mark espeland phd

RESEARCH DESIGN AND METHODS—

Conclusions—, article information, reduction in weight and cardiovascular disease risk factors in individuals with type 2 diabetes : one-year results of the look ahead trial.

Authors and members of the Look AHEAD trial are listed in the appendix .

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The Look AHEAD Research Group; Reduction in Weight and Cardiovascular Disease Risk Factors in Individuals With Type 2 Diabetes : One-year results of the Look AHEAD trial . Diabetes Care 1 June 2007; 30 (6): 1374–1383. https://doi.org/10.2337/dc07-0048

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OBJECTIVE —The effectiveness of intentional weight loss in reducing cardiovascular disease (CVD) events in type 2 diabetes is unknown. This report describes 1-year changes in CVD risk factors in a trial designed to examine the long-term effects of an intensive lifestyle intervention on the incidence of major CVD events.

RESEARCH DESIGN AND METHODS —This study consisted of a multicentered, randomized, controlled trial of 5,145 individuals with type 2 diabetes, aged 45–74 years, with BMI >25 kg/m 2 (>27 kg/m 2 if taking insulin). An intensive lifestyle intervention (ILI) involving group and individual meetings to achieve and maintain weight loss through decreased caloric intake and increased physical activity was compared with a diabetes support and education (DSE) condition.

RESULTS —Participants assigned to ILI lost an average 8.6% of their initial weight vs. 0.7% in DSE group ( P < 0.001). Mean fitness increased in ILI by 20.9 vs. 5.8% in DSE ( P < 0.001). A greater proportion of ILI participants had reductions in diabetes, hypertension, and lipid-lowering medicines. Mean A1C dropped from 7.3 to 6.6% in ILI ( P < 0.001) vs. from 7.3 to 7.2% in DSE. Systolic and diastolic pressure, triglycerides, HDL cholesterol, and urine albumin-to-creatinine ratio improved significantly more in ILI than DSE participants (all P < 0.01).

CONCLUSIONS —At 1 year, ILI resulted in clinically significant weight loss in people with type 2 diabetes. This was associated with improved diabetes control and CVD risk factors and reduced medicine use in ILI versus DSE. Continued intervention and follow-up will determine whether these changes are maintained and will reduce CVD risk.

Look AHEAD (Action for Health in Diabetes) is an National Institutes of Health–funded clinical trial, conducted in 16 centers in the U.S., investigating the long-term health impact of an intensive lifestyle intervention (ILI) in 5,145 overweight or obese adults with type 2 diabetes. The design and methods of this trial have been reported elsewhere ( 1 ), as have the baseline characteristics of the randomized cohort ( 2 ). Its primary objective is to determine whether cardiovascular morbidity and mortality in individuals with type 2 diabetes can be reduced by long-term weight reduction, achieved by an ILI that includes diet, physical activity, and behavior modification ( 3 ). The goal of this intervention is for individuals to achieve and maintain a loss of at least 7% of initial body weight. Results of the ILI group will be compared with a usual-care condition that includes diabetes support and education (DSE). Follow-up of Look AHEAD participants is ongoing and is planned to extend for up to 11.5 years. For the study to continue for this period, two feasibility criteria were set by the Look AHEAD study group based on 1-year changes: 1 ) a difference between ILI and DSE participants of >5 percentage points in the average percent change in weight from baseline and 2 ) an average absolute percent weight loss from baseline among ILI participants (not using insulin at baseline) of >5%. This report documents the success of Look AHEAD in meeting these 1-year feasibility criteria and describes changes in the two groups at the end of the 1st year in fitness, cardiovascular disease risk factors, and use of medicines.

For inclusion in the study, participants were 45–74 years of age (which was changed to 55–74 years during the 2nd year of recruitment to increase the anticipated cardiovascular event rate), had a BMI >25 kg/m 2 (>27 kg/m 2 if currently taking insulin), A1C <11%, blood pressure <160 (systolic) and <100 (diastolic) mmHg, and triglycerides <600 mg/dl.

Participants completed maximal graded exercise tests to assess fitness before randomization. The test consisted of the participant walking on a motorized treadmill at a constant self-selected walking speed (1.5, 2.0, 2.5, 3.0, 3.5, or 4.0 mph). The elevation of the treadmill was initially set at 0% grade and increased by 1.0% every minute. Heart rate and rating of perceived exertion (RPE) using the Borg 15-category scale ( 4 ) were measured during the final 10 s of each exercise stage and at the point of test termination. To determine eligibility at baseline, a maximal exercise test was performed. For individuals not taking prescription medicine that would affect heart rate response during exercise (e.g., β-blocker), the baseline test was considered valid if the individual achieved at least 85% of age-predicted maximal heart rate (age-predicted maximal heart rate = 220 − age) and a minimum of 4 metabolic equivalents (METS). For individuals taking prescription medicine that would affect the heart rate response during exercise, the baseline test was considered valid if the individual achieved an RPE of at least 18 and a minimum of 4 METS. Individuals not achieving these criteria were not eligible for randomization into Look AHEAD. METS at each exercise stage and at test termination were estimated from a standardized formula that incorporates walking speed and grade ( 5 ).

The goal was to recruit approximately equal numbers of men and women, with >33% from racial and ethnic minority groups. Informed consent was obtained from all participants before screening and at enrollment, consistent with the Helsinki Declaration and the guidelines of each center's institutional review board. After all eligibility criteria were confirmed, participants were randomly assigned with equal probability to either the ILI or the DSE comparison condition. Randomization was stratified by clinical center.

Interventions

Before randomization, all study participants were required to complete a 2-week run-in period that included successful self-monitoring of diet and physical activity, and they were provided an initial session of diabetes education with particular emphasis on aspects of diabetes care related to the trial such as management of hypoglycemia and foot care. The session stressed the importance of eating a healthy diet and being physically active for both weight loss and improvement of glycemic control. All individuals who smoked were encouraged to quit and were provided self-help materials and/or referral to local programs as appropriate.

The weight loss intervention prescribed in the 1st year has been described in detail ( 3 ). Briefly, it combines diet modification and increased physical activity and was designed to induce a minimum weight loss of 7% of initial body weight during the 1st year. Individual participants were encouraged to lose >10% of their initial body weight, with the expectation that aiming high would ensure that a greater number of participants would achieve the minimum 7% weight loss. The intervention was modeled on group behavioral programs developed for the treatment of obese patients with type 2 diabetes and included treatment components from the Diabetes Prevention Program ( 6 – 8 ) and the National Heart, Lung, and Blood Institute's clinical guidelines ( 9 ). During months 1–6, participants were seen weekly with three group meetings and one individual session per month. During months 7–12, group sessions were provided every other week and the monthly individual session was continued. Sessions were led by intervention teams that included registered dietitians, behavioral psychologists, and exercise specialists.

Caloric restriction was the primary method of achieving weight loss. The macronutrient composition of the diet was structured to enhance glycemic control and to improve CVD risk factors. It included a maximum of 30% of total calories from fat (with a maximum of 10% of total calories from saturated fat) and a minimum of 15% of total calories from protein ( 10 ). Participants were prescribed portion-controlled diets, which included the use of liquid meal replacements (provided free of charge) and frozen food entrées, as well as structured meal plans (comprised of conventional foods) for those who declined the meal replacements. Monthly reviews took place at an individual session to reassess progress.

The physical activity program prescribed in the ILI relied heavily on home-based exercise with gradual progression toward a goal of 175 min of moderate-intensity physical activity per week. Although walking was encouraged, participants were allowed to choose other types of moderate-intensity physical activity, and programs were tailored based on the results of a baseline physical fitness test and safety concerns.

The ILI included a “toolbox” approach, as used in the Diabetes Prevention Program ( 6 , 7 ), to help participants achieve and maintain the study's weight loss and activity goals. Use of the toolbox was based on a preset algorithm and assessment of participant progress. After the first 6 months, the toolbox algorithm included use of a weight loss medicine (orlistat) and/or advanced behavioral strategies for individuals who had difficulty in meeting the trial's weight or activity goals. Specific protocols were used to determine when to initiate medication or other approaches, to monitor participants, and to determine when to stop a particular intervention.

Participants assigned to DSE attended the initial prerandomization diabetes education session (described above) and were invited to three additional group sessions during the 1st year. A standard protocol was used for conducting these sessions, which provided information and opportunities for discussing topics related to diet, physical activity, and social support. However, the DSE group was not weighed at these sessions and received no counseling in behavioral strategies for changing diet and activity.

Ongoing clinical care

All participants in the ILI and DSE groups continued to receive care for their diabetes and all other medical conditions from their own physicians. Changes in all medicines were made by the participants’ own physicians, except for temporary reductions in hyperglycemia medicines during periods of intensive weight loss intervention, which were made by the intervention sites following a standardized treatment protocol aimed at avoiding hypoglycemia.

Assessments

Anthropometry..

All participants were scheduled to attend baseline and 1-year assessments, at which time measures were collected by staff members who were masked to participants’ intervention assignments. Weight and height were assessed in duplicate using a digital scale and a standard stadiometer. Seated blood pressure was measured in duplicate, using an automated device after a 5-min rest. Participants brought all prescription medicines to the clinic to ensure recording accuracy. History of cardiovascular disease was based on self-report of myocardial infarction, stroke, transient ischemic event, percutaneous transluminal coronary angioplasty, or coronary artery bypass graft.

At 1 year, a submaximal exercise test was performed and terminated when the participant first achieved or exceeded 80% of age-predicted maximal heart rate (HR Max in beats per min = 220 − age). If the participant was taking a β-blocker at baseline or 1-year assessment, the submaximal test was terminated at the point when the participant first reported achieving or exceeding 16 on the 15-category RPE scale. For participants not taking a β-blocker, change in cardiorespiratory fitness was computed as the difference in estimated METS between points during the baseline and 1-year tests when >80% of age-predicted maximal heart rate was attained. For participants taking β-blockers at either baseline or 1 year, change in cardiorespiratory fitness was computed as the difference in estimated METS between points during the baseline and 1-year tests when RPE >16 was attained.

Serum measures.

