Page 1 of 47 Diabetesdiabetes.diabetesjournals.org/content/diabetes/early/...1 01/12/15 Risk factors for Cardiovascular Disease in Type 1 Diabetes The Diabetes Control and Complications

1

01/12/15

Risk factors for Cardiovascular Disease in Type 1 Diabetes

The Diabetes Control and Complications Trial (DCCT)-Epidemiology of Diabetes Interventions and

Complications (EDIC) Research Group*

*A complete list of participants in the DCCT-EDIC Research Group is presented in the

Supplementary Material published online for the article in N Engl J Med 2015;372:1722-33.

Running title: Risk Factors for CVD in T1D

Writing Group: David M. Nathan1, Ionut Bebu

2, Barbara H. Braffett

2, Trevor J. Orchard

3,

Catherine C. Cowie4, Maria Lopes-Virella

5, Mark Schutta

6, John M. Lachin

2

1. Massachusetts General Hospital, Harvard Medical School, Boston, MA

2. The Biostatistics Center, George Washington University, Rockville, MD

3. Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA

4. National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD

5. Medical University of South Carolina, Charleston, SC

6. Hospital of the University of Pennsylvania, Philadelphia, PA

Corresponding Author:

John M. Lachin, Sc.D.

The Biostatistics Center

The George Washington University

6110 Executive Blvd. Rockville, MD 20852

Telephone: (301) 881-9260

Fax: (301) 881-0179

Email: [email protected]

Clinical Trials Registration Numbers: NCT00360893, NCT00360815

Type: Original Article for Diabetes.

Abstract: 195 words (max 200)

Text: 3976 words (max 4000)

Tables & Figures: 5 (4 & 1) (max 8)

Supplements for Web-only Publication: Yes

References: 44 (max 50)

Page 1 of 47 Diabetes

Diabetes Publish Ahead of Print, published online February 19, 2016

2

ABSTRACT

Risk factors for CVD are well-established in type 2 but not type 1 diabetes (T1DM). We

assessed risk factors in the long-term (mean 27 years) follow-up of the Diabetes Control and

Complications Trial (DCCT) T1DM cohort. Cox proportional hazards multivariate models assessed

the association of traditional and novel risk factors, including HbA1c, with major atherosclerotic

cardiovascular events (MACE: fatal or non-fatal myocardial infarction or stroke) and any-CVD

(MACE plus confirmed angina, silent MI, revascularization or congestive heart failure). Age and

mean HbA1c were strongly associated with any-CVD and with MACE. For each percentage point

increase in mean HbA1c, the risk for any-CVD and for MACE increased by 31% and 42%,

respectively. CVD and MACE were associated with seven other conventional factors such as blood

pressure, lipids and lack of ACE-inhibitor use, but not with gender. The areas under the receiver

operating characteristics curves for the association of age and HbA1c taken together with any-CVD

and for MACE were 0.70 and 0.77, respectively, and for the final models, including all significant

risk factors, were 0.75 and 0.82. Although many conventional CVD risk factors apply in T1DM,

hyperglycemia is an important risk factor second only to age.

Page 2 of 47Diabetes

3

Type 1 diabetes (TIDM) confers a high risk for cardiovascular disease (CVD) compared with

the age-matched non-diabetic population (1-3) that historically has also accounted for the majority of

premature mortality in type 1 diabetes and is associated with the development of nephropathy (4-6).

The Diabetes Control and Complications Trial (DCCT) previously demonstrated that a mean

6.5 years of intensive diabetes therapy with a mean HbA1c of ~7% substantially reduced

microvascular complications, including nephropathy, compared with conventional therapy with

HbA1c of ~9% (7). After an additional 11 years of observational follow-up in the Epidemiology of

Diabetes Interventions and Complications (EDIC) study, the risk of major atherosclerotic

cardiovascular events (MACE: fatal or non-fatal myocardial infarction or stroke) was reduced by

58%, and aggregate CVD (MACE plus confirmed angina, silent MI, revascularization or congestive

heart failure) by 42%, in the original intensive versus conventional therapy group (8).

In 2013 EDIC reached a pre-specified landmark of 100 former DCCT conventionally treated

subjects with an adjudicated CVD event that provides adequate power to describe risk factor effects

reliably in multivariate Cox proportional hazard regression models. We now present analyses of

established and putative risk factors for CVD, including glycemic control, after a mean of 27 years

of follow-up of the DCCT/EDIC cohort.

RESEARCH DESIGN AND METHODS

The detailed DCCT/EDIC methods have been described (9, 10). In brief, the DCCT (1983-

1993) was a controlled clinical trial of 1441 patients with T1DM randomized to either conventional

diabetes therapy or intensive therapy to assess whether reducing hyperglycemia would decrease the

risk of complications of TIDM. Conventional therapy utilized one or two daily injections of insulin

aimed at preventing symptoms of hypo- or hyper-glycemia but with no glucose targets. Intensive

therapy used multiple (>3) daily injections or insulin pump therapy, guided by self-monitoring of


4

blood glucose, aimed at achieving glycemic control as close to the non-diabetic range as safely

possible.

Subjects

At DCCT baseline, the 13-39 year old study cohort included a primary prevention cohort

with 1-5 years diabetes duration, no retinopathy based on 7-field stereoscopic fundus photography

and <40 mg/24h of albuminuria. The secondary intervention cohort had 1-15 years duration,

minimal to moderate non-proliferative retinopathy and <200 mg/24h of albuminuria (9). Exclusion

criteria included neuropathy requiring therapy, hypertension (>140/90 mmHg or medication use) and

hyperlipidemia (a fasting serum cholesterol level ≥3 SD above age- and sex-specific means, or

medication use).

Risk Factors

Risk factors were assessed by standardized methods during DCCT/EDIC (9, 10). HbA1c

was measured by high performance liquid chromatography quarterly during DCCT and annually

during EDIC (11). Fasting lipoprotein levels and albuminuria were measured annually during

DCCT and on alternate years during EDIC. Serum creatinine was measured annually throughout.

The DCCT/EDIC central biochemistry laboratory performed all laboratory measurements with

standardized methods and long-term controls to guard against assay drift.

Candidate risk factors were grouped into the following 11 blocks (described in detail in

Supplementary Table 1): design (treatment group and cohort), physical (gender, age, weight, body

mass index), behavioral (smoking, alcohol intake, exercise), family history (of hypertension,

myocardial infarction (MI), and type 1 and type 2 diabetes), blood pressure/pulse (systolic and

diastolic blood pressure, pulse pressure, pulse rate), medication use (angiotensin converting enzyme

inhibitors, angiotensin receptor blockade, beta-adrenergic blockers, lipid-lowering agents, calcium


5

channel blockers), lipid levels (total cholesterol, triglycerides, LDL and HDL cholesterol levels),

diabetes specific (duration of diabetes, baseline stimulated C-peptide, daily insulin dose, estimated

glucose disposal rate (12)), microvascular complications (estimated GFR, albumin excretion rate,

presence of microalbuminuria, presence of macroalbuminuria), hypoglycemia events (episodes

requiring assistance, coma or seizure), and glycemia (HbA1c at eligibility and mean HbA1c during

DCCT/EDIC).

Some covariates were fixed (e.g. baseline) while others were time-dependent covariates

representing either the current (most recent) measurement, or the updated mean of all follow-up

values since randomization, or both. For covariates measured at different frequencies during DCCT

and EDIC (e.g. HbA1c), the updated time-weighted mean was computed weighting each value by

the interval between measurements.

Cardiovascular Outcomes

EDIC embargoed CVD risk factor analyses until 100 conventional group subjects had

experienced a CVD event. This led to data lock as of 12/31/13 for these analyses. CVD events were

ascertained based on the patient-reported updated annual CVD histories supported by medical

records, and annual centrally-graded electrocardiograms. Events were adjudicated and classified by a

committee masked to DCCT treatment assignment and HbA1c levels. (13)

The primary CVD outcome (“any-CVD”) was time to the first occurrence of cardiovascular

death, non-fatal myocardial infarction (MI), non-fatal stroke, subclinical myocardial infarction on

ECG, angina confirmed by ischemic changes with exercise tolerance testing or by clinically

significant obstruction on coronary angiography, revascularization (with angioplasty or coronary

artery bypass) or congestive heart failure (paroxysmal nocturnal dyspnea, orthopnea or marked

limitation of physical activity caused by heart disease). The secondary CVD outcome, major


6

atherosclerotic cardiovascular events (MACE), a subset of any-CVD, included only the time to

cardiovascular death, non-fatal MI or non-fatal stroke, whichever occurred first.

Statistical Analysis

Quartiles describe quantitative variables, and percentages describe discrete variables.

A Cox proportional hazards model with 100 conventional group CVD cases, or

approximately 150 cases in the combined cohort, provided 97% power to detect a 30% risk reduction

per SD change in a factor adjusted for 10 other covariates with an R2=0.35 with that factor, and

using a test at the 0.01 level (two-sided). (14).

The analysis was based on the time to the first component event for each outcome (any-CVD

or MACE). The Kaplan-Meier method estimated the probability of remaining CVD- or MACE-free

over time (i.e. the “survival” function). Semi-parametric Cox proportional hazards models assessed

the influence of fixed and time-dependent covariates on risk of CVD/MACE. (15) Smoothing splines

assessed the shape of the empirical log hazard functions of any-CVD and MACE over the range of

age and weighted-mean HbA1c. (16).

Given the large number of risk factors, variables were entered into the Cox proportional

hazards model one block at a time in the order displayed in Supplement Table A1, starting with

design factors, then demographic-physical, etc. Details of the variable selection/deletion process are

described in the Supplementary Material. Briefly, after adding each block, a variable is deleted if not

nominally significant, and yields a poor Akaike Information Criterion (17), and has a penalized

likelihood estimate of zero. (18) After the last block is entered, the final model is fit using the

selected covariates. Two additional sensitivity analyses started with the complete set of variables

followed by subset selection based either on the Akaike Information Criterion or the penalized


7

likelihood. Interaction terms investigated gender differences in the effect of covariates on risk of

CVD.

There is no standard measure of the proportion of variation explained by a factor in the Cox

PH model. However, in other models the measure of R2 is directly proportional to the test statistic

value or inversely proportional to the p-value. Accordingly, the Z-test value is used to measure the

relative strength of the predictive association with CVD risk.

The area under the receiver operating characteristics curve (AUC=sensitivity versus 1 –

specificity) describes the predictive accuracy of a model, with AUC=0.5 meaning chance

predictions, and AUC=1 providing 100% accurate predictions. To allow for time-dependent

covariates, a separate model was fit for each year of follow-up and the simple average of the separate

AUC estimates was obtained. The AUC value can be interpreted as the probability that a subject

who experienced an event has a higher risk score than a subject who is event-free.

