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PUBH : Intervention Studies/Randomized Trials

Homework 4 (23 points)



· To understand the design and analysis of clinical trials

· To understand the importance of randomization in clinical trials

· To understand the principle of the intention-to-treat analysis

· To understand the concept of number needed to treat

Procedure – Read

· Diabetes Prevention Program (DPP) Research Group. (2002). Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. New England Journal of Medicine, 346(6), 393-403.

· Diabetes Prevention Program (DPP) Research Group. (1999). Design and methods for a clinical trial in the prevention of type 2 diabetes. Diabetes Care, 22, 623-634.

· Pages 623-624 (Eligibility Criteria, Recruitment and Staged Screening Process) and page 628 (Biostatistical considerations, Sample size goal)

Questions – Complete

1. Related to the study design and type of trial conducted in the DPP study.

a. What were the aims of this study? What is the design? (3 points)

b. What were the randomization groups? (3 points)

c. What was the primary outcome of the trial? (1 point)

d. Were there any secondary outcomes? If so, list them. (2 points)

e. Explain the concept of blinding and if/how it was applied in the DPP study. (3 points)

2. Consider Table 1 in the NEJM (2002) paper. Discuss why you think that the randomization scheme was successful (or not) comparing the baseline characteristics of the two groups. (2 points)

3. Consider the presentation of the analysis and results of the effect of the randomization group on cumulative incidence of diabetes in Figure 2, Table 2, and on page 397 of the NEJM (2002) paper.

a. Describe the three curves shown in Figure 2. Which randomization group (intervention) seems to have the greatest impact on diabetes occurrence? (1 point)

b. What type of measure of incidence is shown in Figure 2? (1 point)

c. Compare the measures shown in Figure 2 and the incidence measures shown in Table 2. What is the key difference, and which do you think is preferable and why? (2 points)

4. The trial was stopped early – in fact by a full year (NEJM, 2002 paper, p. 394, right column). What do you think contributed to the early closure of the trial? (5 points)

The New England




C o p y r ig h t © 2 0 0 2 b y t h e M a s s a c h u s e t t s Me d i c a l S o c i e t y

V O L U M E 3 4




7 , 2 0 0


N U M B E R 6

N Engl J Med, Vol. 346, No. 6


February 7, 2002























Type 2 diabetes affects approximate-
ly 8 percent of adults in the United States. Some risk
factors — elevated plasma glucose concentrations in
the fasting state and after an oral glucose load, over-
weight, and a sedentary lifestyle — are potentially
reversible. We hypothesized that modifying these
factors with a lifestyle-intervention program or the
administration of metformin would prevent or delay
the development of diabetes



We randomly assigned 3234 nondiabetic
persons with elevated fasting and post-load plasma
glucose concentrations to placebo, metformin (85


mg twice daily), or a lifestyle-modification program
with the goals of at least a 7 percent weight loss and
at least 150 minutes of physical activity per week.
The mean age of the participants was 51 years, and
the mean body-mass index (the weight in kilograms
divided by the square of the height in meters) was
34.0; 68 percent were women, and 45 percent were
members of minority groups.


The average follow-up was 2.8 years. The
incidence of diabetes was 11.0, 7.8, and 4.8 cases per
100 person-years in the placebo, metformin, and life-
style groups, respectively. The lifestyle intervention
reduced the incidence by 58 percent (95 percent con-
fidence interval, 48 to 66 percent) and metformin by
31 percent (95 percent confidence interval, 17 to 43
percent), as compared with placebo; the lifestyle in-
tervention was significantly more effective than met-
formin. To prevent one case of diabetes during a
period of three years, 6.9 persons would have to par-
ticipate in the lifestyle-intervention program, and 13.


would have to receive metformin.


Lifestyle changes and treatment with
metformin both reduced the incidence of diabetes in
persons at high risk. The lifestyle intervention was
more effective than metformin. (N Engl J Med 2002;


Copyright © 2002 Massachusetts Medical Society.

The writing group (William C. Knowler, M.D., Dr.P.H., Elizabeth Bar-
rett-Connor, M.D., Sarah E. Fowler, Ph.D., Richard F. Hamman, M.D.,
Dr.P.H., John M. Lachin, Sc.D., Elizabeth A. Walker, D.N.Sc., and David
M. Nathan, M.D.) takes responsibility for the content of this article.

Address reprint requests to the Diabetes Prevention Program Coordinat-
ing Center, Biostatistics Center, George Washington University, 6110 Ex-
ecutive Blvd., Suite 750, Rockville, MD 20852.

*The members of the Diabetes Prevention Program Research Group are
listed in the Appendix.

YPE 2 diabetes mellitus, formerly called
non-insulin-dependent diabetes mellitus, is
a serious, costly disease affecting approxi-
mately 8 percent of adults in the United



Treatment prevents some of its devastating


but does not usually restore normo-
glycemia or eliminate all the adverse consequences.
The diagnosis is often delayed until complications are


Since current methods of treating diabetes
remain inadequate, prevention is preferable. The hy-
pothesis that type 2 diabetes is preventable


is sup-
ported by observational studies and two clinical tri-
als of diet, exercise, or both in persons at high risk
for the disease



but not by studies of drugs used to
treat diabetes.


The validity of generalizing the results of previous
prevention studies is uncertain.


Interventions that
work in some societies may not work in others, be-
cause social, economic, and cultural forces influence
diet and exercise. This is a special concern in the
United States, where there is great regional and ethnic
diversity in lifestyle patterns and where diabetes is es-
pecially frequent in certain racial and ethnic groups,
including American Indians, Hispanics, African Amer-
icans, Asians, and Pacific Islanders.


The Diabetes Prevention Program Research Group
conducted a large, randomized clinical trial involv-
ing adults in the United States who were at high risk
for the development of type 2 diabetes. The study
was designed to answer the following primary ques-
tions: Does a lifestyle intervention or treatment with


Copyright © 2002 Massachusetts Medical Society. All rights reserved


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N Engl J Med, Vol. 346, No. 6


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T h e N e w E n g l a n d Jo u r n a l o f Me d i c i n e

metformin, a biguanide antihyperglycemic agent, pre-
vent or delay the onset of diabetes? Do these two
interventions differ in effectiveness? Does their ef-
fectiveness differ according to age, sex, or race or
ethnic group?


We conducted a clinical trial involving persons at 27 centers
who were at high risk for diabetes. The methods have been de-
scribed in detail elsewhere,


and the protocol is available at http://
www.bsc.gwu.edu/dpp. The institutional review board at each
center approved the protocol, and all participants gave written in-
formed consent.


Eligibility criteria included an age of at least 25 years, a body-
mass index (the weight in kilograms divided by the square of the
height in meters) of 24 or higher (22 or higher in Asians), and a
plasma glucose concentration of 95 to 125 mg per deciliter (5.3
to 6.9 mmol per liter) in the fasting state («125 mg per deciliter
in the American Indian clinics) and 140 to 199 mg per deciliter
(7.8 to 11.0 mmol per liter) two hours after a 75-g oral glucose
load. These concentrations are elevated but are not diagnostic of
diabetes according to the 1997 criteria of the American Diabetes


Before June 1997, the criterion for plasma glucose in
the fasting state was 100 to 139 mg per deciliter (5.6 to 7.7 mmol
per liter), or «139 mg per deciliter in the American Indian clinics.
Eligible persons were excluded if they were taking medicines known
to alter glucose tolerance or if they had illnesses that could seriously
reduce their life expectancy or their ability to participate in the trial.
Recruitment was designed to enroll approximately half the partic-
ipants from racial or ethnic minority groups. A four-step screen-
ing and recruitment process was developed to identify eligible par-



Eligible participants were randomly assigned to one of three in-
terventions: standard lifestyle recommendations plus metformin
(Glucophage) at a dose of 850 mg twice daily, standard lifestyle
recommendations plus placebo twice daily, or an intensive pro-
gram of lifestyle modification. The study initially included a fourth
intervention, troglitazone, which was discontinued in 1998 be-
cause of the drug’s potential liver toxicity.


The results in the tro-
glitazone group are not reported here.

Treatment with metformin was initiated at a dose of 850 mg
taken orally once a day, with placebo tablets also given once a day
initially. At one month, the dose of metformin was increased to
850 mg twice daily, unless gastrointestinal symptoms warranted
a longer titration period. The initiation of treatment with half a
tablet was optional. Adherence to the treatment regimen was as-
sessed quarterly on the basis of pill counts and structured inter-
views. The standard lifestyle recommendations for the medication
groups were provided in the form of written information and in
an annual 20-to-30-minute individual session that emphasized the
importance of a healthy lifestyle. Participants were encouraged to
follow the Food Guide Pyramid


and the equivalent of a National
Cholesterol Education Program Step 1 diet,


to reduce their
weight, and to increase their physical activity.

The goals for the participants assigned to the intensive lifestyle
intervention were to achieve and maintain a weight reduction of
at least 7 percent of initial body weight through a healthy low-
calorie, low-fat diet and to engage in physical activity of moderate
intensity, such as brisk walking, for at least 150 minutes per week.
A 16-lesson curriculum covering diet, exercise, and behavior mod-
ification was designed to help the participants achieve these goals.
The curriculum, taught by case managers on a one-to-one basis

during the first 24 weeks after enrollment, was flexible, culturally
sensitive, and individualized. Subsequent individual sessions (usu-
ally monthly) and group sessions with the case managers were de-
signed to reinforce the behavioral changes.

Outcome Measures

The primary outcome was diabetes, diagnosed on the basis of
an annual oral glucose-tolerance test or a semiannual fasting plasma
glucose test, according to the 1997 criteria of the American Diabe-
tes Association: a value for plasma glucose of 126 mg per deciliter
(7.0 mmol per liter) or higher in the fasting state or 200 mg per
deciliter (11.1 mmol per liter) or higher two hours after a 75-g
oral glucose load.