The Central Biochemistry Laboratory (Northwest Lipid Research Laboratories, University of Washington, Seattle, WA) conducted standardized analyses of shipped frozen specimens. A1C was measured by a dedicated ion exchange high-performance liquid chromatography instrument (Biorad Variant 11). Fasting serum glucose was measured enzymatically on a Hitachi 917 autoanalyzer using hexokinase and glucose-6-phosphate dehydrogenase. Total serum cholesterol and triglycerides were measured enzymatically using methods standardized to the Centers for Disease Control and Prevention reference methods. LDL cholesterol was calculated by the Friedewald equation ( 11 ). HDL cholesterol was analyzed by the treatment of whole plasma with dextran sulfate minus Mg 2+ to precipitate all of the apolipoprotein B–containing lipoproteins. Albumin and creatinine concentrations were measured from spot urine samples.

Participants were classified as having the metabolic syndrome using the criteria proposed by the National Cholesterol Education Program Adult Treatment Program III panel ( 12 ). They also were classified according to their success in meeting treatment goals published by the American Diabetes Association (ADA) ( 13 ). Glycemic control was defined as A1C <7.0%, blood pressure control as systolic blood pressure <130 and diastolic blood pressure <80 mmHg, and lipid control as LDL cholesterol <100 mg/dl.

Statistical methods

Cross-sectional differences between participants assigned to the ILI and DSE conditions were assessed using ANCOVA and logistic regression, with adjustment for clinical center (the sole factor used to stratify randomization). Changes in outcome measures from baseline to 1 year were compared using ANCOVA and Mantel-Haenszel tests.

Participants’ baseline characteristics

Figure 1 describes trial enrollment. Of 28,622 individuals who provided information during prescreening, 15,561 (54.4%) were found to be eligible for clinic visits to confirm eligibility. The most common reasons for ineligibility at this stage were related to age (13.5%), lack of diabetes (8.6%), and the likelihood that the diabetes was type 1 (4.4%). Of 9,045 (58.1%) who attended clinic visits, 5,145 (56.9%) were ultimately randomized: 2,570 participants were assigned to ILI and 2,575 to DSE. At this stage, individuals were most commonly ineligible due to staff judgment (7.6%), elevated blood pressure (7.0%), or incomplete behavioral run ins (4.8%).

At baseline, the characteristics of participants assigned to the two intervention conditions were similar ( Table 1 ). Overall, 14.0% reported a history of cardiovascular disease, 94.0% met the National Cholesterol Education Program Adult Treatment Panel III definition for the metabolic syndrome ( 12 ), 15.3% were taking insulin, 87.5% were using diabetes medicines (including insulin), 75.3% were using antihypertensive medicines, and 51.0% were using lipid-lowering medicines. Baseline BMI, weight, waist circumference, and fitness are given by sex in Table 1 . A BMI of ≥30.0 kg/m 2 was present in 85.1% of participants.

Weight loss

The 1-year examination was attended by 2,496 (97.1%) of the ILI and 2,463 (95.7%) of the DSE participants ( P = 0.004). Among the factors listed in Table 1 , only the distribution of baseline insulin use significantly varied between nonattendees (21.0%) versus attendees (15.1%) ( P = 0.04). Over the 1st year of the trial, the ILI group lost an average of (means ± SD) 8.6 ± 6.9% of initial body weight compared with 0.7 ± 4.8% in the DSE group ( P < 0.001). Figure 2A portrays the cumulative distribution of weight changes in the two groups. Within the ILI group, 37.8% of participants met the individual weight loss goal (>10% of initial weight) and 55.2% met the group average goal (>7%) compared with 3.2 and 7.0% of DSE participants, respectively. These weight losses were accompanied by greater mean reductions in waist circumference in the ILI than DSE group, with mean decreases of 6.2 ± 10.2 vs. 0.5 ± 8.5 cm ( P < 0.001).

In the ILI group, the average weight loss among baseline insulin users was 7.6 ± 7.0% compared with 8.7 ± 6.9% in nonusers ( P = 0.002). Insulin users, compared with noninsulin users, were less likely to achieve weight losses >10% (33.5 vs. 38.5%) or >7% (47.8 vs. 56.4%). In the DSE group, average weight loss was 0.3 ± 5.1% among insulin users versus 0.8 ± 4.7% among noninsulin users.

Changes in fitness

Figure 2B illustrates the cumulative distribution of measured 1-year fitness changes in 4,246 participants who had repeat testing. Fitness tended to increase in both groups; however, increases were more prevalent and tended to be larger among ILI participants; 70.1% of the ILI participants had increased fitness at 1 year compared with 46.3% of the DSE participants ( P < 0.001). Fitness increases averaged 20.9 ± 29.1% among ILI participants compared with 5.8 ± 22.0% among DSE participants ( P < 0.001). These changes could not be fully accounted for by changes in weight. After covariate adjustment for weight changes, the fitted mean difference in fitness increases between groups remained statistically significant (15.9% for ILI vs. 10.8% for DSE, P < 0.001).

Changes in medicines and cardiovascular risk factors

During the 1st year, use of glucose-lowering medicines among ILI participants decreased from 86.5 to 78.6%, whereas it increased from 86.5 to 88.7% among DSE participants ( P < 0.001). As shown in Table 2 , despite this difference, mean fasting glucose declined more among ILI participants compared with DSE participants ( P < 0.001), as did mean A1C ( P < 0.001).

As described in Table 2 , the prevalence of antihypertensive medicine use remained unchanged among ILI participants but increased by 2.2% (0.6%) among DSE participants ( P = 0.02). Mean systolic and diastolic blood pressure levels declined in both groups, but reductions were significantly greater in ILI than in DSE participants (both P < 0.001).

Use of lipid-lowering medicines increased in both groups; however, the increase was significantly smaller among ILI participants than in DSE participants ( P < 0.001). Mean levels of LDL cholesterol declined by similar magnitudes in both groups ( P = 0.49). Mean HDL cholesterol levels increased more among ILI than DSE participants ( P < 0.001), whereas mean triglyceride levels decreased more among ILI ( P < 0.001). The prevalence of urine albumin-to-creatinine ratios ≥30.0 μg/mg decreased more among ILI participants than DSE participants ( P = 0.002).

Classification of participants

The percentage meeting criteria for the metabolic syndrome decreased significantly more among ILI than DSE participants ( P < 0.001). As shown in Table 2 , the prevalence declined from 93.6 to 78.9% in the ILI group compared with a decline of 94.4 to 87.3% in the DSE group. The prevalence of meeting ADA goals for A1C, blood pressure, and LDL cholesterol increased among both ILI and DSE participants ( Table 3 ). These increases were greater among ILI participants ( P < 0.001) for A1C and blood pressure 26.4 ± 1.0% vs. 5.4 ± 1.07% and 15.1 ± 1.1% vs. 7.0 ± 1.2%, respectively (both P < 0.001), but were of similar magnitudes for LDL cholesterol. The prevalence simultaneously meeting all three goals increased from 10.8 to 23.6% among ILI participants compared with an increase from 9.5 to 16.0% among DSE participants ( P < 0.001).

The present results show that clinically significant weight loss is broadly achievable in subjects with type 2 diabetes and is associated with improved cardiovascular risk factors. At 1 year, participants in ILI achieved an average loss of 8.6% of initial body weight and a 21% improvement in cardiovascular fitness. Separate manuscripts are underway that will provide details on the relative contributions of individual strategies (e.g., meal replacement, orlistat) toward this successful outcome. Even participants on insulin lost an average of 7.6% of initial weight. The ILI was associated with an increase from 46 to 73% in the participants who met the ADA goal of A1C <7% and a doubling in the percent of individuals who met all three of the ADA goals for glycemic control, hypertension, and dyslipidemia.

Look AHEAD is the first large clinical trial to compare an intensive weight loss intervention (i.e., ILI) with a support and education group (i.e., DSE) in individuals with type 2 diabetes. As expected, participants in the ILI group had significantly greater weight loss and improvement in fitness at 1 year than those in the DSE group. Moreover, they had a significantly greater decrease in the number of medicines used to treat their diabetes and blood pressure. Despite the greater reductions in these medicines, the ILI group showed greater improvements in their glycemic control, albumin-to-creatinine ratio, systolic and diastolic blood pressure, triglycerides, and HDL cholesterol than the DSE group. Changes in LDL cholesterol were comparable in the two groups. Of particular note is that mean A1C fell from 7.2 to 6.6%. Few studies, even trials of newer diabetes medicines, have achieved levels of A1C of 6.6%. Although the DSE group had smaller benefits than ILI, it is important to recognize that these participants also experienced some improvement (not worsening), on average, in weight, fitness, and cardiovascular risk factors.

The Look AHEAD participants are of similar ethnic distribution to that observed in the National Health and Nutrition Examination Survey 1999–2000 ( 14 ), but their average baseline BMI was higher. Overall, they are healthier than diabetic individuals in the National Health and Nutrition Examination Survey with regard to glucose, A1C, and lipid levels and are less likely to smoke. A large percentage was taking medicines for risk factors at study enrollment, and many had a significant history of cardiovascular disease. Despite the level of health of the sample, fewer than half met the ADA goal for A1C and only 10% met all three ADA goals ( 13 ). The ILI was extremely effective in increasing the percent of participants who met these goals. At 1 year, 72.7% met the goal for A1C and 23.6% met all three goals, compared with only 50.8 and 16.0%, respectively, for the DSE group. The ILI also was associated with significantly greater remission of the metabolic syndrome than was the DSE intervention.

