Type 2 diabetes: Which interventions best reduce absolute risks of adverse events?

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Original Research

Type 2 diabetes: Which interventions best reduce absolute risks of adverse events?

J Fam Pract. 2009 June;58(6):E1-E10

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References

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First, it represents as continuous variables the physiologic and other processes that are continuous in reality—unlike, say, the Markov model that introduces progressions abruptly at specified intervals.

Second, it is more comprehensive, containing more than 100 variables: biologic factors, symptoms, tests, treatments, and outcomes.

Third, because it is written with differential equations and object-oriented programming at a level that represents physiologic processes, it more accurately depicts comorbidities and the multiple possible effects of treatments.^8,9

Fourth, the accuracy of a model’s projections depends on the assumptions built into the model. The data used to build Archimedes were derived from basic laboratory studies, clinical trials, and the Kaiser Permanente clinical database. Thus, the model is anchored to a wide variety of populations, treatments, and outcomes, protecting it from over-specification.

How we applied Diabetes PHD to our study. To use Diabetes PHD, we entered sociodemographic information for our hypothetical patient (described below); patient and family health histories; blood pressure, cholesterol, fasting glucose, and glycosylated hemoglobin (HbA1c) levels; and medications the patient was taking for diabetes or for blood pressure or cholesterol reduction. The Archimedes software creates 1000 simulated patients identical to the profile entered by the user. The outcomes for these 1000 patients are simulated over the lifespan of each patient, and each run can be thought of as a clinical trial with 1000 participants.

Results are reported as absolute risk (AR) projections out to >30 years for myocardial infarction (MI), cerebrovascular accident (CVA), end-stage renal disease (ESRD), retinopathy, blindness, foot ulceration, and foot amputation. Once risk projections have been generated, the user can choose from a variety of interventions. Archimedes recalculates the risks, displaying the size of the ARRs graphically.

Our hypothetical base case

The Mount Hood Challenge, established in 2000, is a periodic gathering of university research teams for the purpose of cross-validating diabetes simulation models.^10,11 In the first 3 Mount Hood Challenges, the number of models increased with each gathering, as did the rigor of model validation. In the fourth Mount Hood Challenge, held in 2005, 5 diabetes risk engines were compared using 2 published patient data sets and 1 hypothetical case (Patient 3 from the third Mount Hood Challenge).¹¹ This simulated patient is the one we used in our study.

The patient is a 65-year old Caucasian man with a 5-year history of type 2 diabetes mellitus, an HbA1c of 10%, blood pressure of 140/90 mm Hg, low-density lipoprotein (LDL) cholesterol level of 120 mg/dL, high-density lipoprotein (HDL) of 45 mg/dL, and a body mass index (BMI) of 27 kg/m². This profile is not substantially different from the “average” patient enrolled in several primary care-based studies: mean age 58 to 59.5 years; BMI 30-33 kg/m²; HbA1c 8.1%; BP 136-140/76-90 mm Hg; and LDL cholesterol 109-118 mg/dL.^12-14

Archimedes assumes that an intervention occurs at the beginning of a simulation. We used this feature of the model to analyze the impact of various interventions on the ARs for MI, CVA, ESRD, blindness, foot ulceration, and lower extremity amputation. The interventions we examined were moderate exercise, reduction of BMI to 25, reduction of HbA1c to 7.0% and 6.5%, reduction of systolic BP to 130 and 120 mm Hg, reduction of LDL cholesterol to 100 and 70 mg/dL, and treatment with low-dose aspirin, an ACE inhibitor, and a β-blocker ( TABLE 1 ).

FAST TRACK

In our base case, aspirin and moderate exercise together reduced the risk of MI by 8.9% and CVA by 7.8%.

We examined the benefits of these interventions for our base case and for 3 other cases in which a single factor changed (sex, race, age). We chose to examine ARs and ARRs at 10 years from baseline because the trial-to-trial variability of these estimates was much more stable than the 30-year estimates. For example, over the course of 10 separate runs using the same input, estimated 10-year risks of MI varied by an average of 0.8%, while the 30-year risk estimates varied by an average of 9.8%.

Unfortunately, Archimedes does not allow the user to adjust the exercise level without entering a new patient profile. We did so, realizing that we were comparing 2 different sets of 1000 simulated patients while assuming the only difference between them was level of exercise.

TABLE 1
Absolute risk reduction predicted by Archimedes risk engine
Base case: 65-year-old white male, sedentary, nonsmoker with a 5-year history of diabetes mellitus; BMI 27 kg/m²; BP 140/90 mm Hg; HbA1c 10%; LDL 120 mg/dL; HDL 45 mg/dL

	MI	CVA	ESRD	BLINDNESS	FOOT ULCERATION	FOOT AMPUTATION
Estimated 10-year AR before interventions	22.3%	14.4%	0%	0.9%	5.2%	0.5%
INTERVENTIONS*			RISK (ARR)
Aspirin, 81 mg/d	15.5% (6.8%)	11.1% (3.3%)	0% (0%)	0.7% (0.2%)	4.8% (0.4%)	0.5% (0%)
Moderate aerobic exercise	19.6% (2.7%)	7.6% (6.8%)	0% (0%)	0.8% (0.1%)	3.4% (1.8%)	0.5% (0%)
Reduce HbA1c to 7.0%	17.2% (5.1%)	10.1 (4.3%)	0% (0%)	0.5% (0.4%)	0.6% (4.6%)	0.5% (0%)
Reduce HbA1c to 6.5%	15.9% (6.4%)	9.2% (5.2%)	0% (0%)	0.5% (0.4%)	0.6% (4.6%)	0.5% (0%)
Reduce SBP to 130 mm hg	20.9% (1.4%)	11.7% (2.7%)	0% (0%)	0% (0.9%)	4.8% (0.4%)	0.5% (0%)
Reduce SBP to 120 mm hg	17.3% (5.0%)	9.5% (4.9%)	0% (0%)	0% (0.9%)	4.8% (0.4%)	0.5% (0%)
Reduce LDL to 100 mg/dL	20.9% (1.4%)	14.2% (0.2%)	0% (0%)	0.8% (0.1%)	5.0% (0.2%)	0.5% (0%)
Reduce LDL to 70 mg/dL	18.8% (3.5%)	14.0% (0.4%)	0% (0%)	0.7% (0.2%)	4.6% (0.6%)	0.5% (0%)
β-Blocker	20.6% (1.7%)	13.1% (1.3%)	0% (0%)	0.9% (0%)	5.2% (0%)	0.5% (0%)
All of the above	7.1% (15.2%)	3.3% (11.1%)	0% (0%)	0.2% (0.7%)	0.6% (4.6%)	0.5% (0%)
AR, absolute risk; ARR, absolute risk reduction; BMI, body mass index; BP, blood pressure; CVA, cerebrovascular accident; ESRD, end-stage renal disease; HbA1c, glycosylated hemoglobin; HDL, high-density lipoprotein; LDL, low-density lipoprotein; MI, myocardial infarction; SBP, systolic blood pressure.
*Weight loss alone and use of an ACE inhibitor had no effect on any outcome.