In addition to the semiannual measurements,
fasting plasma glucose was measured if symptoms suggestive of
diabetes developed. The diagnosis required confirmation by a sec-
ond test, usually within six weeks, according to the same criteria.
If diabetes was diagnosed, the participants and their physicians
were informed and glucose-tolerance tests were discontinued, but
fasting plasma glucose was measured every six months, with gly-
cosylated hemoglobin measured annually. As long as the fasting
plasma glucose concentration was less than 140 mg per deciliter,
participants were asked to monitor their blood glucose and to con-
tinue their assigned study treatment. If the fasting plasma glucose
concentration reached or exceeded 140 mg per deciliter, the study
medication was discontinued and the participant was referred to his
or her physician for treatment. Measurements of glucose and gly-
cosylated hemoglobin (HbA


) were performed centrally. All tests
were performed without interrupting the assigned treatment, ex-
cept that placebo or metformin was not taken on the morning of
the test. The investigators and the participants were unaware of the
results of these measurements and were informed only if the results
exceeded the specified threshold for a change in the treatment.

Self-reported levels of leisure physical activity were assessed annu-
ally with the Modifiable Activity Questionnaire.


The physical-
activity level was calculated as the product of the duration and fre-
quency of each activity (in hours per week), weighted by an estimate
of the metabolic equivalent of that activity (MET) and summed
for all activities performed, with the result expressed as the aver-
age MET-hours per week for the previous year. Usual daily caloric
intake during the previous year, including calories from fat, carbo-
hydrate, protein, and other nutrients, was assessed at base line and
at one year with the use of a modified version of the Block food-
frequency questionnaire.



Statistical Analysis and Early Closure

Random treatment assignments were stratified according to the
clinical center. Assignments to metformin and placebo were dou-
ble-blinded. The study design and analysis followed the inten-
tion-to-treat principle. Nominal (unadjusted) P values and confi-
dence intervals are reported.

The blinded treatment phase was terminated one year early, in
May 2001, on the advice of the data monitoring board, on the
basis of data obtained through March 31, 2001, the closing date
for this report. By then, we had obtained evidence of efficacy on
the basis of 65 percent of the planned person-years of observation.
To maintain a type I error level of 0.05 for significance in pairwise
comparisons of the risk of diabetes between groups, with adjust-
ment for repeated interim analyses, the group-sequential log-rank


required a P value of less than 0.0159. For pairwise compar-
isons of other outcomes, a Bonferroni-adjusted criterion of P< 0.0167 was used. The study design provided 90 percent power to detect a 33 percent reduction from an incidence of 6.5 cases of diabetes per 100 person-years, with a 10 percent rate of loss to follow-up per year.

The time to the outcome was assessed with the use of life-table


Modified product-limit curves for the cumulative in-
cidence of diabetes were compared with the use of the log-rank
test. The estimated cumulative incidence at three years and the

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N Engl J Med, Vol. 346, No. 6


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Greenwood estimate of the standard error were used to calculate
the number of persons who would need to be treated in order to
prevent one case of confirmed diabetes during a period of three
years and the associated 95 percent confidence interval. Risk re-
duction, heterogeneity among strata, and interactions between
treatment assignments and covariates were assessed by proportion-
al-hazards regression. Fixed-effects models with the assumption
of normally distributed errors


were used to assess differences
over time in body weight and plasma glucose and glycosylated
hemoglobin values among the three groups.


Study Cohort and Follow-up

From 1996 to 1999, we randomly assigned 3234
study participants to one of the three interventions
(1082 to placebo, 1073 to metformin, and 1079 to
the intensive lifestyle intervention). Base-line charac-
teristics, including all measured risk factors for dia-
betes, were similar among the three study groups
(Table 1).


The participants were followed for an av-

erage of 2.8 years (range, 1.8 to 4.6). At the close of
the study, 99.6 percent of the participants were alive,
of whom 92.5 percent had attended a scheduled vis-
it within the previous five months.

Adherence to Interventions

Fifty percent of the participants in the lifestyle-
intervention group had achieved the goal of weight
loss of 7 percent or more by the end of the curricu-
lum (at 24 weeks), and 38 percent had a weight loss
of at least 7 percent at the time of the most recent
visit; the proportion of participants who met the
goal of at least 150 minutes of physical activity per
week (assessed on the basis of logs kept by the par-
ticipants) was 74 percent at 24 weeks and 58 percent
at the most recent visit. Dietary change was assessed
only at one year. Daily energy intake decreased by a
mean (±SE) of 249±27 kcal in the placebo group,
296±23 kcal in the metformin group, and 450±26

*Plus–minus values are means ±SD.

†Twenty Pacific Islanders were included in this category.

‡Information was not available for one participant.

§To convert the values for glucose to millimoles per liter, multiply by 0.05551.

¶Data are based on responses to the Modifiable Activity Questionnaire.


MET denotes metabolic
equivalent. MET-hours represent the average amount of time engaged in specified physical activities
multiplied by the MET value of each activity.





























Sex — no. (%)

1043 (32.3)
2191 (67.7)

335 (31.0)
747 (69.0)

363 (33.8)
710 (66.2)

345 (32.0)
734 (68.0)

Race or ethnic group — no. (%)
African American
American Indian

1768 (54.7)
645 (19.9)
508 (15.7)
171 (5.3)
142 (4.4)

586 (54.2)
220 (20.3)
168 (15.5)
59 (5.5)
49 (4.5)

602 (56.1)
221 (20.6)
162 (15.1)
52 (4.8)
36 (3.4)

580 (53.8)
204 (18.9)
178 (16.5)
60 (5.6)
57 (5.3)

Family history of diabetes
— no. (%)

2243 (69.4) 758 (70.1) 733 (68.3) 752 (69.8)‡

History of gestational diabetes
— no. of women (%)

353 (16.1) 122 (16.3) 111 (15.7)‡ 120 (16.3)

Age — yr 50.6±10.7 50.3±10.4 50.9±10.3 50.6±11.3

Weight — kg 94.2±20.3 94.3±20.2 94.3±19.9 94.1±20.8

Body-mass index 34.0±6.7 34.2±6.7 33.9±6.6 33.9±6.8

Waist circumference — cm 105.1±14.5 105.2±14.3 104.9±14.4 105.1±14.8

Waist-to-hip ratio 0.92±0.09 0.93±0.09 0.93±0.09 0.92±0.08

Plasma glucose — mg/dl§
In the fasting state
Two hours after an oral glucose






Glycosylated hemoglobin — % 5.91±0.50 5.91±0.50 5.91±0.50 5.91±0.51

Leisure physical activity — MET-hr/wk¶ 16.3±25.8 17.0±29.0 16.4±25.9 15.5±22.1

Copyright © 2002 Massachusetts Medical Society. All rights reserved.
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N Engl J Med, Vol. 346, No. 6


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T h e N e w E n g l a n d Jo u r n a l o f Me d i c i n e

kcal in the lifestyle-intervention group (P<0.001). Average fat intake, which was 34.1 percent of total calories at base line, decreased by 0.8±0.2 percent in the placebo and metformin groups and by 6.6±0.2 percent in the lifestyle-intervention group (P< 0.001). The proportion of participants who took at least 80 percent of the prescribed dose of the study medication was slightly higher in the placebo group than in the metformin group (77 percent vs. 72 per- cent, P<0.001). Ninety-seven percent of the partic-

ipants taking placebo and 84 percent of those taking
metformin were given the full dose of one tablet
(850 mg in the case of metformin) twice a day; the
remainder were given one tablet a day to limit side

Changes in weight and leisure physical activity in all
three groups and adherence to the medication regi-
men in the metformin and placebo groups are shown
in Figure 1. Participants assigned to the lifestyle in-
tervention had much greater weight loss and a great-

Figure 1.

Changes in Body Weight (Panel A) and Leisure Physical Activity (Panel B) and Adherence to
Medication Regimen (Panel C) According to Study Group.
Each data point represents the mean value for all participants examined at that time. The number of
participants decreased over time because of the variable length of time that persons were in the study.
For example, data on weight were available for 3085 persons at 0.5 year, 3064 at 1 year, 2887 at 2 years,
and 1510 at 3 years. Changes in weight and leisure physical activity over time differed significantly
among the treatment groups (P<0.001 for each comparison).




0 4.0





0.5 1.0 1.5 2.0 2.5 3.0 3.5














0 4.0
0.5 1.0 1.5 2.0 2.5 3.0 3.5


















0 4.0






0.5 1.0 1.5 2.0 2.5 3.0 3.5







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N Engl J Med, Vol. 346, No. 6


February 7, 2002





er increase in leisure physical activity than did par-
ticipants assigned to receive metformin or placebo.
The average weight loss was 0.1, 2.1, and 5.6 kg in the
placebo, metformin, and lifestyle-intervention groups,
respectively (P<0.001).

Incidence of Diabetes

The cumulative incidence of diabetes was lower in
the metformin and lifestyle-intervention groups than
in the placebo group throughout the follow-up pe-
riod (Fig. 2). The crude incidence was 11.0, 7.8, and
4.8 cases per 100 person-years for the placebo, met-
formin, and lifestyle-intervention groups, respective-
ly (Table 2). The incidence of diabetes was 58 per-
cent lower (95 percent confidence interval, 48 to 66
percent) in the lifestyle-intervention group and 31
percent lower (95 percent confidence interval, 17 to
43 percent) in the metformin group than in the pla-
cebo group. The incidence of diabetes was 39 per-
cent lower (95 percent confidence interval, 24 to 51
percent) in the lifestyle-intervention group than in
the metformin group. The results of all three pair-
wise group comparisons were statistically significant
by the group-sequential log-rank test. None of these
results were materially affected by adjustment for
base-line characteristics. The estimated cumulative
incidence of diabetes at three years was 28.9 percent,
21.7 percent, and 14.4 percent in the placebo, met-
formin, and lifestyle-intervention groups, respective-
ly. On the basis of these rates, the estimated number
of persons who would need to be treated for three
years to prevent one case of diabetes during this pe-
riod is 6.9 (95 percent confidence interval, 5.4 to
9.5) for the lifestyle intervention and 13.9 (95 per-
cent confidence interval, 8.7 to 33.9) for metformin.