Several large clinical trials of individuals with impaired glucose tolerance ( 6 , 15 ) or hypertension ( 16 , 17 ) have achieved average weight losses of 4–7% at 1 year using intensive lifestyle interventions that emphasized behavior change. These weight losses were associated with marked improvement in health status. Although a number of smaller studies ( 18 , 19 ) have shown that it is possible, using strong behavioral programs, to produce significant weight loss in patients with type 2 diabetes, most studies of weight loss in such individuals have had only modest success. It appears that individuals with diabetes (especially those on insulin) may have more difficulty losing weight and then keeping it off than those without diabetes ( 20 ). For example, among adult Pima Indians receiving standard clinical care for type 2 diabetes, those treated with insulin lost less weight than those treated without drugs or with oral agents ( 21 ). The larger weight losses in Look AHEAD than in prior clinical trials may be attributable to the combination of group and individual contact, the higher physical activity goal that was prescribed, and/or the more intense dietary intervention, which included not only calorie and fat restrictions but also structured meal plans, each of which has previously been associated with successful weight loss and maintenance ( 22 – 25 ). Although Look AHEAD participants using insulin achieved less average weight loss than those not on insulin (7.6 vs. 8.7%), the weight loss of the participants on insulin demonstrates that use of insulin does not prevent successful weight loss. A recent meta-analysis ( 26 ) found that the use of meal replacements increased both short- and long-term average weight loss by ∼2.5 kg, compared with prescription of a conventional reducing diet with the same calorie goals. Our findings that participants in the ILI had significant improvements in cardiovascular risk factors confirms prior studies showing that initial weight loss in type 2 diabetes is associated with improved glycemic control and cardiovascular risk factors at 1 year ( 27 , 28 ). However, the long-term impact of such weight losses remains unclear.

Estimated fitness improved in both groups over the year, but it improved significantly more in the ILI group. It is unknown how much of the improvement in either treatment group was due to measurement variability and greater familiarity with the testing procedure at the 1-year visit and how much represented physiologic change. The difference in improvement between the ILI and DSE groups, however, can be taken as a measure of the ILI treatment effect. This treatment effect persisted even after adjustment for the 1-year weight change. The changes in fitness compared favorably with those observed in prior studies with both diabetic ( 29 , 30 ) and nondiabetic ( 29 , 31 , 32 ) participants. Thus, the modest increase in physical activity, primarily walking, had a very beneficial effect. This may translate into a lower rate of cardiovascular events, including mortality, as suggested in some observational studies ( 33 , 34 ).

The primary outcome of the Look AHEAD trial is the effect of weight loss on the development of cardiovascular disease. Although the difference between the ILI and DSE groups in the change in risk factors at 1-year points to the potential cardiovascular benefits of the ILI, we will need several additional years to determine whether the initial weight loss can be maintained, whether weight loss has a long-term effect on the risk factors, and whether the favorable risk factor changes translate into reduced cardiovascular events. This is critical information for establishing evidence-based recommendations with regard to weight loss for the prevention of cardiovascular disease in individuals with diabetes.

Xavier Pi-Sunyer, MD; George Blackburn, MD, PhD; Frederick L. Brancati, MD, MHS; George A. Bray, MD; Renee Bright, MS; Jeanne M. Clark, MD, MPH; Jeffrey M. Curtis, MD, MPH; Mark A. Espeland, PhD; John P. Foreyt, PhD; Kathryn Graves, MPH, RD, CDE; Steven M. Haffner, MD; Barbara Harrison, MS; James O. Hill, PhD; Edward S. Horton, MD; John Jakicic, PhD; Robert W. Jeffery, PhD; Karen C. Johnson, MD, MPH; Steven Kahn, MB, ChB; David E. Kelley, MD; Abbas E. Kitabchi, MD, PhD; William C. Knowler, MD, DrPH; Cora E. Lewis, MD, MSPH; Barbara J. Maschak-Carey, MSN, CDE; Brenda Montgomery, RN, MS, CDE; David M. Nathan, MD; Jennifer Patricio, MS; Anne Peters, MD; J. Bruce Redmon, MD; Rebecca S. Reeves, DrPH, RD; Donna H. Ryan, MD; Monika Safford, MD; Brent Van Dorsten, PhD; Thomas A. Wadden, PhD; Lynne Wagenknecht, DrPH; Jacqueline Wesche-Thobaben, RN, BSN, CDE; Rena R. Wing, PhD; Susan Z. Yanovski, MD.

Clinical sites

The Johns Hopkins Medical Institutions: Frederick L. Brancati, MD, MHS; Jeff Honas, MS; Lawrence Cheskin, MD; Jeanne M. Clark, MD, MPH; Kerry Stewart, EdD; Richard Rubin, PhD; Jeanne Charleston, RN; Kathy Horak, RD.

Pennington Biomedical Research Center: George A. Bray, MD; Kristi Rau; Allison Strate, RN; Brandi Armand, LPN; Frank L. Greenway, MD; Donna H. Ryan, MD; Donald Williamson, PhD; Amy Bachand; Michelle Begnaud; Betsy Berhard; Elizabeth Caderette; Barbara Cerniauskas; David Creel; Diane Crow; Helen Guay; Nancy Kora; Kelly LaFleur; Kim Landry; Missy Lingle; Jennifer Perault; Mandy Shipp, RD; Marisa Smith; Elizabeth Tucker.

The University of Alabama at Birmingham: Cora E. Lewis, MD, MSPH; Sheikilya Thomas, MPH; Monika Safford, MD; Vicki DiLillo, PhD; Charlotte Bragg, MS, RD, LD; Amy Dobelstein; Stacey Gilbert, MPH; Stephen Glasser, MD; Sara Hannum, MA; Anne Hubbell, MS; Jennifer Jones, MA; DeLavallade Lee; Ruth Luketic, MA, MBA, MPH; Karen Marshall; L. Christie Oden; Janet Raines, MS; Cathy Roche, RN, BSN; Janet Truman; Nita Webb, MA; Audrey Wrenn, MAEd.

Harvard center: Massachusetts General Hospital: David M. Nathan, MD; Heather Turgeon, RN, BS, CDE; Kristina Schumann, BA; Enrico Cagliero, MD; Linda Delahanty, MS, RD; Kathryn Hayward, MD; Ellen Anderson, MS, RD; Laurie Bissett, MS, RD; Richard Ginsburg, PhD; Valerie Goldman, MS, RD; Virginia Harlan, MSW; Charles McKitrick, RN, BSN, CDE; Alan McNamara, BS; Theresa Michel, DPT, DSc, CCS; Alexi Poulos, BA; Barbara Steiner, EdM; Joclyn Tosch, BA. Joslin Diabetes Center: Edward S. Horton, MD; Sharon D. Jackson, MS, RD, CDE; Osama Hamdy, MD, PhD; A. Enrique Caballero, MD; Sarah Bain, BS; Elizabeth Bovaird, BSN, RN; Ann Goebel-Fabbri, PhD; Lori Lambert, MS, RD; Sarah Ledbury, MEd, RD; Maureen Malloy, BS; Kerry Ovalle, MS, RCEP, CDE. Beth Israel Deaconess Medical Center: George Blackburn, MD, PhD; Christos Mantzoros, MD, DSc; Kristina Day, RD; Ann McNamara, RN.

University of Colorado Health Sciences Center: James O. Hill, PhD; Marsha Miller, MS, RD; JoAnn Phillipp, MS; Robert Schwartz, MD; Brent Van Dorsten, PhD; Judith Regensteiner, PhD; Salma Benchekroun, MS; Ligia Coelho, BS; Paulette Cohrs, RN, BSN; Elizabeth Daeninck, MS, RD; Amy Fields, MPH; Susan Green; April Hamilton, BS, CCRC; Jere Hamilton, BA; Eugene Leshchinskiy; Michael McDermott, MD; Lindsey Munkwitz, BS; Loretta Rome, TRS; Kristin Wallace, MPH; Terra Worley, BA.

Baylor College of Medicine: John P. Foreyt, PhD; Rebecca S. Reeves, DrPH, RD; Henry Pownall, PhD; Ashok Balasubramanyam, MBBS; Peter Jones, MD; Michele Burrington, RD; Chu-Huang Chen, MD, PhD; Allyson Clark, RD; Molly Gee, MEd, RD; Sharon Griggs; Michelle Hamilton; Veronica Holley; Jayne Joseph, RD; Patricia Pace, RD: Julieta Palencia, RN; Olga Satterwhite, RD; Jennifer Schmidt; Devin Volding, LMSW; Carolyn White.

University of California at Los Angeles School of Medicine: Mohammed F. Saad, MD; Siran Ghazarian Sengardi, MD; Ken C. Chiu, MD; Medhat Botrous; Michelle Chan, BS; Kati Konersman, MA, RD, CDE; Magpuri Perpetua, RD.

The University of Tennessee Health Science Center: Karen C. Johnson, MD, MPH; Helen Lambeth, RN, BSN; Carolyn M. Gresham, RN; Abbas E. Kitabchi, MD, PhD; Stephanie A. Connelly, MD, MPH; Lynne Lichtermann, RN, BSN.

University of Minnesota: Robert W. Jeffery, PhD; Carolyn Thorson, CCRP; John P. Bantle, MD; J. Bruce Redmon, MD; Richard S. Crow, MD; Scott Crow, MD; Susan K. Raatz, PhD, RD; Kerrin Brelje, MPH, RD; Carolyne Campbell; Jeanne Carls, MEd; Tara Carmean-Mihm, BA; Emily Finch, MA; Anna Fox, MA; Elizabeth Hoelscher, MPH, RD, CHES; La Donna James; Vicki A. Maddy, BS, RD; Therese Ockenden, RN; Birgitta I. Rice, MS, RPh CHES, BS; Ann D. Tucker, BA; Mary Susan Voeller, BA; Cara Walcheck, BS, RD.

St. Luke's Roosevelt Hospital Center: Xavier Pi-Sunyer, MD; Jennifer Patricio, MS; Stanley Heshka, PhD; Carmen Pal, MD; Lynn Allen, MD; Diane Hirsch, RNC, MS, CDE; Mary Anne Holowaty, MS, CN.

University of Pennsylvania: Thomas A. Wadden, PhD; Barbara J. Maschak-Carey, MSN, CDE; Stanley Schwartz, MD; Gary D. Foster, PhD; Robert I. Berkowitz, MD; Henry Glick, PhD; Shiriki K. Kumanyika, PhD, RD, MPH; Johanna Brock; Helen Chomentowski; Vicki Clark; Canice Crerand, PhD; Renee Davenport; Andrea Diamond, MS, RD; Anthony Fabricatore, PhD; Louise Hesson, MSN; Stephanie Krauthamer-Ewing, MPH; Robert Kuehnel, PhD; Patricia Lipschutz, MSN; Monica Mullen, MS, RD; Leslie Womble, PhD, MS; Nayyar Iqbal, MD.