RESULTS

As of 12/31/13, 85.8% of the original cohort (93.2% of the 1327 surviving participants) was

under active follow-up, with a median follow-up of 27 years. All total, 184 subjects had a CVD

event (any-CVD cases) and 88 had MACE, with 82 CVD and 39 MACE intensive group cases and

102 CVD and 49 MACE conventional group cases. Approximately 85% of the cohort remained free

of any-CVD after 27 years of follow-up, and over 90% were free of MACE (Figure 1).

Baseline Characteristics

Table 1 shows the baseline characteristics of the DCCT cohort as a whole, and among those

who did versus did not have any-CVD event, and the corresponding hazard ratio without adjustment

for other factors. Supplementary Table A2 shows the baseline characteristics for subjects with and

without a MACE event. At baseline, 53% of the participants were men, the median age was 27


8

years, duration of diabetes was 49 months, HbA1c was 8.8% (73 mmol/mol) and 19% were smokers.

Nominally significant baseline factors associated with a higher risk of any-CVD included the

secondary versus primary cohort, older age, greater weight and body mass index (BMI) in women

but not men, smoking, longer duration of diabetes, family history of MI and of type 2 diabetes,

higher blood pressure and pulse, and higher total cholesterol, triglyceride, LDL-cholesterol (LDLc)

and HbA1c levels. These risk factors were also associated with MACE, albeit with lower degrees of

significance, presumably owing to fewer events (See Supplemental Table A.2). Of note, the rate of

any-CVD and MACE were not statistically different between men and women, (p=0.98 and 0.23,

respectively, Table 1 and Supplemental Table A2).

Time-Dependent Characteristics

Table 2 presents the hazard ratios for any-CVD and MACE based on the current value or the

updated mean value of each time-dependent covariate, without adjustment for other factors; and

Supplemental Tables A3 present the values of each covariate among those still at risk of any-CVD at

10, 20 and 25 years. During the study, weight and BMI increased among men and women, smoking

decreased, alcohol consumption increased and exercise declined, and there were age-related

increases in blood pressure and lipids and use of respective medications, and increases in the

prevalence of microvascular complications (Table A3). All of these, except for weight, alcohol

consumption and exercise, were significantly associated with the risk of any-CVD, much more so

than the baseline value. Similar associations were observed for MACE (Supplement Table A4).

Individual Covariate Effects

Age and time-weighted mean HbA1c levels were the most significant univariate risk factors

for any-CVD, with respective Z-test values of 8.1 and 6.6 (p <1.0E-10) each adjusted for the other,

and also for MACE. Figures A.1 and A.2 of the Supplemental Appendix show that the spline-


9

smoothed model-free estimates of the log (hazard) function for any-CVD and for MACE were both

strongly linear functions of age and time-weighted mean HbA1c.

Table 3 presents the covariates that remained significantly associated with any-CVD and

MACE after adjustment for age and time-weighted mean HbA1c. A higher risk of any-CVD was

predicted by family history of MI, higher blood pressure and pulse variables, use of calcium channel

blockers (but not the other “cardioprotective” medications), higher cholesterol, triglycerides and

LDLc, and lower HDLc (which became significant after adjustment), diabetes-related history

variables (including higher mean insulin dose), higher albumin excretion rate and history of micro-

and macroalbuminuria, but not eGFR. While use of ACE inhibitors was not significant alone or

when adjusted for age and time-weighted HbA1c, it became significant when also adjusted for blood

pressure levels.

Similarly, a higher risk of MACE was predicted by the same set of factors with the

exceptions that higher insulin dose and microalbuminuria were not significant, but

macroalbuminuria (AER≥300 mg/24 h) was significant.

Final Multivariate Models

Table 4 shows the final multivariate Cox models for any-CVD and for MACE, with the

covariates listed in the order of the unsigned covariate Z-values (or p-values). Since any Z≥3.28 has

p<0.001, and Z-values as high as 7 are observed, the Z-value better represents the significance of the

covariate effect in the model than does the designation “p<0.001”. In the model for any-CVD (Table

4.A), older age (HR=1.54 per 5 years, CI 1.36, 1.73, Z=7.07, p<0.001) was the most significant risk

factor. A higher time-weighted mean HbA1c was the next most significant factor (HR=1.31 per 1%,

CI 1.15, 1.50, z=4.0, p<0.001). Other nominally significant variables were higher mean systolic

blood pressure (Z=3.1, p=0.002), higher current log(triglycerides) (Z=3.0, p=0.003), higher mean


10

pulse rate (Z=2.8, p=0.005), longer duration of diabetes (Z=2.5, p=0.02), absent use of ACE

inhibitor (Z=-2.3, p=0.03, ACEi use being protective), family history of MI (Z=2.15, p=0.04) and

higher updated mean LDLc (Z=2.07, p=0.04). Thus, age is by far the most significant factor

followed by HbA1c that is more significant than any other factor in the model, even after adjusting

for age and the other factors.

The final time-dependent Cox model was fit separately in men and women (Supplemental

Tables A5 and A6). Non-significant interaction terms between gender and each of the variables in

the multivariable model indicated that the coefficients for men and women were not significantly

different.

The multivariable Cox model for MACE (Table 4.B) was very similar to that for any-CVD

even though there were fewer cases of MACE. Again, age was by far the most significant factor

followed by time-weighted mean HbA1c and then other factors. The only differences between the

sets of variables in the MACE versus any-CVD models were that smoking replaced family history of

MI, while the current LDLc value replaced the updated mean LDLc. For each factor that appears in

both models in the same manner, the coefficient was somewhat higher in the MACE versus the any-

CVD model but the confidence limits were wider owing to the fewer MACE events.

These models for any-CVD and MACE were obtained from a joint forward addition and

backwards elimination of successive blocks of covariates (see methods). Two sensitivity analyses

were also conducted using different model selection methods (see methods). Both analyses selected

the same sets of covariates for any-CVD and MACE as presented in Table 4.

The AUC measure of predictive ability for each outcome (any-CVD and MACE) was

assessed for a Cox model with age as the only covariate, another with age and time-weighted mean


11

HbA1c, and the other using the full model. The respective AUC values were 0.67, 0.70, and 0.75 for

any-CVD and 0.71, 0.77, and 0.82 for MACE.

DISCUSSION

These results establish mean HbA1c over time as a strong risk factor for clinical CVD

(events) in T1DM, even when adjusted for age and other traditional risk factors. The causal effect of

hyperglycemia on risk of CVD in T1DM was first suggested a decade ago when the DCCT/EDIC

established the salutary effects of intensive therapy on CVD (8). Although an association of HbA1c

levels with CVD outcomes was demonstrated, the limited number of CVD events at that time

precluded a thorough investigation of risk factors as included herein. The long-term, standardized

measurement of numerous established and putative risk factors for CVD during DCCT/EDIC

provided the opportunity to examine not only cross-sectional, including baseline, risk factors, but the

effects of longitudinal exposure to changing (time-dependent) values of risk factors over time. Our

extensive collection of risk factors over many years in patients who began the study when they were

relatively young and without CVD, also enables an understanding of the temporal relationship

between risk factors and outcomes. This minimizes the potential for reverse-causality between CVD

and a risk factor.

After adjusting for the two most statistically significant risk factors, age and mean HbA1c,

essentially the same set of covariates, including higher mean systolic blood pressure, mean pulse

rate, current log(triglycerides), current or mean LDL-cholesterol and diabetes duration were

significantly associated with the risk of any-CVD or MACE (Table 4). Current use of an ACE

inhibitor was protective in both models. The only difference in risk factors between the two models

was that family history of MI appeared in the any-CVD model whereas smoking appeared in the

MACE model.


12

There are a number of possible explanations for our ability to demonstrate a strong

relationship between glycemia and CVD, when older observational cohort studies in T1DM were

unable to do so (1, 5). The more frequent and consistent measurement of glycemia over time with

standardized methods in DCCT/EDIC provided an accurate assessment of long-term glycemia. In

addition, the younger age and exclusion of high cardiovascular risk participants from entry into the

DCCT, and relatively infrequent history of smoking in our cohort, may have limited the influence of

traditional risk factors and allowed the effects of glycemia to be manifest. Finally, the relatively

lower average HbA1c levels achieved may have also contributed as recent data from the Swedish

Registry showed a stronger association with CVD events over a lower HbA1c range (19).

As for the other risk factors identified, systolic blood pressure or hypertension has

consistently been reported as a major risk factor for CVD. The importance of the blood pressure

finding is magnified by a recent temporal analysis that showed that hypertension remains the major

unaddressed risk factor for major diabetes complications (20).

The strong association of triglycerides with CVD is consistent with prior studies which show

that triglyceride concentration is a particularly strong CVD predictor in diabetes (21). Further, this

association was observed at very low mean values of triglycerides, even in those with subsequent

CVD, supporting a recent call for resetting “normal” values in T1DM (22). These findings suggest

that a trial to examine the effects of triglyceride lowering in T1DM should be performed and that the

current lack of ADA guidelines for treatment of triglycerides (23) should be reconsidered.

Likewise, the strong reduction in risk with ACE inhibition observed herein, when adjusted

for blood pressure, suggests that a trial of the effects of ACE inhibition in a comparable T1DM

population may be warranted. The strong effect of increased pulse rate is also noteworthy. This may

reflect autonomic neuropathy that has been shown to predict coronary heart disease (24).


13

The factors that do not emerge as predictors are also of interest. The similar rates of CVD in

men and women with T1DM have been seen in other studies (1, 5, 25, 26) and with even higher rates in

women than men with type 2 diabetes (27, 28). This finding contrasts with the higher risk of CVD

among men than women in the general population (29). As we have observed in DCCT/EDIC, loss of

the female protection in diabetes may be related to less aggressive care in women than in men resulting

in lower achievement of recommended risk factor levels (30, 31). Diabetes has also been hypothesized

to have a relatively larger deleterious effect on risk factor levels in women than men, including lipids

and blood pressure, markers of coagulation, and fibrinolysis (32, 33). One recent study in T1DM also

demonstrated that HDL-cholesterol lost its protective effect above 50mg/dl in women but not in men

(34).

Another risk factor established for CVD in type 2 diabetes (35) that did not emerge in our study

was obesity or BMI. BMI has not been a strong risk factor for CVD (1, 5) or mortality in other studies

in T1DM (36, 37). Weight gain was greater in the intensively treated participants during the DCCT (38)

and its potential adverse effect on CVD risk might have been mitigated by the other benefits of

intensive therapy, including lower mean HbA1c. The absence of a deleterious effect of increased BMI

is confirmed by a previous report that showed that weight gain in the presence of improved glycemic

control was not disadvantageous (39).