Treatment Effects among Subgroups

Incidence rates and risk reductions within sub-
groups of participants and the results of tests of the
homogeneity of risk reduction among subgroups are
shown in Table 2; 95 percent confidence intervals for
the subgroup data indicate the precision of the risk-
reduction estimate for each stratum. The study had
inadequate power to assess the significance of effects
within the subgroups, nor were such tests planned.
Significant heterogeneity indicates that treatment ef-
fects differed according to the values of the covariates.
Treatment effects did not differ significantly accord-
ing either to sex or to race or ethnic group (Table 2).
The lifestyle intervention was highly effective in all
subgroups. Its effect was significantly greater among
persons with lower base-line glucose concentrations
two hours after a glucose load than among those
with higher base-line glucose values. The effect of met-
formin was less with a lower body-mass index or a low-
er fasting glucose concentration than with higher

values for those variables. Neither interaction was
explained by the other variable or by age. The ad-
vantage of the lifestyle intervention over metformin
was greater in older persons and those with a lower
body-mass index than in younger persons and those
with a higher body-mass index.

Glycemic Changes

In the first year, there was a similar reduction in
the mean fasting plasma glucose values in the met-
formin and lifestyle-intervention groups, whereas the
values rose in the placebo group (Fig. 3). The values
rose in parallel in all three groups in subsequent
years. There was a similar temporal pattern in the
values for glycosylated hemoglobin, except that the
values in the metformin group were in between
those in the lifestyle-intervention and placebo groups.
Figure 4 shows the percentage of participants who
had normal glucose concentrations (fasting values,
post-load values, and both) at each annual examina-
tion. Metformin and the lifestyle intervention were
similarly effective in restoring normal fasting glucose
values, but the lifestyle intervention was more effec-
tive in restoring normal post-load glucose values.

Adverse Events

The rate of gastrointestinal symptoms was highest
in the metformin group, and the rate of musculo-
skeletal symptoms was highest in the lifestyle-inter-
vention group (Table 3). Hospitalization and mor-
tality rates were unrelated to treatment. No deaths
were attributed to the study intervention.

Figure 2.

Cumulative Incidence of Diabetes According to Study
The diagnosis of diabetes was based on the criteria of the
American Diabetes Association.


The incidence of diabetes dif-
fered significantly among the three groups (P<0.001 for each comparison).





0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0















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T h e N e w E n g l a n d Jo u r n a l o f Me d i c i n e


Our results support the hypothesis that type 2 di-
abetes can be prevented or delayed in persons at
high risk for the disease. The incidence of diabetes
was reduced by 58 percent with the lifestyle inter-
vention and by 31 percent with metformin, as com-
pared with placebo. These effects were similar in
men and women and in all racial and ethnic groups.
The intensive lifestyle intervention was at least as ef-
fective in older participants as it was in younger par-
ticipants. The results of our study extend previous
data showing that lifestyle interventions can reduce
the incidence of diabetes


and demonstrate the ap-
plicability of this finding to the ethnically and cul-

turally diverse population of the United States. The
risk reduction associated with the lifestyle interven-
tion in our study was the same as that in a study
conducted in Finland,


and was higher than the re-
ductions associated with diet (31 percent), exercise
(46 percent), and diet plus exercise (42 percent) in
a study in China.


Our lifestyle intervention was systematic and in-
tensive, with the study participants receiving de-
tailed, individualized counseling. The study, however,
was not designed to test the relative contributions of
dietary changes, increased physical activity, and weight
loss to the reduction in the risk of diabetes, and the
effects of these components remain to be determined.

*CI denotes confidence interval.

†P<0.05 for the test of heterogeneity across strata. Age, body-mass index, and plasma glucose were analyzed as continuous variables.

‡This category includes 20 Pacific Islanders.

§The eligibility criterion was a body-mass index of at least 22 for Asians and at least 24 for all other persons.

¶To convert the values for glucose to millimoles per liter, multiply by 0.05551.

¿This category includes American Indian participants who had a fasting glucose concentration that was less than 95 mg per deciliter, ac-
cording to the eligibility criteria.


**This category includes 54 participants with a fasting glucose concentration of 126 to 139 mg per deciliter who were enrolled before
June 1997,


when the eligibility criteria were changed to conform to the diagnostic criteria of the American Diabetes Association, published
that year.



























(95% CI)*














cases/100 person-yr percent

Overall 3234 (100) 11.0 7.8 4.8 58 (48 to 66) 31 (17 to 43) 39 (24 to 51)

25–44 yr
45–59 yr
»60 yr

1000 (30.9)
1586 (49.0)
648 (20.0)




48 (27 to 63)
59 (44 to 70)
71 (51 to 83)

44 (21 to 60)
31 (10 to 46)
11 (¡33 to 41)

8 (¡36 to 37)†
41 (18 to 57)†
69 (47 to 82)†


1043 (32.3)
2191 (67.7)




65 (49 to 76)
54 (40 to 64)

37 (14 to 54)
28 (10 to 43)

46 (20 to 63)
36 (16 to 51)

Race or ethnic group
African American
American Indian

1768 (54.7)
645 (19.9)
508 (15.7)
171 (5.3)
142 (4.4)




51 (35 to 63)
61 (37 to 76)
66 (41 to 80)
65 (7 to 87)
71 (24 to 89)

24 (3 to 41)
44 (16 to 63)
31 (¡9 to 56)
25 (¡72 to 68)
38 (¡55 to 75)

36 (14 to 52)
29 (¡18 to 58)
51 (13 to 72)
52 (¡35 to 83)
52 (¡46 to 84)

Body-mass index§
22 to <30 30 to <35 »35

1045 (32.3)
995 (30.8)

1194 (36.9)





65 (46 to 77)
61 (40 to 75)
51 (34 to 63)

3 (¡36 to 30)†
16 (¡19 to 41)†
53 (36 to 65)†

63 (44 to 76)†
53 (28 to 70)†
¡4 (¡47 to 26)†

Plasma glucose¶
In the fasting state

95–109 mg/dl¿
110–125 mg/dl**

Two hours after an oral load
140–153 mg/dl
154–172 mg/dl
173–199 mg/dl

2174 (67.2)
1060 (32.8)

1049 (32.4)
1103 (34.1)
1082 (33.5)










55 (38 to 68)
63 (51 to 72)

76 (58 to 86)†
60 (41 to 72)†
50 (33 to 63)†

15 (¡12 to 36)†
48 (33 to 60)†

41 (11 to 61)
38 (13 to 56)
26 (3 to 43)

48 (27 to 63)
30 (6 to 48)

59 (27 to 77)
34 (2 to 56)
33 (9 to 51)

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N Engl J Med, Vol. 346, No. 6


February 7, 2002





The incidence of diabetes in our placebo group
(11.0 cases per 100 person-years) was higher than
we had anticipated


and was higher than the inci-
dence in observational studies,


perhaps owing to
the greater frequency of glucose testing or to the se-
lection of persons at higher risk in our study. The
incidence of diabetes in the placebo group was similar
among racial and ethnic groups despite differences in
these subgroups in observational, population-based
studies.10 Racial and ethnic-group differences in the
incidence of diabetes were presumably reduced in

our study by the selection of persons who were over-
weight and had elevated fasting and post-load glu-
cose concentrations — three of the strongest risk
factors for diabetes.

Previous studies have not demonstrated that drugs
used to treat diabetes are effective for its prevention,
perhaps because of small samples and the lack of data
on adherence to the prescribed regimens.5 In con-
trast, metformin was effective in our study, although
less so than the lifestyle intervention. Metformin was
less effective in persons with a lower base-line body-

Figure 3. Fasting Plasma Glucose Concentrations (Panel A) and Glycosylated Hemoglobin Values (Pan-
el B) According to Study Group.
The analysis included all participants, whether or not diabetes had been diagnosed. Changes in fasting
glucose values over time in the three groups differed significantly (P<0.001). Glycosylated hemoglobin values in the three groups differed significantly from 0.5 to 3 years (P<0.001). To convert the values for glucose to millimoles per liter, multiply by 0.05551.



0 4.0




0.5 1.0 1.5 2.0 2.5 3.0 3.5












0 4.0



0.5 1.0 1.5 2.0 2.5 3.0 3.5










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T h e N e w E n g l a n d Jo u r n a l o f Me d i c i n e

Figure 4. Participants with Normal Plasma Glucose Values, According to Study Group.
Panel A shows the proportions of participants with normal glucose values in the fasting state (<110 mg per deciliter [6.1 mmol per liter]), Panel B the proportions with normal values two hours after an oral glucose load (<140 mg per deciliter [7.8 mmol per liter]), and Panel C the proportions with normal values for both measurements. Persons in whom a diagnosis of diabetes had been made were considered to have abnormal values, regardless of the actual values at the time. By design, no participants had normal post-load glucose values at base line, but base-line fasting glucose values were normal in 67 percent of persons in the placebo group, 67 percent of those in the metformin group, and 68 percent of those in the lifestyle-intervention group. Metformin and lifestyle intervention were similarly effective in restoring normal fasting glucose concentrations, but lifestyle intervention was more effective in restoring normal post-load glu- cose concentrations.