University of Pittsburgh: David E. Kelley, MD; Jacqueline Wesche-Thobaben, RN, BSN, CDE; Lewis Kuller, MD, DrPH; Andrea Kriska, PhD; Janet Bonk, RN, MPH; Rebecca Danchenko, BS; Daniel Edmundowicz, MD; Mary L. Klem, PhD, MLIS; Monica E. Yamamoto, DrPH, RD, FADA; Barb Elnyczky, MA; George A. Grove, MS; Pat Harper, MS, RD, LDN; Janet Krulia, RN, BSN, CDE; Juliet Mancino, MS, RD, CDE, LDN; Anne Mathews, MS, RD, LDN; Tracey Y. Murray, BS; Joan R. Ritchea; Jennifer Rush, MPH; Karen Vujevich, RN-BC, MSN, CRNP; Donna Wolf, MS.

The Miriam Hospital/Brown Medical School: Rena R. Wing, PhD; Renee Bright, MS; Vincent Pera, MD; John Jakicic, PhD; Deborah Tate, PhD; Amy Gorin, PhD; Kara Gallagher, PhD; Amy Bach, PhD; Barbara Bancroft, RN, MS; Anna Bertorelli, MBA, RD; Richard Carey, BS; Tatum Charron, BS; Heather Chenot, MS; Kimberley Chula-Maguire, MS; Pamela Coward, MS, RD; Lisa Cronkite, BS; Julie Currin, MD; Maureen Daly, RN; Caitlin Egan, MS; Erica Ferguson, BS, RD; Linda Foss, MPH; Jennifer Gauvin, BS; Don Kieffer, PhD; Lauren Lessard, BS; Deborah Maier, MS; J.P. Massaro, BS; Tammy Monk, MS; Rob Nicholson, PhD; Erin Patterson, BS; Suzanne Phelan, PhD; Hollie Raynor, PhD, RD; Douglas Raynor, PhD; Natalie Robinson, MS, RD; Deborah Robles; Jane Tavares, BS.

The University of Texas Health Science Center at San Antonio: Steven M. Haffner, MD; Maria G. Montez, RN, MSHP, CDE; Carlos Lorenzo, MD.

University of Washington/VA Puget Sound Health Care System: Steven Kahn MB, ChB; Brenda Montgomery, RN, MS, CDE; Robert Knopp, MD; Edward Lipkin, MD; Matthew L. Maciejewski, PhD; Dace Trence, MD; Terry Barrett, BS; Joli Bartell, BA; Diane Greenberg, PhD; Anne Murillo, BS; Betty Ann Richmond, MEd; April Thomas, MPH, RD.

Southwestern American Indian Center, Phoenix, Arizona, and Shiprock, New Mexico: William C. Knowler, MD, DrPH; Paula Bolin, RN, MC; Tina Killean, BS; Jonathan Krakoff, MD; Jeffrey M. Curtis, MD, MPH; Justin Glass, MD; Sara Michaels, MD; Peter H. Bennett, MB, FRCP; Tina Morgan; Shandiin Begay, MPH; Bernadita Fallis, RN, RHIT, CCS; Jeanette Hermes, MS, RD; Diane F. Hollowbreast; Ruby Johnson; Cathy Manus, LPN; Maria Meacham, BSN, RN, CDE; Julie Nelson, RD; Carol Percy, RN; Patricia Poorthunder; Sandra Sangster; Nancy Scurlock, MSN, ANP-C, CDE; Leigh A. Shovestull, RD, CDE; Janelia Smiley; Katie Toledo, MS, LPC; Christina Tomchee, BA; Darryl Tonemah, PhD.

University of Southern California: Anne Peters, MD; Valerie Ruelas, MSW, LCSW; Siran Ghazarian Sengardi, MD; Kathryn Graves, MPH, RD, CDE; Kati Konersman, MA, RD, CDE; Sara Serafin-Dokhan.

Coordinating center

Wake Forest University: Mark A. Espeland, PhD; Judy L. Bahnson, BA; Lynne Wagenknecht, DrPH; David Reboussin, PhD; W. Jack Rejeski, PhD; Alain Bertoni, MD, MPH; Wei Lang, PhD; Gary Miller, PhD; David Lefkowitz, MD; Patrick S. Reynolds, MD; Paul Ribisl, PhD; Mara Vitolins, DrPH; Michael Booth, MBA; Kathy M. Dotson, BA; Amelia Hodges, BS; Carrie C. Williams, BS; Jerry M. Barnes, MA; Patricia A. Feeney, MS; Jason Griffin, BS; Lea Harvin, BS; William Herman, MD, MPH; Patricia Hogan, MS; Sarah Jaramillo, MS; Mark King, BS; Kathy Lane, BS; Rebecca Neiberg, MS; Andrea Ruggiero, MS; Christian Speas, BS; Michael P. Walkup, MS; Karen Wall, AAS; Michelle Ward; Delia S. West, PhD; Terri Windham.

Central resources centers

Dual-Energy X-Ray Absorptiometry Reading Center, University of California at San Francisco: Michael Nevitt, PhD; Susan Ewing, MS; Cynthia Hayashi; Jason Maeda, MPH; Lisa Palermo, MS, MA; Michaela Rahorst; Ann Schwartz, PhD; John Shepherd, PhD.

Central Laboratory, Northwest Lipid Research Laboratories: Santica M. Marcovina, PhD, ScD; Greg Strylewicz, MS.

Electrocardiogram Reading Center, EPICARE, Wake Forest University School of Medicine: Ronald J. Prineas, MD, PhD; Teresa Alexander; Lisa Billings; Charles Campbell, AAS, BS; Sharon Hall; Susan Hensley; Yabing Li, MD; Zhu-Ming Zhang, MD.

Diet Assessment Center, University of South Carolina, Arnold School of Public Health, Center for Research in Nutrition and Health Disparities: Elizabeth J Mayer-Davis, PhD; Robert Moran, PhD.

Hall-Foushee Communications: Richard Foushee, PhD; Nancy J. Hall, MA.

Enrollment of Look AHEAD participants.

Distribution of 1-year changes in percent weight ( A ) and fitness ( B ) (METS) among individuals grouped by intervention assignment. Dashed lines are used to indicate the percentages of ILI participants with weight losses exceeding 10, 7, and 5%, respectively.

Baseline characteristics of the ILI and DSE groups

Data are means ± SD or frequency (%).

ANCOVA, adjusted for clinical center.

Self-report of prior myocardial infarction, stroke, transient ischemic attack, angioplasty/stent, coronary artery bypass graft, carotid endarterectomy, angioplasty of lower extremity, aortic aneurysm repair, or heart failure.

Changes in measures of diabetes control, blood pressure control, measures of lipid/lipoproteins control, albumin-to-creatinine ratio, and prevalence of metabolic syndrome among participants seen at year 1

Data are means ± SE or % ± SE.

Logistic regression with adjustment for clinical site.

Mantel-Haenszel test with adjustment for clinical site.

ANCOVA, with adjustment for clinical site.

Changes in percentage of participants meeting ADA goals for risk factors

Data are % ± SD.

This study is supported by the Department of Health and Human Services through the following cooperative agreements from the National Institutes of Health: DK57136, DK57149, DK56990, DK57177, DK57171, DK57151, DK57182, DK57131, DK57002, DK57078, DK57154, DK57178, DK57219, DK57008, DK57135, and DK56992. The following federal agencies have contributed support: National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; National Institute of Nursing Research; National Center on Minority Health and Health Disparities; Office of Research on Women's Health; and the Centers for Disease Control and Prevention. This research was supported in part by the Intramural Research Program of the National Institute of Diabetes and Digestive and Kidney Diseases.

Additional support was received from the Johns Hopkins Medical Institutions Bayview General Clinical Research Center (M01RR02719); the Massachusetts General Hospital Mallinckrodt General Clinical Research Center (M01RR01066); the University of Colorado Health Sciences Center General Clinical Research Center (M01RR00051) and Clinical Nutrition Research Unit (P30 DK48520); the University of Tennessee at Memphis General Clinical Research Center (M01RR0021140); the University of Pittsburgh General Clinical Research Center (M01RR000056 44); National Institutes of Health Grant DK 046204; the University of Washington/VA Puget Sound Health Care System Medical Research Service, Department of Veterans Affairs; and Frederic C. Bartter General Clinical Research Center (M01RR01346).

Federal support: National Institute of Diabetes and Digestive and Kidney Diseases (to Barbara Harrison, MS; Van S. Hubbard, MD PhD; and Susan Z. Yanovski, MD); the National Heart, Lung, and Blood Institute (to Lawton S. Cooper, MD, MPH; Jeffrey Cutler, MD, MPH; and Eva Obarzanek, PhD, MPH, RD); and the Centers for Disease Control and Prevention (to Edward W. Gregg, PhD; David F. Williamson, PhD; and Ping Zhang, PhD).

The following organizations have committed to make major contributions to Look AHEAD: Federal Express, Health Management Resources, Johnson & Johnson, LifeScan, Optifast-Novartis Nutrition, Roche Pharmaceuticals, Ross Product Division of Abbott Laboratories, and Slim-Fast Foods Company.

Published ahead of print at http://care.diabetesjournals.org on 15 March 2007. DOI: 10.2337/dc07-0048. Clinical trial reg. no. NCT00017953, clinicaltrials.gov.

A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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Key searches, research finds air pollution may affect the way the brain ages and functions.