A major factor that did not emerge as a risk factor for CVD in the final model was renal

disease, measured as albuminuria (either AER 30-300 mg/24 h or ≥300 mg/24 h), which has been

thought for many years to be a major contributor to CVD (40). More recent studies have also

supported a relatively greater role for albuminuria than for reduced GFR in CVD (41). Several

factors may explain our inability to demonstrate an association between albuminuria and CVD. First,

since HbA1c levels are strongly associated with the development of albuminuria in our study (42),

adjusting for HbA1c may have reduced the putative adverse effects of albuminuria. Second, the


14

putative adverse effects of albuminuria may be confounded by the common use of ACE-inhibitors,

which reduce the risk of CVD in the setting of albuminuria. Finally, the null association in the final

model may be a function of inadequate power (with a limited number of cases of macroalbuminuria,

for example), or over-adjustment since blood pressure may be in the causal pathway between AER

and CVD.

Measurement error may have also contributed to failure to observe a significant association

with some factors, e.g. behavioral risk factors or those based on self-report (such as smoking,

exercise and alcohol use). Measurement errors would bias the estimates of associations towards the

null, thus reducing power to detect associations. Conversely, a risk factor measured with high

precision, such as HbA1c, will provide much greater power to detect a given association. Further,

when a precisely measured covariate and one measured with error represent the same causal pathway

to the outcome, that measured precisely will show a more significant effect. Accordingly, a study

similar to ours but with highly precise measures of other exposures, such as exercise, might provide

substantially different results than those presented herein. However, the results herein would be

expected to apply to other populations with a similar precision of measurement of such factors, as is

typically the case in observational follow-up.

The obvious strengths of these analyses include the careful and standardized assessments of

established and putative risk factors and cardiovascular outcomes prospectively over decades. In

addition, follow-up has been complete with 93% of the surviving cohort continuing to be followed

over an average of more than 27 years. Limitations include the exclusion of patients with

hypertension and dyslipidemia and some patients with albuminuria at baseline. However, owing to a

baseline mean age of 27 years and diabetes duration of only 6 years, it is unlikely that any more than


15

a small number of patients at higher risk may have been excluded because of these established and

putative CVD risk factors.

Regarding the modeling, data-dependent model selection has been shown to be susceptible to

various types of biases including bias in the set of covariates selected for inclusion, the coefficient

estimates and the levels of significance. However, we are confident that the resulting models are

reliable. The covariates selected for any-CVD and for MACE were highly internally consistent, each

model including the same five most significant covariates – age, HbA1c, systolic BP, triglycerides

and pulse rate, all at p < 0.01. Further, while the initial model building was based on a stepwise

process adding one block at a time, exactly the same final models were obtained in two sensitivity

analyses-- one using a penalized likelihood approach and the other was based on selection of an

optimal subset of covariates using the Akaike Information Criterion.

While these models could be employed as the basis for a “risk” or prediction score, we

hesitate to do so owing to the relatively small numbers of subjects with an outcome event (184 any-

CVD, 88 MACE) compared, for example, to the 1174 CVD cases used to develop, validate and

calibrate the Framingham Risk Score (43). However, it is encouraging that the AUC, a measure of

predictive ability, for the any-CVD model was 0.75 and that for MACE was 0.82.

It is clear that HbA1c is a robust and important risk factor in the DCCT/EDIC cohort over the

substantial but still limited period of study. However, the cohort is still young (mean age of 55 as of

2013), the proportion of survivors (1327 or 92%) is still quite high (44), and the cumulative

incidence of any-CVD is still only about 17% (Figure 1). Thus, the impact of hyperglycemia or other

risk factors may indeed be substantially different in future decades in which the overall incidence of

CVD will increase.


16

In conclusion, in the DCCT/EDIC T1DM cohort, increasing age is the most significant risk

factor for clinical CVD, as in the general population, followed by the updated weighted-mean

HbA1c. Other traditional risk factors also appear to be important as risk factors for CVD and for

MACE, particularly blood pressure and triglycerides. Thus, in T1DM, control of glycemia as well as

other CVD risk factors should be aggressively pursued in order to reduce major cardiovascular

events.


17

ACKNOWLEDGMENTS

A complete list of participants in the DCCT/EDIC Research Group is presented in the

Supplementary Material published online for the article in N Engl J Med 2015;372:1722-33.

Authors Contributions: DMN and JML wrote the initial draft of the manuscript. IB and BHB

conducted statistical analyses under the direction of JML. IB, BHB, TJO, CC, MLV, and MS

contributed revisions to the paper. All authors approve the final content.

Conflict of Interest Statement: None

Guarantor Statement: John M. Lachin is the guarantor of this work and, as such, had full access to

all the data in the study and takes responsibility for the integrity of the data and the accuracy of the

data analysis.

Funding/Support: The DCCT/EDIC has been supported by cooperative agreement grants (1982-

1993, 2012-2017), and contracts (1982-2012) with the Division of Diabetes Endocrinology and

Metabolic Diseases of the National Institute of Diabetes and Digestive and Kidney Disease (current

grant numbers U01 DK094176 and U01 DK094157), and through support by the National Eye

Institute, the National Institute of Neurologic Disorders and Stroke, the General Clinical Research

Centers Program (1993-2007), and Clinical Translational Science Center Program (2006-present),

Bethesda, Maryland, USA.

Industry Contributions: Industry contributors have had no role in the DCCT/EDIC study but have

provided free or discounted supplies or equipment to support participants’ adherence to the study:

Abbott Diabetes Care (Alameda, CA), Animas (Westchester, PA), Bayer Diabetes Care (North

America Headquarters, Tarrytown, NY), Becton Dickinson (Franklin Lakes, NJ), Eli Lilly

(Indianapolis, IN), Extend Nutrition (St. Louis, MO), Insulet Corporation (Bedford, MA) , Lifescan

(Milpitas, CA), Medtronic Diabetes (Minneapolis, MN), Nipro Home Diagnostics (Ft. Lauderdale,


18

FL), Nova Diabetes Care (Billerica, MA), Omron (Shelton, CT), Perrigo Diabetes Care (Allegan,

MI), Roche Diabetes Care (Indianapolis, IN) , and Sanofi-Aventis (Bridgewater, NJ).


19

REFERENCES

1. Orchard TJ, Costacou T, Kretowski A, Nesto RW. Type 1 diabetes and coronary artery disease.

Diabetes Care. 2006 Nov;29(11):2528-38.

2. Livingstone SJ, Looker HC, Hothersall EJ, Wild SH, Lindsay RS, Chalmers J, et al. Risk of

cardiovascular disease and total mortality in adults with type 1 diabetes: Scottish registry linkage

study. PLoS Med. 2012;9(10):e1001321.

3. Soedamah-Muthu SS, Fuller JH, Mulnier HE, Raleigh VS, Lawrenson RA, Colhoun HM. High

risk of cardiovascular disease in patients with type 1 diabetes in the U.K.: a cohort study using the

general practice research database. Diabetes Care. 2006 Apr;29(4):798-804.

4. Jensen T, Borch-Johnsen K, Kofoed-Enevoldsen A, Deckert T. Coronary heart disease in young

type 1 (insulin-dependent) diabetic patients with and without diabetic nephropathy: incidence and

risk factors. Diabetologia. 1987 Mar;30(3):144-8.

5. Orchard TJ, Olson JC, Erbey JR, Williams K, Forrest KY, Smithline Kinder L, et al. Insulin

resistance-related factors, but not glycemia, predict coronary artery disease in type 1 diabetes: 10-

year follow-up data from the Pittsburgh Epidemiology of Diabetes Complications Study. Diabetes

Care. 2003 May;26(5):1374-9.

6. Pambianco G, Costacou T, Ellis D, Becker DJ, Klein R, Orchard TJ. The 30-year natural history

of type 1 diabetes complications: the Pittsburgh Epidemiology of Diabetes Complications Study

experience. Diabetes. 2006 May;55(5):1463-9.

7. The DCCT Research Group. The effect of intensive treatment of diabetes on the development and

progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med. 1993

Sep 30;329(14):977-86.

8. Nathan DM, Cleary PA, Backlund JY, Genuth SM, Lachin JM, Orchard TJ, et al. Intensive

diabetes treatment and cardiovascular disease in patients with type 1 diabetes. N Engl J Med. 2005

Dec 22;353(25):2643-53.

9. The DCCT Research Group. The Diabetes Control and Complications Trial (DCCT). Design and

methodologic considerations for the feasibility phase. Diabetes. 1986 May;35(5):530-45.

10. The DCCT/EDIC Research Group. Epidemiology of Diabetes Interventions and Complications

(EDIC). Design, implementation, and preliminary results of a long-term follow-up of the Diabetes

Control and Complications Trial cohort. Diabetes Care. 1999 Jan;22(1):99-111.

11. Feasibility of centralized measurements of glycated hemoglobin in the Diabetes Control and

Complications Trial: a multicenter study. The DCCT Research Group. Clin Chem. 1987

Dec;33(12):2267-71.

12. Williams KV, Erbey JR, Becker D, Arslanian S, Orchard TJ. Can clinical factors estimate insulin

resistance in type 1 diabetes? Diabetes. 2000 Apr;49(4):626-32.


20

13. Lachin JM, Orchard TJ, Nathan DM, DCCT/EDIC Research Group. Update on cardiovascular

outcomes at 30 years of the Diabetes Control and Complications Trial/Epidemiology of Diabetes

Interventions and Complications study. Diabetes Care. 2014;37(1):39-43.

14. Hsieh FY, Lavori PW. Sample-size calculations for the Cox proportional hazards regression

model with nonbinary covariates. Control Clin Trials. 2000 Dec;21(6):552-60.

15. Lachin JM. Biostatistical Methods : The assessment of relative risks. 2nd ed. Hoboken, N.J.:

Wiley; 2011.

16. Therneau TM, Grambsch PM. Modeling survival data: extending the Cox model. New York ;

Berlin: Springer; 2000.

17. Claeskens G, Hjort NL. Model selection and model averaging. Cambridge ; New York:

Cambridge University Press; 2008.

18. Tibshirani R. The lasso method for variable selection in the Cox model. Stat Med. 1997 Feb

28;16(4):385-95.

19. Lind M, Bounias I, Olsson M, Gudbjornsdottir S, Svensson AM, Rosengren A. Glycaemic

control and incidence of heart failure in 20,985 patients with type 1 diabetes: an observational study.

Lancet. 2011 Jul 9;378(9786):140-6.

