabetes The first scenario
assesses the benefit of lifelong oral pharmacotherapy to achieve intensive glucose control It
consists of a newly diagnosed person with diabetes with an HbA1c of 85 who is
prescribed metformin and experiences a reduction in the HbA1c level of 15 points to 70
which remains at this level over the course of the person’s life The second scenario assesses
the benefit of augmenting an oral pharmacotherapy regimen with insulin In this scenario
insulin therapy is initiated for the same patient in the first treatment scenario after failing’
10 years of oral antihyperglycemic therapy with a rise in HbA1c level back to 85 Insulin
therapy reduces the HbA1c level to 75 and remains at this level over the remainder of the
person’s life The lifetime absolute benefits of intensive glycemic control for each scenario
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Author Manuscript Author Manuscript Author Manuscript Author Manuscriptdepending on the age at which diabetes is initially diagnosed are shown in Figure 2 In both
scenarios the potential benefit of intensive glycemic control greatly declines with the age at
which an individual is diagnosed For an average 75 year old with newly diagnosed diabetes
initiating metformin (Figure 2A) the NNT for preventing endstage renal disease (ESRD)
vision loss and amputation over that person’s lifetime are 143 200 and 125 respectively
For an average 55 year old who failed’ oral antihyperglycemic therapy and was
subsequently initiated on insulin 10 years later for uncontrolled’ diabetes (HbA1c of 85
on oral therapy) the NNT are well above 100 for each microvascular endpoint (Figure 2B)
In other words greater than 99 of adults 65 years of age or older initiated on insulin
therapy to achieve intensive glycemic control will not derive any benefit with respect to
clinically apparent microvascular complications within their lifetime
Although the NNT for preventing nonfatal MIs are considerably more favorable compared
to preventing patientcentered microvascular outcomes across all age groups for both
scenarios the confidence behind these estimates are limited due to the increase in
cardiovascular mortality observed in the ACCORD trial as well as the nonsignificant
increase seen in metaanalyses28 34 36
These findings illustrate the stark differences in using relative versus absolute risks to inform
treatment decisions Even when relative risk reductions for surrogate microvascular and
cardiovascular outcomes are the same across individuals the absolute risk reductions for
corresponding clinically meaningful outcomes may be vastly different for individuals with
different baseline risk profiles and life expectancies Relying on relative risks can vastly
overestimate the benefits from treatment and is the reason why absolute risks are the
preferred method to inform therapeutic decisions
ASSESSING THE TIME HORIZON TO BENEFIT FOR INTENDED THERAPIES
As discussed above a major limitation of absolute measures of risk is that they do not
capture the full effect of time Rather absolute measures of risk quantify the benefits of
treatment in a given time period Consequently absolute measures of risk cannot be used to
quantify the potential benefits of postponing an outcome For example consider a
hypothetical trial of adults with a 100 year followup period where the primary outcome is
mortality Because adult human life expectancies rarely exceed 100 years all trial subjects
will die within the followup period irrespective of any intervention aimed at reducing
mortality in this study Thus the observed absolute risk reduction for the intervention will be
0 (with a NNT of infinity) at the conclusion of the trial In this extreme example relying
solely on the ARR or NNT as measures of effect size may fail to capture a potential benefit
of treatment if therapy postponed the inevitable outcome of death for a clinically meaningful
amount of time (eg perhaps subjects receiving the intervention postponed death by 10
years even if they inevitably died within the 100 year follow up period)
Similarly absolute measures of risk also do not consider the time horizon to benefit—that is
the time that must be accrued on treatment until a meaningful benefit emerges This is a
more commonly encountered issue than postponement of an outcome since study followup
periods tend to be limited in duration For a treatment with a sufficiently long time horizon
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Author Manuscript Author Manuscript Author Manuscript Author Manuscriptto benefit individuals with a life expectancy less than the time horizon to treatment benefit
will not reap the potential benefits of treatment Thus these individuals will be exposed to
the potential upfront harms of therapy without any chance of benefit a classic scenario of
overtreatment To avoid these potential harms only individuals whose anticipated life
expectancy exceeds the estimated time horizon to benefit should be considered as candidates
for treatment
The time horizon to benefit can be estimated from clinical studies by calculating the
difference in the area under the survival curves though these measures are infrequently
quantified and reported Alternately the time horizon to benefit can be qualitatively
estimated by assessing KaplanMeier survival curves for the intervention and control groups
to identify the point at which the two curves diverge47 This divergence point provides an
estimate of the minimum time horizon to benefit for a given treatment To illustrate how to
estimate the time horizon to benefit using survival curves and understand its implications
we will return to the example of diabetes
Time Horizon to Benefit for Intensive Glycemic Control in Diabetes
Based on the KaplanMeier curve from the UKPDS trial it takes approximately 9 years of
intensive glycemic control to yield an observable reduction in composite microvascular
events in the treatment group (vertical dashed line in Figure 3) However it is important to
note that the composite microvascular outcome reported in the UKPDS trial consists mostly
of intermediate outcomes that may not directly harm patients (ie need for photocoagulation
vitreous hemorrhage or renal failure defined as an elevated creatinine >28 mgdL) The
potential for intensive glycemic control to prevent more meaningful microvascular outcomes
(ie vision loss or ESRD requiring dialysis) is estimated to take 2 or more decades to
manifest48 Of note even with an additional 10 years of followup in the UKPDS trial (for a
total of 25 years) improvements in these endpoints have not yet been reported49 This
suggests that the legacy effect observed for surrogate microvascular endpoints seen after a
decade of early intensive glycemic control in patients with newly diagnosed diabetes may
not translate into reductions in patientcentered microvascular outcomes
Despite the long time horizon to benefit for intensive glycemic control many patients
prescribed intensive glycemic control nonetheless have life expectancies less than 20 years
and potentially even less than 9 years the earliest time interval after which one could expect
to observe benefits for intermediate microvascular outcomes50 This is a clear example of
overtreatment – individuals who are initiated on intensive glycemic control who have a life
expectancy of less than 9 years are exposed to the potential harms of treatment without any
reasonable chance of benefit Consequently a pragmatic approach to avoiding the harms of
overtreatment would be to defer intensive glycemic control in individuals with a life
expectancy that is clearly less than 9 years For example individuals with advanced cancers
ESRD advanced dementia cirrhosis and endstage heart failure and lung disease are
unlikely to benefit from intensive glycemic control
There are also several highly prevalent but less commonly recognized conditions that also
indicate poor prognosis and limited life expectancy After a first hospitalization for heart
failure with either preserved or reduced ejection fraction individuals have a 70 5year
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Author Manuscript Author Manuscript Author Manuscript Author Manuscriptmortality rate51 52 Likewise after the first hospitalization for chronic obstructive
pulmonary disease (COPD) exacerbation individuals have an 80 9year mortality53 Thus
initiating intensive glycemic control during or after an index hospitalization for either heart
failure or COPD is unlikely to yield any benefit beyond that of a conventional glycemic
control strategy
Individuals with multimorbidity and impaired functional status also have limited life
expectancy due to the cumulative burden of illness though prognosis can be challenging to
assess in these complex patients The Lee Schonberg Index is a validated tool that quantifies
the 4year and 10year risk of mortality among community dwelling adults 50 years of age
or older (httpeprognosisucsfeduleeschonbergphp)54 55 This index assesses the
cumulative contribution of age selected comorbidities and health behaviors (diabetes
cancer heart disease lung disease body mass index < 25 and current smoker) and
impairments in functioning (bathing managing finances ambulating and pushing or pulling
heavy objects) on the risk of mortality using a point score ranging from 0 to 25 with higher
scores corresponding to higher risk of death The Lee Schonberg Index has excellent
discrimination (Cstatistic of 083) and calibration (less than a 4 difference between
predicted and observed mortality rates across all risk levels)55
In a nationally representative longitudinal cohort the Lee Schonberg Index identified that
25 of community dwelling individuals 50 years of age or older have a greater than 50
risk of death within 10 years55 Thus 1 in 4 middleaged and older adults in the US are
unlikely to live 10 years let alone 20 years in order to reap the benefits of intensive
glycemic control This is reflected in the exceedingly low lifetime absolute benefits for
intensive glycemic control estimated for individuals who have high point scores on the Lee
Schonberg Index In a decision analysis study Huang and colleagues developed a simulation
model based on data from the UKPDS trial and found that among older adults with diabetes
those with greater multimorbidity and functional impairment are far less likely to benefit
from intensive glucose control56 For example for individuals aged 60 to 64 years who have
newonset diabetes and only 1 point on the Lee Schonberg Index the NNT to prevent
ESRD blindness and amputation over one’s lifetime are approximately 125 83 and 77
respectively In contrast the lifetime NNT for the same scenario except for patients who
have significant multimorbidity and functional impairment (Lee Schonberg Index score of
15 points) are infinity (ARR of 0) 2700 and 1125 respectively56 Thus only the few
older adults with diabetes and almost no functional limitations will derive benefit from
intensive glucose control Those with substantial multimorbidity and functional limitations
have an infinitesimally small probability of deriving any benefits from this treatment
strategy
ASSESSING THE BALANCE BETWEEN POTENTIAL BENEFITS VERSUS
HARMS OF TREATMENT
Overtreatment may arise when one focuses only on the benefits of therapy without any
consideration of potential harms since this would lead to always favoring treatment even if
the benefit of treatment is extremely small Thus it is critical to understand and assess the
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Author Manuscript Author Manuscript Author Manuscript Author Manuscriptpotential harms of treatment and to incorporate this knowledge into treatment decisions
The potential harms of therapy are quantified through estimates of the absolute risk increase
and the number needed to harm (NNH) for specific adverse effects related to treatment
Awareness of both the NNT and NNH for a given treatment can help physicians and patients
alike make more informed decisions about whether the potential for benefits is worth taking
the risks
There are several challenges in assessing the balance between the NNT and NNH for
treatments First since each individual beneficial or harmful effect will have varying impact
on quality of life it may be difficult to directly compare benefits and harms Consider for
example the potential benefit of preventing a stroke versus the potential harm of causing a
bleed with anticoagulation therapy for atrial fibrillation Compared to major bleeding
having a stroke is considered more detrimental to quality of life since major bleeding is
more likely to be transient and reversible than neurologic deficits from a stroke57 Second
treatments may have a myriad of beneficial and harmful effects consequently it can be
difficult to simultaneously assess the net balance of benefits and harms Third the NNT and
NNH are reported for selected benefits and harms that are discrete in nature (ie present or
absent) and are not designed to take into account the effect of treatment on other measures
of quality of life (ie treatment burden) that are also important to patients By only
considering the value of treatment by the NNT and NNH important information may be lost
on other dimensions of therapy
An approach to overcome these limitations is to quantify the balance between the potential
benefits and harms of therapy by estimating the net qualityadjusted life years (QALYs)