Exposure to air pollution has been known to affect respiratory diseases, lung function and cardiac health, but a new study led by Keck School of Medicine of the University of Southern California (USC) researchers shows for the first time that it may also have a negative impact on how the brain’s white matter ages. The research indicates that older women who lived in geographic locations with higher levels of fine particulate matter in ambient air had significantly smaller white matter volumes across a wide range of brain areas. Fine particulate matter is smaller than 2.5 micrometers and is known as PM2.5, a form of pollution that easily enters the lungs and possibly the bloodstream. White matter connects brain regions and determines how information is processed in the brain. “Investigating the impact of air pollution on the human brain is a new area of environmental neurosciences,” said Jiu-Chiuan Chen, MD, MPH, ScD, associate professor of preventive medicine at the Keck School of Medicine and lead author of the research. “Our study provides convincing evidence that several parts of the aging brain, especially the white matter, are an important target of neurotoxic effects induced by long-term exposure to fine particles in the air.” The study found that older women ages 71 – 89 who had lived in places with greater PM2.5 exposures had significantly smaller volumes of white matter, and that this could not be explained by the geographic region where they lived, their race or ethnic background, socioeconomic status, lifestyle, or medical conditions that may also influence brain volumes. The researchers performed brain magnetic resonance imaging (MRI) scans of 1,403 women who are part of the Women’s Health Initiative Memory Study (WHIMS), a nationwide study based at Wake Forest Baptist Medical Center in Winston-Salem, N.C. The researchers also used residential histories and air monitoring data to estimate the participants’ exposure to air pollution in the previous six to seven years. This is the first study to differentiate between white and gray matter while examining the neurotoxic effects of PM2.5 on brain volumes of older people. The USC-led research may be the largest neuroimaging study conducted in community-dwelling elderly persons to examine the association between long-term PM2.5 exposures and volumes of gray matter and white matter in the brain. White matter contains nerve fibers and connects brain regions with each other by traveling deep within and passing nerve signals throughout the brain. Gray matter is primarily composed of neuronal cell bodies, dendrites, glial cells and capillaries. The study did not find impacts from exposure to air pollution in participants’ gray matter. The WHIMS study began in 1996 at Wake Forest Baptist Medical Center for the purpose of studying how postmenopausal hormone treatment affects cognitive impairment and brain aging. The research appears in the June 15, 2015 issue of the Annals of Neurology . Co-authors include Xinhui Wang, MS, and Helena Chui, MD of the Keck School of Medicine of USC; John McArdle, PhD of the USC Dornsife College of Letters, Arts and Sciences; Gregory Wellenius, ScD of Brown University; Mark Serre, PhD of the University of North Carolina; Ira Driscoll, PhD of the University of Wisconsin; Ramon Casanova, PhD and Mark Espeland, PhD of Wake Forest Baptist Medical Center; and JoAnn Manson, MD, Dr PH of Harvard Medical School. The collaborative study was funded in part by the National Institutes of Health grant R01AG033078 and by the Rosenblith Award from the Health Effects Institute, an organization jointly funded by the United States Environmental Protection Agency and certain auto and engine manufacturers. The work was also supported by the Southern California Environmental Health Sciences Center (5P30ES007048). The research was also supported by the National Heart, Lung, and Blood Institute, National Institute on Aging, National Institutes of Health, U.S. Department of Health and Human Services through contracts and by Wyeth Pharmaceuticals, Inc, St. Davids, Pa., and Wake Forest Baptist Medical Center, which funds the Women’s Health Initiative Program and its memory study. Article cited: Chen, J.C., Wang, X., Wellenius. G.A., Serre, M.L., Driscoll, I., Casanova, R. McArdle, J.J., Manson, J.E., Chui, H.C., Espeland, M.A.. Ambient Air Pollution and Neurotoxicity on Brain Structure: Evidence from Women’s Health Initiative Memory Study. Annals of Neurology June 15, 2015. doi: 10.1002/ana.24460. [Epub ahead of print]. PMID: 26075655

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Faculty Publications

Effects of a physical activity intervention on measures of physical performance: results of the lifestyle interventions and independence for elders pilot (life-p) study.

Marco Pahor Steven N. Blair , University of South Carolina - Columbia Follow Mark Espeland Roger Fielding Thomas M. Gill Jack M. Guralnik Cinzia Maraldi Michael E. Miller Anne B. Newman Walter J. Rejeski Sergei Romashkan Stephanie Studenski

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Publication info.

The LIFE Study Investigators (Writing Group--Marco Pahor, MD, Steven N. Blair, PED, Mark Espeland, PhD, Roger Fielding, PhD, Thomas M. Gill, MD, Jack M. Guralnik, MD, PhD, Evan C. Hadley, MD, Abby C. King, PhD, Stephen B. Kritchevsky, PhD, Cinzia Maraldi, MD, Michael E. Miller, PhD, Anne B. Newman, MD, Walter J. Rejeski, PhD, Sergei Romashkan, MD, PhD, Stephanie Studenski, MD, MPH). (2006) Effects of a Physical Activity Intervention on Measures of Physical Performance: Results of the Lifestyle Interventions and Independence for Elders Pilot (LIFE-P) Study. Journal of Gerontology 61(11);1157-65.

© Journal of Gerontology 2006, Oxford University Press

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Effect of Linagliptin vs Glimepiride on Major Adverse Cardiovascular Outcomes in Patients With Type 2 Diabetes

Julio rosenstock.

1 Dallas Diabetes Research Center at Medical City, Dallas, Texas

2 University of Texas Southwestern Medical Center, Dallas

Steven E. Kahn

3 Division of Metabolism, Endocrinology and Nutrition, Department of Medicine, VA Puget Sound Health Care System, Seattle, Washington

4 University of Washington, Seattle

Odd Erik Johansen

5 Boehringer Ingelheim Norway KS, Asker, Norway

Bernard Zinman

6 Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Canada

7 Division of Endocrinology, University of Toronto, Toronto, Canada

Mark A. Espeland

8 Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina

Hans J. Woerle

9 Ulm University, Ulm, Germany.

10 Boehringer Ingelheim International GmbH & Co KG, Ingelheim, Germany

Annett Keller

Michaela mattheus, david baanstra.

11 Boehringer Ingelheim, Alkmaar, the Netherlands

Thomas Meinicke

12 Boehringer Ingelheim International GmbH & Co KG, Biberach, Germany

Jyothis T. George

Maximilian von eynatten, darren k. mcguire, nikolaus marx.

13 Department of Internal Medicine I, University Hospital Aachen, RWTH Aachen University, Germany

Group Information: The CAROLINA investigators appear at the end of the article.

Accepted for Publication: August 15, 2019.

Published Online: September 19, 2019. doi:10.1001/jama.2019.13772

Author Contributions: Drs Rosenstock and Marx had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Rosenstock, Kahn, Johansen, Zinman, Woerle, Baanstra, Meinicke, McGuire, Marx.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Johansen, Espeland, Pfarr, Keller, Marx.

Critical revision of the manuscript for important intellectual content: Rosenstock, Kahn, Johansen, Zinman, Espeland, Woerle, Mattheus, Baanstra, Meinicke, George, von Eynatten, McGuire, Marx.

Statistical analysis: Kahn, Espeland, Pfarr, Keller, Mattheus, Meinicke, von Eynatten.

Obtained funding: Johansen, Zinman.

Administrative, technical, or material support: Woerle.

Supervision: Rosenstock, Johansen, Zinman, Woerle, Baanstra, Meinicke, George, von Eynatten, Marx.

Conflict of Interest Disclosure: Dr Rosenstock reported serving on scientific advisory boards and received honoraria and consulting fees from Eli Lilly, Sanofi, Novo Nordisk, Janssen, AstraZeneca, Boehringer Ingelheim, and Intarcia and receiving grants/research support from Merck, Pfizer, Sanofi, Novo Nordisk, Bristol-Myers Squibb, Eli Lilly, GlaxoSmithKline, Genentech, Janssen, Lexicon, Boehringer Ingelheim, and Intarcia. Dr Kahn reported receiving personal fees from Boehringer Ingelheim, Elcelyx, Eli Lilly, Intarcia, Janssen, Merck, Neurimmune, and Novo Nordisk. Dr Johansen is employed by Boehringer Ingelheim, Norway. Dr Zinman reported receiving grant support from Boehringer Ingelheim, AstraZeneca, and Novo Nordisk and consulting fees from AstraZeneca, Boehringer Ingelheim, Eli Lilly, Janssen, Merck Sharp & Dohme, Novo Nordisk, and Sanofi Aventis. Dr Espeland reported receiving consulting fees from Boehringer Ingelheim during the conduct of the study and grants from the National Institute of Diabetes and Digestive and Kidney Diseases and the National Institute on Aging outside the submitted work. Dr Woerle is a former employee of Boehringer Ingelheim, Germany, and is now employed by Nestle. Mr Pfarr, Mrs Mattheus, and Drs Keller, Meinicke, George, and von Eynatten are employed by Boehringer Ingelheim, Germany. Mr Baanstra is employed by Boehringer Ingelheim, the Netherlands. Dr McGuire reported receiving personal fees from Boehringer-Ingelheim, Janssen Research and Development LLC, Sanofi-Aventis Group, Merck Sharp & Dohme, Eli Lilly USA, Novo Nordisk, GlaxoSmithKline, AstraZeneca, Lexicon, Eisai, Esperion, Pfizer, Metavant, and Applied Therapeutics. Dr Marx is funded by the German Research Foundation SFB TRR 219 (projects M-03 and M-05); reported giving lectures for and receiving honoraria from Amgen, Boehringer Ingelheim, Sanofi-Aventis, Merck Sharp & Dohme, Bristol-Myers Squibb, AstraZeneca, Lilly, Novo Nordisk; receiving unrestricted research grants from Boehringer Ingelheim; serving as an advisor for Amgen, Bayer, Boehringer Ingelheim, Sanofi-Aventis, Merck Sharp & Dohme, Bristol-Myers Squibb, AstraZeneca, Novo Nordisk; serving in trial leadership for Boehringer Ingelheim and Novo Nordisk; and declining all personal compensation from pharmaceutical and device companies.

Funding/Support: This study was sponsored by Boehringer Ingelheim and Eli Lilly and Company.

Role of the Funder/Sponsor: Representatives of Boehringer Ingelheim were involved in the design and conduct of the study; management, analysis, and interpretation of the data; and preparation, review, and approval of the manuscript. The decision to submit the manuscript for publication was taken by the academic leadership of the steering committee, and the sponsor had no veto right to publish or to control the decision to which journal to submit to.

Group Information: The trial was designed by independent academic investigators along with clinician scientists employed by Boehringer Ingelheim, the latter as nonvoting members of the steering committee that oversaw the trial. Investigators and committee members are listed in eAppendix 1 and 2 in Supplement 3 . Site monitoring, data management, and data analysis were conducted by Boehringer Ingelheim. Members of Leuven Biostatistics and Statistical Bioinformatics Centre, Belgium, conducted an independent statistical analysis of the cardiovascular and mortality outcomes (eAppendix 2 in Supplement 3 ).