20. Miller RG, Secrest AM, Ellis D, Becker DJ, Orchard TJ. Changing impact of modifiable risk

factors on the incidence of major outcomes of type 1 diabetes: the Pittsburgh Epidemiology of

Diabetes Complications Study. Diabetes Care. 2013 Dec;36(12):3999-4006.

21. Jaiswal M, Schinske A, Pop-Busui R. Lipids and lipid management in diabetes. Best Pract Res

Clin Endocrinol Metab. 2014 Jun;28(3):325-38.

22. Tolonen N, Forsblom C, Makinen VP, Harjutsalo V, Gordin D, Feodoroff M, et al. Different

lipid variables predict incident coronary artery disease in patients with type 1 diabetes with or

without diabetic nephropathy: the FinnDiane study. Diabetes Care. 2014 Aug;37(8):2374-82.

23. American Diabetes Association. Standards of Medical Care in Diabetes-2015. Diabetes Care.

2015;38(1 Supp).

24. May O, Arildsen H, Damsgaard EM, Mickley H. Cardiovascular autonomic neuropathy in

insulin-dependent diabetes mellitus: prevalence and estimated risk of coronary heart disease in the

general population. J Intern Med. 2000 Dec;248(6):483-91.

25. Livingstone SJ, Looker HC, Hothersall EJ, Wild SH, Lindsay RS, Chalmers J, Cleland S, Leese

GP, McKnight J, Morris AD, Pearson DW, Peden NR, Petrie JR, Philip S, Sattar N, Sullivan F,

Colhoun HM. Risk of cardiovascular disease and total mortality in adults with type 1 diabetes:

Scottish registry linkage study. PLoS Med. 2012;9(10):e1001321.

26. Laing SP, Swerdlow AJ, Slater SD, Burden AC, Morris A, Waugh NR, Gatling W, Bingley PJ,


21

Patterson CC. Mortality from heart disease in a cohort of 23,000 patients with insulin-treated

diabetes. Diabetologia. 2003;46:760-5.

27. Peters SA, Huxley RR, Woodward M. Diabetes as a risk factor for stroke in women compared

with men: a systematic review and meta-analysis of 64 cohorts, including 775,385 individuals and

12,539 strokes. Lancet. 2014 Jun 7;383(9933):1973-80.

28. Peters SA, Huxley RR, Woodward M. Diabetes as risk factor for incident coronary heart disease

in women compared with men: a systematic review and meta-analysis of 64 cohorts including

858,507 individuals and 28,203 coronary events. Diabetologia. 2014 Aug;57(8):1542-51.

29. Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, Cushman M, et al. Heart disease

and stroke statistics--2015 update: a report from the American Heart Association. Circulation. 2015

Jan 27;131(4):e29-322.

30. Ferrara A, Mangione CM, Kim C, Marrero DG, Curb D, Stevens M, et al. Sex disparities in

control and treatment of modifiable cardiovascular disease risk factors among patients with diabetes:

Translating Research Into Action for Diabetes (TRIAD) Study. Diabetes Care. 2008 Jan;31(1):69-

74.

31. Larkin ME, Backlund JY, Cleary P, Bayless M, Schaefer B, Canady J, et al. Disparity in

management of diabetes and coronary heart disease risk factors by sex in DCCT/EDIC. Diabet Med.

2010 Apr;27(4):451-8.

32. Williams K, Tchernof A, Hunt KJ, Wagenknecht LE, Haffner SM, Sniderman AD. Diabetes,

abdominal adiposity, and atherogenic dyslipoproteinemia in women compared with men. Diabetes.

2008 Dec;57(12):3289-96.

33. Peters SA, Huxley RR, Sattar N, Woodward M. Sex Differences in the Excess Risk of

Cardiovascular Diseases Associated with Type 2 Diabetes: Potential Explanations and Clinical

Implications. Curr Cardiovasc Risk Rep. 2015;9(7):36.

34. Costacou T, Evans RW, Orchard TJ. High-density lipoprotein cholesterol in diabetes: is higher

always better? J Clin Lipidol. 2011 Sep-Oct;5(5):387-94.

35. Meigs JB, Wilson PW, Fox CS, Vasan RS, Nathan DM, Sullivan LM, et al. Body mass index,

metabolic syndrome, and risk of type 2 diabetes or cardiovascular disease. J Clin Endocrinol Metab.

2006 Aug;91(8):2906-12.

36. Conway B, Miller RG, Costacou T, Fried L, Kelsey S, Evans RW, et al. Adiposity and mortality

in type 1 diabetes. Int J Obes (Lond). 2009 Jul;33(7):796-805.

37. Soedamah-Muthu SS, Chaturvedi N, Witte DR, Stevens LK, Porta M, Fuller JH; EURODIAB

Prospective Complications Study Group. Relationship between risk factors and mortality in type 1

diabetic patients in Europe: the EURODIAB Prospective Complications Study (PCS). Diabetes

Care. 2008; 31:1360-6.


22

38. The DCCT Research Group. Adverse events and their association with treatment regimens in the

Diabetes Control and Complications Trial. Diabetes Care. 1995 Nov;18(11):1415-27.

39. Williams KV, Erbey JR, Becker D, Orchard TJ. Improved glycemic control reduces the impact

of weight gain on cardiovascular risk factors in type 1 diabetes. The Epidemiology of Diabetes

Complications Study. Diabetes Care. 1999 Jul;22(7):1084-91.

40. Pedersen MM, Christensen CK, Mogensen CE. Long-term (18 year) prognosis for normo- and

microalbuminuric type 1 (insulin-dependent) diabetic patients. Diabetologia. 1992;35(1 Supp):A60.

41. Matsushita K, Coresh J, Sang Y, Chalmers J, Fox C, Guallar E, et al. Estimated glomerular

filtration rate and albuminuria for prediction of cardiovascular outcomes: a collaborative meta-

analysis of individual participant data. Lancet Diabetes Endocrinol. 2015 Jul;3(7):514-25.

42. DCCT/EDIC research group. Effect of intensive diabetes treatment on albuminuria in type 1

diabetes: long-term follow-up of the Diabetes Control and Complications Trial and Epidemiology of

Diabetes Interventions and Complications study. Lancet Diabetes Endocrinol. 2014 Oct;2(10):793-

800.

43. D'Agostino RB S, Vasan RS, Pencina MJ, Wolf PA, Cobain M, Massaro JM, et al. General

cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation. 2008

Feb 12;117(6):743-53.

44. DCCT/EDIC research group. Intensive Diabetes Treatment and Cardiovascular Outcomes in

Type 1 Diabetes: The DCCT/EDIC Study 30 year Follow-up. Submitted for publication.


23

Table 1. Median and inter-quartile range or prevalence (%) for fixed baseline characteristics of DCCT/EDIC participants

according to the presence or absence of any-CVD over the course of the DCCT/EDIC study, and the corresponding hazard ratio

for any-CVD per unit change in the baseline covariate. An identical table for MACE is presented in the Supplemental Appendix.

Any-CVD

Overall No Yes HR 95% CI p-value

N 1441 1257 184

DESIGN

Treatment group (% conventional) 51 50 55 1.29 (0.964, 1.725) 0.0864

Cohort (% secondary) 50 48 62 1.592 (1.18, 2.147) 0.0023

DEMOGRAPHIC

Physical

Gender (% men) 53 53 52 1.004 (0.752, 1.341) 0.9786

Age (yr) 27 (22,32) 27 (21,32) 31 (27,35) 1.091 (1.066, 1.116) <0.0001

Adult vs. adolescent (< 18 years) 86 85 95 3.378 (1.727, 6.611) 0.0004

Weight Men (kg) 74 (67,82) 74 (67,82) 76 (70,84) 1.011 (0.993, 1.029) 0.2422

Weight Women (kg) 62 (56,69) 61 (55,68) 65 (57,70) 1.034 (1.011, 1.057) 0.0032

BMI Men (kg/m2) 24 (22,25) 23 (22,25) 24 (22,26) 1.065 (0.993, 1.142) 0.0764

BMI Women (kg/m2) 23 (21,25) 23 (21,25) 24 (22,26) 1.096 (1.022, 1.175) 0.0098

Behavioral

Smoking (%) 19 17 27 1.834 (1.325, 2.538) 0.0003

Alcohol (% occasional or regular) 22 22 20 0.888 (0.617, 1.279) 0.5246

Exercise (% moderate or strenuous) 70 70 71 1.067 (0.775, 1.468) 0.6901

Family History

Family history of HT (%) 56 56 59 1.123 (0.838, 1.506) 0.4377

Family history of MI (%) 49 47 60 1.615 (1.202, 2.169) 0.0015

Family history of T1D (%) 14 14 17 1.294 (0.884, 1.894) 0.1856



24

TRADITIONAL

Blood Pressure

Systolic (mm Hg) 114 (106,122) 114 (106,120) 116 (110,124) 1.016 (1.004, 1.029) 0.0117

Diastolic (mm Hg) 72 (68,80) 72 (68,80) 74 (68,80) 1.021 (1.004, 1.038) 0.0131

Pulse pressure (mm Hg) 40 (34,48) 40 (34,48) 42 (34,48) 1.006 (0.991, 1.02) 0.4554

Pulse rate (bpm) 76 (68,84) 76 (68,82) 78 (72,88) 1.019 (1.006, 1.031) 0.0029

Lipids

Total cholesterol (mg/dl) 174 (153,197) 172 (152,195) 185 (162,211) 1.012 (1.008, 1.016) <0.0001

Triglycerides (mg/dl) 73 (55,94) 72 (55,93) 80 (59,97) 1.614 (1.184, 2.199) 0.0024

HDLc (mg/dl) 49 (42,57) 50 (42,58) 47 (41,55) 0.992 (0.98, 1.004) 0.2001

LDLc (mg/dl) 107 (91,127) 105 (89,125) 119 (98,144) 1.014 (1.01, 1.019) <0.0001

DIABETES-RELATED

History

Duration of Diabetes (months) 49 (26,108) 47 (26,104) 69 (29,130) 1.004 (1.001, 1.007) 0.0032

C-peptide (nmol/L)*

Diabetes duration <5 years 0.13 (0.04,0.25) 0.12 (0.04,0.24)2) 0.13 (0.03,0.29) 1.5571 (0.325, 7.458) 0.5796

Duration ≥5 years 0.03 (0.03,0.04) 0.03 (0.03,0.04) 0.03 (0.03,0.03) 0.079 (0, 33.708) 0.4115

Microvascular

Log AER (mg/24 hr) 24 (20,29) 23 (20,28) 24 (20,30) 1.17 (0.978, 1.401) 0.0861

Glycemia

HbA1c [% (mmol/mol)] 8.8 (7.8,10.1)

73 (62,87)

8.8 (7.8,10.1)

73 (62,87)

9.0 (8.1,10.3)

75 (65,89) 1.093 (1.003,1.19) 0.0426 BMI=body mass index; HT=hypertension; MI=myocardial infarction; T1D=type 1 diabetes; T2D=type 2 diabetes; HDLc=high-density lipoprotein

cholesterol; LDLc=low-density lipoprotein cholesterol; AER=albumin excretion rate

Data are median (first quartile, third quartile) or %.