1 432


Fasting and Post-Load GlucoseP













1 432

Post-Load Glucose

1 432

Fasting Glucose


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N Engl J Med, Vol. 346, No. 6 · February 7, 2002 · www.nejm.org · 401

mass index or a lower fasting plasma glucose con-
centration than in those with higher values for these
variables. The reduction in the average fasting plas-
ma glucose concentration was similar in the lifestyle-
intervention and metformin groups, but the lifestyle
intervention had a greater effect than metformin on
glycosylated hemoglobin, and a larger proportion of
participants in the lifestyle-intervention group had
normal post-load glucose values at follow-up. These
findings are consistent with the observation that met-
formin suppresses endogenous glucose production,
the main determinant of fasting plasma glucose con-

Rates of adverse events, hospitalization, and mor-
tality were similar in the three groups, except that
the rate of gastrointestinal symptoms was highest in
the metformin group and the rate of musculoskele-
tal symptoms was highest in the lifestyle-interven-
tion group. Thus, the interventions were safe in ad-
dition to being effective.

An estimated 10 million persons in the United
States resemble the participants in the Diabetes Pre-
vention Program in terms of age, body-mass index,
and glucose concentrations, according to data from
the third National Health and Nutrition Examination
Survey.23 If the study’s interventions were implement-
ed among these people, there would be a substantial
reduction in the incidence of diabetes. Ultimately, the
benefits would depend on whether glucose concen-
trations could be maintained at levels below those
that are diagnostic of diabetes and whether the main-
tenance of these lower levels improved the long-term
outcome. These questions should be addressed by
continued follow-up of the study participants and by

analysis of the main secondary outcomes — reduc-
tions in risk factors for cardiovascular disease, in the
proportion of participants with atherosclerosis, and
in the proportion with cardiovascular disease, which
is the leading cause of death among patients with
type 2 diabetes.24,25

Optimal approaches to identifying candidates for
preventive measures remain to be determined. Al-
though elevation of either the fasting or the post-load
glucose concentration strongly predicts diabetes,26,27

both were required for eligibility in this study.
Whether the results would be similar in persons with
an isolated elevation of the fasting or post-load glu-
cose concentration or other risk factors for diabetes
is likely but unknown.

In summary, our study showed that treatment
with metformin and modification of lifestyle were
two highly effective means of delaying or preventing
type 2 diabetes. The lifestyle intervention was par-
ticularly effective, with one case of diabetes prevent-
ed per seven persons treated for three years. Thus, it
should also be possible to delay or prevent the de-
velopment of complications, substantially reducing
the individual and public health burden of diabetes.

Supported by the National Institutes of Health through the National In-
stitute of Diabetes and Digestive and Kidney Diseases, the Office of Re-
search on Minority Health, the National Institute of Child Health and Hu-
man Development, and the National Institute on Aging; the Indian Health
Service; the Centers for Disease Control and Prevention; the General Clin-
ical Research Center Program, National Center for Research Resources;
the American Diabetes Association; Bristol-Myers Squibb; and Parke-

Dr. Hamman owns stock in Bristol-Myers Squibb, which sells metformin
in the United States.

We are indebted to the participants in the study for their dedica-
tion to the goal of preventing diabetes; to Lipha Pharmaceuticals for
the metformin and placebo; to LifeScan, Health-O-Meter, Hoechst
Marion Roussel, Merck-Medco Managed Care, Merck, Nike, Slim-
Fast Foods, and Quaker Oats for materials, equipment, and medi-
cines for concomitant conditions; and to McKesson BioServices, Mathews
Media Group, and the Henry M. Jackson Foundation for support
services provided under subcontract with the Coordinating Center.


The following investigators were members of the Diabetes Prevention
Program Research Group (asterisks indicate principal investigators, and
daggers program coordinators): Pennington Biomedical Research Center
— G.A. Bray,* I.W. Culbert,† C.M. Champagne, M.D. Crow, L. Dawson,
B. Eberhardt, F.L. Greenway, F.G. Guillory, A.A. Hebert, M.L. Jeffirs, K.
Joyce, B.M. Kennedy, J.C. Lovejoy, S. Mancuso, L.E. Melancon, L.H.
Morris, L. Reed, J. Perault, K. Rau, D.H. Ryan, D.A. Sanford, K.G. Smith,
L.L. Smith, S.R. Smith, J.A. St. Amant, M. Terry, E. Tucker, R.T. Tulley,
P.C. Vicknair, D. Williamson, and J.J. Zachwieja; University of Chicago —
D.A. Ehrmann,* M.J. Matulik,† B. Clarke, D.A. Collins, K.B. Czech, C.
DeSandre, G. Geiger, S. Grief, B. Harding-Clay, R.M. Hilbrich, D. le
Grange, M.R. McCormick, W.L. McNabb, K.S. Polonsky, N.P. Sauter,
A.R. Semenske, K.A. Stepp, and J.A. Tobian; Jefferson Medical College —
P.G. Watson,* J.T. Mendoza,† K.A. Smith,† J. Caro, B. Goldstein, C. Lark,
L. Menefee, L. Murphy, C. Pepe, and J.M. Spandorfer; University of Mi-
ami — R.B. Goldberg,* P. Rowe,† J. Calles, P. Casanova, R.P. Donahue,
H.J. Florez, A. Giannella, G. Larreal, V. McLymont, J. Mendez, P. O’Hara,
J. Ojito, R. Prineas, and P.G. Saab; The University of Texas Health Science
Center — S.M. Haffner,* M.G. Montez,† C. Lorenzo, H. Miettinen,

*Gastrointestinal symptoms included diarrhea, flatulence, nausea, and

†P<0.0167 for the comparison with placebo.

‡Most participants with musculoskeletal symptoms had myalgia, arthri-
tis, or arthralgia.



Gastrointestinal symptoms (no. of events/
100 person-yr)*

30.7 77.8† 12.9†

Musculoskeletal symptoms (no. of events/
100 person-yr)‡

21.1 20.0 24.1†

One or more admissions (% of

Rate (no. of admissions/100 person-yr)
Median stay (days)







Deaths (no./100 person-yr) 0.16 0.20 0.10

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402 · N Engl J Med, Vol. 346, No. 6 · February 7, 2002 · www.nejm.org