Data Sharing Statement: See Supplement 5 .

Additional Contributions: The authors thank the investigators, coordinators, clinical expert committee members, and patients who participated in this trial. We thank John M. Lachin, PhD, and John J. P. Kastelein, MD, former steering committee members of CAROLINA, for their invaluable contribution in the initial trial design and planning, supported financially by Boehringer Ingelheim. We also thank the following Boehringer Ingelheim employees: Uli Broedl, MD, for midtrial steering committee contributions; Maria Weber, MD, for support in the adverse events data review; Knut R, Andersen, MSc, for operational oversight work, Anna Cooper, BSc, for trial programming work, and Valeska Berwind-Max, medical documentation specialist, for data management work. We acknowledge Matt Smith, PhD, CMPP, and Giles Brooke, PhD, CMPP, from Envision Scientific Solutions, for graphical support (Kaplan-Meier plots and forest plots), supported financially by Boehringer Ingelheim.

Associated Data

What is the effect of linagliptin compared with glimepiride on major cardiovascular events in patients with relatively early type 2 diabetes and elevated cardiovascular risk?

In this randomized noninferiority clinical trial that included 6033 participants followed up for a median of 6.3 years, the use of linagliptin compared with glimepiride added to usual care resulted in rates of the composite outcome (cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke) of 11.8% vs 12.0%. The upper limit of the 95.47% CI of the hazard ratio was 1.14, which met the noninferiority criterion of a hazard ratio of less than 1.3.

Compared with glimepiride, the use of linagliptin demonstrated noninferiority with regard to the risk of major cardiovascular events over a median of 6.3 years in patients with relatively early type 2 diabetes and elevated cardiovascular risk.

Type 2 diabetes is associated with increased cardiovascular risk. In placebo-controlled cardiovascular safety trials, the dipeptidyl peptidase-4 inhibitor linagliptin demonstrated noninferiority, but it has not been tested against an active comparator.

This trial assessed cardiovascular outcomes of linagliptin vs glimepiride (sulfonylurea) in patients with relatively early type 2 diabetes and risk factors for or established atherosclerotic cardiovascular disease.

Design, Setting, and Participants

Randomized, double-blind, active-controlled, noninferiority trial, with participant screening from November 2010 to December 2012, conducted at 607 hospital and primary care sites in 43 countries involving 6042 participants. Adults with type 2 diabetes, glycated hemoglobin of 6.5% to 8.5%, and elevated cardiovascular risk were eligible for inclusion. Elevated cardiovascular risk was defined as documented atherosclerotic cardiovascular disease, multiple cardiovascular risk factors, aged at least 70 years, and evidence of microvascular complications. Follow-up ended in August 2018.

Interventions

Patients were randomized to receive 5 mg of linagliptin once daily (n = 3023) or 1 to 4 mg of glimepiride once daily (n = 3010) in addition to usual care. Investigators were encouraged to intensify glycemic treatment, primarily by adding or adjusting metformin, α-glucosidase inhibitors, thiazolidinediones, or insulin, according to clinical need.

Main Outcomes and Measures

The primary outcome was time to first occurrence of cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke with the aim to establish noninferiority of linagliptin vs glimepiride, defined by the upper limit of the 2-sided 95.47% CI for the hazard ratio (HR) of linagliptin relative to glimepiride of less than 1.3.

Of 6042 participants randomized, 6033 (mean age, 64.0 years; 2414 [39.9%] women; mean glycated hemoglobin, 7.2%; median duration of diabetes, 6.3 years; 42% with macrovascular disease; 59% had undergone metformin monotherapy) were treated and analyzed. The median duration of follow-up was 6.3 years. The primary outcome occurred in 356 of 3023 participants (11.8%) in the linagliptin group and 362 of 3010 (12.0%) in the glimepiride group (HR, 0.98 [95.47% CI, 0.84-1.14]; P  < .001 for noninferiority), meeting the noninferiority criterion but not superiority ( P  = .76). Adverse events occurred in 2822 participants (93.4%) in the linagliptin group and 2856 (94.9%) in the glimepiride group, with 15 participants (0.5%) in the linagliptin group vs 16 (0.5%) in the glimepiride group with adjudicated-confirmed acute pancreatitis. At least 1 episode of hypoglycemic adverse events occurred in 320 (10.6%) participants in the linagliptin group and 1132 (37.7%) in the glimepiride group (HR, 0.23 [95% CI, 0.21-0.26]).

Conclusions and Relevance

Among adults with relatively early type 2 diabetes and elevated cardiovascular risk, the use of linagliptin compared with glimepiride over a median 6.3 years resulted in a noninferior risk of a composite cardiovascular outcome.

Trial Registration

ClinicalTrials.gov Identifier: {"type":"clinical-trial","attrs":{"text":"NCT01243424","term_id":"NCT01243424"}} NCT01243424

This randomized noninferiority clinical trial examines the effect of treatment with the dipeptidyl peptidase-4 inhibitor linagliptin vs the commonly used sulfonylurea glimepiride on cardiovascular safety in patients with type 2 diabetes and cardiovascular risk factors or established atherosclerotic cardiovascular disease.

Introduction

When choosing medications to manage type 2 diabetes, cardiovascular safety, glucose-lowering potency, hypoglycemia risk, effect on body weight, and cost are important considerations. 1 , 2 , 3 Most guidelines state that metformin should be first-line therapy followed by various options for second-line treatment if sufficient glycemic control is not achieved after metformin monotherapy. 1 , 2 , 3 Sulfonylureas and dipeptidyl peptidase-4 (DPP-4) inhibitors are the most commonly used second-line glucose-lowering treatments in many countries. 4 Sulfonylureas are used mainly based on their low cost, well-established glucose-lowering action, and a long-standing experience in clinical practice. However, sulfonylureas are associated with increased risk of hypoglycemia 1 , 3 , 5 , 6 , 7 and modest weight gain. 1 , 5 In addition, there is an ongoing controversy regarding their long-term cardiovascular safety, based on early data from the University Group Diabetes Program in the 1960s 8 and multiple observational and smaller studies indicating conflicting results. 9 , 10

Linagliptin is a selective, once-daily, DPP-4 inhibitor approved for glycemic management of type 2 diabetes, with low risk of hypoglycemia and weight neutrality. 11 To date, no head-to-head trial has compared the long-term effect of these agents on cardiovascular morbidity and mortality or glucose-lowering efficacy in patients with type 2 diabetes.

The Cardiovascular Outcome Study of Linagliptin vs Glimepiride in Type 2 Diabetes (CAROLINA) examined the effect of treatment with the DPP-4 inhibitor linagliptin vs the commonly used sulfonylurea glimepiride on cardiovascular safety in patients with relatively early type 2 diabetes and cardiovascular risk factors or established atherosclerotic cardiovascular disease using a noninferiority design.

The study protocol was approved by the institutional review board or independent ethics committee from each site, and all patients provided written informed consent; the trial protocol is available is Supplement 1 and the statistical analysis plan in Supplement 2 .

The trial was conducted in accordance with the principles of the Declaration of Helsinki and the Harmonized Tripartite Guideline for Good Clinical Practice from the International Conference on Harmonisation and was approved by local authorities.

Trial Oversight

An independent, unmasked data monitoring committee regularly reviewed trial data. Investigator-reported cardiovascular outcome events, deaths, pancreatitis, and pancreatic cancer were prospectively captured and centrally adjudicated by clinical events committees masked to treatment assignment.

Trial Design

The trial design has been previously published. 12 In brief, this was a multicenter, randomized, double-blind, active-controlled clinical trial conducted at 607 centers across 43 countries, aimed to continue until at least 631 participants had an adjudication-confirmed primary outcome event.

Trial Participants

Adults with type 2 diabetes, glycated hemoglobin (HbA 1c ) level of 6.5% to 8.5%, and high cardiovascular risk were eligible for inclusion. Participants naive to sulfonylurea or glinide therapy had to have a HbA 1c level of 6.5% to 8.5%, while participants who were currently treated with a sulfonylurea or glinide as monotherapy or in a dual combination with metformin or α-glucosidase inhibitor (who also were eligible for the trial) had to have an HbA 1c level of 6.5% to 7.5%. The sulfonylurea or glinide were discontinued at randomization. High cardiovascular risk was defined as (1) established atherosclerotic cardiovascular disease (documented ischemic heart disease, cerebrovascular disease, or peripheral artery disease), (2) multiple risk factors (at least 2 of the following: type 2 diabetes duration >10 years, systolic blood pressure >140 mm Hg [or receiving at least 1 blood pressure–lowering treatment], current smoker, low-density lipoprotein cholesterol ≥135 mg/dL [3.5 mmol/L], or receiving lipid-lowering treatment), (3) age at least 70 years, and (4) evidence of microvascular complications (impaired kidney function [estimated glomerular filtration rate of 30-59 mL/min/1.73 m 2 ], urine albumin/creatinine ratio ≥30 μg/mg, or proliferative retinopathy). Insulin therapy or previous exposure to DPP-4 inhibitors, glucagonlike peptide-1 receptor agonists, or thiazolidinediones were exclusion criteria, as was New York Heart Association class III to IV heart failure (eAppendix 3 and 4 in Supplement 3 ).

Information on race and ethnicity was captured by investigators based on self-classification by trial participants as reported in the electronic case record form (fixed categories) following written informed consent. This information was collected to allow for subgroup analysis, given some previous reports about potential heterogeneity of effects of sulfonylureas and incretin-based therapies on different genetic background, 13 , 14 and as required by regulatory bodies. 15

Trial Procedures

Participants were randomized 1:1 using an interactive telephone- and web-based system in a block size of 4 to receive 5 mg of once-daily oral linagliptin or 1 to 4 mg of once-daily glimepiride ( Figure 1 ). Treatment assignment was determined by a computer-generated random sequence with stratification by center. Glimepiride was started at 1 mg/d and uptitrated to a potential maximum dose of 4 mg/d every 4 weeks during the first 16 weeks. After the first 16 weeks, participants returned for follow-up study visits every 16 weeks until the end of the study. A final follow-up visit was scheduled 30 days after treatment cessation. Investigators were encouraged to monitor and use additional medication for glycemic control per local guidelines, particularly if HbA 1c was greater than 7.5% after the end of the titration phase. Recommended strategies were adjustments of background therapy or addition of pioglitazone, metformin, α-glucosidase inhibitor, or basal insulin. Investigators were also encouraged to manage all other cardiovascular risk factors in accordance with applicable guidelines and current standards of care. Participants who prematurely discontinued the study medication were followed up for ascertainment of cardiovascular events, mortality, adverse events, and other end points. Attempts were made to collect vital status and outcome event information on every randomized individual at study completion, in compliance with local law and regulations.