*C-peptide is presented separately within diabetes duration strata because the eligibility range differed among those ≤ 5 years duration (0 – 0.5 nmol/L)

and those > 5 years (0 – 0.2 nmol/L).


25

Table 2. Hazard ratio for any-CVD and for MACE per unit change in each time-dependent covariate with no other adjustments,

and an indication of the type of covariate used in the analysis.

Any-CVD MACE

Type* HR 95% CI p-value HR 95% CI p-value

DEMOGRAPHIC

Physical

Age (yr) C 1.091 (1.066, 1.116) <0.0001 1.112 (1.074, 1.151) <0.0001

Weight Men (kg) C 1 (0.987, 1.014) 0.954 0.984 (0.964, 1.004) 0.1092

Weight Women (kg) C 1.009 (0.995, 1.022) 0.1956 1.008 (0.988, 1.028) 0.4519

Mean BMI (kg/m2) M 1.04 (1, 1.081) 0.0486 1.009 (0.952, 1.069) 0.758

BMI Men (kg/m2) C 1.01 (0.967, 1.055) 0.6557 0.966 (0.903, 1.034) 0.3216

BMI Women (kg/m2) C 1.024 (0.985, 1.064) 0.2303 1.019 (0.962, 1.08) 0.5147

Behavioral

Smoking (yes vs. no) C 1.529 (1.076, 2.173) 0.0179 2.247 (1.411, 3.579) 0.0007

Alcohol (% occasional or regular vs. non-drinker) C 0.86 (0.727, 1.018) 0.0797 0.783 (0.608, 1.007) 0.0568

Exercise (% moderate or strenuous vs. sedentary) C 0.914 (0.707, 1.181) 0.4898 0.979 (0.676, 1.416) 0.909

TRADITIONAL

Blood Pressure C

Systolic (mm Hg) C 1.027 (1.018, 1.037) <0.0001 1.034 (1.022, 1.046) <0.0001

Mean Systolic (mm Hg) M 1.061 (1.043, 1.078) <0.0001 1.071 (1.046, 1.096) <0.0001

Diastolic (mm Hg) C 1.009 (0.993, 1.025) 0.2721 1.01 (0.987, 1.034) 0.3842

Mean Diastolic (mm Hg) M 1.055 (1.028, 1.083) 0.0001 1.044 (1.005, 1.085) 0.027

Pulse pressure (mm Hg) C 1.036 (1.025, 1.047) <0.0001 1.045 (1.03, 1.059) <0.0001

Hypertension (yes vs. no) C 2.01 (1.448, 2.79) <0.0001 2.198 (1.348, 3.586) 0.0016

Any Hypertension (yes vs. no) A 2.308 (1.583, 3.365) <0.0001 2.291 (1.303, 4.027) 0.004

Pulse rate (bpm) C 1.021 (1.008, 1.034) 0.0012 1.029 (1.011, 1.048) 0.0016


26

Mean Pulse rate (bpm) M 1.057 (1.036, 1.078) <0.0001 1.074 (1.044, 1.106) <0.0001

Medications

ACE (yes vs. no) C 1.092 (0.782, 1.523) 0.6062 0.945 (0.583, 1.533) 0.8191

ARB (yes vs. no) C 1.421 (0.878, 2.3) 0.1523 1.024 (0.486, 2.158) 0.9495

Beta Blockers (yes vs. no) C 1.827 (1.002, 3.333) 0.0493 2.796 (1.441, 5.424) 0.0024

Calcium Channel Blockers (yes vs. no) C 2.84 (1.801, 4.478) <0.0001 2.385 (1.216, 4.68) 0.0115

Lipid Lowering (yes vs. no) C 1.401 (0.991, 1.98) 0.056 1.141 (0.696, 1.872) 0.6006

Lipids

Total cholesterol (mg/dl) C 1.01 (1.007, 1.014) <0.0001 1.011 (1.007, 1.016) <0.0001

Mean Total cholesterol (mg/dl) M 1.018 (1.013, 1.023) <0.0001 1.018 (1.011, 1.025) <0.0001

Triglycerides (mg/dl) C 2.133 (1.674, 2.719) <0.0001 2.522 (1.807, 3.518) <0.0001

Mean Triglycerides (mg/dl) M 2.458 (1.786, 3.382) <0.0001 2.923 (1.87, 4.568) <0.0001

HDLc (mg/dl) C 0.995 (0.986, 1.005) 0.3191 0.984 (0.97, 0.999) 0.0323

Mean HDLc (mg/dl) M 0.989 (0.977, 1.001) 0.0847 0.983 (0.965, 1.002) 0.0754

LDLc (mg/dl) C 1.011 (1.006, 1.015) <0.0001 1.014 (1.008, 1.019) <0.0001

Mean LDLc (mg/dl) M 1.019 (1.014, 1.025) <0.0001 1.02 (1.012, 1.029) <0.0001

Hyperlipidemia (yes vs. no) C 1.767 (1.3, 2.401) 0.0003 1.647 (1.055, 2.571) 0.0282

DIABETES-RELATED

History

Insulin Dose (units/kg/day) C 1.595 (1.095, 2.325) 0.0151 1.363 (0.694, 2.678) 0.3691

Mean Insulin Dose (units/kg/day) M 1.674 (0.797, 3.516) 0.174 1.296 (0.433, 3.874) 0.6431

Estimated Glucose Disposal Rate C 0.819 (0.761, 0.882) <0.0001 0.763 (0.683, 0.853) <0.0001

Microvascular

Estimated GFR (mL/min per 1.73 m2) C 0.985 (0.978, 0.991) <0.0001 0.978 (0.971, 0.986) <0.0001

eGFR <60 (yes vs. no) C 2.479 (1.332, 4.613) 0.0042 4.356 (2.21, 8.586) <0.0001

Any eGFR <60 (yes vs. no) A 2.529 (1.472, 4.346) 0.0008 3.949 (2.099, 7.429) <0.0001

Log AER (mg/24 hr) C 1.229 (1.133, 1.334) <0.0001 1.283 (1.151, 1.431) <0.0001


27

Sustained AER ≥30 mg/dl (yes vs. no) C 1.8 (1.278, 2.535) 0.0008 1.916 (1.18, 3.109) 0.0085

AER ≥40 mg/dl (yes vs. no) C 1.891 (1.346, 2.656) 0.0002 2.171 (1.355, 3.478) 0.0013

AER ≥300 mg/dl (yes vs. no) C 2.312 (1.434, 3.728) 0.0006 3.028 (1.64, 5.593) 0.0004

Any AER ≥40 mg/dl (yes vs. no) A 1.768 (1.316, 2.374) 0.0002 1.729 (1.127, 2.654) 0.0122

Any AER ≥300 mg/dl (yes vs. no) A 1.958 (1.287, 2.978) 0.0017 3.072 (1.834, 5.148) <0.0001

Hypoglycemia

Coma/Seizure (yes vs. no) C 0.972 (0.812, 1.163) 0.7542 1.021 (0.835, 1.248) 0.8379

Requiring Assistance (yes vs. no) C 1.002 (0.93, 1.079) 0.9626 1.005 (0.905, 1.114) 0.9319

Glycemia

HbA1c (%) C 1.241 (1.129, 1.364) <0.0001 1.297 (1.139, 1.478) 0.0001

Mean HbA1c (%) M 1.382 (1.231, 1.551) <0.0001 1.539 (1.309, 1.808) <0.0001 BMI=body mass index; ACE=angiotensin converting enzyme inhibitors; ARB=angiotensin receptor blockers; HDLc=high-density lipoprotein

cholesterol; LDLc=low-density lipoprotein cholesterol; GFR=glomerular filtration rate; AER=albumin excretion rate

*C=Current (or most recent) value, M=Updated mean value, A=Cumulative Incidence (such as Any Use). Categories C, M, and A correspond to time-

dependent covariates assessed or measured at or most recently prior to each event time or right censoring time, i.e. at the most recent visit up to the

particular time-point.


28

Table 3. Hazard ratios for any-CVD and for MACE per unit change in each baseline or time-dependent covariate that was

nominally significant at p≤0.01 in separate Cox Models, minimally adjusted for age and updated mean HbA1c.

Type* Any-CVD MACE

Hazard Ratio

(95% CI)

p-value Hazard Ratio

(95% CI)

p-value

DESIGN

Secondary cohort (yes vs. no)

B 1.57 (1.17, 2.13) 0.003

DEMOGRAPHIC

Behavioral

Smoking status (yes vs. no) C 1.89 (1.18, 3.04) 0.009

Family History

History of MI (yes vs. no) B 1.53 (1.14, 2.06) 0.005

TRADITIONAL

Blood Pressure

Systolic (mm Hg) C 1.02 (1.01, 1.03) <0.001 1.02 (1.01, 1.03) <0.001

Mean systolic (mm Hg) M 1.04 (1.02, 1.06) <0.001 1.04 (1.02, 1.07) <0.0014

Mean diastolic (mm Hg) M 1.04 (1.01, 1.07) 0.004

Pulse pressure C 1.02 (1.01, 1.03) <0.001 1.03 (1.01, 1.04) 0.001

Mean Pulse rate (bpm) M 1.05 (1.03, 1.07) <0.001 1.07 (1.03, 1.10) <0.001

Medications

Calcium channel blockers (yes vs. no) C 2.02 (1.28, 3.20) 0.003

Lipids

Total cholesterol (mg/dl) C 1.008 (1.004, 1.012) <0.001 1.009 (1.004, 1.0139) <0.001

Triglycerides (log) C 1.98 (1.53, 2.56) <0.001 2.37 (1.65, 3.40) <0.001

LDL cholesterol (mg/dl) C 1.008 (1.004, 1.013) <0.001 1.011 (1.005, 1.017) <0.001

HDL cholesterol (mg/dl) C 0.98 (0.966, 0.995) 0.007


29

MI=myocardial infarction; LDL=low-density lipoprotein; HDLc=high-density lipoprotein cholesterol; AER=albumin excretion rate

*B=Baseline Value, C=Current (or most recent) value, M=Updated mean value, A=Cumulative Incidence (such as Any Use). Categories C, M, and A

correspond to time-dependent covariates assessed or measured at or most recently prior to each event time or right censoring time, i.e. at the most

recent visit up to the particular time-point.