T h e N e w E n g l a n d Jo u r n a l o f Me d i c i n e

C.M. Mobley, L.A. Mykkanen, and M.M. Rozek; University of Colorado
— R.F. Hamman,* P.V. Nash,† L. Testaverde,† D.R. Anderson, L.B. Bal-
lonoff, A. Bouffard, B.N. Calonge, M. Farago, W.J. Georgitis, J.O. Hill,
S.R. Hoyer, B.T. Jortberg, J.A. Merenich, M. Miller, J.G. Regensteiner,
H.M. Seagle, C.M. Smith, S.C. Steinke, and B. VanDorsten; Joslin Diabe-
tes Center — E.S. Horton,* K.E. Lawton,† R.A. Arky, M. Bryant, J.P.
Burke, E. Caballero, K.M. Callaghan, D. Devlin, T. Franklin, O.P. Ganda,
A.E. Goebel-Fabbri, M. Harris, S.D. Jackson, A.M. Jacobsen, L.M. Kula,
M. Kocal, S. Ledbury, M.A. Malloy, C. Mullooly, M. Nicosia, C.F. Old-
mixon, J. Pan, C. Pomposelli, M. Quitongan, S. Rubtchinsky, D. Schwei-
zer, E.W. Seely, D. Simonson, F. Smith, C.G. Solomon, J. Tyson, and J.
Warram; University of Washington and Veterans Affairs Puget Sound
Health Care System — S.E. Kahn,* B.K. Montgomery,† M. Alger, E.
Allen, T. Barrett, D. Bhanji, J. Cowan, J. Cullen, W.Y. Fujimoto, B. Katz,
R.H. Knopp, E.W. Lipkin, M. Marr, B.S. McCann, J.P. Palmer, R.S.
Schwartz, and D. Uyema; University of Tennessee — A.E. Kitabchi,* M.E.
Murphy,† W.B. Applegate, M. Bryer-Ash, J.H. Coble, A. Crisler, G. Cun-
ningham, A.W. Franklin, S.L. Frieson, D.L. Green, R. Imseis, C.L.
Kennedy, H.C. Lambeth, K.A. Latif, L.C. Lichtermann, M.D. McIntyre,
J.D. Nault, H. Oktaei, M.L. O’Toole, H. Ricks, L.M.K. Rutledge, S.C.
Schussler, A.R. Sherman, C.M. Smith, J.E. Soberman, K.J. Stewart, D.L.
VanBrunt, and B.J. Williams-Cleaves; Northwestern University Medical
School — B.E. Metzger,* M.K. Johnson,† C. Behrends, M.L. Cook, M.
Fitzgibbon, M.M. Giles, D. Heard, C. Johnson, D. Larsen, A. Lowe, M.
Lyman, D. McPherson, M.E. Molitch, T. Pitts, R. Reinhart, S. Roston, and
P.A. Schinleber; Massachusetts General Hospital — D.M. Nathan,* C.
McKitrick,† K. Abbott, E. Anderson, L. Bissett, E. Cagliero, S. Crowell,
L. Delahanty, S. Fritz, K. Hayward, E. Levina, T. Michel, D. Norman, J.
O’Keefe, A. Poulos, L. Ronan, M. Rosal, M. Salerno, M. Schneider, C.
Shagensky, B. Steiner, H. Turgeon, and A. Young; University of Califor-
nia, San Diego — J.M. Olefsky,* M.L. Carrion-Petersen,† E. Barrett-Con-
nor, M. Beltran, K. Caenepeel-Mills, S.V. Edelman, R.O. Ford, J. Garcia,
M. Hagerty, R.R. Henry, M. Hill, J. Horne, D. Leos, J. Matney, S. Mu-
daliar, G. Petersen, A. Pollard, W. Polonsky, S. Szerdi, J. Torio-Hurley, and
K. Vejvoda; St. Luke’s–Roosevelt Hospital — F.X. Pi-Sunyer,* J.E. Lee,†
D.B. Allison, N. Agharanya, N.J. Aronoff, M. Baldo, S.T. Foo, S. Hagamen,
C. Pal, K. Parkes, M. Pena, and G.E.H. Van Wye; Indiana University —
D.G. Marrero,* M.S. Kukman-Kelly,† Y.F. Dotson, S.E. Fineberg, J.C.
Guare, A. Hadden, B. Hills, J.M. Ignaut, M.A. Jackson, M.S. Kirkman, K.
Mather, G. McAtee, B.D. Porter, M.J. Prince, and M.L. Wheeler; Medstar
Research Institute — R.E. Ratner,* G. Youssef,† S. Shapiro,† A. Bonar,
M. Bronsord, E. Brown, W.W. Cheatham, S. Cola, A. Comfort, G. Boggs,
C. Eagle, C. Evans, E. Gorman, R. Johnson, C. Levetan, T. Kellum, M.
Lagarda, A.K. Nair, M.D. Passaro, and W. Phillips; UCLA Medical School
— M.F. Saad,* M. Budgett,† S. Fahmi,† S.D. Jinagouda,† B. Bernaba, S.L.
Bodkin, V. Ciobanu, R. Commisso, C. Cosenza, T. Dinh, M. Gonzalez,
A. Khan, D. Kumar, G. Lui, V. Mehta, A. Sharma, S. Soukiazian, K. Sza-
mos, A. Tramanian, A. Vargas, and N. Zambrana; Washington University,
St. Louis — N.H. White,* A.S. Santiago,† S. Das,† A.L. Brown, S. Da-
gogo-Jack, E.B. Fisher, E. Hurt, T. Jones, M. Kerr, L. Ryder, J.V. Santiago
(deceased), and C. Wernimont; Johns Hopkins School of Medicine — C.D.
Saudek,* V.L. Bradley,† T. Fowlkes,† H. Joseph,† F.L. Brancati, J.B.
Charleston, J.M. Clark, K. Horak, D. Jiggetts, H. Mosley, R.R. Rubin, A.
Samuels, K.J. Stewart, L. Thomas, and P. Williamson; University of New
Mexico School of Medicine — D.S. Schade,* K.S. Adams,† L.F. Atler, A.
Bland, D.A. Bowling, P.J. Boyle, M.R. Burge, L. Butler, J.L. Canady, L.
Chai, K.M. Colleran, M. Guillen, Y. Gonzales, M. Gutierrez, D. Horn-
beck, C. Johannes, P. Katz, C. King, E.N. Libby III, R. McCalman, D.A.
Montoya, A. Rassam, S. Rubinchik, and W. Senter; Albert Einstein Col-
lege of Medicine — H. Shamoon,* J.O. Brown,† J. Adames, E. Blanco, L.
Cox, J.P. Crandall, H. Duffy, S. Engel, A. Friedler, T. Harroun, C.J.
Howard-Century, S. Kloiber, N. Longchamp, D. Pompi, E. Violino, E.A.
Walker, J. Wylie-Rosett, E. Zimmerman, and J. Zonszein; University of
Pittsburgh — R.R. Wing,* M.K. Kramer,† S. Barr, M.A. Boraz, L. Clif-
ford, R. Culyba, M. Frazier, R. Gilligan, L. Harris, S. Harrier, W. Hender-
son, S. Jeffries, G. Koenning, A.M. Kriska, K. Maholic, Q. Manjoo, M.
Mullen, A. Noel, T.J. Orchard, A. Otto, L.N. Semler, C. Smith, M. Smith,
V. Stapinski, J. Viteri, T. Wilson, K.V. Williams, and J. Zgibor; University
of Hawaii — R.F. Arakaki,* R.W. Latimer,† N.K. Baker-Ladao, R.M.
Beddow, R. Braginsky, M. Calizar, L.M. Dias, N. Durham, D.A. Dupont,
L.L. Fukuhara, J. Inouye, M.K. Mau, K. Mikami, P. Mohideen, S.K.
Odom, B. Sinkule-Kam, J.S. Tokunaga, R.U. Twiggs, C.Y. Wang, and J. Vi-
ta; Southwest American Indian Center for Diabetes Prevention — W.C.
Knowler,* N.J. Cooeyate,† M.A. Hoskin,† C.A. Percy,† K.J. Acton, V.L.
Andre, S. Antone, N.M. Baptisto, R. Barber, S. Begay, P.H. Bennett, M.B.
Benson, S. Beyale, E.C. Bird, B.A. Broussard, M. Chavez, T.S. Dacawyma,
M.S. Doughty, R. Duncan, C. Edgerton, J.M. Ghahate, M. Glass, D. Goh-

des, W. Grant, R.L. Hanson, E. Horse, G. Hughte, L.E. Ingraham, M.C.
Jackson, P.A. Jay, R.S. Kaskalla, D. Kessler, K.M. Kobus, J. Krakoff, C.
Manus, T. Morgan, Y. Nashboo (deceased), J. Nelson, G.L. Pauk, S. Poir-
ier, E. Polczynski, M. Reidy, J. Roumain, D.H. Rowse, R.J. Roy, S. Sang-
ster, J. Sewemaenewa, D. Tonemah, C. Wilson, and M. Yazzie; George
Washington University Biostatistics Center — S. Fowler,* T. Brenne-
man,† S. Abebe, R. Bain, J. Bamdad, J. Callaghan, S.L. Edelstein, Y. Gao,
K.L. Grimes, N. Grover, K. Hirst, S. Jones, T.L. Jones, R.J. Katz, J.M.
Lachin, R. Orlosky, C.E. Stimpson, C. Suiter, M.G. Temprosa, and F.E.M.
Walker-Murray; National Institute of Diabetes and Digestive and Kidney
Diseases Program Office — S. Garfield,† R. Eastman, and J. Fradkin; Na-
tional Institute on Aging — R. Andres; Centers for Disease Control and
Prevention — M.M. Engelgau, K.M. Venkat Narayan, and D.F. William-
son; University of Michigan — W.H. Herman; Central Biochemistry Lab-
oratory (University of Washington) — S.M. Marcovina,* A. Aldrich, and
W.L. Chandler; Central ECG Reading Center (Wake Forest University)
— P.M. Rautaharju,* N.T. Pemberton, R. Prineas, F.S.R. Rautaharju, and
Z. Zhang; Nutrition Coding Center (University of South Carolina) —
E.J. Mayer-Davis,* T. Costacou, M. Martin, and K.L. Sparks; Central Ca-
rotid Ultrasound Unit (New England Medical Center) — D.H.
O’Leary,* L.R.C. Funk, K.A. O’Leary, and J.F. Polak; CT-Scan Reading
Unit (University of Colorado) — E.R. Stamm* and A.L. Scherzinger;
Lifestyle Resource Core (University of Pittsburgh) — R.R. Wing,* B.P.
Gillis, C. Huffmyer, A.M. Kriska, and E.M. Venditti; Medication Resource
Workgroup (Albert Einstein College of Medicine) — E.A. Walker* and T.
Harroun; Quality of Well Being Reading Unit (University of California,
San Diego) — T.G. Ganiats,* E.J. Groessl, P.R. Beerman, K.M. David,
R.M. Kaplan, and W.J. Sieber; Data Monitoring Board — S.M. Genuth
(chair), G.F. Cahill, F.L. Ferris III, J.R. Gavin III, J.B. Halter, and J. Wittes;
Ancillary Studies Subcommittee — R.R. Henry and S.M. Haffner
(chairs); Behavioral Scientists — R.R. Rubin (chair); Clinic Operations
— B.K. Montgomery (chair); Concomitant Conditions — R.E. Ratner
(chair); Economic Evaluation — W.H. Herman (chair); Interventions —
S.E. Kahn, J.V. Santiago (deceased), and J. Olefsky (chairs); Lifestyle Advisory
Group — R.R. Wing (chair); Outcomes — C. Saudek (chair); Outcomes Clas-
sification — R.E. Ratner (chair); Program Coordinators Subcommittee —
M. Montez and K. Kramer (chairs); Protocol Oversight — R.F. Hamman
(chair); Publications and Presentations — W.C. Knowler (chair); Quality
Control — R.B. Goldberg (chair); Recruitment — W.Y. Fujimoto (chair);
Recruitment Coordinators Subcommittee — J. Charleston (chair); Reten-
tion — R.R. Rubin (chair); Screening and Eligibility — R.F. Hamman
(chair); Study Chair and Vice Chair — D.M. Nathan and R.F. Hamman.


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Reviews/C o m me n ta ries / Pos itio n State m e nts


Diabetes Prevention Program

Design and methods for a clinical trial in the prevention of type 2 diabetes


The Diabetes Prevention Program is a randomized clinical trial testing strategies to prevent or

delay the development of type 2 diabetes in high-risk individuals with elevated fasting plasma

glucose concentrations and impaired glucose tolerance. The 27 clinical centers in the u.s. are

recruiting at least 3,000 participants of both sexes, ~50% of whom are minority patients and

20% of whom are >65 years old, to be assigned at random to one of three intervention groups:

an intensive lifestyle intervention focusing on a healthy diet and exercise and two masked med-

ication treatment groups~metformin or placebo-combined with standard diet and exercise

recommendations. Participants are being recruited during a 2 2I3~year period, and all will be

followed for an additional 3 1/3 to 5 years after the close of recruitment to a common closing

date in 2002. The primary outcome is the development of diabetes, diagnosed by fasting or

post-challenge plasma glucose concentrations meeting the 1997 American Diabetes Associa-

tion criteria. The 3,000 participants will provide 90% power to detect a 33% reduction in an
expected diabetes incidence rate of at least 6.5% per year in the placebo group. Secondary out-

comes include cardiovascular disease and its risk factors; changes in glycemia, j3-cell function,

insulin sensitivity, obesity, diet, physical activity, and health-related quality of life; and occur-

rence of adverse events. A fourth treatment group~troglitazone combined with standard diet

and exercise recommendations-was included initially but discontinued because of the liver

toxicity of the drug. This randomized clinical trial will test the possibility of preventing or

delaying the onset of type 2 diabetes in individuals at high risk.