There were 19 participants (9 in the linagliptin group and 10 in the glimepiride group) identified to have been enrolled and treated at multiple sites. For these participants, treatment group allocation according to first randomization was used and only objective data (eg, selected baseline characteristics, serious adverse events, and trigger events sent for adjudication) were included in the analyses. Patients could meet more than 1 exclusion criteria. BMI indicates body mass index; CV, cardiovascular; HbA 1c , glycated hemoglobin.

Trial Outcomes

The primary end point was time to first occurrence of cardiovascular death, nonfatal myocardial infarction (MI), or nonfatal stroke (3-point major cardiovascular event [3P-MACE] composite). The original protocol included hospitalization for unstable angina in the primary end point (4-point major cardiovascular event [4P-MACE] composite); however, this was changed by a protocol amendment in April 2016, based on emerging evidence that a primary end point definition of 3P-MACE was preferred by regulators and consistent with other outcome trials of glucose-lowering therapies. 16 , 17 The steering committee and sponsor remained blinded to all trial data prior to database lock. Time to first occurrence of 4P-MACE was hierarchically evaluated as the first of the prespecified key secondary end points, followed by analyses of the proportion of patients receiving treatment and maintaining HbA 1c of less than or equal to 7.0% at the final follow-up visit who (1) were without the need for rescue medication, did not have any moderate/severe hypoglycemic episodes, and did not have greater than 2% weight gain or (2) were without the need for rescue medication and did not have greater than 2% weight gain between the end of titration and final visit.

Other secondary cardiovascular end points included individual components of 3P-MACE and 4P-MACE and time to any confirmed adjudicated cardiovascular events (cardiovascular death, including fatal stroke and fatal MI; nonfatal MI; nonfatal stroke; hospitalization for unstable angina; transient ischemic attack; hospitalization for HF; hospitalization for coronary revascularization procedures). Secondary diabetes-related end points included change in laboratory parameters from baseline to final visit (eg, HbA 1c , fasting plasma glucose, total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides). In addition, we prespecified several tertiary cardiovascular end points (ie, occurrence of and time to first occurrence of each of the confirmed adjudicated end points), tertiary diabetes-related end points (eg, change of laboratory parameters from baseline to each planned week, hypoglycemia occurrence, change in weight and rescue medication use), and other end points (including noncardiovascular death and adverse events). All predefined outcomes and end point definitions are presented in Supplement 1 , Supplement 3 (eAppendix 5), and Supplement 4 .

Safety was assessed based on adverse events that occurred during treatment or within 7 days after the last dose of a study drug and coded using the Medical Dictionary for Drug Regulatory Activities version 21.0. Adverse events prespecified as being of special interest included hypersensitivity reactions, skin lesions, pancreatitis, pancreatic cancer, and hypoglycemia. Categories of hypoglycemia were analyzed as “any,” “moderate or severe,” “severe,” or “leading to hospitalization” (for definitions of each categorization, see eAppendix 5 in Supplement 3 ).

Statistical Analysis

The primary aim of the study was to evaluate whether linagliptin was noninferior to glimepiride for the time to 3P-MACE, defined by the upper limit of the multiplicity-adjusted 2-sided 95.47% CI for the hazard ratio (HR) of linagliptin relative to glimepiride of less than 1.3. 15 This margin (ie, an upper limit of the 2-sided 95% CI <1.3) was deemed able to demonstrate a reassuring point estimate of overall cardiovascular risk between study groups in the context of a noninferiority assessment by the US Food and Drug Administration. A 5-step hierarchical testing strategy was prespecified, in which each subsequent test would be performed in case of significant prior results. If noninferiority was achieved for the primary outcome, the subsequent tests were (1) superiority test of 3P-MACE, (2) superiority test of 4P-MACE, (3) superiority test of the second key secondary end point (ie, proportion of patients receiving treatment and maintaining HbA 1c ≤7.0% at the final visit who were without the need for rescue medication following the end of titration, did not have moderate/severe hypoglycemic episodes, and did not have >2% weight gain), and (4) superiority test of the third key secondary end point (ie, proportion of patients receiving treatment and maintaining HbA 1c ≤7.0% at the final visit who were, from the end of titration, without the need for rescue medication and did not have >2% weight gain). Not adjusted for interim analyses, a total of 631 individuals with an adjudication-confirmed 3P-MACE would provide 90.9% power to demonstrate noninferiority (noninferiority margin, 1.3) of linagliptin vs glimepiride at the overall 1-sided α level of 2.5% assuming an HR of 1.0, and 80% power for superiority assuming an HR of 0.80. The 95.47% bound for the CI reflected an O’Brien-Fleming α-spending adjustment for the 2 interim analyses of the primary outcome, 18 in addition to Bonferroni adjustment, to control for type I error for the change from 4P-MACE to 3P-MACE after the first interim analysis. The interim analyses were planned to be performed after 190 and 411 participants experienced a primary outcome event. Outcomes were analyzed in all randomized patients treated with at least 1 dose of the study drug (treated set) using the intention-to-treat principle. Patients were analyzed according to their randomized treatment group. Additional sensitivity analyses are described in eAppendix 6 in Supplement 3 . Time-to-event outcomes were analyzed using a Cox proportional hazards model, with treatment assignment as a factor in the model. Proportional hazards assumptions were explored by plotting log(−log [survival function]) against the log of time × treatment group and checked for parallelism. Further, Schoenfeld residuals were plotted against time and log(time). For all Cox proportional hazards analyses, the proportional hazard assumption was met. Subgroup analyses included additional factors for subgroup and treatment by subgroup interaction.

In addition, Kaplan-Meier estimates are presented. Censoring was applied the day a participant was last known to be free of the specific outcome event. Because of declining numbers of participants at risk, Kaplan-Meier plots were truncated at 6.5 years after randomization. Logistic regression models with randomized treatment as the factor and χ 2 tests were used to analyze noncardiovascular key secondary efficacy end points. For continuous parameters, the change from baseline over time was evaluated with a restricted maximum likelihood–based mixed-model repeated-measures approach (2-sided significance threshold P  < .05; eAppendix 6 in Supplement 3 ). As prespecified, data were included up to the planned week that could theoretically be achieved by all patients. The prespecified approach for handling missing data are described in the statistical analysis plan ( Supplement 2 ). The approach varied according to the statistical analysis employed (eg, censoring in Cox models and Kaplan-Meier plots for time-to-event analysis and mixed models for continuous variables). Specifically, we defined the censoring date for the time-to-event analysis as the last date a patient was known to be free of an end point event, including any start dates of adverse event/outcome events, onset dates of adjudicated-confirmed events, date of percutaneous coronary intervention/coronary artery bypass grafting, or date of trial completion (defined as the latest of date of the last clinic visit, telephone call, or contact if lost to follow-up). Except for the prespecified 5-step hierarchical testing strategy, there was no adjustment for multiple comparisons and, therefore, the results of subgroup analyses and other end points should be interpreted as exploratory. Safety assessments were conducted using descriptive statistics for adverse events, except for analyses of hypoglycemia, which was analyzed using a Cox proportional hazards model (2-sided P value threshold < .05). Analyses were conducted using SAS version 9.4 (SAS Institute).

Participants were screened from November 2010 through December 2012, with final follow-up on August 21, 2018. A total of 6042 participants were randomized, of whom 6033 received at least 1 dose of the study medication and were included in the primary outcome analysis ( Figure 1 ).

Baseline clinical characteristics were well balanced between groups ( Table 1 ), with 42% of all participants having prevalent atherosclerotic cardiovascular disease at the time of screening. Median (quartile [Q] 1, Q3) follow-up was 6.3 (5.9, 6.6) years in both the linagliptin and glimepiride groups. Median (Q1, Q3) study medication exposure was 5.9 years in the linagliptin group and 5.9 (3.4, 6.4) years in the glimepiride group (eAppendix 7 in Supplement 3 ). Cumulative participant-years of follow-up was 18 336 for the linagliptin group and 18 212 for the glimepiride group. Overall, 96.0% of participants completed the study, with 38.2% prematurely discontinuing the study drug (incidence rate per 100 years at risk of 7.6 in the linagliptin group and 8.0 in the glimepiride group). Vital status was available for 99.3% of participants at the end of the study ( Figure 1 ).

Abbreviations: ACE, angiotensin-converting enzyme; ARB, angiotensin-receptor blocker; BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); eGFR, estimated glomerular filtration rate; HDL, high-density lipoprotein; LDL, low-density lipoprotein; MDRD, Modification of Diet in Renal Disease study equation 19 ; UACR, urinary albumin-to-creatinine ratio.

SI conversion factors: To convert cholesterol to mmol/L, multiply values by 0.0259; triglycerides to mmol/L, multiply by 0.0113; and glucose to mmol/L, multiply by 0.0555.

Primary End Point

The primary 3P-MACE end point occurred in 356 of 3023 participants (11.8%) treated with linagliptin (2.1 per 100 person-years) and 362 of 3010 (12.0%) treated with glimepiride (2.1 per 100 person-years), meeting the criterion for noninferiority (HR, 0.98 [95.47% CI, 0.84-1.14], P <.001 for noninferiority; Table 2 and Figure 2 A). The subsequent testing for superiority according to the prespecified testing procedure was not statistically significant ( P  = .76). Overall, the HR for 3P-MACE was consistent across prespecified subgroups (eAppendix 8 in Supplement 3 ).

Abbreviations: 3P-MACE, 3-point major adverse cardiovascular event; 4P-MACE, 4-point major adverse cardiovascular event; HbA 1c , glycated hemoglobin.