associated with treatment This measure of overall health impact incorporates both the
quantity and quality of life related to all potential benefits and harms of therapy QALYs
integrate the general quality of life on a scale from 0 to 1 with values closer to 1 indicating
higher quality of life based on an individual’s probability of being in various disease and
treatment complication states each year58 59 Estimated QALYs when available can thus
allow for direct comparisons of health impact between different treatments
In the absence of studies evaluating the net QALYs gained from therapy the NNT can be
used to estimate the magnitude of benefit for a treatment Acknowledging that the NNT does
not fully account for many factors including the clinical significance of the outcome (ie
microalbuminuria versus ESRD) the cost convenience and invasiveness of the therapy (ie
metformin versus insulin) and the number needed to harm (NNH) for various adverse
effects one may roughly interpret that a NNT greater than 15 is associated with a small net
treatment benefit and a NNT ≤ 5 is typically associated with a meaningful net benefit60
Balancing the Harms and Benefits of Intensive Glycemic Control in Diabetes
With respect to diabetes there are several important potential harms to consider before
prescribing antihyperglycemic therapy While risks are unique to each therapy the most
common side effects of intensive glycemic control reported in clinical trials were severe
hypoglycemia and weight gain both attributable to higher rates of insulin use among these
patients31 33 Severe hypoglycemia occurred in 49 of those on intensive glycemic control
versus 20 among those on conventional glycemic control (absolute risk increase of 29
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptNNH of 35)31 Additionally intensive glycemic control increased body weight by
approximately 333 Another important but often overlooked harm of intensive glycemic
control is the potential decrease in a person’s overall quality of life due to the burden of the
treatment itself Due to the burden of polypharmacy multiple insulin injections frequent
blood glucose monitoring and increased frequency of health care visits an intensive
glycemic control strategy per the UKPDS trial protocol was perceived by individuals to have
a median quality of life utility value of 085 (mean of 067 ± 034) on a scale where perfect
health is 1 and death is 061 A utility of 085 – also referred to as a disutility of 015 – means
individuals equate living 10 years with intensive glycemic control the same as living 85
years in perfect health Notably the decrease in quality of life due to intensive glycemic
control is perceived by patients to be of the same magnitude as that due to a mild stroke
(Figure 4)
In order to balance the potential benefits of intensive glycemic control with the potential
harms Vijan and colleagues used a Markov simulation model as described previously to
estimate the net lifetime QALYs gained with therapy The authors assigned quality of life
utility values to each disease state along the spectrum from asymptomatic diabetes to death
based on prior literature to estimate net QALYs gained or lost40 62 63 The overall treatment
burden was estimated across a range of disutilities for intensive glycemic control for a
scenario where an individual was prescribed a pharmacologic therapy that reduced the
HbA1c from 85 to 75 In this scenario treatment burden has a profoundly detrimental
impact on the net QALYs gained from treatment (Figure 5) If an individual experiences no
treatment burden whatsoever (ie a treatment burden of 0) antihyperglycemic therapy in this
scenario would yield only modest net benefits across all four age groups with a net lifetime
gain of 09 QALYs for an average 45 year old to 01 QALYs for an average 75 year old
However a treatment burden as little as 004 negates any benefit of intensive glycemic
control for all age groups and actually results in loss of quality of life Therefore the value
of intensive glycemic control depends on an individual’s experienced or perceived treatment
burden
These findings should be interpreted in the context of certain limitations First the authors’
optimistic assumptions of a 15 risk reduction in nonfatal myocardial infarction events and
relatively low estimates of treatment disutilities (capped at 005 much lower than the
previously reported median disutility of 015 for intensive glycemic control in Figure 4)
biases the results in favor of intensive glycemic control The actual net loss in quality of life
is likely to be greater than this study suggests Second as discussed earlier the net benefits
of intensive glycemic control are estimated for the average patient for each age group
Individuals with greater risk for microvascular and cardiovascular disease (eg tobacco use
hypertension high cholesterol) compared to the average patient with diabetes (mean blood
pressure of 13080 mmHg and mean lowdensity lipoprotein cholesterol of 100 mg per
deciliter)64 are more likely to derive benefits from intensive glycemic control However
individuals with a lower than average risk profile will have even less to potentially gain from
therapy than the modeled scenarios suggest
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptASSESSING WHETHER TREATMENT IS CONSISTENT WITH PATIENT
VALUES AND PREFERENCES SHARED DECISION MAKING
Shareddecision making (SDM) is defined as a partnership between physicians and patients
to make preferencesensitive decisions together guided by the best available evidence and
the patient’s risks prognosis and sociopersonal context65 Preferencesensitive therapeutic
decisions indicate that there is clinical equipoise regarding two or more treatment options
such that a person’s values and preferences can meaningfully shift the decision towards one
therapeutic option SDM is not indicated for every clinical decision For decisions where
there is overwhelming support for a particular treatment such that the benefits clearly
outweigh the harms (ie insulin in diabetic ketoacidosis) a more parentalistic model of
decisionmaking is preferred
There are four key steps to implementing SDM in clinical practice 1) explain to the
individual that there is clinical equipoise with respect to how best to treat the disease 2)
present information on the different choices based on the best available evidence 3) support
deliberation between the various therapeutic choices by discussing the person’s values and
their sociopersonal context (eg lifestyle social support financial means workload
capacity) to effectively implement different treatments and 4) formulate a decision (Table
2)65–67 For SDM to be effective physicians must both provide information in an unbiased
manner and support the decision making process In a populationbased survey in the US
nearly everyone (96) reported that they would like to be offered choices and to participate
in the decision making process (steps 1–3 above) however half of respondents preferred
their physician to make the final decision (step 4)68 In these situations a physician can still
engage individuals in SDM through empathic conversation followed by choosing a
therapeutic option that best matches the person’s values and the individual’s effort time
and energy to effectively implement treatment within their lives and routine 69–71
The practice of SDM has many benefits including improving patient’s knowledge regarding
treatment options reducing patient decisional conflict stimulating patients to take a more
active role in the decision making process and leading patients to make more conservative
treatment choices compared to their physicians72 73 For example among patients with
stable coronary disease more complete SDM discussions were strongly associated with
fewer patients choosing to undergo angiography and possible percutaneous coronary
intervention73 Despite these benefits the practice of SDM is suboptimal in current clinical
practice with few physicians providing a balanced explanation of the pros and cons of
therapeutic options and fewer exploring patients’ preferences and values73–75 This may be
in part because implementing SDM in clinical practice is challenging and because the
optimal strategies for practice of SDM have yet to be identified and represent a growing area
of research To facilitate SDM the use of decision aids (either in electronic pamphlet or
video format) can help clarify the decision present evidencebased information regarding
the potential benefits and harms of different therapeutic options and elicit patient’s values72
The use of visual aids such as icon arrays have been shown to improve a patient’s
understanding of probabilistic information on the benefits and harms of treatment76
Makam and Nguyen Page 12
Circulation Author manuscript available in PMC 2018 January 10
Author Manuscript Author Manuscript Author Manuscript Author ManuscriptShared Decision Making in Diabetes
Given the very modest potential gains from antihyperglycemic treatment (Figure 2) an
individual’s treatment burden can potentially negate any benefit gained from intensive
glycemic control (Figure 5) Consequently there is clinical equipoise regarding treating to
an HbA1c of 64–70 among adults with diabetes Thus it is essential to elicit patients’
values preferences and sociopersonal context and use this information to make treatment
decisions To translate the principles of shared decision making into a pragmatic clinical
model we outline a SDM approach in Table 2 through the lens of a treatment decision
scenario of whether or not to initiate insulin This SDM model is informed by the conceptual
framework by Charles and colleagues and extends on principles from two other pragmatic
SDM approaches65–67 77 To our knowledge no decision aid for setting glycemic goals in
diabetes currently exists However once the decision has been made to treat diabetes the
Diabetes Medication Choice decision aid (httpsdiabetesdecisionaidmayoclinicorg) can
help physicians prescribe the optimal medication that best aligns with the patient’s
preferences and sociopersonal context71 78 since the best available evidence shows that
there are no meaningful differences between the available antihyperglycemic drugs for
reducing cardiovascular or allcause mortality79
OVERTREATMENT IN TYPE 2 DIABETES
Current evidence strongly supports that there is a potential epidemic of overtreatment with
antihyperglycemic therapies in diabetes A considerable number of individuals are being
treated aggressively despite the fact that the potential harms of therapy exceed potential
benefits Nationally representative data from three different waves of NHANES from 1999
to 2004 show that glycemic control as measured through HbA1c levels have trended down
among American adults with diabetes80 As of 2012 over 50 of people with diabetes have
achieved HbA1c levels less than 7 which by standard convention is considered well
controlled’ (Figure 6) However achieving tight’ glycemic control is not an end in and of
itself and may represent overtreatment if the patients who have achieved HbA1c levels less
than 7 have minimal potential for benefit are exposed to greater risk of harm andor have
life expectancies shorter than the time horizon to benefit
A closer examination of the data indeed shows that many of these individuals who have
achieved tight’ glycemic control are likely being overtreated – those with the most potential
for harm and the least potential to benefit are being treated too intensively Using NHANES
data Lipska and colleagues found that nearly 60 (18 million) of the 3 million older
patients with diabetes in the US with limited life expectancy [ie health classified as being
complex intermediate (≥ 3 chronic conditions or ≥ 2 instrumental activities of daily living
impairments) or complex poor (dialysis dependent or ≥ 2 activities of daily living
impairments)] nonetheless have HbA1c levels less than 781 Furthermore among these 18
million older adults nearly 60 are using insulin andor sulfonylureas two classes of
antihyperglycemic therapies with the greatest potential for harms81 This implies that many
of these multimorbid and frail older adults are unlikely to experience the potential benefits
of intensive glycemic control but nonetheless are exposed to the potential harms of therapy
including hypoglycemia and decreased quality of life due to the treatment burden itself
Makam and Nguyen Page 13
Circulation Author manuscript available in PMC 2018 January 10
Author Manuscript Author Manuscript Author Manuscript Author ManuscriptIn the Veteran Affairs healthcare system the pattern of overtreatment is similar
Approximately 50 of older veterans who are prescribed insulin andor a sulfonylurea and
are at high risk for hypoglycemia (≥ 75 years of age serum creatinine ≥ 2 mgdL andor
dementia) have achieved HbA1c levels less than 782 While the authors were unable to
assess the rate of severe hypoglycemia in this high risk cohort others have shown that
hospitalizations for hypoglycemia among older adults with diabetes are now more common
in the US than hospitalizations for hyperglycemia (105 vs 70 admissions per 100000
personyears)83 with patients with the lowest HbA1c levels being at greatest risk84
Lastly in a national cohort of more than 30000 individuals with diabetes enrolled in private