Mean total cholesterol (mg/dl) M 1.012 (1.006, 1.017) <0.001 1.010 (1.002, 1.018) 0.013

Mean triglycerides (log) M 2.23 (1.60, 3.12) <0.001 2.56 (1.60, 4.11) <0.001

Mean LDL cholesterol (mg/dl) M 1.013 (1.007, 1.020) <0.001 1.013 (1.004, 1.022) 0.007

Mean HDL cholesterol (mg/dl) M 0.984 (0.971, 0.996) 0.010 0.976 (0.958, 0.994) 0.010

DIABETES-RELATED

History

Duration (months) B 1.005 (1.002, 1.008) <0.001 1.006 (1.002, 1.01) 0.006

Mean insulin dose (units/kg/day) M 3.72 (1.70, 8.14) 0.001

Microvascular

AER (log) (mg/24 hr) C 1.17 (1.06, 1.28) 0.001 1.21 (1.06, 1.37) 0.004

Any AER ≥40 (yes vs. no) A 1.66 (1.21, 2.26) 0.002

Any AER ≥300 (yes vs. no) A 2.41 (1.39, 4.18) 0.002


30

Table 4. The final multivariable Cox models for any-CVD and for MACE as a function of fixed

(baseline) and time-dependent covariates, the latter either the current value or mean from

baseline as stated. Covariates listed in the order of significance as indicated by the unsigned Z-

value.

Any-CVD Model

Covariate Hazard Ratio (95% CI)* Z-test value p-value

Baseline Age (per 5 yrs) 1.5366 (1.3641, 1.731) 7.0711 <0.001

Mean HbA1c (per 1%) 1.3115 (1.1488, 1.4972) 4.0133 <0.001

Mean systolic BP (per 10 mm Hg) 1.3186 (1.1096, 1.567) 3.1419 0.002

Current Triglycerides (log) 1.5536 (1.1688, 2.065) 3.0346 0.003

Mean Pulse rate (per 10 bpm) 1.3855 (1.1051, 1.737) 2.8267 0.005

Baseline Duration of Diabetes (per 5yrs) 1.247 (1.0514, 1.4789) 2.5364 0.02

Current use of ACE Inhibitor (yes vs. no) 0.6732 (0.4777, 0.9486) -2.2611 0.03

Baseline family history of MI (yes vs. no) 1.3866 (1.0294, 1.8678) 2.1507 0.04

Mean LDLc (per 10 mg/dl) 1.0721 (1.0037, 1.1451) 2.0697 0.04

MACE Model

Covariate Hazard Ratio (95% CI) Z-test value p-value

Baseline Age (per 5 yrs) 1.7748 (1.4872, 2.1179) 6.3613 <0.001

Mean HbA1c (per 1%) 1.4186 (1.1785, 1.7077) 3.6965 <0.001

Mean Pulse rate (per 10 bpm) 1.5975 (1.1576, 2.2046) 2.8509 0.005

Current Triglycerides (log) 1.7844 (1.1909, 2.6737) 2.8071 0.005

Mean systolic BP (per 10 mm Hg) 1.3863 (1.0929, 1.7583) 2.6931 0.007

Current smoking (yes vs. no) 1.8686 (1.1647, 2.9978) 2.5924 0.01

Baseline Duration of Diabetes (per 5 yrs) 1.3334 (1.0399, 1.7098) 2.2685 0.03

Current use of ACE Inhibitor (yes vs. no) 0.5819 (0.3553, 0.9529) -2.1515 0.04

Current LDLc (per 10 mg/dl) 1.0692 (1.0035, 1.1392) 2.0685 0.04

BP=blood pressure; ACE=angiotensin converting enzyme inhibitors; MI=myocardial infarction; LDL=low-

density lipoprotein; bpm=beats per minute

*The hazard ratio (HR) in the Cox proportional hazards model can be converted from HR per x-units (e.g. per 5

years of age above) to HR per y-units (e.g. per 1 year), using the equation: HR(y/x)

. For example, the hazard

ratio for MACE per 1 year of Age is (1.7748)1/5

=1.1216. The same equation applies to the confidence limits.

The Z-test and p-values are unchanged by a change of scale of the HRs.


31

FIGURE LEGENDS

Figure 1. Kaplan-Meier survival (event-free) curves (solid lines), and 95% confidence intervals

(dashed lines) for MACE (top) and CVD (bottom), with number of subjects at risk for each at 10, 20

and 30 years of follow-up. The number at risk beyond 23 years declines as a function of staggered entry

into the study over 1983-89.


0 5 10 15 20 25 30

0.70

0.75

0.80

0.85

0.90

0.95

1.00

Years since Entry

Eve

nt−

Fre

e (S

urvi

val)

Pro

babi

lity

Any−CVD

MACE

Number at risk

1441 1391 1292 1058 40

1441 1380 1235 988 37


1

Online Appendix

Risk Factors for Cardiovascular Disease in Type 1 Diabetes

The Diabetes Control and Complications Trial (DCCT)-Epidemiology of Diabetes Interventions and

Complications (EDIC) Research Group*

This Appendix presents supplemental materials cited in the text of the main manuscript.

Model Selection

The final models for Any-CVD and MACE presented in Table 4 of the main manuscript were

obtained in a forward fashion by sequentially considering the blocks of variables described in

Supplementary Table A1 herein. The models were also confirmed in two sensitivity analyses that

started with all variables from all blocks.

Three statistical methods were employed for variable selection/deletion. One approach simply

fit a Cox PH model and deleted factors that were not statistically significant. Another approach

conducted a search for the best subset model based on the minimum (best) Akaike Information

Criterion (AIC) (17). A third identified covariate deletions by fitting a model with a penalized

likelihood “lasso” (least absolute shrinkage and selection operator) method (18). The lasso shrinks the

regression coefficients toward zero, and sets those deemed unimportant to zero (penalized). A model

can then be fit with the remaining selected variables.

For the final models, the forward variable selection approach started with the variables in the

Design block in Table A1, namely cohort and treatment group, and the three approaches were applied.

First, a Cox model that included both variables was fit, and a variable was selected for inclusion if its p-

value was below a certain cut-off value (0.10 was used herein). Second, a penalized likelihood model

was fit using both variables, and those with non-zero coefficients were retained. Third, a search

identified the sub-model with the lowest AIC value, and the variables included in that model were

retained. A risk factor was retained if it met at least one of the three criteria. From the Design block,

both cohort and treatment group were selected (e.g., they both had p-values less than 0.10).

At the next step, the variables in the next block, in this case the Demographic-Physical block

(such as gender, age, weight and BMI), were added to the previously selected variables (i.e., cohort and

treatment group). The three variable selection criteria were applied to this set of variables, all of them,

not just those added; and again, variables that met at least one criterion were selected, and the others

were dropped. This could include deletion of variables entered in preceding blocks.

The procedure continued in a similar fashion by adding each block to the already selected risk

factors, and variables selected by at least one criterion were kept in the model, while the others were

dropped. After the final block (Glycemia) was considered, the remaining set of variables that were


2

considered of interest were employed in a Cox model, and variables that did not reach statistical

significance at level 0.05 were then dropped to yield the final model.

Two sensitivity analyses were conducted to confirm the final model, and they both started with

all variables in all blocks. The first approach was to fit a penalized Cox model to identify variables to

be deleted (those with a zero coefficient), followed by a Cox model using only the variables that were

retained (had non-zero coefficients). The second method identified the sub-model with the lowest AIC,

and then fit a Cox model using only the variables selected by the AIC criterion. Both approaches led to

the same set of significant variables as obtained using the forward selection procedure shown in Table

4.


3

Table A1. CVD risk factors (by block) employed in the analyses with a description of availability.

Block Variable Availability*

DESIGN

Cohort B

Treatment Group B

DEMOGRAPHIC

Physical Gender (male versus female) B

Age (yr) B

Adult B

Weight (kg) B, C†, M

†

Weight Gain (kg) C†

Body mass index (kg/m2) B, C

†, M

†

Behavioral Current cigarette smoker B, C†

Occasional or regular drinker B, C†

Moderate or strenuous activity B, C†

Family History Family history

Hypertension B

Myocardial infarction B

Type 1 Diabetes B

Type 2 Diabetes B

TRADTIONAL

Blood pressure Systolic (mm Hg) B, C†, M

†

Diastolic (mm Hg) B, C†, M

†

Pulse pressure (mm Hg) B, C†

Pulse rate (bpm) B, C†, M

†

Hypertension (>140/90 or medication) B, C†, A

†

Medications ACE C‡

ARB C‡

Beta Blockers C‡

Calcium Channel Blockers C‡

Lipid Lowering C‡

Lipids Total cholesterol (mg/dl) B, C§, M

§

Triglycerides (mg/dl) B, C§, M

§

HDL cholesterol (mg/dl) B, C§, M

§

LDL cholesterol (mg/dl) B, C§, M

§

Hyperlipidemia (LDL > 130 or medication) B, C§

DIABETES-RELATED

History Duration of diabetes (yr) B

Stimulated C-peptide (nmol/L) B

Duration <60 months

Duration ≥60 months

Insulin dose (units/kg/day) B, C†, M

†

eGlucose Disposal Rate C‡

Microvascular Nephropathy B

eGFR (mL/min per 1.73 m2) B, C

†


4

eGFR<60 C†, A

†

AER (mg/24 hr)

AER ≥40, AER≥300, Sustained

AER≥30mg/24 hr

B, C§,

A§

Hypoglycemia Coma and/or seizure B, C†

Requiring assistance B, C†

Glycemia HbA1c (%) B, C†, M

†

*A=Cumulative Incidence (such as Any Use), B=Baseline Value, C=Current Value, M=Updated Mean

Value. Categories C, M and A enter the analyses as time dependent covariates. †Collected annually during DCCT and EDIC

‡Collected annually in EDIC, not collected in DCCT

§Collected annually in DCCT, every two years in EDIC


5

Table A.2. Median and inter-quartile range or prevalence (%) for fixed baseline characteristics of DCCT/EDIC participants

according to the presence or absence of MACE over the course of the DCCT/EDIC study, and the corresponding hazard ratio of

any CVD per unit change in the baseline covariate.