Diabetes Care 22:623-634,1999

ype 2 diabetes is a common chronic

disease affecting an estimated 12% of

40- to 74-year-old people in the U.S.
(1). It is a major cause of premature mortal-

ity and morbidity due to cardiovascular,

renal, ophthalmic, and neurologic diseases.

Although treatment of type 2 diabetes can

improve hyperglycemia, normalization of

glycemia and glycohemoglobin is rarely

achieved or maintained. Furthermore, macro-

vascular disease and its risk factors are often

already present in individuals at high risk of

developing type 2 diabetes (2). Therefore, a

policy of prevention rather than early detec-

tion and treatment of diabetes might be

more effective in preventing microvascular

and macrovascular complications.

People with impaired glucose tolerance

(IGT), an intermediate category between

normoglycemia and diabetes (1,3), defined

by an oral glucose tolerance test (OGTT)

are at increased risk of developing diabetes.

The Diabetes Prevention Program (DPP)

was developed to compare several strate-

gies to prevent or delay type 2 diabetes in

individuals with IGT.


The primary research goal is a comparison

of the efficacy and safety of each of three

interventions (an intensive lifestyle inter-

vention or standard lifestyle recommenda-

tions combined with metformin or placebo)

in preventing or delaying the development

of diabetes. Diabetes is diagnosed by fasting

plasma glucose (FPG) or glucose tolerance

testing according to the 1997 American

Diabetes Association (ADA)

criteria (1).


Secondary research goals include assessing

differences between the three treatment

groups in the development of cardiovascu-

lar disease and its risk factors; changes in

glycemia, j3-cell function, insulin sensitiv-

ity, obesity, physical activity, nutrient intake,

and health-related quality of life; and
occurrence of adverse events.

Subgroup research goals
Other research goals include assessing the
consistency of the effects of the interven-

tions by baseline demographic, clinical,
biochemical, and psychosocial attributes.


Eligibility criteria
An aim of recruitment is for at least half of

the study group to be women, -20% to be

>65 years old, and approximately half to

be composed of the following ethnic

minorities: African-American, Hispanic,

American Indian, Asian American, and

Pacific Islander.

The inclusion and exclusion criteria

for the trial are summarized in Table 1.

They were based on the goals of 1) recruit-

ing nondiabetic individuals with a high

risk of progression to type 2 diabetes and 2)

excluding individuals with conditions that

might increase the risk of adverse effects

from the interventions, severely shorten life

expectancy, interfere with the conduct of

the trial, or affect the assessment for inci-

dent type 2 diabetes.

The main entry criterion is IGT based

on a single 75-g OGTT. Eligible individuals

must have no prior diagnosis of diabetes

(other than during pregnancy), be nondia-

betic by 1997 ADA and 1985 World Health

Organization (WHO) criteria, and have IGT:

FPG <126 mg/dl (7.0 mmol/l) and 2-h

post-load plasma glucose >140 mg/dl (7.8

mmol/l) and <200 mg/dl (11.1 mmol/l)

(1,3). In addition, to include individuals at

A complete list of the members of the Diabetes Prevention Program Research Group and their professional

affiliations can be found in APPENDIX 2.

Address correspondence and reprint requests to Reprint Requests, DPP Coordinating Center, The George

Washington University, Biostatistics Center, 6110 Executive Blvd., #750, Rockville, MD 20852.

Received for publication 17 September 1998 and accepted in revised form 30 November 1998.

Abbreviations: ADA, American Diabetes Association; DPP, Diabetes Prevention Program; FPG, fasting

plasma glucose; IGT, impaired glucose tolerance; NlDDK, National Institute of Diabetes and Digestive and

Kidney Diseases; OGTT, oral glucose tolerance test; WHO, World Health Organization.

A table elsewhere in this issue shows conventional and systeme International (SO units and conversion

factors for many substances.


Diabetes Prevention Program

Table I~Inclusion and exclusion criteria


Age >25 years

BMI >24 kg/m2 (>22 kg/m2 among Asian Americans)

IGT (2-h plasma glucose 140~199 mg/dl based on 75-g OGTT)

Elevated FPG (95~125 mg/dl*), except in the American Indian centers


Diabetes at baseline

FPG >126 mg/dl*

2-h plasma glucose >200 mg/dl based on 75-g


Diabetes diagnosed by a physician and confirmed by other clinical data, other than

during pregnancy

Ever used antidiabetic medication, other than during pregnancy

Medical conditions likely to limit life span and/or increase risk of intervention

Cardiovascular disease

Hospitalization for treatment of heart disease in past 6 months

New York Heart Association Functional Class>


Left bundle branch block or third degree AV block

Aortic stenosis

Systolic blood pressure> 180 mmHg or diastolic blood pressure> 105 mmHg

Cancer requiring treatment in the past 5 years, unless the prognosis is considered good

Renal disease (creatinine > 1.4 mg/dl for men, or >1.3 mg/dl for women, or urine

protein >2 + )|

Anemia (hematocrit <36% in men or <33% in women)

Hepatitis (based on history or serum transaminase elevation)

Other gastrointestinal disease (pancreatitis, inflammatory bowel disease)

Recent or significant abdominal surgery

Pulmonary disease with dependence on oxygen or daily use of bronchodilators

Chronic infection (e.g., HIV, active tuberculosis)

Conditions or behaviors likely to affect conduct of the trial

Unable to communicate with clinic staff

Unwilling to accept treatment assignment by randomization

Participation in another intervention research project that might interfere with DPP

Weight loss of > 10% in past 6 months for any reason except postpartum weight loss

Unable to walk 0.25 miles in 10 min

Pregnancy and childbearing

Currently pregnant or within 3 months postpartum

Currently nursing or within 6 weeks of having completed nursing

Pregnancy anticipated during the course of the trial

Unwilling to undergo pregnancy testing or report possible pregnancy promptly

Unwilling to take adequate contraceptive measures, if potentially fertile

Major psychiatric disorder

Excessive alcohol intake, either acute or chronic

Medications and medical conditions likely to confound the assessment for diabetes

Thiazide diuretics

j3-Blockers, systemic

Niacin, in doses indicated for lowering serum triglycerides

Glucocorticoids, systemic

Selective serotonin re-uptake inhibitors in doses indicated for weight reduction

Other prescription weight-loss medications

Thyroid disease, suboptimally treated as indicated by abnormal serum thyroid-stimulating.


Other endocrine disorders (e.g., Cushing’s syndrome, acromegaly)

Fasting plasma triglyceride >600 mg/dl, despite treatment

*WHO criteria (3) were used to exclude diabetes (FPG > 140 mg/dl or 2-h plasma glucose >200 mg/dl)
until June 1997, and the FPG inclusion range was 100~139 mg/dl. |Since March 1998, a creatinine clear-
ance of >75 ml/min, based on a 24-h urine collection, was required for eligibility for potential volunteers
who were or would become >80 years of age during the study.

particularly high risk of diabetes, the FPG

must be 95~125 mg/dl. However, there is no

lower eligibility limit for FPG in the clinical

centers enrolling only American Indians

because they have an unusually high risk of

type 2 diabetes even at lower levels ofFPG (4).

The DPP began before the release of the

new ADA diagnostic criteria in June 1997.

The 1985 WHO criteria for IGT used for

DPP eligibility at that time required an FPG

<140 mg/dl (7.8 mmol/l) and 2-h post-

load plasma glucose;:: 140 mg/dl and

<200 mg/dl (3). An additional DPP

requirement was for the FPG to be 100-139

mg/dl. Only 7% of those enrolled in the

DPP before this change in eligibility criteria

would have been ineligible by the new cri-

teria because ofFPG >126 mg/dl but <140

mg/dl. These participants remain in the

DPP, but their outcome assessment of dia-

betes will be done with the new criteria (1).

Although most recruitment is directed

at overweight individuals aged >35 years,

the age criterion was set at >25 years to

include groups at high risk for type 2 dia-

betes in early adulthood, such as American

Indians and young women with a history of

gestational diabetes (4). The BMI criterion is

>24 kg/m2 because individuals with lower

BMIs are at a lower risk for type 2 diabetes

and may not be suitable candidates for the

weight-loss goals of the interventions. The

BMI criterion was set at >22 kg/m2 for

Asian Americans because of their high risk

of diabetes at this range of BMIs (5).

Most exclusion criteria were chosen to

reduce the risk of adverse effects related to

the interventions. Individuals with clinically

significant ischemic heart disease (defined in

Table 1), aortic stenosis, or uncontrolled

hypertension are excluded because the

intensive lifestyle intervention requires

increased physical activity. Individuals with

renal insufficiency or congestive heart failure

are excluded because of their increased risk

of lactic acidosis with metformin (6,7). Also

excluded are pregnant or nursing women, as

well as women who anticipate pregnancy

during the course of the program, because

met form in has not been shown to be safe

during pregnancy or nursing.