and Medicare Advantage insurance plans in the US nearly 20 of those with a HbA1c level
less than 7 were individuals with advanced clinical complexity (≥75 years of age or high
comorbidity burden) received intensive antihyperglycemic therapy These individuals had
nearly double the probability of severe hypoglycemia (30) compared to those receiving
standard antihyperglycemic therapy (17)85 Taken together these data suggest that we as
a collective profession are substantially overtreating diabetes without regard for absolute
benefits harms or time horizon to benefit
Aside from making the appropriate initial recommendation of whether or not to pursue
intensive glycemic control another approach to overcoming overtreatment of diabetes is to
deintensify antihyperglycemic medications when HbA1c levels are at or below goal by either
reducing medication doses or discontinuing therapy altogether if warranted However
medication deintensification is uncommon in clinical practice Among older veterans who
are actively being treated for diabetes medication deintensification rates are fairly low
(<30) even among patients with extremely tight’ glycemic control (HbA1c levels < 6)
and limited life expectancy as predicted by multimorbidity and age86
There are several reasons for this clinical inertia First a substantial proportion of physicians
believe that intensive glycemic control is beneficial even among older adults at high risk for
adverse effects In a national survey of primary care physicians nearly 40 believed that a
hypothetical older adult with diabetes at high risk for hypoglycemia (HbA1c of 64
chronic kidney disease and treated with a sulfonylurea) would benefit from an HbA1c level
lower than 7087 Similarly almost half of providers (45) worried that this individual
would be harmed by an HbA1c level above 7087 Second practice guidelines for diabetes
focus primarily on glycemic goals and have been slow to incorporate EBM and patient
centered principles into revised recommendations In the 2015 American Diabetes
Association (ADA) Standards of Medical Care in Diabetes (93 pages) and the ADA and
European Association for the Study of Diabetes position statement (20 pages) there was not
a single mention of the absolute magnitude of potential harms or benefit of intensive
glycemic control88 Furthermore practice guidelines for diabetes are relatively blind to
context In a review of 28 different practice guidelines for setting glycemic goals in type 2
diabetes only 60 considered comorbidities 40 considered sociopersonal context (eg
financial means caregiver support) and 40 considered patient preference89 Overall the
synthesis of best available evidence to incorporate information on absolute benefits and
harms and on patient preferences remains suboptimal and may unintentionally lead to
uniform rather than personalized application of glycemic control goals to patient care even
Makam and Nguyen Page 14
Circulation Author manuscript available in PMC 2018 January 10
Author Manuscript Author Manuscript Author Manuscript Author Manuscriptwhen the harms of therapy outweigh the potential benefits in many individuals with
diabetes
CONCLUSION AN EBM APPROACH IS NEEDED TO PREVENT
OVERTREATMENT
In summary Figure 1 illustrates an EBM framework that can be used for clinical decision
making to inform treatment decisions To promote personalized care and overcome overuse
it is essential to incorporate best available evidence (balancing absolute harms and benefits
while incorporating the time horizon to benefit) with the physician’s judgment
(individualizing the evidence based on a patient’s risk profile prognosis and context) and the
patient’s preferences and values (via shared decision making) What EBM does not entail is
eschewing clinical significance and patient preferences for statistical significance nor does
it entail the uniform application of therapies based on measures of average population
tendencies especially when the level of evidence is weak In contrast an EBM approach
calls for making personalized treatment recommendations with full consideration given to a
patient’s individual sociopersonal context and values
Applying this EBM framework to the example of managing hyperglycemia in type 2
diabetes highlights the clinical equipoise in setting glycemic goals for diabetes—that no
single HbA1c level is appropriate for all patients As such we should abandon the notion that
HbA1c levels less than or equal to 7 are well controlled’ and greater than 7 are
uncontrolled’ This arbitrary dichotomy does not adequately portray whether we are
optimizing the benefits of treatment quality of life and value for individuals since most
people with diabetes in the uncontrolled’ range (ie HbA1c >7) are nonetheless
asymptomatic (Figure 6) and achieving tight’ glycemic control does not meaningfully
reduce cardiovascular complications Rather an EBM approach would consist of treating to
achieve adequate glycemic control to prevent symptomatic disease (eg polyuria
polydipsia) followed by further consideration of more intensive treatment if a clinical
assessment suggests that the potential absolute benefits outweigh the harms as with any
other cardiovascular risk factor This assessment would encompass a thorough understanding
of the patient’s risks prognosis (ie age comorbidities and functional status) and socio
personal context (eg lifestyle social support workload capacity) as well as engaging with
the patient to elicit perceived or experienced treatment burden and values and preferences
for care Above all else it is imperative for physicians to remember that the fundamental
goal is to help individuals who have diabetes make the best therapeutic decision to improve
their overall health and quality of life not to prevent diabetesrelated complications by any
means possible
The EBM approach we present here is not limited to the consideration of intensive glycemic
control in type 2 diabetes but rather is intended to serve as a framework to inform treatment
decisions more broadly Furthermore this EBM framework also enables physicians to
directly advance the overall goal of the national precision medicine’ initiative—to
individualize treatments to achieve the best health outcomes for each person15 To achieve
this goal further advances in genomics and other biomedical knowledge will undoubtedly be
Makam and Nguyen Page 15
Circulation Author manuscript available in PMC 2018 January 10
Author Manuscript Author Manuscript Author Manuscript Author Manuscriptinstrumental however physicians currently have the tools available at their disposal to
personalize care for many important treatment decisions without further medical innovation
As such the purpose of this review is a call to action for physicians medical educators
researchers and policy leaders to apply the principles of EBM to individualize treatment
decisions to optimize the health and wellbeing of patients
Acknowledgments
The authors would like to thank Lei Xuan PhD Division of Outcomes and Health Services Research UT
Southwestern Medical Center for her assistance in analyzing the National Health and Nutrition Examination Study
data used in Figure 6 All persons who have made substantial contributions to the manuscript but who do not fulfill
authorship criteria are named with their specific contributions in the Acknowledgements section of the manuscript
and all persons named in the Acknowledgements section have provided the corresponding author with written
permission to be named in the manuscript
SOURCES OF FUNDING
Drs Makam and Nguyen received funding from the UT Southwestern KL2 Scholars Program (NIHNCATS KL2
TR0001103) Dr Makam was also supported by a NIHNIA K23 award (K23 AG052603) Dr Nguyen was also
supported by the Agency for Healthcare Research and Qualityfunded UT Southwestern Center for Patient
Centered Outcomes Research (R24 HS022418)
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82 Tseng CL Soroka O Maney M Aron DC Pogach LM Assessing potential glycemic
overtreatment in persons at hypoglycemic risk JAMA Intern Med 2014 174259–268 [PubMed
24322626]
83 Lipska KJ Ross JS Wang Y Inzucchi SE Minges K Karter AJ Huang ES Desai MM Gill TM
Krumholz HM National trends in US hospital admissions for hyperglycemia and hypoglycemia
among Medicare beneficiaries 1999 to 2011 JAMA Intern Med 2014 174(7)1116–1124
[PubMed 24838229]
84 Lipska KJ Warton EM Huang ES Moffet HH Inzucchi SE Krumholz HM Karter AJ HbA1c
and risk of severe hypoglycemia in type 2 diabetes the Diabetes and Aging Study Diabetes Care
2013 363535–3542 [PubMed 23900589]
85 McCoy RG Lipska KJ Yao X Ross JS Montori VM Shah ND Intensive Treatment and Severe
Hypoglycemia Among Adults With Type 2 Diabetes JAMA Intern Med 2016 176969–978
[PubMed 27273792]
86 Sussman JB Kerr EA Saini SD Holleman RG Klamerus ML Min LC Vijan S Hofer TP Rates
of Deintensification of Blood Pressure and Glycemic Medication Treatment Based on Levels of
Makam and Nguyen Page 20
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptControl and Life Expectancy in Older Patients With Diabetes Mellitus JAMA Intern Med
20151–8
87 Caverly TJ Fagerlin A ZikmundFisher BJ Kirsh S Kullgren JT Prenovost K Kerr EA
Appropriate Prescribing for Patients With Diabetes at High Risk for Hypoglycemia National
Survey of Veterans Affairs Health Care Professionals JAMA Intern Med 20151–3
88 McCormack JP Martin SA Newman DH Comment on Inzucchi et al Management of
Hyperglycemia in Type 2 Diabetes 2015 A PatientCentered Approach Update to a Position
Statement of the American Diabetes Association and the European Association for the Study of
Diabetes Diabetes Care 201538140–149 Diabetes Care 2015 38e141–142 [PubMed
26294778]
89 Wyatt KD Stuart LM Brito JP Carranza Leon B Domecq JP Prutsky GJ Egginton JS Calvin
AD Shah ND Murad MH Montori VM Out of context clinical practice guidelines and patients
with multiple chronic conditions a systematic review Med Care 2014 52(Suppl 3)S92–S100
[PubMed 23969592]
Makam and Nguyen Page 21
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptFigure 1 EvidenceBased Medicine Framework for Clinical Decision Making
Adapted from a conceptual framework put forth by Sacket et al17
aEstimated based on age comorbidities and functional status
bIncludes an individual’s lifestyle social support financial circumstances and workload
capacity
Makam and Nguyen Page 22
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptFigure 2 Estimated Lifetime Absolute Benefits of Intensive Glycemic Control for Preventing
Microvascular Outcomes
A Treatment Scenario 1 initiation of metformin at diagnosis with HbA1c reduction from
85 to 70
B Treatment Scenario 2 initiation of insulin 10 years after failing’ initial oral therapy with
HbA1c reduction from 85 to 75
Abbreviations ESRD endstage renal disease MI myocardial infarction The number
needed to treat values were calculated from the estimated absolute risk reductions based on
Vijan and colleagues’ Markov simulation model40 For scenario 2 the absolute risk
reduction for prevention vision loss among 75 year olds with newonset diabetes was 0
thus yielding a number needed to treat of infinity
Makam and Nguyen Page 23
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptFigure 3 Time horizon to benefit for intensive glycemic control for intermediate microvascular
outcomes
The composite microvascular endpoint was defined as retinopathy requiring
photocoagulation presence of vitreous hemorrhage and or fatal or nonfatal renal failure
defined as an elevated creatinine >28 mgdL Reprinted from the Lancet 352(9131) 837–
853 Copyright ©1998 with permission from Elsevier27
Makam and Nguyen Page 24
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptFigure 4 Patients’ Perceptions of Quality of Life for Selected Diabetes Treatments and
Complications
Median quality of life utility values for various treatments and complications were derived
from Huang et al61 The orange bars for intensive glucose control and mild stroke are added
for emphasis to highlight that on average patients perceive these different states as having
the same magnitude in the decrease in quality of life
Makam and Nguyen Page 25
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptFigure 5 Balancing Benefits and Harms of Antihyperglycemic Treatment
Net lifetime qualityadjusted life years gained or lost by a treatment that leads to a 1
reduction in the hemoglobin A1C level (from 85 to 75) across four age groups and
different views of the burden of treatment (disutility value for treatment ranging from 0 to
005) This figure was reproduced with permission from JAMA Internal Medicine 2014
174(8) 1227–123440 Copyright ©2014 American Medical Association
Makam and Nguyen Page 26
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptFigure 6 Conceptual Model for Classifying Hemoglobin A1c Distribution Among US Adults
with Diabetes NHANES 2011–2012
Abbreviations NHANES National Health and Nutrition Examination Survey The current
paradigm of glucose management in type 2 diabetes is to classify adults as being
controlled (solid shaded grey area) if the hemoglobin A1C level is less than 7 and
uncontrolled if the hemoglobin A1C level is greater than 7 (solid shaded light grey area)
Since this classification does not define whether treating glucose to lower levels is beneficial
for an individual patient we propose classifying diabetes as asymptomatic and symptomatic
(shaded areas indicated by dashed lines) such that for asymptomatic patients a shared
