Evidence-Based Diabetes Management

Clinical Outcomes Associated With Rates of Sulfonylurea Use Among Physicians | Page 2

Published Online: July 08, 2013
Katalin Bognar, PhD; Kelly Fee Bell, PharmD, MS Phr; Darius Lakdawalla, PhD; Anshu Shrestha, PhD; Julia Thornton Snider, PhD; Nina Thomas, MPH; and Dana Goldman, PhD
Rates of T2DM drug use are summarized in Table 2. The biguanide (metformin) was used during 80,244 patientmonths (37.46% of the total patientmonths). Sulfonylureas were the second most commonly used (21,429 patientmonths; 10.00%). TZDs were the thirdmost commonly used (8835; 4.12%). Every other drug class was filled less than 3% of the total patient-months. All insulin classes combined (bolus, basal,premixed) totaled 9709 patient-months(4.53%). Because metformin is widely accepted as the first-line T2DM medication,4 these data suggest that sulfonylureas are the most commonly prescribed second-line agent in this  cohort. 

We compared baseline ECIs among all patients newly initiating each class of diabetes medication (Table 3). Patients newly initiating the biguanide had an average ECI of 2.38 in the year prior to initiation, the lowest score of any T2DM drug class. Sulfonylureas were prescribed to patients who had the second-fewest comorbidities at initiation (average ECI: 2.75). Patients who received amylinomimetics had the most comorbidities, on average (4.00).

Rates of complications are summarized in Table 4. Cardiovascular complications were the most common, in 6378 patient-months (2.98% of the total patient-months), and neuropathy complications the least common, in 804 patient-months (0.38% of the total patientmonths). Overall, 15,492 patient-months (7.23% of the total patient-months) involved any diabetes-related complication.

Among the incident cohort, we identified10,457 distinct prescribing physicians. The average number of distinct prescribing physicians per incident T2DM patient was 1.7 (range, 1-9), whereas the average number of distinct incident T2DM patients (covered by Humana insurance) per prescribing physician was 1.3 (range, 1-18).

Figure 3 relates prescribing patterns to patient outcomes. Low-performing physicians (ie, those exhibiting higher complication rates for a given patient case-mix) were more likely than highperforming peers to prescribe metformin, sulfonylureas, and insulin. By contrast, high-performing physicians were more likely than peers to prescribe DPP-4 inhibitors, TZDs, GLP-1 agonists,or other classes of diabetes medications. The strongest correlation of drug use to performance was for DPP-4 inhibitors (R2 = 0.1662), with increasing use of this drug class positively associated with fewer T2DM complications. Sulfonylureas (R2 = 0.0857) and insulin (R2 = 0.0166) were more commonly prescribed by low performers. The insulin relationship appeared nonlinear, with high prescription rates among both high and low performers, and lower rates among average performers.

After expanding the regression model to incorporate prescriptions of T2DM drug classes, we were able to predict the number of complications that would be avoided by moving from the prescribing patterns of bottom-decile to top-decile performers. In a population of 100,000 incident T2DM patients, such a change in prescribing patterns would amount to 924 avoided complications per year (95% CI, 597-1251).


Our analysis suggests that physicians prescribing sulfonylureas more frequently have a greater proportion of patients with long-term complications than those prescribing other second-line T2DM medications. After accounting for the prior-year health of patients, and other covariates such as age and gender, physicians prescribing sulfonylureas more frequently did worse than expected in preventing T2DM-related complications. Those using DPP-4 inhibitors at higher rates did better than expected, given the observedhealth of their patients. Physicians prescribing TZDs, GLP-1 agonists, or other newer agents at higher rates also performed better than expected. The amount of variance in prescribing a given drug class explained by physician performance is in the range of 1.7% to 16.6%—consistent with similar models using administrative claims data for various disease states including diabetes.28-33