MACE

Overall No Yes HR 95% CI p-value

DESIGN

Treatment group (% conventional) 51 50 56 1.302 (0.855, 1.984) 0.2184

Cohort (% secondary) 50 49 64 1.603 (1.036, 2.479) 0.0341

DEMOGRAPHIC

Physical

Gender (% men) 53 52 58 1.293 (0.847, 1.975) 0.234

Age (yr) 27 (22,32) 27 (22,32) 32 (28,36) 1.112 (1.074, 1.151) 0

Adult vs. adolescent (< 18 years) 86 86 97 5.044 (1.591, 15.992) 0.006

Weight Men (kg) 74 (67,82) 74 (67,82) 76 (69,82) 1.001 (0.976, 1.026) 0.9579

Weight Women (kg) 62 (56,69) 61 (56,68) 64 (58,70) 1.04 (1.005, 1.076) 0.0244

BMI Men (kg/m2) 24 (22,25) 24 (22,25) 24 (22,25) 1.034 (0.938, 1.14) 0.4975

BMI Women (kg/m2) 23 (21,25) 23 (21,25) 24 (22,26) 1.108 (0.996, 1.232) 0.0586

Behavioral

Smoking (%) 19 17 38 2.927 (1.901, 4.508) 0

Alcohol (% occasional or regular) 22 22 16 0.692 (0.391, 1.226) 0.2073

Exercise (% moderate or strenuous) 70 70 75 1.259 (0.777, 2.041) 0.3495

Family History

Family history of HT (%) 56 56 53 0.9 (0.592, 1.368) 0.6218

Family history of MI (%) 49 48 55 1.251 (0.822, 1.903) 0.2964



TRADITIONAL

Blood Pressure

Systolic (mm Hg) 114 (106,122) 114 (106,122) 113 (108,126) 1.013 (0.995, 1.031) 0.1618

Diastolic (mm Hg) 72 (68,80) 72 (68,80) 76 (68,80) 1.021 (0.997, 1.046) 0.0854


6

Pulse pressure (mm Hg) 40 (34,48) 40 (35,48) 40 (34,48) 1.001 (0.98, 1.023) 0.9303

Pulse rate (bpm) 76 (68,84) 76 (68,82) 80 (74,88) 1.025 (1.008, 1.043) 0.0042

Lipids

Total cholesterol (mg/dl) 174 (153,197) 173 (152,196) 184 (160,207) 1.011 (1.005, 1.017) 3.00E-04

Triglycerides (mg/dl) 73 (55,94) 72 (55,93) 84 (59,105) 1.981 (1.291, 3.04) 0.0017

HDLc (mg/dl) 49 (42,57) 50 (42,57) 45 (41,58) 0.988 (0.97, 1.006) 0.1864

LDLc (mg/dl) 107 (91,127) 106 (90,126) 119 (98,137) 1.013 (1.006, 1.02) 2.00E-04

DIABETES-RELATED

History

Duration of Diabetes (months) 49 (26,108) 48 (26,106) 70 (30,134) 1.005 (1.001, 1.009) 0.0238

C-peptide (nmol/L)*

Diabetes duration <5 years 0.13 (0.04,0.25) 0.13 (0.04,0.25) 0.12 (0.03,0.24) 0.441 (0.039, 5.025) 0.5097

Duration ≥5 years 0.03 (0.03,0.04) 0.03 (0.03,0.04) 0.03 (0.03,0.03) <0.001 (0, 7.958) 0.1094

Microvascular

Log AER (mg/24 hr) 2.4 (2,2.9) 2.4 (2,2.9) 2.6 (1.8,2.9) 1.087 (0.837, 1.411) 0.5328

Glycemia

HbA1c [% (mmol/mol)] 8.8 (7.8,10.1)

73 (62,87)

8.8 (7.8,10.1)

73 (62,87)

9.3 (8.1,10.7)

78 (65,93) 1.168 (1.037, 1.316) 0.0106 ACE=angiotensin converting enzyme inhibitors; ARB=angiotensin receptor blockers; BMI=body mass index; HT=hypertension; MI=myocardial

infarction; T1D=type 1 diabetes; T2D=type 2 diabetes; HDLc=high-density lipoprotein cholesterol; LDLc=low-density lipoprotein cholesterol;

AER=albumin excretion rate

Data are median (first quartile, third quartile) or %.

*C-peptide is presented separately within diabetes duration strata because the eligibility range differed among those ≤ 5 years duration (0 – 0.5 nmol/L)

and those > 5 years (0 – 0.2 nmol/L).


7

Table A.3. Median and inter-quartile range or prevalence (%) for time-dependent characteristics of DCCT/EDIC participants at

DCCT baseline and at 10, 20 and 25 years of follow-up for those at risk of any cardiovascular disease over the course of the

DCCT/EDIC study. The covariate type is also indicated, M = the updated mean value over follow-up, C = the current or most

recent covariate value.

Type Baseline Year 10 Year 20 Year 25

N 1441 1380 1235 988

DEMOGRAPHIC

Physical

Age (yr) C 27 (22,32) 36 (31,42) 46 (41,51) 51 (45,56)

Weight Men (kg) C 74 (67,82) 83 (76,92) 90 (80,100) 90 (80,101)

Weight Women (kg) C 62 (56,69) 69 (62,78) 73 (65,84) 73 (65,84)

Mean BMI(kg/m2) M 23 (21,25) 25 (23,27) 26 (24,28) 26 (24,29)

BMI Men (kg/m2) C 24 (22,25) 26 (24,29) 28 (25,31) 28 (25,31)

BMI Women (kg/m2) C 23 (21,25) 25 (23,28) 27 (24,31) 27 (24,31)

Behavior

Smoking (%) C 19 19 14 13

Alcohol (% occasional or regular) C 22 41 46 45

Exercise (% moderate or strenuous) C 70 55 55 56

TRADITIONAL

Blood Pressure C

Systolic (mm Hg) C 114 (106,122) 118 (110,126) 120 (111,129) 120 (110,130)

Mean Systolic (mm Hg) M 114 (106,122) 115 (110,121) 118 (112,124) 118 (112,124)

Diastolic (mm Hg) C 72 (68,80) 76 (70,82) 74 (68,80) 71 (65,78)

Mean Diastolic (mm Hg) M 72 (68,80) 74 (71,78) 75 (71,78) 74 (71,77)

Pulse C

Pulse pressure (mm Hg) C 40 (34,48) 42 (36,50) 46 (39,53) 48 (41,56)


8

Pulse rate (bpm) C 76 (68,84) 72 (68,80) 72 (64,80) 70 (63,78)

Mean Pulse rate (bpm) M 76 (68,84) 74 (69,78) 73 (69,77) 73 (69,77)

Hypertension (%) A 3 19 56 64

Hypertension Cumulative (%) C 0 23 70 79

Medications

ACE (%) C 0 7 39 43

ARB (%) C 0 0 12 16

Beta Blockers (%) C 0 1 4 9

Calcium Channel Blockers (%) C 0 1 5 8

Lipid Lowering (%) C 0 3 43 59

Lipids

Total cholesterol (mg/dl) C 174 (153,197) 184 (161,207) 177 (155,200) 172 (149,195)

Mean Total cholesterol (mg/dl) M 174 (153,197) 181 (163,202) 183 (165,199) 181 (165,196)

Triglycerides (mg/dl) C 70 (55,94) 73 (54,104) 71 (51,104) 65 (50,91)

Mean Triglycerides (mg/dl) M 70 (52,93) 73 (59,97) 74 (59,99) 74 (59,97)

HDLc (mg/dl) C 49 (42,57) 52 (44,62) 53 (45,65) 59 (49,72)

Mean HDLc (mg/dl) M 49 (42,57) 50 (44,59) 53 (45,61) 53 (46,63)

LDLc (mg/dl) C 107 (91,127) 113 (93,135) 103 (86,123) 94 (77,111)

Mean LDLc (mg/dl) M 107 (91,127) 112 (96,131) 112 (97,127) 108 (95,121)

Hyperlipidemia (%) C 23 30 55 65

DIABETES-RELATED

History

Insulin Dose (units/kg/day) C 0.64 (05,0.8) 0.63 (0.51,0.76) 0.54 (0.36,0.69) 0.51 (0.33,0.69)

Mean Insulin Dose (units/kg/day) M 0.64 (0.5,0.8) 0.65 (0.55,0.79) 0.61 (0.5,0.72) 0.59 (0.49,0.71)

Estimated Glucose Disposal Rate C NA (NA,NA) 9 (7,10) 7 (5,9) 6 (5,8)

Microvascular

Estimated GFR (mL/min per 1.73 m2) C 125 (118,134) 113 (105,120) 101 (90,110) 96 (86,105)


9

eGFR<60 (%) C 0 0 3 5

Any eGFR<60 (%) A 0 0 4 7

Log AER (mg/24 hr) C 2.4 (2,3.9) 2.3 (1.8,3) 2.4 (2,3.1) 2.4 (2,3.1)

Sustained AER ≥30 (%) C 5 13 16 15

AER≥40 (%) C 5 13 16 16

AER≥300 (%) C 0 3 6 6

Any AER≥40 (%) A 5 28 38 44

Any AER≥300 (%) A 0 4 9 10

Hypoglycemia

Coma/Seizure (%) C 0 9 19 14

Requiring Assistance (%) C 0 34 46 43

Glycemia

HbA1c [% (mmol/mol)] C

8.8 (7.8,10.1)

73 (62,87)

8.1 (7.3,9.1)

65 (56,76)

7.7 (7.0,8.6)

61 (53,70)

7.8 (7.1,8.5)

62 (54,69)

Mean HbA1c [% (mmol/mol)] M

8.8 (7.8,10.1)

73 (62,87)

8.0 (7.2,9.0)

64 (54,75)

7.9 (7.3,8.6)

63 (56,70)

7.9 (7.3,8.5)

63 (56,69) BMI=body mass index; ACE=angiotensin converting enzyme inhibitors; ARB=angiotensin receptor blockers; HDLc=high-density lipoprotein


*C=Current (or most recent) value, M=Updated mean value, A=Cumulative Incidence (such as Any Use). Categories C, M, and A correspond to

time-dependent covariates assessed or measured at or most recently prior to each event time or right censoring time, i.e. at the most recent visit up

to the particular time-point.

Data are median (first quartile, third quartile) or %. For each time-dependent covariate, average value (and quartiles) are computed

from all values over the entire period of follow-up to the event time (any CVD “yes”) or censoring (any CVD “no”). Only subjects at

risk at the particular time-point were included; for example, at year 10 there were 1380 active participants without a prior CVD event.

The number at risk beyond year 24 declines owing to staggered entry of participants into the DCCT during 1983-1989, only 37 being at

risk of any CVD in year 30.


10

Table A.4. Median and inter-quartile range or prevalence (%) for time-dependent characteristics of DCCT/EDIC participants at

DCCT baseline and at 10, 20 and 25 years of follow-up for those at risk of MACE over the course of the DCCT/EDIC study, and

the corresponding hazard ratio of any CVD per unit change in the covariate.