decision making discussion between the patient and clinician should occur first before
reflexively treating glucose to lower levels Although we dichotomize this distinction at 9
at the population level patients may have symptoms related to hyperglycemia at lower
values of hemoglobin A1C
Makam and Nguyen Page 27
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptAuthor Manuscript Author Manuscript Author Manuscript Author Manuscript
Makam and Nguyen Page 28
Table 1
Relative Benefits of Intensive Glycemic Control in Type 2 Diabetes Mellitus
Outcome Relative risk reduction Source
Retinopathy * 29 per 09 ↓ A1c UKPDS27
Neuropathy † 19 per 09 ↓ A1c UKPDS27
Microalbuminuria‡ 33 per 09 ↓ A1c UKPDS27
Nonfatal myocardial infarction 15 per 10 ↓ A1c Boussageon et al31
*Surrogate outcome defined as one microaneurysm or more in one eye or worse retinopathy and progression of retinopathy as a twostep change in
Early Treatment of Diabetic Retinopathy Study grade
†Surrogate outcome defined as loss of both ankle or both knee reflexes or mean biothesiometer reading from both toes > 25 volts
‡Surrogate outcome defined as urinary albumin concentration greater than 50 mgL
Circulation Author manuscript available in PMC 2018 January 10Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Makam and Nguyen Page 29
Table 2
Shared Decision Making Model for Clinical Practice
Treatment decision scenario Should a patient with diabetes with a hemoglobin A
1C
value of 85 despite taking three oral antihyperglycemic medications initiate insulin to target an A
1C
of
75
Step 1 Explain equipoise
Step 2 Present information
Step 3 Support deliberation by empathic conversation
Step 4 Formulate a decision
Explain equipoise
Regarding your
diabetes let’s talk about how best to move forward There is good evidence
to support two different treatment strategies to managing your diabetes These strategies have different pros and cons As such people differ in what they believe is most important
Invitation for SDM
To figure out the
best approach for you shall we discuss
the details for each treatment approach
Present options
The two different treatment
options include starting insulin to lower your blood sugar versus continuing your current diabetes medications and monitoring your blood sugars every 3 to 6 months as we have been doingExplain the details of the treatment which here
in this example includes insulin administration and need for frequent blood glucose monitoring Explain potential benefits and harms of therapy using absolute measures of risk (with the use
of visual aids if available) and the time horizon of benefit
Openended questions
Having discussed the two treatment options
what from your perspective is most important to
you
What are the most important aspects of insulin
that you are factoring into your decision
What do you think of the possible benefits of starting insulinWhat do you think of the potential harms of
starting insulin
Specific probes to assess how the treatment may
fit within a patient’s lifestyle and routine
What is your typical meal schedule like
What barriers do you foresee in injecting insulin
or checking your blood sugars regularly within
your current routineAre there others at home who can help
Clarify roles
Some people prefer to make the
decision together Others prefer to defer the decision entirely to their doctor while some prefer to make the decision themselves Which do you preferFinalizing a decision Patient is decider
Are you ready to make a
decision Would you like more time to more carefully think it over or discuss it with your friends
or family
Doctor is involved in the decision
Understanding
what you value and how you seem to weigh the pros and cons I recommend we should proceed with…Review the decision
To ensure that we are on the
same page you [we] have decided that proceeding
with […] is the best approach for you Is that
correct
Throughout the shared decision making conversation
Check understanding periodically using
ask tell ask
in a nonjudgmental way
To make sure I am doing a good job explaining things to you can you please tell me what we discussed about […] I know
we discussed a lot of information and it can be hard to keep everything straight so let’s review what you understand about […]
Defer closure by patients who prefer to defer the decision entirely to the clinician before expressing their values and opinions
I would be pleased to make the decision for you but for me to make the
best decision about how to move forward it is important I understand how you value each treatment
This model for shared decision making was informed by models from Elwyn
et al
and Stiggelbout
et al
66
67
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Therapy in Diabetes to Overcome Overtreatment
Anil N Makam MD MAS12 and Oanh K Nguyen MD MAS12
1Division of General Internal Medicine UT Southwestern Medical Center
2Division of Outcomes & Health Services Research UT Southwestern Medical Center
Abstract
Overtreatment is pervasive in medicine and leads to potential patient harms and excessive costs in
healthcare Although evidencebased medicine (EBM) is often derided as practice by rote
algorithmic medicine the appropriate application of key EBM principles in clinical decision
making is fundamental to preventing overtreatment and promoting highvalue individualized
patientcentered care Specifically this article discusses the importance of 1) using absolute rather
than relative estimates of benefits to inform treatment decisions 2) considering the time horizon to
benefit of treatments 3) balancing potential harms and benefits and 4) using shared decision
making by physicians to incorporate the patient’s values and preferences into treatment decisions
Here we illustrate the application of these principles to considering the decision of whether or not
to recommend intensive glycemic control to patients in order to minimize microvascular and
cardiovascular complications in type 2 diabetes mellitus Through this lens this example will
illustrate how an EBM approach can be used to individualize glycemic goals and prevent
overtreatment and can serve as a template for applying EBM to inform treatment decisions for
other conditions to optimize health and individualize patient care
Keywords
Diabetes Mellitus EvidenceBased Medicine Medical Overuse Diabetes Complications Clinical
DecisionMaking Review [Publication Type]
INTRODUCTION WHAT IS OVERTREATMENT
Overtreatment is defined by the Institute of Medicine as the use of a treatment even when the
potential harms exceed the possible benefits1 Overtreatment is pervasive in medicine and is
not limited to a single therapeutic category2 Overuse which encompasses both overtesting
and overtreatment accounts for nearly 20 of the estimated 750 billion of wasteful
spending in health care in the United States3 Additionally many physicians in the US
recognize that their own patients are receiving too much medical care that is potentially
Correspondence to Anil N Makam MD MAS 5323 Harry Hines Blvd Dallas TX 753909169 (t) 2146483272 (f) 2146483232
AnilMakam@UTSouthwesternedu
DISCLOSURES
None
HHS Public Access
Author manuscript
Circulation Author manuscript available in PMC 2018 January 10
Published in final edited form as
Circulation 2017 January 10 135(2) 180–195 doi101161CIRCULATIONAHA116022622
Author Manuscript Author Manuscript Author Manuscript Author Manuscriptharmful In a nationally representative survey 42 of US primary care physicians thought
their patients were receiving too much care in their own practices4 Even more were
concerned about overly aggressive practice styles among medical subspecialists (61)4
Despite the potential for harm the enormous costs and increasing awareness overtreatment
nonetheless remains prevalent due to many systemlevel factors including financial
incentives malpractice concerns performance metrics practice culture and time
constraints3–14 Although legal policy and health system reforms are needed frontline
action in parallel by individual physicians is also critical to addressing the epidemic of
overtreatment Applying the principles of evidencebased medicine (EBM) to the clinical
decision making process is a key strategy that physicians can use both at the bedside and in
guideline development and policy decisions to prevent overtreatment in their immediate
spheres of influence This review article will outline an EBM framework to guide clinical
decision making to enable individualized medical treatment decisions concordant with the
aims of patientcentered and personalized healthcare increasing areas of national
priority15 16
WHAT IS EVIDENCEBASED MEDICINE
In the words of the late David Sackett a founding father of evidencebased medicine EBM
is the conscientious explicit and judicious use of current best evidence in making
decisions about the care of individual patients [emphasis added]17 The practice of EBM
does not consist of universal rote application of clinical guidelines Rather EBM requires
physicians to assess and understand what the best available evidence is use his or her
clinical judgment to apply this knowledge to the treatment of individual patients and do so
in the context of the patient’s values and preferences (Figure 1) Thus the practice of EBM
is not cookbook’ medicine but is a complex and nuanced approach requiring mastery of
three separate but overlapping domains of knowledge
There are two key reasons why practicing EBM is not synonymous with the delivery of
algorithmic cookbook’ medicine First many recommendations and guidelines are poorly
substantiated by current evidence and as such should not be broadly disseminated and
indiscriminately applied18 For example among the American College of Cardiology (ACC)
and the American Heart Association (AHA) practice guidelines issued between 1984 and
2008 only 11 of the 2711 recommendations were classified as level of evidence A (ie
supported by multiple randomized trials or a metaanalysis)19 Furthermore among the
1305 class I ACCAHA guideline recommendations which indicate general consensus that
a particular health care service is useful and effective only 19 have level of evidence A19
As such approximately 20 of class I ACCAHA guideline recommendations were
downgraded reversed or omitted within a decade suggesting questionable durability in the
absence of strong evidence20 The proliferation of recommendations based on a weak or
nonexistent evidence base is not only an issue for practice guidelines but is a phenomenon
observed among popular online evidencebased’ resources For example approximately
twothirds of the 9400 graded recommendations in UpToDate are supported by weak
evidence (ie absence of clinical trials or robust observational studies)18
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptThe second and more compelling reason why EBM is not synonymous with cookbook’
medicine is that even for recommendations based on strong levels of evidence decisions in
clinical practice are still ultimately value judgements – ie decisions ultimately hinge on the
physician’s and patient’s assessment of whether or not a treatment is actually worth it after
considering the potential harms and benefits enumerated in the scientific literature17 18
Science can be used to inform clinical decisions but cannot definitively inform value
judgements since the significance of potential benefits and harms of a therapy are in the eye
of the beholder and will differ across individuals Thus the EBM triad requires a bottomup
approach that incorporates the best available evidence with both the physician’s expertise
and judgement and the patient’s values and preferences
AN EBM APPROACH TO OVERCOMING OVERTREATMENT AND
PERSONALIZING THERAPEUTIC DECISIONS
Distilled to its simplest form an EBM approach provides guidance for making the best
therapeutic decision for an individual patient through the understanding and application of
four key principles
1 Absolute estimates of benefit What are the absolute (and not relative) benefits
of a particular therapy for patientcentered outcomes
2 Time horizon to benefit How long must a patient be on a particular therapy in
order to reap the potential benefit compared to their current life expectancy
3 Balance of benefits versus harms Do the potential absolute benefits outweigh
the potential harms of therapy for the specific patient under consideration
4 Shared decision making Is the decision to treat consistent with the patient’s
values and preferences
Case Example Should Physicians Recommend Intensive Glycemic Control in Patients
With Type 2 Diabetes Mellitus
To illustrate how EBM principles should be applied to clinical decision making we present
the case example of considering whether to recommend intensive glycemic control in
patients with type 2 diabetes mellitus (henceforth referred to as diabetes’) to reduce
microvascular and cardiovascular complications While using an EBM approach is not
unique to specific diseases diabetes is an ideal disease model to illustrate how an EBM
approach can prevent the harms of overtreatment because 1) diabetes is highly prevalent21
2) the strategy of intensive glycemic control has been thoroughly investigated and there is a
large body of evidence available on the benefits and harms of this treatment strategy 3) the
decision to pursue glycemic control is influenced less by external factors (ie financial