Thiazide diuretics and j3-blockers are

commonly used to treat hypertension (8),

which often coexists with IGT. Because

these agents may cause IGT (9~13), indi-

viduals using thiazides or j3-blockers on a

daily basis are ineligible. Such individuals

may be included if they meet glycemic and

other eligibility criteria after their treatment

is changed to other antihypertensive drugs


The Diabetes Prevention Program Research Group

Table 2~Staged screening process for determination of eligibility



Assessment Comments


Prescreening questionnaire

Single glucose measurement


Physical measurements


Other laboratory assays

3 Run-in/behavioral trial


Clinical evaluation


Serum human chorionic


Review eligibility checklist

Initial assessment for eligibility by telephone

Fasting or casual, in the field or at the clinic

Definitive assessment of age, medical history,

medication use

Assess BMI and blood pressure

FPG 95~125 mg/dl and

2-h plasma glucose 140~199 mg/dl

Liver function tests, electrolytes, serum creatinine,

plasma triglycerides, complete blood count,

thyroid-stimulating hormone, urinalysis

3-week trial of compliance with pill taking

and recordkeeping

History and physical examination

Assessed for acute ischemia or dysrhythmia

Rule out pregnancy

If eligible, then randomize

without known adverse effects on glucose



Clinic-specific recruitment strategies appro-

priate for the identified target populations

include use of mass media, mail, and tele-

phone contacts and recruitment through

employment or social groups or health care

systems. Recruitment workshops were held

for the DPP investigators and staff to share

information and assistance on recruitment,

interpersonal skills and cultural sensitivity.

effective transmission of information, meth-

ods for developing support systems for

problem solving, and clinic-specific recruit-

ment methods. Procedures were developed

to monitor recruitment and provide a timely

response to problems.

Participant recruitment began in June

1996, after completion of the protocol and

manual of operations and approval by the

DPP Steering Committee, the external Data

Monitoring Board, the NationalInstitute of

Diabetes and Digestive and Kidney Dis-

eases (NIDDK), and the Food and Drug

Administration. Recruitment is anticipated

to end ~ 2 2/3 years after this date, in the

first half of 1999. Treatment and follow-up

of all participants are planned to continue

until the middle of 2002.

Staged screening process and

informed consent

A four-step combined screening, recruit-
ment, and informed consent process pro-

vides increasing amounts of information

about the DPP to participants as they

progress through recruitment and screen-

ing (Table 2). Each step in the informed

consent process includes verbal and written

descriptions of relevant information and

opportunity for discussion of questions

from the volunteer, facilitating a decision of

whether to proceed to the next step. A

3-week run-in, or practice, period is

included in step 3 to give prospective par-

ticipants a trial of compliance with pill tak-

ing (placebos only) and keeping records of

diet and physical activity.

Data directly related to eligibility deter-

mination and baseline data are collected

during the screening process. The staged

screening process minimizes the data col-

lection burden on potential participants

and clinic staff by placing simpler, less

expensive assessments (e.g., a 10-min tele-

phone interview) earlier in the screening

process, while more complex assessments

are done later. A participant must com-

plete all the components of step 1 and be

judged potentially eligible before moving

on to step 2, etc. In contrast, progress

within each step is flexible, e.g., a partici-

pant at step 3 may schedule the clinical

evaluation and electrocardiogram (Table 2)

at his or her convenience. To maintain par-

ticipant interest and minimize the likeli-

hood of changes in health during baseline

assessment, yet to give potential volunteers

time to consider participation in an

informed fashion, a window of 3~13 weeks

is allowed from the OGTT in step 2 to ran-
domization at step 4.


Primary outcome. The primary outcome

of the DPP is the development of diabetes

by the 1997 ADA criteria for FPG or 2-h

plasma glucose during an OGTT (1).

Although the eligibility criteria were

selected to identify individuals at high risk

of type 2 diabetes, a small proportion of

individuals recruited into the DPP may be

in the early stages of development of type 1

diabetes (14) or other specific forms of dia-

betes (1). It is not feasible to identify all such

individuals at entry. Therefore, the primary

outcome is defined as diabetes of any type.

Diabetes is assessed by testing FPG

every 6 months and performing an annual

75-g OGTT. FPG is also measured when-

ever symptoms consistent with diabetes

are noted (e.g., polyuria, polydipsia, or

polyphagia). These tests are performed

withoUt interruption of the assigned treat-

ment except that study drugs are omitted

the morning of the test. If the FPG or OGTT

results meet the 1997 ADA criteria for dia-

betes (i.e., either FPG >126 mg/dl or 2-h

plasma glucose >200 mg/dl), a second FPG

or OGTT is performed within 6 weeks. If

both tests are diagnostic of diabetes, the

participant is considered to have reached

the primary outcome. Otherwise, the par-

ticipant will continue on the assigned treat-

ment. To maintain masking, a subset of

participants chosen at random by the Coor-

dinating Center has a repeat annual OGTT
or semiannual test. The annual OGTT and
semiannual FPG are postponed for up to

6 weeks in case of a temporary condition

that could affect glucose tolerance. Partici-

pants who become pregnant during the

study will have outcome assessment sus-

pended until 6~8 weeks after delivery. when

an OGTT is performed. To insure standard-
ized assessment of OUtcomes, any antidia-

betic medication initiated during pregnancy

is stopped before the OGTT. If this is not

possible, two elevated FPG determinations

may be used to define diabetes in place of

the OGTT. Investigators and participants

remain masked to primary outcome data

until progression to diabetes is confirmed.

If the primary outcome of diabetes

occurs, participants, DPP investigators, and

primary care providers are unmasked to

the diagnosis and to subsequent measure-

ments of plasma glucose and HbA1c’

For those participants in whom FPG is

< 140 mg/dl, all study-related oral glucose


Diabetes Prevention Program

tolerance testing is terminated, participants

continue to be followed with FPG at semi-

annual visits, original treatment recommen-

dations are reinforced, coded medication is

continued if the participant and his/her

physician agree, monitoring is intensified,

and self-monitoring of blood glucose is

introduced, with the goal of achieving opti-

mal glycemic control (15). In the event that

participants progress to FPG 2: 140 mg/dl

on two occasions, study medicines are dis-

continued and patients are referred for

appropriate diabetes care (15) independent

of the study protocol. Participants continue

to be followed at scheduled intervals to col-

lect other outcome data, including FPG at

semiannual visits.

Secondary outcomes. The secondary out-

comes include cardiovascular risk profile and

disease; changes in glycemia, j3-cell function,

insulin sensitivity, renal function, body com-

position, physical activity, and nutrient intake;

and health-related quality of life. Safety and

health economics are also monitored. Mor-

talityand morbidity, including cardiovascular

events, are monitored throughout the study,

and the following parameters are evaluated at

specified intervals.

Glycemia. In addition to plasma glu-

cose measured during the OGTT, HbA Ie is

monitored to reflect recent average gly-

cemia, to test its relationship to the OGTT,

and to assess its predictive value for dia-

betes. Specific secondary outcomes will

include the development of fasting hyper-

glycemia at a level of 2: 140 mg/dl (7.8

mmol/l), Le., a level greater than that re-

quired for diagnosis of diabetes, and

improvement in glucose tolerance to normal.

j3-Cell function and insulin sensitivity.

j3-Cell function is estimated from the fast-

ing and 30-min plasma insulin and glucose

during the OGTT and from the fasting

plasma proinsulin. Fasting plasma insulin

is used as a surrogate for insulin sensitivity.

Cardiovascular disease rish profile. Car-

diovascular risk profile is assessed by car-

diovascular history and symptoms, an

electrocardiogram, smoking history, hemo-

static and fibrinolytic factors (C-reactive

protein, fibrinogen, tissue plasminogen acti-

vator), and lipoprotein profile, including

derived j3 quantification (fullj3 quantifica-

tion if triglycerides are >400 mg/dl), LDL

particle size, and LDL apolipoprotein-B.

Cardiovascular disease. Disease meas-

ures include carotid intimal wall thickness

assessed by ultrasonography, arm blood

pressure, and ankle:brachial systolic blood


Kidney function. Urinary albumin and

creatinine concentrations in an untimed

urine sample are used to determine urinary

albumin excretion.

Physical activity, nutrition, and body

composition. Two standardized question-

naire assessments (16~18) are used to

evaluate the level of physical activity, and

a semiquantitative food frequency ques-

tionnaire is used to determine nutrient

intake (19). Body composition measure-

ments include height, weight, waist and

hip circumference, abdominal sagittal

diameter, skin-fold thicknesses, and, in a

substudy of some participants, abdominal

computed tomography scanning for vis-

ceral fat content.

Health-related quality of life. The Beck

Anxiety and Depression Inventories (20),


Medical Outcomes Study 36-item short

form (21), and a social support question-

naire are used to assess mood, general

adjustment, and health-related quality-of-

life issues.

Health economics. Resource utilization,

costs, health utilities, and effectiveness of

treatments to prevent diabetes will be


Safety. Periodic safety tests include

liver function tests, serum creatinine, com-

plete blood count, and pregnancy testing

(as needed), as well as recording of adverse

events and interval history.



Standard lifestyle recommendation. After

randomization, all participants (regardless of

treatment assignment) receive written infor-

mation and a 20- to 30-min individual ses-

sion with their case manager addressing the

importance of a healthy lifestyle for the pre-

vention of type 2 diabetes. Specifically, par-

ticipants are encouraged to follow the Food

Pyramid guidelines and to consume the

equivalent of a National Cholesterol Educa-

tion Program step 1 diet (22); to lose 5~10%

of their initial weight through a combination

of diet and exercise; to increase their activity

gradually with a goal of at least 30 min of an

activity such as walking 5 days each week;

and to avoid excessive alcohol intake. All par-

ticipants who smoke are encouraged to stop.

These recommendations are reviewed annu-

ally with all participants.

Intensive lifestyle intervention. The

intensive lifestyle intervention is based on

previous literature suggesting that obesity

and a sedentary lifestyle may both inde-

pendently increase the risk of developing

type 2 diabetes (23). The goals are essen-

tially the same as those of the standard

lifestyle recommendation, but the approach

to implementation is more intensive.

The goals for the intensive lifestyle

intervention are to:

~ achieve and maintain a weight reduction

of at least 7% of initial body weight

through healthy eating and physical

activity, and to

~ achieve and maintain a level of physical

activity of at least 150 min/week (equiv-

alent to ~700 kcal/week) through mod-

erate intensity activity (such as walking

or bicycling).