Baseline Year 10 Year 20 Year 25 HR 95% CI p-value

N 1441 1391 1292 1058

DEMOGRAPHIC

Physical

Age (yr) 27 (22,32) 36 (31,42) 46 (41,51) 51 (46,56) 1.112 (1.074, 1.151) 0

Weight Men (kg) 74 (67,82) 83 (76,92) 90 (80,100) 90 (80,101) 0.984 (0.964, 1.004) 0.1092

Weight Women (kg) 62 (56,69) 69 (62,78) 73 (65,84) 74 (65,84) 1.008 (0.988, 1.028) 0.4519

Mean BMI (kg/m2) 23 (21,25) 25 (23,27) 26 (24,29) 26 (24,29) 1.009 (0.952, 1.069) 0.758

BMI Men (kg/m2) 24 (22,25) 26 (24,29) 28 (25,31) 28 (25,31) 0.966 (0.903, 1.034) 0.3216

BMI Women (kg/m2) 23 (21,25) 25 (23,28) 27 (24,31) 27 (24,31) 1.019 (0.962, 1.08) 0.5147

Behavior

Smoking (%) 19 19 14 12 2.247 (1.411, 3.579) 7.00E-04

Alcohol (% occasional or regular) 22 40 45 45 0.783 (0.608, 1.007) 0.0568

Exercise (% moderate or strenuous) 70 55 55 55 0.979 (0.676, 1.416) 0.909

TRADITIONAL

Blood Pressure

Systolic (mm Hg) 114 (106,122) 118 (110,126) 120 (112,129) 120 (110,130) 1.034 (1.022, 1.046) 0

Mean Systolic (mm Hg) 114 (106,122) 115 (110,121) 118 (112,124) 118 (112,124) 1.071 (1.046, 1.096) 0

Diastolic (mm Hg) 72 (68,80) 76 (70,82) 74 (68,80) 71 (65,78) 1.01 (0.987, 1.034) 0.3842

Mean Diastolic (mm Hg) 72 (68,80) 74 (71,78) 75 (71,78) 74 (71,77) 1.044 (1.005, 1.085) 0.027

Pulse pressure (mm Hg) 40 (34,48) 42 (36,50) 46 (39,54) 48 (41,57) 1.045 (1.03, 1.059) 0

Hypertension (%) 3 19 58 65 2.198 (1.348, 3.586) 0.0016

Any Hypertension (%) 0 23 71 79 2.291 (1.303, 4.027) 0.004

Pulse rate (bpm) 76 (68,84) 74 (68,80) 72 (64,80) 70 (62,78) 1.029 (1.011, 1.048) 0.0016

Mean Pulse rate (bpm) 76 (68,84) 74 (69,78) 73 (69,77) 73 (69,77) 1.074 (1.044, 1.106) 0

Medications

ACE (%) 0 7 40 44 0.945 (0.583, 1.533) 0.8191


11

ARB (%) 0 0 12 16 1.024 (0.486, 2.158) 0.9495

Beta Blockers (%) 0 1 4 11 2.796 (1.441, 5.424) 0.0024

Calcium Channel Blockers (%) 0 1 5 8 2.385 (1.216, 4.68) 0.0115

Lipid Lowering (%) 0 3 44 60 1.141 (0.696, 1.872) 0.6006

Lipids

Total cholesterol (mg/dl) 174 (153,197) 184 (161,207) 177 (155,200) 171 (149,195) 1.011 (1.007, 1.016) 0

Mean Total cholesterol (mg/dl) 174 (153,197) 181 (163,202) 184 (165,200) 181 (165,197) 1.018 (1.011, 1.025) 0

Triglycerides (mg/dl) 70 (55,94) 73 (54,104) 71 (51,104) 66 (50,92) 2.522 (1.807, 3.518) 0

Mean Triglycerides (mg/dl) 70 (52,93) 74 (59,97) 74 (59,99) 74 (59,98) 2.923 (1.87, 4.568) 0

HDLc (mg/dl) 49 (42,57) 52 (44,62) 53 (45,65) 58 (48,72) 0.984 (0.97, 0.999) 0.0323

Mean HDLc (mg/dl) 49 (42,57) 50 (44,59) 53 (45,61) 53 (46,63) 0.983 (0.965, 1.002) 0.0754

LDLc (mg/dl) 107 (91,127) 113 (93,135) 103 (86,122) 93 (75,111) 1.014 (1.008, 1.019) 0

Mean LDLc (mg/dl) 107 (91,127) 112 (96,131) 112 (97,127) 109 (96,122) 1.02 (1.012, 1.029) 0

Hyperlipidemia (%) 23 30 56 67 1.647 (1.055, 2.571) 0.0282

DIABETES-RELATED

History

Insulin Dose (units/kg/day) 0.64 (0.5,0.8) 0.63 (0.51,0.75) 0.53 (0.36,0.69) 0.51 (0.33,0.69) 1.363 (0.694, 2.678) 0.3691

Mean Insulin Dose (units/kg/day) 0.64 (0.5,0.8) 0.65 (0.55,0.79) 0.61 (0.5,0.73) 0.59 (0.49,0.71) 1.296 (0.433, 3.874) 0.6431

Estimated Glucose Disposal Rate NA (NA,NA) 9 (7,10) 7 (5,9) 6 (5,8) 0.763 (0.683, 0.853) 0

Microvascular

Estimated GFR (mL/min per 1.73 m2) 125 (118,134) 113 (105,120) 101 (90,109) 96 (85,104) 0.978 (0.971, 0.986) 0

eGFR<60 (%) 0 0 3 5 4.356 (2.21, 8.586) 0

Any eGFR<60 (%) 0 1 4 7 3.949 (2.099, 7.429) 0

Log AER (mg/24 hr) 2.4 (2.0,2.9) 2.3 (1.9,3.0) 2.4 (2.0,3.1) 2.4 (2.0,3.2) 1.283 (1.151, 1.431) 0

Sustained AER ≥30 mg/dl (%) 5 14 16 16 1.916 (1.18, 3.109) 0.0085

AER ≥40 mg/dl (%) 5 13 16 17 2.171 (1.355, 3.478) 0.0013

AER ≥300 mg/dl (%) 0 3 6 6 3.028 (1.64, 5.593) 4.00E-04

Any AER ≥40 mg/dl (%) 5 28 39 45 1.729 (1.127, 2.654) 0.0122

Any AER ≥300 mg/dl (%) 0 4 10 10 3.072 (1.834, 5.148) 0

Hypoglycemia

Coma/Seizure (%) 0 9 18 13 1.021 (0.835, 1.248) 0.8379


12

Requiring Assistance (%) 0 34 45 42 1.005 (0.905, 1.114) 0.9319

Glycemia

HbA1c [% (mmol/mol)]

8.8 (7.8,10.1)

73 (62,87)

8.1 (7.3,9.1)

65 (56,76)

7.7 (7.0,8.6)

61 (53,70)

7.8 (7.1,8.6)

62 (54,70) 1.297 (1.139, 1.478) 1.00E-04

Mean HbA1c [% (mmol/mol)]

8.8 (7.8,10.1)

73 (62,87)

8.0 (7.2,9.0)

64 (54,75)

7.9 (7.3,8.6)

63 (56,70)

7.9 (7.3,8.6)

63 (56,70) 1.539 (1.309, 1.808) 0

BMI=body mass index; ACE=angiotensin converting enzyme inhibitors; ARB=angiotensin receptor blockers; HDLc=high-density lipoprotein


*C=Current (or most recent) value, M=Updated mean value, A=Cumulative Incidence (such as Any Use). Categories C, M, and A correspond to time-

dependent covariates assessed or measured at or most recently prior to each event time or right censoring time, i.e. at the most recent visit up to the

particular time-point.

Data are medians (first quartile, third quartile) or %. Only subjects at risk at the particular time-point were included; for example, at year 10 there were

1391 active participants without a prior MACE event. The number at risk beyond year 24 declines owing to staggered entry of participants into the

DCCT during 1983-1989, only 40 being at risk of MACE in year 30.


13

Table A.5. The final time-dependent multivariable Cox model for any CVD fit among males.

Hazard Ratio 95% CI Z-test value p-value

Age (per 5 yrs) 1.4831 1.2502 1.7594 4.5222 0

Family History of MI 1.3025 0.8641 1.9632 1.2626 0.2067

Mean systolic BP (per 10 mm Hg) 1.1128 0.8594 1.441 0.8110 0.4173

Mean Pulse (per 10 bpm) 1.5725 1.1519 2.1467 2.8510 0.0043

(Log) Triglycerides 1.6978 1.1748 2.4537 2.8176 0.0048

Mean LDL (per 10 mg/dl) 1.0624 0.9715 1.1619 1.3276 0.1842

Current use of ACE Inhibitor 0.7393 0.4645 1.1767 -1.2735 0.2028

Duration of Diabetes (per 5yrs) 1.2465 0.9817 1.5828 1.8087 0.0704

Mean HbA1c 1.2284 1.0139 1.4883 2.1013 0.0356

Table A.6. The final time-dependent multivariable Cox model for any CVD fit among females.

Hazard Ratio 95% CI Z-test value p-value

Age (per 5 yrs) 1.4991 1.2634 1.7786 4.6407 0

Family History of MI 1.4173 0.9127 2.2008 1.5534 0.1203

Mean systolic BP (per 10 mm Hg) 1.6630 1.2819 2.1575 3.8301 0.0001

Mean Pulse (per 10 bpm) 1.1208 0.7694 1.6325 0.5944 0.5522

(Log) Triglycerides 1.3258 0.8362 2.1021 1.1995 0.2303

Mean LDL (per 10 mg/dl) 1.0963 0.993 1.2103 1.8215 0.0685

Current use of ACE Inhibitor 0.5884 0.3495 0.9906 -1.9955 0.0459

Duration of Diabetes (per 5yrs) 1.2388 0.9643 1.5914 1.6757 0.0937

Mean HbA1c 1.4152 1.1780 1.7002 3.7112 0.0002


14

Figure A.1. Risk gradients showing the linearity of the log hazard rate for any CVD (A) and for MACE

(B) as a function of the weighted mean HbA1c (a time-dependent covariate) and age at baseline.

A. Any CVD

6 7 8 9 10 11

-2-1

01

2

Weighted Mean HbA1c

Log Hazard

15 20 25 30 35 40

-2-1

01

2

Age

Log Hazard


15

B. MACE

6 7 8 9 10 11

-2-1

01

2

Weighted Mean HbA1c

Log Hazard

15 20 25 30 35 40

-2-1

01

2

Age

Log Hazard


Documents

Page 1 of 47 Diabetesdiabetes.diabetesjournals.org/content/diabetes/early/...1 01/12/15 Risk factors for Cardiovascular Disease in Type 1 Diabetes The Diabetes Control and Complications