incentives and malpractice concerns) and more by physicians’ clinical decision making
compared to other conditions (eg percutaneous coronary intervention for stable
angina)22 23 and 4) applying an EBM approach to the treatment of hyperglycemia in type 2
diabetes highlights the discordance between the current prevailing paradigm of treatment
versus what is actually supported by the best available current evidence
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptASSESSING THE ABSOLUTE ESTIMATES OF TREATMENT BENEFIT FOR
PATIENTCENTERED OUTCOMES
To understand why absolute estimates of benefit are the preferred measure of treatment
efficacy it is first necessary to understand the limitations of relative risks Imagine a
hypothetical trial assessing the benefit of drug X versus placebo in preventing myocardial
infarction over a oneyear treatment period If the outcome occurs in 10 of individuals on
drug X (risk 1) versus 15 taking placebo (risk 2) the relative risk (RR) of a myocardial
infarction for individuals prescribed drug X is 067 (risk 1risk 2) and the corresponding
relative risk reduction (RRR) is 33 (100*(1RR)) In this example the absolute risk
reduction (ARR) for myocardial infarction among individuals treated with drug X is 5
(risk 2–risk 1) and the number needed to treat (NNT) is 20 (1ARR) For this same
hypothetical trial if the risk of myocardial infarction for those prescribed drug X is only 1
and the risk in the placebo group is only 15 the RR remains a deceptively impressive
067 but the ARR is now only 05 and the NNT is 200 indicating a minimally effective
therapy Thus reports of the RR or RRR do not provide physicians any information on the
magnitude of treatment benefit Relying on these measures alone makes it impossible to
assess the clinical relevance of the treatment and may lead to erroneously inflated estimates
about the potential benefit
In contrast absolute estimates of treatment benefit in the form of ARR or NNT more
accurately convey the treatment effect size and potential clinical significance of treatment In
the hypothetical trial above a NNT of 20 means that one would need to treat 20 individuals
(with characteristics within the parameters of the trial’s inclusion and exclusion criteria)
with drug X for one year to prevent one additional myocardial infarction compared to
placebo Notably a NNT of 20 also implies that for every 20 people treated with drug X on
average 19 people derive no benefit with respect to preventing a myocardial infarction
compared to being prescribed placebo over this time period While both the ARR and NNT
are valid measures to convey the absolute benefit of therapy the NNT more clearly
illustrates that the benefits of treatment are not shared equally by every individual in the
treatment group and that most individuals in this example will not derive any benefit after
one year of therapy even for what many would consider a clinically meaningful effect size
There are important limitations to the interpretation and application of absolute risks First
absolute risks are estimated at the population level As the evolutionary biologist Stephen
Jay Gould astutely stated in his essay The Median isn’t the Message variation is the hard
reality not a set of imperfect measures for a central tendency24 Thus ARR and NNT
convey average estimates of benefit in a group and cannot predict the potential benefit for
an individual patient Physicians must therefore also consider an individual’s risk profile for
the outcome of interest based on established risk factors Assessing the potential benefits
(and harms) of treatment in the context of individuals’ risks is essential to the optimal
selection of individuals for treatment Second treating individuals who are either healthier
or sicker than those included in studies can significantly alter the harmbenefit profile of a
therapy25 This phenomenon commonly referred to as indication drift can markedly reduce
the effectiveness of therapies Lastly absolute measures of risk (as well as relative risks) are
Makam and Nguyen Page 4
Circulation Author manuscript available in PMC 2018 January 10
Author Manuscript Author Manuscript Author Manuscript Author Manuscriptestimated only for specific durations of time on treatment and as such do not capture the
full effect of time26 Consequently ARR and NNT provide limited information to guide
treatment decisions beyond the duration reported in clinical studies Despite these
limitations the absolute risk is essential to understanding the magnitude of potential benefit
and is the first step in deciding whether the treatment is valuable for an individual patient
What are the estimated benefits of intensive glycemic control in type 2 diabetes
Large Relative Benefits in Preventing (Mostly Surrogate) Outcomes—Intensive
glycemic control is defined in randomized controlled trials as treatment strategies resulting
in a hemoglobin A1c (HbA1c) value between 64–70 and conventional glycemic control is
defined as treatment strategies resulting in a modestly higher HbA1c between 79 and
8427–31 The relative benefits of intensive versus conventional glycemic control in
diabetes are summarized in Table 1 In the landmark UKPDS trial the relative benefits of 10
years of intensive glycemic control for individuals with newly diagnosed diabetes were only
demonstrated for intermediate markers of microvascular complications (ie progression of
retinopathy on eye exam loss of reflexes or change in biothesiometer readings and
microalbuminuria) but not for actual meaningful clinical manifestations of microvascular
disease (ie vision loss symptomatic neuropathy amputation or endstage renal disease
requiring dialysis)27 Other trials have similarly failed to show improvement in these more
clinically meaningful endpoints32 33
The evidence for the relative benefits of intensive glycemic control for preventing
cardiovascular disease is even less well substantiated Although the benefits for reducing
surrogate microvascular outcomes have been consistently observed in trials31 34 the 15
relative risk reduction for the cardiovascular outcome of nonfatal myocardial infarction
(MI) has not been consistently observed Although three of the four landmark trials on
intensive glycemic control (UKPDS VADT and ADVANCE) did not show a statistically
significant reduction in nonfatal MIs27–30 35 the results of a metaanalysis more clearly
supported this 15 relative reduction31 However it should be noted that intensive glycemic
control has not been shown in parallel to also reduce cardiovascular diseasespecific
mortality (RR 111 95 CI 086–143) or allcause mortality (RR 104 95 CI 091–
119) calling into question the reliability and significance of the reduced risk in nonfatal
MIs31 Additionally intensive glycemic control does not reduce the risk of strokes36 Thus
while diabetes remains a strong prognostic marker for cardiovascular disease achieving
intensive glycemic control does not modify the risk of cardiovascular disease
Of note two recent multicenter diabetes outcomes trials of empagliflozin and liraglutide
demonstrated clinically significant reductions in both cardiovascular diseasespecific and all
cause mortality37 38 While potentially representing important advances in the therapy of
type 2 diabetes the observed mortality reduction in these trials was likely not mediated
through the mechanism of intensive glycemic control for several reasons First while not
explicitly designed to test the effect of intensive glycemic control there was only a modest
reduction in HbA1c of 04 compared to approximately 1 reduction achieved in other
trials none of which showed reductions in cardiovascular or allcause mortality31 37 38
Second the modest37 to nonexistent reductions38 in large vessel atheroscleroticmediated
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Author Manuscript Author Manuscript Author Manuscript Author Manuscriptcardiovascular outcomes (MIs and strokes) were disproportionately smaller in magnitude
than the observed reduction in cardiovascular diseasespecific mortality in these trials These
results suggest that these medications may be working through mechanisms other than
preventing the progression of atherosclerosis which is the implicated causal pathway
between hyperglycemia of diabetes and cardiovascular diseasespecific mortality39 Lastly
the improvement in cardiovascular mortality in both of these trials emerged far earlier than
expected (within the first 3 months for empagliflozin and 6 months for liraglutide) given the
natural history of the progression of atherosclerosis due to hyperglycemia39 Taken together
these trials suggest that the reductions in mortality observed with these medications are not
attributed to intensive glycemic control but rather are due to medicationspecific effects on
other unidentified mechanistic pathways
Modest Absolute Benefits of Intensive Glycemic Control for Diabetes—There is
no direct evidence of an absolute benefit of intensive glycemic control on patientcentered
outcomes such as clinically apparent microvascular disease or mortality despite several well
conducted clinical trials with up to 15 years of followup33 Consequently to estimate the
absolute benefits of glycemic control we must rely instead on simulation studies that model
the potential benefits of glycemic control on clinical outcomes extrapolating the observed
effects on intermediate outcomes from landmark trials over a much longer timespan than is
feasible in those trials This approach represents the best available evidence regarding the
absolute benefits of intensive glycemic control with respect to clinically relevant outcomes
that patients and physicians care about To this end Vijan and colleagues developed a
Markov simulation model to estimate the absolute benefits of intensive glycemic control
using simulated individuals with characteristics based on adults with diabetes sampled in the
National Health and Nutrition Examination Study (NHANES) a nationally representative
population survey in the US40 The authors modeled the risk of progression from the onset
of asymptomatic diabetes to intermediate microvascular outcomes and the cardiovascular
outcome of nonfatal MI using the relative risk reductions with intensive glycemic control
observed in clinical trials (Table 1) The authors then estimated the likelihood of progression
from these intermediate outcomes to endstage complications (eg visual loss amputation
endstage renal disease) and death using findings from other randomized controlled trials
and US populationbased observational studies41–46
Using this model the authors simulated two treatment scenarios commonly encountered in
clinical practice to estimate the absolute benefits of intensive glycemic control on clinically
apparent microvascular and cardiovascular complications of diabetes The first scenario
assesses the benefit of lifelong oral pharmacotherapy to achieve intensive glucose control It
consists of a newly diagnosed person with diabetes with an HbA1c of 85 who is
prescribed metformin and experiences a reduction in the HbA1c level of 15 points to 70
which remains at this level over the course of the person’s life The second scenario assesses
the benefit of augmenting an oral pharmacotherapy regimen with insulin In this scenario
insulin therapy is initiated for the same patient in the first treatment scenario after failing’
10 years of oral antihyperglycemic therapy with a rise in HbA1c level back to 85 Insulin
therapy reduces the HbA1c level to 75 and remains at this level over the remainder of the
person’s life The lifetime absolute benefits of intensive glycemic control for each scenario
Makam and Nguyen Page 6
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Author Manuscript Author Manuscript Author Manuscript Author Manuscriptdepending on the age at which diabetes is initially diagnosed are shown in Figure 2 In both
scenarios the potential benefit of intensive glycemic control greatly declines with the age at
which an individual is diagnosed For an average 75 year old with newly diagnosed diabetes
initiating metformin (Figure 2A) the NNT for preventing endstage renal disease (ESRD)
vision loss and amputation over that person’s lifetime are 143 200 and 125 respectively
For an average 55 year old who failed’ oral antihyperglycemic therapy and was
subsequently initiated on insulin 10 years later for uncontrolled’ diabetes (HbA1c of 85
on oral therapy) the NNT are well above 100 for each microvascular endpoint (Figure 2B)
In other words greater than 99 of adults 65 years of age or older initiated on insulin
therapy to achieve intensive glycemic control will not derive any benefit with respect to
clinically apparent microvascular complications within their lifetime
Although the NNT for preventing nonfatal MIs are considerably more favorable compared
to preventing patientcentered microvascular outcomes across all age groups for both
scenarios the confidence behind these estimates are limited due to the increase in
cardiovascular mortality observed in the ACCORD trial as well as the nonsignificant
increase seen in metaanalyses28 34 36
These findings illustrate the stark differences in using relative versus absolute risks to inform
treatment decisions Even when relative risk reductions for surrogate microvascular and
cardiovascular outcomes are the same across individuals the absolute risk reductions for