A, Composite end point of cardiovascular death, first nonfatal myocardial infarction, or first nonfatal stroke (3-point major cardiovascular event [3P-MACE] outcome). Median (quartile [Q] 1, Q3) follow-up was 6.2 (5.8, 6.6) years in the linagliptin group and 6.2 (5.6, 6.5) years in the glimepiride group. The 95.47% CI for the primary end point was adjusted for multiplicity due to 2 interim analyses and change of the primary end point. B, Median (Q1, Q3) follow-up was 6.3 (5.9, 6.6) years in the linagliptin group and 6.3 (5.9, 6.6) years in the glimepiride group. C, Median (Q1, Q3) follow-up was 6.3 (5.9, 6.6) years in the linagliptin group and 6.3 (5.9, 6.6) years in the glimepiride group. D, Median (Q1, Q3) follow-up was 6.3 (5.9, 6.6) years in the linagliptin group and 6.3 (5.9, 6.6) years in the glimepiride group. 3P-MACE indicates 3-point major adverse cardiovascular event.

Key Secondary End Points

Because the result of the test for superiority was null, findings for the key secondary outcomes are presented descriptively. Post hoc analytic results can be found in eAppendix 9 and eTable 3 in Supplement 3 . The secondary 4P-MACE outcome occurred in 398 of 3023 participants (13.2%) in the linagliptin group and 401 of 3010 (13.3%) in the glimepiride group ( Table 2 ). The second key secondary end point of the proportion of patients receiving treatment and maintaining HbA 1c less than or equal to7.0% at the final visit who were (following the end of titration) without the need for rescue medication, without any moderate/severe hypoglycemic episodes, and without greater than 2% weight gain occurred in 481 of 3023 participants (16.0%) in the linagliptin group and 305 of 3010 (10.2%) in the glimepiride group ( Table 2 ; eAppendix 9 in Supplement 3 ). The third key secondary end point of the proportion of patients receiving treatment and maintaining HbA 1c less than or equal to 7.0% at the final visit who were (following the end of titration) without the need for rescue medication and did not have greater than 2% weight gain occurred in 524 of 3023 participants (17.4%) in the linagliptin group and in 422 of 3010 (14.1%) in the glimepiride group ( Table 2 ; eAppendix 9 Supplement 3 ).

Other Secondary and Tertiary Cardiovascular End Points

Death from any cause was not significantly different between participants in the linagliptin (308 of 3023 [10.2%]) and glimepiride (336 of 3010 [11.2%]) groups (HR, 0.91 [95% CI, 0.78-1.06]; Figure 2 B), with an HR for cardiovascular death of 1.00 (95% CI, 0.81-1.24; Figure 2 C) and an HR for noncardiovascular death of 0.82 (95% CI, 0.66-1.03; Figure 2 D; eAppendix 9 in Supplement 3 ). The distribution of causes of noncardiovascular death in the linagliptin group (139 of 3023 participants [4.6%]) and the glimepiride group (168 of 3010 participants [5.6%]) is provided in eAppendix 10 in Supplement 3 . Adjudication-confirmed hospitalizations for HF, alone or included in composite outcomes with cardiovascular mortality or investigator-reported HF events, were not significantly different between groups ( Table 2 ; eAppendix 9 in Supplement 3 ).

Secondary and Tertiary Diabetes-Related and Other End Points

The mean (SD) dose of glimepiride over the trial duration was 2.9 (1.1) mg daily (eAppendix 11 in Supplement 3 ), with 49% of participants using the highest 4-mg dose at week 16 and 61% at week 256. Initially, the effect on adjusted mean change in HbA 1c favored glimepiride over linagliptin, but overall there was no significant difference between the groups (weighted mean treatment difference in adjusted means until week 256, 0% [95% CI, −0.05% to 0.05%]; Figure 3 A). Introduction of additional glucose-lowering therapies occurred in similar proportions across study groups, with a pattern of shorter time to introduction in the linagliptin group compared with the glimepiride group (eAppendix 12 in Supplement 3 ).

Weighted average mean difference for panels A and B based on mixed-model repeated measures, including treatment, week repeated within participants, week × treatment interaction, continuous baseline HbA 1c and weight, and baseline HbA 1c × week and weight × week interaction for patients who received at least 1 dose of a study drug and had a baseline and at least 1 postbaseline measurement. The squares and triangles indicate the unadjusted mean, the solid lines indicate the median (quartile [Q] 1, Q3), and the dashed lines indicate the median value at baseline. A, Median (Q1, Q3) follow-up was 6.1 (5.2, 6.4) years in the linagliptin group and 6.1 (4.8, 6.4) years in the glimepiride group. B, Median (Q1, Q3) follow-up was 6.1 (5.2, 6.5) years in the linagliptin group and 6.1 (4.9, 6.4) years in the glimepiride group.

Modest weight gain was observed in the glimepiride group early in the study and maintained thereafter, with a weighted mean between-group difference of −1.54 kg (95% CI, −1.80 to −1.28; Figure 3 B). Fasting plasma glucose, blood pressure, and lipid levels over time were not significantly different between groups (eAppendix 13 and 14 in Supplement 3 ).

Frequencies of adverse events, serious adverse events, and adverse events leading to discontinuation of study medication were comparable between groups ( Table 3 ). Overall, the number of participants with at least 1 hospitalization was 1245 (41.2%) in the linagliptin group and 1303 (43.3%) in the glimepiride group. There was no between-group imbalance in adjudication-confirmed pancreatitis or pancreatic cancer.

Incidence of hypoglycemic events was lower in the linagliptin group than in the glimepiride group across all predefined hypoglycemia severity categories ( Table 3 ). Rates of investigator-reported hypoglycemia were 2.3 events per 100 participant-years in the linagliptin group and 11.1 per 100 participant-years in the glimepiride group (incidence rate difference, −8.7 [95% CI, −9.4 to −8.0]; HR, 0.23 [95% CI, 0.21-0.26]; P  < .001); rates of moderate or severe hypoglycemic events were 1.4 per 100 participant-years in the linagliptin group and 8.4 per 100 participant-years in the glimepiride group (incidence rate difference, −7.0 [95% CI, −7.6 to −6.5]; HR, 0.18 [95% CI, 0.15-0.21]; P  < .001; Figure 4 ). Rates of severe hypoglycemic events were 0.07 per 100 participant-years in the linagliptin group and 0.45 per 100 participant-years in the glimepiride group (incidence rate difference, −0.4 [95% CI, −0.5 to −0.3]; HR, 0.15 [95% CI, 0.08-0.29]; P  < .001; Table 3 ), and hospitalization due to hypoglycemia rates were 0.01 per 100 patient-years in the linagliptin group vs 0.18 per 100 patient-years in the glimepiride group (incidence rate difference, −0.2 [95% CI, −0.2 to −0.1]; HR, 0.07 [95% CI, 0.02-0.31]; P  < .001; Table 3 ). Hypoglycemia risk was increased across the entire dose range for the glimepiride group (eAppendix 15 in Supplement 3 ). A consistently lower hypoglycemia risk was observed in the linagliptin group than in the glimepiride group across all subgroups analyzed (eAppendix 16 in Supplement 3 ).

Median (quartile 1, quartile 3) follow-up was 5.9 (2.8, 6.5) years in the linagliptin group and 4.3 (0.8, 6.2) years in the glimepiride group. Moderate or severe hypoglycemia was defined as time to the first occurrence of symptomatic investigator-defined hypoglycemic adverse event with plasma glucose ≤70 mg/dL or a severe hypoglycemic adverse event. Analysis based on hypoglycemic adverse events occurring between first study drug intake until 7 days after receiving the study drug for the final time. Severe hypoglycemia was defined as an event requiring the assistance of another person to actively administer carbohydrate, glucagon, or other resuscitative actions. Hazard ratio (HR) for hypoglycemia derived by Cox regression model analyses in patients treated with ≥1 dose of the study drug.

In this long-term, multicenter, double-blind, randomized, active comparator trial of individuals with relatively early type 2 diabetes at elevated cardiovascular risk, linagliptin was noninferior to glimepiride for the combined 3P-MACE end point.

Currently, 4 large cardiovascular outcome trials have established the cardiovascular safety of DPP-4 inhibitors vs placebo in patients with type 2 diabetes at a high cardiovascular risk, 20 , 21 , 22 , 23 including the Cardiovascular and Renal Microvascular Outcome Study with Linagliptin (CARMELINA). 23 In 2009, when the current trial was designed, sulfonylureas were the most commonly used second-line glucose-lowering agents after metformin, followed by DPP-4 inhibitors, but no head-to-head cardiovascular outcome trial existed for those 2 classes of medications. The current study demonstrates noninferior cardiovascular safety effects for linagliptin vs glimepiride when used predominantly as a second-line glucose-lowering treatment option after metformin.

The current study reaffirms clinical recommendations to choose an oral agent after metformin based on proven cardiovascular benefit, 1 , 2 which none of the agents studied provide. However, when additional glucose-lowering therapy is required, a DPP-4 inhibitor, such as linagliptin, is an option with a low risk of hypoglycemia and weight gain.

Limitations

This study has several limitations. First, because the trial recruited participants with relatively early type 2 diabetes and insulin treatment was an exclusion criterion, the results may not necessarily be applicable to patients with more advanced disease. While there was no statistically significant heterogeneity in the effects on the 3P-MACE outcome in subgroups based on diabetes duration or cardiovascular risk at baseline, the study may have been underpowered to test for interactions. Second, inherent for many long-term trials is the early termination of study medication, which could have influenced the results. However, medication exposure was comparable between study groups, and annualized discontinuation rates are in line with most of the contemporary cardiovascular outcome trials of glucose-lowering therapies, all of which were of shorter duration. 17 , 18 , 20 , 21 , 24 Furthermore, analyses limited to events that were occurring while patients were receiving study medication yielded results consistent with the primary analysis.

Conclusions

Among adults with relatively early type 2 diabetes and elevated cardiovascular risk, the use of linagliptin compared with glimepiride over a median of 6.3 years resulted in a noninferior risk of a composite cardiovascular outcome.

Supplement 1.

Clinical trial protocol

Supplement 2.

Statistical analysis plan

Supplement 3.

Supplement 4..

List of predefined endpoints beyond those listed in the trial statistical analysis plan

Supplement 5.

Data sharing statement