Sulfonylureas are the most commonly prescribed T2DM medication after metformin. It is thus notable that physician tendencies to prescribe sulfonylureas more often are associated with poorer risk-adjusted outcomes. This finding is consistent with related findings in the clinical literature. Sulfonylurea or sulfonylurea-plus-metformin use may be associated with higher mortality rates than metformin alone.34-37 Sulfonylureas are associated with a 4-fold increased risk for mild/moderate hypoglycemia compared with metformin alone.9 When sulfonylureas were used as monotherapy, patients had higher blood pressure a year later than when they were prescribed metformin, an effect likely explained by increased body mass index (BMI) with sulfonylureas.38 Likewise, adjusting for cardiovascular risk factors, the incidence of cardiovascular events such as myocardial infarction or stroke is higher in patients taking sulfonylureas versus metformin.39,40 Compared with metformin, sulfonylurea use increased the risk of worsening glomerular filtration rate, progression to endstage renal disease, and death.41

The American Diabetes Association (ADA) has estimated that the cost of diagnosed diabetes in 2012 was $245 billion; $176 billion for direct medical costs and $69 billion in reduced productivity.42 The largest portion of this (43%) was due to inpatient care costs incurred due to diabetes complications. A greater portion of the total estimated cost of diabetes was spent on medications to treat the diabetes complications (18%) than on diabetes medications and supplies themselves (12%).42 A 2007-2009 survey estimated that insulins and oral hypoglycemic agents were the second- and fourth most-common causes of emergency admission, together accounting for 1 in 4 emergent medication-related admissions.43 Given the high cost of diabetes complications, future research should investigate whether the cost savings of using an inexpensive drug class (sulfonylureas) actually represents an overall cost savings when complication rates are high and may outweigh initial savings.

Our study did have limitations. The relationship between physician prescription patterns and patient complications may be confounded by the patients’ diabetes severity level and other health characteristics. Although we accounted for age, sex, and comorbidities in our analyses, data limitations prevented us from controlling for a fuller set of characteristics. Because sulfonylureas are a common therapy and patients initiating them are relatively healthy (Table 3), we find it noteworthy that a strong positive association between sulfonylurea prescription and T2DM complications remains. Further research is needed to shed light on this issue.

As ours and other studies have shown, sulfonylureas are a popular second-line agent in the treatment of T2DM. However, our physician-level study design suggests a potential pitfall associated with their use. Physicians who prescribe sulfonylureas more frequently than their peers have patients with higher complication rates than would be expected from their age, sex, and preexisting comorbidities. This could be due to the properties of the drugs themselves; it could also be due to the skills and characteristics of the physicians who choose to use these drugs more often, or the unmeasured characteristics of their patients. Further investigation is needed to assess whether physician prescribing choices accurately predict patient outcomes, and whether they can serve as an additional metric of quality in today’s changing healthcare reimbursement landscape.

Author Affiliations: From Precision Health Economics (KB, AS, JTS), Santa Monica, CA; Bristol-Myers Squibb (KFB, NT),Plainsboro, NJ; University of SouthernCalifornia (DL, DG), Los Angeles, CA.

Funding Source: Bristol-Myers Squibb.

Author Disclosures: The authors reported that Precision Health Economics has a consulting contract with Bristol-Myers Squibb.

Authorship Information: Concept and design (KB, KFB, DL, AS, JTS, NT, DG); acquisition of data (KFB, DL, AS, DG);analysis and interpretation of data (KB,KFB, DL, AS, JTS, NT, DG); drafting of the manuscript (KB, JTS, NT); critical revision of the manuscript for important intellectual content (KB, DL, AS, JTS, NT, DG); statistical analysis (KB, AS, JTS);rovision of study materials or patients(KFB, NT); obtaining funding (KFB, DL, NT, DG); administrative, technical, or logistic support (KB, KFB, JTS); and supervision (KB, KFB, DL, JTS, DG).

Address correspondence to: Katalin Bognar, Precision Health Economics, 11100 Santa Monica Blvd, Suite 500, Los Angeles,CA 90025, kata.bognar@pheconomics.com.
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