corresponding clinically meaningful outcomes may be vastly different for individuals with
different baseline risk profiles and life expectancies Relying on relative risks can vastly
overestimate the benefits from treatment and is the reason why absolute risks are the
preferred method to inform therapeutic decisions
ASSESSING THE TIME HORIZON TO BENEFIT FOR INTENDED THERAPIES
As discussed above a major limitation of absolute measures of risk is that they do not
capture the full effect of time Rather absolute measures of risk quantify the benefits of
treatment in a given time period Consequently absolute measures of risk cannot be used to
quantify the potential benefits of postponing an outcome For example consider a
hypothetical trial of adults with a 100 year followup period where the primary outcome is
mortality Because adult human life expectancies rarely exceed 100 years all trial subjects
will die within the followup period irrespective of any intervention aimed at reducing
mortality in this study Thus the observed absolute risk reduction for the intervention will be
0 (with a NNT of infinity) at the conclusion of the trial In this extreme example relying
solely on the ARR or NNT as measures of effect size may fail to capture a potential benefit
of treatment if therapy postponed the inevitable outcome of death for a clinically meaningful
amount of time (eg perhaps subjects receiving the intervention postponed death by 10
years even if they inevitably died within the 100 year follow up period)
Similarly absolute measures of risk also do not consider the time horizon to benefit—that is
the time that must be accrued on treatment until a meaningful benefit emerges This is a
more commonly encountered issue than postponement of an outcome since study followup
periods tend to be limited in duration For a treatment with a sufficiently long time horizon
Makam and Nguyen Page 7
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Author Manuscript Author Manuscript Author Manuscript Author Manuscriptto benefit individuals with a life expectancy less than the time horizon to treatment benefit
will not reap the potential benefits of treatment Thus these individuals will be exposed to
the potential upfront harms of therapy without any chance of benefit a classic scenario of
overtreatment To avoid these potential harms only individuals whose anticipated life
expectancy exceeds the estimated time horizon to benefit should be considered as candidates
for treatment
The time horizon to benefit can be estimated from clinical studies by calculating the
difference in the area under the survival curves though these measures are infrequently
quantified and reported Alternately the time horizon to benefit can be qualitatively
estimated by assessing KaplanMeier survival curves for the intervention and control groups
to identify the point at which the two curves diverge47 This divergence point provides an
estimate of the minimum time horizon to benefit for a given treatment To illustrate how to
estimate the time horizon to benefit using survival curves and understand its implications
we will return to the example of diabetes
Time Horizon to Benefit for Intensive Glycemic Control in Diabetes
Based on the KaplanMeier curve from the UKPDS trial it takes approximately 9 years of
intensive glycemic control to yield an observable reduction in composite microvascular
events in the treatment group (vertical dashed line in Figure 3) However it is important to
note that the composite microvascular outcome reported in the UKPDS trial consists mostly
of intermediate outcomes that may not directly harm patients (ie need for photocoagulation
vitreous hemorrhage or renal failure defined as an elevated creatinine >28 mgdL) The
potential for intensive glycemic control to prevent more meaningful microvascular outcomes
(ie vision loss or ESRD requiring dialysis) is estimated to take 2 or more decades to
manifest48 Of note even with an additional 10 years of followup in the UKPDS trial (for a
total of 25 years) improvements in these endpoints have not yet been reported49 This
suggests that the legacy effect observed for surrogate microvascular endpoints seen after a
decade of early intensive glycemic control in patients with newly diagnosed diabetes may
not translate into reductions in patientcentered microvascular outcomes
Despite the long time horizon to benefit for intensive glycemic control many patients
prescribed intensive glycemic control nonetheless have life expectancies less than 20 years
and potentially even less than 9 years the earliest time interval after which one could expect
to observe benefits for intermediate microvascular outcomes50 This is a clear example of
overtreatment – individuals who are initiated on intensive glycemic control who have a life
expectancy of less than 9 years are exposed to the potential harms of treatment without any
reasonable chance of benefit Consequently a pragmatic approach to avoiding the harms of
overtreatment would be to defer intensive glycemic control in individuals with a life
expectancy that is clearly less than 9 years For example individuals with advanced cancers
ESRD advanced dementia cirrhosis and endstage heart failure and lung disease are
unlikely to benefit from intensive glycemic control
There are also several highly prevalent but less commonly recognized conditions that also
indicate poor prognosis and limited life expectancy After a first hospitalization for heart
failure with either preserved or reduced ejection fraction individuals have a 70 5year
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Author Manuscript Author Manuscript Author Manuscript Author Manuscriptmortality rate51 52 Likewise after the first hospitalization for chronic obstructive
pulmonary disease (COPD) exacerbation individuals have an 80 9year mortality53 Thus
initiating intensive glycemic control during or after an index hospitalization for either heart
failure or COPD is unlikely to yield any benefit beyond that of a conventional glycemic
control strategy
Individuals with multimorbidity and impaired functional status also have limited life
expectancy due to the cumulative burden of illness though prognosis can be challenging to
assess in these complex patients The Lee Schonberg Index is a validated tool that quantifies
the 4year and 10year risk of mortality among community dwelling adults 50 years of age
or older (httpeprognosisucsfeduleeschonbergphp)54 55 This index assesses the
cumulative contribution of age selected comorbidities and health behaviors (diabetes
cancer heart disease lung disease body mass index < 25 and current smoker) and
impairments in functioning (bathing managing finances ambulating and pushing or pulling
heavy objects) on the risk of mortality using a point score ranging from 0 to 25 with higher
scores corresponding to higher risk of death The Lee Schonberg Index has excellent
discrimination (Cstatistic of 083) and calibration (less than a 4 difference between
predicted and observed mortality rates across all risk levels)55
In a nationally representative longitudinal cohort the Lee Schonberg Index identified that
25 of community dwelling individuals 50 years of age or older have a greater than 50
risk of death within 10 years55 Thus 1 in 4 middleaged and older adults in the US are
unlikely to live 10 years let alone 20 years in order to reap the benefits of intensive
glycemic control This is reflected in the exceedingly low lifetime absolute benefits for
intensive glycemic control estimated for individuals who have high point scores on the Lee
Schonberg Index In a decision analysis study Huang and colleagues developed a simulation
model based on data from the UKPDS trial and found that among older adults with diabetes
those with greater multimorbidity and functional impairment are far less likely to benefit
from intensive glucose control56 For example for individuals aged 60 to 64 years who have
newonset diabetes and only 1 point on the Lee Schonberg Index the NNT to prevent
ESRD blindness and amputation over one’s lifetime are approximately 125 83 and 77
respectively In contrast the lifetime NNT for the same scenario except for patients who
have significant multimorbidity and functional impairment (Lee Schonberg Index score of
15 points) are infinity (ARR of 0) 2700 and 1125 respectively56 Thus only the few
older adults with diabetes and almost no functional limitations will derive benefit from
intensive glucose control Those with substantial multimorbidity and functional limitations
have an infinitesimally small probability of deriving any benefits from this treatment
strategy
ASSESSING THE BALANCE BETWEEN POTENTIAL BENEFITS VERSUS
HARMS OF TREATMENT
Overtreatment may arise when one focuses only on the benefits of therapy without any
consideration of potential harms since this would lead to always favoring treatment even if
the benefit of treatment is extremely small Thus it is critical to understand and assess the
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Author Manuscript Author Manuscript Author Manuscript Author Manuscriptpotential harms of treatment and to incorporate this knowledge into treatment decisions
The potential harms of therapy are quantified through estimates of the absolute risk increase
and the number needed to harm (NNH) for specific adverse effects related to treatment
Awareness of both the NNT and NNH for a given treatment can help physicians and patients
alike make more informed decisions about whether the potential for benefits is worth taking
the risks
There are several challenges in assessing the balance between the NNT and NNH for
treatments First since each individual beneficial or harmful effect will have varying impact
on quality of life it may be difficult to directly compare benefits and harms Consider for
example the potential benefit of preventing a stroke versus the potential harm of causing a
bleed with anticoagulation therapy for atrial fibrillation Compared to major bleeding
having a stroke is considered more detrimental to quality of life since major bleeding is
more likely to be transient and reversible than neurologic deficits from a stroke57 Second
treatments may have a myriad of beneficial and harmful effects consequently it can be
difficult to simultaneously assess the net balance of benefits and harms Third the NNT and
NNH are reported for selected benefits and harms that are discrete in nature (ie present or
absent) and are not designed to take into account the effect of treatment on other measures
of quality of life (ie treatment burden) that are also important to patients By only
considering the value of treatment by the NNT and NNH important information may be lost
on other dimensions of therapy
An approach to overcome these limitations is to quantify the balance between the potential
benefits and harms of therapy by estimating the net qualityadjusted life years (QALYs)
associated with treatment This measure of overall health impact incorporates both the
quantity and quality of life related to all potential benefits and harms of therapy QALYs
integrate the general quality of life on a scale from 0 to 1 with values closer to 1 indicating
higher quality of life based on an individual’s probability of being in various disease and
treatment complication states each year58 59 Estimated QALYs when available can thus
allow for direct comparisons of health impact between different treatments
In the absence of studies evaluating the net QALYs gained from therapy the NNT can be
used to estimate the magnitude of benefit for a treatment Acknowledging that the NNT does
not fully account for many factors including the clinical significance of the outcome (ie
microalbuminuria versus ESRD) the cost convenience and invasiveness of the therapy (ie
metformin versus insulin) and the number needed to harm (NNH) for various adverse
effects one may roughly interpret that a NNT greater than 15 is associated with a small net
treatment benefit and a NNT ≤ 5 is typically associated with a meaningful net benefit60
Balancing the Harms and Benefits of Intensive Glycemic Control in Diabetes
With respect to diabetes there are several important potential harms to consider before
prescribing antihyperglycemic therapy While risks are unique to each therapy the most
common side effects of intensive glycemic control reported in clinical trials were severe
hypoglycemia and weight gain both attributable to higher rates of insulin use among these
patients31 33 Severe hypoglycemia occurred in 49 of those on intensive glycemic control
versus 20 among those on conventional glycemic control (absolute risk increase of 29
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptNNH of 35)31 Additionally intensive glycemic control increased body weight by
approximately 333 Another important but often overlooked harm of intensive glycemic
control is the potential decrease in a person’s overall quality of life due to the burden of the
treatment itself Due to the burden of polypharmacy multiple insulin injections frequent
blood glucose monitoring and increased frequency of health care visits an intensive
glycemic control strategy per the UKPDS trial protocol was perceived by individuals to have
a median quality of life utility value of 085 (mean of 067 ± 034) on a scale where perfect
health is 1 and death is 061 A utility of 085 – also referred to as a disutility of 015 – means
individuals equate living 10 years with intensive glycemic control the same as living 85
years in perfect health Notably the decrease in quality of life due to intensive glycemic
control is perceived by patients to be of the same magnitude as that due to a mild stroke
(Figure 4)
In order to balance the potential benefits of intensive glycemic control with the potential
harms Vijan and colleagues used a Markov simulation model as described previously to
estimate the net lifetime QALYs gained with therapy The authors assigned quality of life
utility values to each disease state along the spectrum from asymptomatic diabetes to death
based on prior literature to estimate net QALYs gained or lost40 62 63 The overall treatment
burden was estimated across a range of disutilities for intensive glycemic control for a
scenario where an individual was prescribed a pharmacologic therapy that reduced the
HbA1c from 85 to 75 In this scenario treatment burden has a profoundly detrimental
impact on the net QALYs gained from treatment (Figure 5) If an individual experiences no
treatment burden whatsoever (ie a treatment burden of 0) antihyperglycemic therapy in this
scenario would yield only modest net benefits across all four age groups with a net lifetime
gain of 09 QALYs for an average 45 year old to 01 QALYs for an average 75 year old
However a treatment burden as little as 004 negates any benefit of intensive glycemic
control for all age groups and actually results in loss of quality of life Therefore the value
of intensive glycemic control depends on an individual’s experienced or perceived treatment
burden
These findings should be interpreted in the context of certain limitations First the authors’
optimistic assumptions of a 15 risk reduction in nonfatal myocardial infarction events and
relatively low estimates of treatment disutilities (capped at 005 much lower than the
previously reported median disutility of 015 for intensive glycemic control in Figure 4)
biases the results in favor of intensive glycemic control The actual net loss in quality of life
is likely to be greater than this study suggests Second as discussed earlier the net benefits
of intensive glycemic control are estimated for the average patient for each age group
Individuals with greater risk for microvascular and cardiovascular disease (eg tobacco use
hypertension high cholesterol) compared to the average patient with diabetes (mean blood
pressure of 13080 mmHg and mean lowdensity lipoprotein cholesterol of 100 mg per
deciliter)64 are more likely to derive benefits from intensive glycemic control However
individuals with a lower than average risk profile will have even less to potentially gain from
therapy than the modeled scenarios suggest
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptASSESSING WHETHER TREATMENT IS CONSISTENT WITH PATIENT
VALUES AND PREFERENCES SHARED DECISION MAKING
Shareddecision making (SDM) is defined as a partnership between physicians and patients
to make preferencesensitive decisions together guided by the best available evidence and
the patient’s risks prognosis and sociopersonal context65 Preferencesensitive therapeutic
decisions indicate that there is clinical equipoise regarding two or more treatment options
such that a person’s values and preferences can meaningfully shift the decision towards one
therapeutic option SDM is not indicated for every clinical decision For decisions where
there is overwhelming support for a particular treatment such that the benefits clearly
outweigh the harms (ie insulin in diabetic ketoacidosis) a more parentalistic model of
decisionmaking is preferred
There are four key steps to implementing SDM in clinical practice 1) explain to the
individual that there is clinical equipoise with respect to how best to treat the disease 2)
present information on the different choices based on the best available evidence 3) support
deliberation between the various therapeutic choices by discussing the person’s values and
their sociopersonal context (eg lifestyle social support financial means workload
capacity) to effectively implement different treatments and 4) formulate a decision (Table
2)65–67 For SDM to be effective physicians must both provide information in an unbiased
manner and support the decision making process In a populationbased survey in the US
nearly everyone (96) reported that they would like to be offered choices and to participate
in the decision making process (steps 1–3 above) however half of respondents preferred
their physician to make the final decision (step 4)68 In these situations a physician can still
engage individuals in SDM through empathic conversation followed by choosing a
therapeutic option that best matches the person’s values and the individual’s effort time
and energy to effectively implement treatment within their lives and routine 69–71
The practice of SDM has many benefits including improving patient’s knowledge regarding
treatment options reducing patient decisional conflict stimulating patients to take a more
active role in the decision making process and leading patients to make more conservative
treatment choices compared to their physicians72 73 For example among patients with
stable coronary disease more complete SDM discussions were strongly associated with
fewer patients choosing to undergo angiography and possible percutaneous coronary
intervention73 Despite these benefits the practice of SDM is suboptimal in current clinical
practice with few physicians providing a balanced explanation of the pros and cons of
therapeutic options and fewer exploring patients’ preferences and values73–75 This may be
in part because implementing SDM in clinical practice is challenging and because the
optimal strategies for practice of SDM have yet to be identified and represent a growing area
of research To facilitate SDM the use of decision aids (either in electronic pamphlet or
video format) can help clarify the decision present evidencebased information regarding
the potential benefits and harms of different therapeutic options and elicit patient’s values72
The use of visual aids such as icon arrays have been shown to improve a patient’s
understanding of probabilistic information on the benefits and harms of treatment76
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptShared Decision Making in Diabetes
Given the very modest potential gains from antihyperglycemic treatment (Figure 2) an
individual’s treatment burden can potentially negate any benefit gained from intensive
glycemic control (Figure 5) Consequently there is clinical equipoise regarding treating to
an HbA1c of 64–70 among adults with diabetes Thus it is essential to elicit patients’
values preferences and sociopersonal context and use this information to make treatment
decisions To translate the principles of shared decision making into a pragmatic clinical
model we outline a SDM approach in Table 2 through the lens of a treatment decision
scenario of whether or not to initiate insulin This SDM model is informed by the conceptual
framework by Charles and colleagues and extends on principles from two other pragmatic
SDM approaches65–67 77 To our knowledge no decision aid for setting glycemic goals in
diabetes currently exists However once the decision has been made to treat diabetes the
Diabetes Medication Choice decision aid (httpsdiabetesdecisionaidmayoclinicorg) can
help physicians prescribe the optimal medication that best aligns with the patient’s
preferences and sociopersonal context71 78 since the best available evidence shows that
there are no meaningful differences between the available antihyperglycemic drugs for
reducing cardiovascular or allcause mortality79
OVERTREATMENT IN TYPE 2 DIABETES
Current evidence strongly supports that there is a potential epidemic of overtreatment with
antihyperglycemic therapies in diabetes A considerable number of individuals are being
treated aggressively despite the fact that the potential harms of therapy exceed potential
benefits Nationally representative data from three different waves of NHANES from 1999
to 2004 show that glycemic control as measured through HbA1c levels have trended down
among American adults with diabetes80 As of 2012 over 50 of people with diabetes have
achieved HbA1c levels less than 7 which by standard convention is considered well
controlled’ (Figure 6) However achieving tight’ glycemic control is not an end in and of
itself and may represent overtreatment if the patients who have achieved HbA1c levels less
than 7 have minimal potential for benefit are exposed to greater risk of harm andor have
life expectancies shorter than the time horizon to benefit
A closer examination of the data indeed shows that many of these individuals who have
achieved tight’ glycemic control are likely being overtreated – those with the most potential
for harm and the least potential to benefit are being treated too intensively Using NHANES
data Lipska and colleagues found that nearly 60 (18 million) of the 3 million older
patients with diabetes in the US with limited life expectancy [ie health classified as being
complex intermediate (≥ 3 chronic conditions or ≥ 2 instrumental activities of daily living
impairments) or complex poor (dialysis dependent or ≥ 2 activities of daily living
impairments)] nonetheless have HbA1c levels less than 781 Furthermore among these 18
million older adults nearly 60 are using insulin andor sulfonylureas two classes of
antihyperglycemic therapies with the greatest potential for harms81 This implies that many
of these multimorbid and frail older adults are unlikely to experience the potential benefits
of intensive glycemic control but nonetheless are exposed to the potential harms of therapy
including hypoglycemia and decreased quality of life due to the treatment burden itself
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptIn the Veteran Affairs healthcare system the pattern of overtreatment is similar
Approximately 50 of older veterans who are prescribed insulin andor a sulfonylurea and
are at high risk for hypoglycemia (≥ 75 years of age serum creatinine ≥ 2 mgdL andor
dementia) have achieved HbA1c levels less than 782 While the authors were unable to
assess the rate of severe hypoglycemia in this high risk cohort others have shown that
hospitalizations for hypoglycemia among older adults with diabetes are now more common
in the US than hospitalizations for hyperglycemia (105 vs 70 admissions per 100000
personyears)83 with patients with the lowest HbA1c levels being at greatest risk84
Lastly in a national cohort of more than 30000 individuals with diabetes enrolled in private
and Medicare Advantage insurance plans in the US nearly 20 of those with a HbA1c level
less than 7 were individuals with advanced clinical complexity (≥75 years of age or high
comorbidity burden) received intensive antihyperglycemic therapy These individuals had
nearly double the probability of severe hypoglycemia (30) compared to those receiving
standard antihyperglycemic therapy (17)85 Taken together these data suggest that we as
a collective profession are substantially overtreating diabetes without regard for absolute
benefits harms or time horizon to benefit
Aside from making the appropriate initial recommendation of whether or not to pursue
intensive glycemic control another approach to overcoming overtreatment of diabetes is to
deintensify antihyperglycemic medications when HbA1c levels are at or below goal by either
reducing medication doses or discontinuing therapy altogether if warranted However
medication deintensification is uncommon in clinical practice Among older veterans who
are actively being treated for diabetes medication deintensification rates are fairly low
(<30) even among patients with extremely tight’ glycemic control (HbA1c levels < 6)
and limited life expectancy as predicted by multimorbidity and age86
There are several reasons for this clinical inertia First a substantial proportion of physicians
believe that intensive glycemic control is beneficial even among older adults at high risk for
adverse effects In a national survey of primary care physicians nearly 40 believed that a
hypothetical older adult with diabetes at high risk for hypoglycemia (HbA1c of 64
chronic kidney disease and treated with a sulfonylurea) would benefit from an HbA1c level
lower than 7087 Similarly almost half of providers (45) worried that this individual
would be harmed by an HbA1c level above 7087 Second practice guidelines for diabetes
focus primarily on glycemic goals and have been slow to incorporate EBM and patient
centered principles into revised recommendations In the 2015 American Diabetes
Association (ADA) Standards of Medical Care in Diabetes (93 pages) and the ADA and
European Association for the Study of Diabetes position statement (20 pages) there was not
a single mention of the absolute magnitude of potential harms or benefit of intensive
glycemic control88 Furthermore practice guidelines for diabetes are relatively blind to
context In a review of 28 different practice guidelines for setting glycemic goals in type 2
diabetes only 60 considered comorbidities 40 considered sociopersonal context (eg
financial means caregiver support) and 40 considered patient preference89 Overall the
synthesis of best available evidence to incorporate information on absolute benefits and
harms and on patient preferences remains suboptimal and may unintentionally lead to
uniform rather than personalized application of glycemic control goals to patient care even
Makam and Nguyen Page 14
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Author Manuscript Author Manuscript Author Manuscript Author Manuscriptwhen the harms of therapy outweigh the potential benefits in many individuals with
diabetes
CONCLUSION AN EBM APPROACH IS NEEDED TO PREVENT
OVERTREATMENT
In summary Figure 1 illustrates an EBM framework that can be used for clinical decision
making to inform treatment decisions To promote personalized care and overcome overuse
it is essential to incorporate best available evidence (balancing absolute harms and benefits
while incorporating the time horizon to benefit) with the physician’s judgment
(individualizing the evidence based on a patient’s risk profile prognosis and context) and the
patient’s preferences and values (via shared decision making) What EBM does not entail is
eschewing clinical significance and patient preferences for statistical significance nor does
it entail the uniform application of therapies based on measures of average population
tendencies especially when the level of evidence is weak In contrast an EBM approach
calls for making personalized treatment recommendations with full consideration given to a
patient’s individual sociopersonal context and values
Applying this EBM framework to the example of managing hyperglycemia in type 2
diabetes highlights the clinical equipoise in setting glycemic goals for diabetes—that no
single HbA1c level is appropriate for all patients As such we should abandon the notion that
HbA1c levels less than or equal to 7 are well controlled’ and greater than 7 are
uncontrolled’ This arbitrary dichotomy does not adequately portray whether we are
optimizing the benefits of treatment quality of life and value for individuals since most
people with diabetes in the uncontrolled’ range (ie HbA1c >7) are nonetheless
asymptomatic (Figure 6) and achieving tight’ glycemic control does not meaningfully
reduce cardiovascular complications Rather an EBM approach would consist of treating to
achieve adequate glycemic control to prevent symptomatic disease (eg polyuria
polydipsia) followed by further consideration of more intensive treatment if a clinical
assessment suggests that the potential absolute benefits outweigh the harms as with any
other cardiovascular risk factor This assessment would encompass a thorough understanding
of the patient’s risks prognosis (ie age comorbidities and functional status) and socio
personal context (eg lifestyle social support workload capacity) as well as engaging with
the patient to elicit perceived or experienced treatment burden and values and preferences
for care Above all else it is imperative for physicians to remember that the fundamental
goal is to help individuals who have diabetes make the best therapeutic decision to improve
their overall health and quality of life not to prevent diabetesrelated complications by any
means possible
The EBM approach we present here is not limited to the consideration of intensive glycemic
control in type 2 diabetes but rather is intended to serve as a framework to inform treatment
decisions more broadly Furthermore this EBM framework also enables physicians to
directly advance the overall goal of the national precision medicine’ initiative—to
individualize treatments to achieve the best health outcomes for each person15 To achieve
this goal further advances in genomics and other biomedical knowledge will undoubtedly be
Makam and Nguyen Page 15
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Author Manuscript Author Manuscript Author Manuscript Author Manuscriptinstrumental however physicians currently have the tools available at their disposal to
personalize care for many important treatment decisions without further medical innovation
As such the purpose of this review is a call to action for physicians medical educators
researchers and policy leaders to apply the principles of EBM to individualize treatment
decisions to optimize the health and wellbeing of patients
Acknowledgments
The authors would like to thank Lei Xuan PhD Division of Outcomes and Health Services Research UT
Southwestern Medical Center for her assistance in analyzing the National Health and Nutrition Examination Study
data used in Figure 6 All persons who have made substantial contributions to the manuscript but who do not fulfill
authorship criteria are named with their specific contributions in the Acknowledgements section of the manuscript
and all persons named in the Acknowledgements section have provided the corresponding author with written
permission to be named in the manuscript
SOURCES OF FUNDING
Drs Makam and Nguyen received funding from the UT Southwestern KL2 Scholars Program (NIHNCATS KL2
TR0001103) Dr Makam was also supported by a NIHNIA K23 award (K23 AG052603) Dr Nguyen was also
supported by the Agency for Healthcare Research and Qualityfunded UT Southwestern Center for Patient
Centered Outcomes Research (R24 HS022418)
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptFigure 1 EvidenceBased Medicine Framework for Clinical Decision Making
Adapted from a conceptual framework put forth by Sacket et al17
aEstimated based on age comorbidities and functional status
bIncludes an individual’s lifestyle social support financial circumstances and workload
capacity
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptFigure 2 Estimated Lifetime Absolute Benefits of Intensive Glycemic Control for Preventing
Microvascular Outcomes
A Treatment Scenario 1 initiation of metformin at diagnosis with HbA1c reduction from
85 to 70
B Treatment Scenario 2 initiation of insulin 10 years after failing’ initial oral therapy with
HbA1c reduction from 85 to 75
Abbreviations ESRD endstage renal disease MI myocardial infarction The number
needed to treat values were calculated from the estimated absolute risk reductions based on
Vijan and colleagues’ Markov simulation model40 For scenario 2 the absolute risk
reduction for prevention vision loss among 75 year olds with newonset diabetes was 0
thus yielding a number needed to treat of infinity
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptFigure 3 Time horizon to benefit for intensive glycemic control for intermediate microvascular
outcomes
The composite microvascular endpoint was defined as retinopathy requiring
photocoagulation presence of vitreous hemorrhage and or fatal or nonfatal renal failure
defined as an elevated creatinine >28 mgdL Reprinted from the Lancet 352(9131) 837–
853 Copyright ©1998 with permission from Elsevier27
Makam and Nguyen Page 24
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptFigure 4 Patients’ Perceptions of Quality of Life for Selected Diabetes Treatments and
Complications
Median quality of life utility values for various treatments and complications were derived
from Huang et al61 The orange bars for intensive glucose control and mild stroke are added
for emphasis to highlight that on average patients perceive these different states as having
the same magnitude in the decrease in quality of life
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptFigure 5 Balancing Benefits and Harms of Antihyperglycemic Treatment
Net lifetime qualityadjusted life years gained or lost by a treatment that leads to a 1
reduction in the hemoglobin A1C level (from 85 to 75) across four age groups and
different views of the burden of treatment (disutility value for treatment ranging from 0 to
005) This figure was reproduced with permission from JAMA Internal Medicine 2014
174(8) 1227–123440 Copyright ©2014 American Medical Association
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Circulation Author manuscript available in PMC 2018 January 10
Author Manuscript Author Manuscript Author Manuscript Author ManuscriptFigure 6 Conceptual Model for Classifying Hemoglobin A1c Distribution Among US Adults
with Diabetes NHANES 2011–2012
Abbreviations NHANES National Health and Nutrition Examination Survey The current
paradigm of glucose management in type 2 diabetes is to classify adults as being
controlled (solid shaded grey area) if the hemoglobin A1C level is less than 7 and
uncontrolled if the hemoglobin A1C level is greater than 7 (solid shaded light grey area)
Since this classification does not define whether treating glucose to lower levels is beneficial
for an individual patient we propose classifying diabetes as asymptomatic and symptomatic
(shaded areas indicated by dashed lines) such that for asymptomatic patients a shared
decision making discussion between the patient and clinician should occur first before
reflexively treating glucose to lower levels Although we dichotomize this distinction at 9
at the population level patients may have symptoms related to hyperglycemia at lower
values of hemoglobin A1C
Makam and Nguyen Page 27
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Author Manuscript Author Manuscript Author Manuscript Author ManuscriptAuthor Manuscript Author Manuscript Author Manuscript Author Manuscript
Makam and Nguyen Page 28
Table 1
Relative Benefits of Intensive Glycemic Control in Type 2 Diabetes Mellitus
Outcome Relative risk reduction Source
Retinopathy * 29 per 09 ↓ A1c UKPDS27
Neuropathy † 19 per 09 ↓ A1c UKPDS27
Microalbuminuria‡ 33 per 09 ↓ A1c UKPDS27
Nonfatal myocardial infarction 15 per 10 ↓ A1c Boussageon et al31
*Surrogate outcome defined as one microaneurysm or more in one eye or worse retinopathy and progression of retinopathy as a twostep change in
Early Treatment of Diabetic Retinopathy Study grade
†Surrogate outcome defined as loss of both ankle or both knee reflexes or mean biothesiometer reading from both toes > 25 volts
‡Surrogate outcome defined as urinary albumin concentration greater than 50 mgL
Circulation Author manuscript available in PMC 2018 January 10Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Makam and Nguyen Page 29
Table 2
Shared Decision Making Model for Clinical Practice
Treatment decision scenario Should a patient with diabetes with a hemoglobin A
1C
value of 85 despite taking three oral antihyperglycemic medications initiate insulin to target an A
1C
of
75
Step 1 Explain equipoise
Step 2 Present information
Step 3 Support deliberation by empathic conversation
Step 4 Formulate a decision
Explain equipoise
Regarding your
diabetes let’s talk about how best to move forward There is good evidence
to support two different treatment strategies to managing your diabetes These strategies have different pros and cons As such people differ in what they believe is most important
Invitation for SDM
To figure out the
best approach for you shall we discuss
the details for each treatment approach
Present options
The two different treatment
options include starting insulin to lower your blood sugar versus continuing your current diabetes medications and monitoring your blood sugars every 3 to 6 months as we have been doingExplain the details of the treatment which here
in this example includes insulin administration and need for frequent blood glucose monitoring Explain potential benefits and harms of therapy using absolute measures of risk (with the use
of visual aids if available) and the time horizon of benefit
Openended questions
Having discussed the two treatment options
what from your perspective is most important to
you
What are the most important aspects of insulin
that you are factoring into your decision
What do you think of the possible benefits of starting insulinWhat do you think of the potential harms of
starting insulin
Specific probes to assess how the treatment may
fit within a patient’s lifestyle and routine
What is your typical meal schedule like
What barriers do you foresee in injecting insulin
or checking your blood sugars regularly within
your current routineAre there others at home who can help
Clarify roles
Some people prefer to make the
decision together Others prefer to defer the decision entirely to their doctor while some prefer to make the decision themselves Which do you preferFinalizing a decision Patient is decider
Are you ready to make a
decision Would you like more time to more carefully think it over or discuss it with your friends
or family
Doctor is involved in the decision
Understanding
what you value and how you seem to weigh the pros and cons I recommend we should proceed with…Review the decision
To ensure that we are on the
same page you [we] have decided that proceeding
with […] is the best approach for you Is that
correct
Throughout the shared decision making conversation
Check understanding periodically using
ask tell ask
in a nonjudgmental way
To make sure I am doing a good job explaining things to you can you please tell me what we discussed about […] I know
we discussed a lot of information and it can be hard to keep everything straight so let’s review what you understand about […]
Defer closure by patients who prefer to defer the decision entirely to the clinician before expressing their values and opinions
I would be pleased to make the decision for you but for me to make the
best decision about how to move forward it is important I understand how you value each treatment
This model for shared decision making was informed by models from Elwyn
et al
and Stiggelbout
et al
66
67
Circulation Author manuscript available in PMC 2018 January 10
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