Recognizing the difficulty of achieving

long-term changes in eating and exercise

behaviors and in body weight, the intensive

lifestyle intervention is designed to maxi-

mize success by using the following inter-

active interventions: training in diet,

exercise, and behavior modification skills;

frequent (no less than monthly) support for

behavior change; diet and exercise inter-

ventions that are flexible, sensitive to cul-

tural differences, and acceptable in the

specific communities in which they are

implemented; a combination of individual

and group intervention; a combination of a

structured protocol (in which all partici-

pants receive certain common information)

and the flexibility to tailor strategies indi-

vidually to help a specific participant

achieve and maintain the study goals; and

emphasis on self-esteem, empowerment,

and social support. A Lifestyle Resource

Core developed intervention materials and

provides ongoing training and support for

intervention staff.

The intervention is conducted by case

managers with training in nutrition, exer-

cise, or behavior modification who meet

with an individual participant for at least 16

sessions in the first 24 weeks and contact

the participant at least monthly thereafter

(with in-person contacts at least every 2

months throughout the remainder of the

program). The initial 16 sessions represent

a core curriculum, with general information

about diet and exercise and behavior strate-

gies such as self-monitoring, goal setting,

stimulus control, problem solving, and

relapse prevention training. Individualiza-

tion is facilitated by use of several different

approaches to self-monitoring and flexibil-

ity in deciding how to achieve the changes

in diet and exercise. All participants are

encouraged to achieve the weight-loss and

exercise goals within the first 24 weeks.

The weight-loss goal is attempted initially

through a reduction in dietary fat intake to


<25% of calories. If weight loss does not

occur with fat restriction, then a calorie goal

is added.

The focus of the exercise intervention is

a gradual increase in brisk walking or other

activities of similar intensity. Two super-

vised group exercise sessions per week are

provided to help participants achieve their

exercise goal, but participants can also

achieve the exercise goal on their own and

are given flexibility in choosing the type of

exercise to perform. Exercise tolerance tests

(performed in individuals with preexisting

coronary heart disease, and in men aged

>40 years and postmenopausal women

not using hormone replacement therapy

who have at least two coronary heart dis-

ease risk factors) are used to modify the

individual’s exercise program.

For individuals having difficulty

achieving or maintaining the weight-loss or

exercise goal, a “tool box” approach is used

to add new strategies for the participant.

Strategies may include incentives such as

items of nominal value. Additional tool box

approaches may include loaning aerobic

exercise tapes or other home exercise

equipment, enrolling the participant in a

class at an exercise facility, and use of more

structured eating plans, liquid formula

diets, or home visits.

Group courses are also offered quar-

terly during maintenance, with each course

lasting 4~6 weeks and focusing on topics

related to exercise, weight loss, or behav-

ioral issues. These courses are designed to

help participants achieve and maintain the

weight-loss and exercise goals.

Adherence to the intervention is deter-

mined through monitoring by the case

manager, measuring weight at the 6-month

assessments, and self-reported physical

activity and diet.

Drug interventions

Metformin and its corresponding placebo

are the pharmacological treatments. They

are started at a dose of 850 mg once daily

and increased to 850 mg twice daily. The

dosage can be adjusted if necessary because

of gastrointestinal symptoms.

Adherence to study medication is

assessed by pill counts and a structured

interview of pill-taking behavior. A Med-

ication Resource Workgroup was formed to

enhance adherence to the medication pro-

tocol while promoting retention of partici-

pants. This group supports clinic staff,

specifically the medication case managers,

by providing a communication network

The Diabetes Prevention Program Research Group

for information, training in counseling and

assessment skills, problem-solving of indi-

vidual participant or clinic situations, and

ideas for the tool box for medication adher-

ence. Clinic data are reviewed by the work-

group so that patterns of poor adherence to

the protocol can be identified early and

interventions can be implemented.


Several potential obstacles to retention have

been identified, such as dissatisfaction with

randomly assigned treatment, masking of

some of the test results, and time commit-

ments. Other barriers include the demands

and costs of transportation, parking, and

child and elder care, which vary consider-

ably among the target populations. Steps to

maximize retention are based on recogniz-

ing these barriers and committing resources

for their removal.

Adherence and retention are fostered

by a comprehensive array of participant

education procedures, which require the

interest, responsiveness, and continuous

availability of the professional staff, and

motivational programs, group activities,

and rewards deployed according to the

judgment of each clinic. Quarterly newslet-

ters are given to participants to encourage

a sense of community within

the DPP.

Program and Recruitment Coordinators

were trained in motivational interviewing,

an approach to changing behavior, based on

several basic principles, including skillful

reflective listening, expression of empathy,

and acceptance of ambivalence (24). Dis-

crepancies are developed by increasing

awareness of consequences of behaviors,

showing the discrepancy between present

behavior and important goals.

Procedures are in place to identify par-

ticipants whose level of adherence and/or

attendance should trigger recovery efforts,

as well as a graded hierarchy of recovery

efforts. A computer-based monitoring sys-

tem allows identification of participants

having problems with adherence to the

protocol and those likely to drop out, thus

qualifying for recovery efforts. Question-

naires are administered at baseline, semi-

annually, and at the end of study for

purposes of predicting adherence and

retention and determining the positive or

negative impact of study interventions.

Since the retention of a large portion of

the participants throughout the study is

key to the statistical power and validity of

the DPP findings, mechanisms are in place

to recover those who no longer actively

participate. Inactive participants continue

to be contacted to remind them of the
opportunity to reenter the DPP and to

complete the final assessment at the end of

the DPP.

Concomitant conditions

Concomitant conditions are defined as

medical illnesses or conditions requiring

treatment that could affect implementation

of the research protocol. Since most clinical

centers do not provide all primary or ancil-

lary care, the program assists other health

care providers in following guidelines for

therapy of concomitant conditions. Treat-

ments that could affect study outcomes are

discouraged when appropriate alternate

treatments are available. The following con-

ditions were considered: pregnancy, lacta-

tion, hypertension, dyslipidemia, smoking,

and cardiovascular diseases.

Women of child-bearing potential are

asked to practice reliable contraception in

view of the unknown risks of the study

drugs on the fetus and mother. Safety mon-

itoring includes pregnancy tests and

monthly menstrual diaries. Women ran-

domized to the drug treatments (including

placebo) who become pregnant while tak-

ing medication are unmasked to treatment

to allow counseling about the potential

effects of the study drugs on the fetus, and

study medication is permanently discon-

tinued. For women who want to become

pregnant, medication is discontinued until

the completion of the pregnancy and nurs-

ing; medication is not unmasked.

Standard guidelines for diagnosis and

treatment of hypertension in adults (25)

are used, except that diuretic agents and

j3-adrenergic blocking agents are strongly

discouraged because they may worsen glu-

cose tolerance (9~13).

The standard and intensive lifestyle

intervention diet plans meet the National

Cholesterol Education Program standards for

dietary management of dyslipidemia (22). At

6 months, 12 months, and annually there-

after, lipid profiles are used to determine

whether individuals qualify lar lipid-lower-

ing agents. Individuals whose lipid levels

during follow-up qualify them for drug ther-

apy based on the guidelines of the National

Cholesterol Education Program (22) have

reached a DPP secondary outcome. Their

lipid levels are unmasked to aid clinical deci-

sions about pharmacotherapy, which will fol-

low these guidelines (22). The use of

nicotinic acid is strongly discouraged because

it can worsen glucose intolerance (26).


Diabetes Prevention Program

Standard approaches are followed to

reduce smoking by discussing its impact on

cardiovascular disease and emphasizing the

overall health benefits of quitting. Partici-

pants are given self-help materials and

referred to smoking cessation programs if


Cardiovascular disease incidence is

likely to be increased in this population

with IGT (27), and these diseases and their

treatments may have an effect on DPP

study outcomes, or vice versa. Participants

who experience new episodes of myocar-

dial infarction, unstable angina, or treat-

ment for coronary heart disease (e.g.,

percutaneous transluminal angioplasty or

coronary artery bypass graft) are eligible to

continue following DPP interventions,

except for participants randomized to the

intensive lifestyle intervention. These par-

ticipants may not resume their DPP exer-

cise program until risk is estimated by

exercise testing, which may result in mod-

ification of the exercise program. Patients

who develop new-onset angina pectoris

during the DPP are referred for appropriate

diagnosis and/or interventions, and their

exercise program is discontinued until their

cardiologic evaluation is complete. Treat-

ment of cardiac patients with j3-blockers is

not impeded by DPP participation.

Biostatistical considerations
Sample size goal. Several published stud-

ies have examined the rates of conversion
from IGT to diabetes defined by WHO cri-
teria (3). There were 21 studies identified
that allowed computation of the partici-
pant-years of follow-up and the incidence
rates of diabetes by the person-years of fol-

low-up. Overall, the conversion rates
ranged as follows: 2.3 per 100 person-years
among Japanese populations, 3 per 100

person-years for Caucasians and Mexican-
Americans, 4.7 per 100 person-years for
Nauruans, 4.0 per 100 person-years for

women with a history of gestational dia-
betes, and between 10 and 11 per 100 per-

son-years for Asian Indians and Pima
Indians (23,28~29). In data from six pop-
ulation-based cohorts provided to the DPP
for calculation of conversion rates from
IGT to diabetes (4) defined by WHO crite-
ria (3), the overall conversion rate was 5.8
per 100 person-years of follow-up. To

decrease the required sample size, a crite-
rion of IGT with elevated FPG was chosen
for eligibility in the DPP. For participants
with an elevated FPG of 95~125 mg/dl, the
conversion rate from IGT to diabetes

defined by the ADA criteria (1) was 7.7 per

100 person-years of follow-up in the six

studies combined (4). To allow for an addi-

tional margin of error, the DPP sample size

was based on an expected conversion rate

of 6.5 per 100 person-years among partic-

ipants assigned to the standard lifestyle rec-

ommendations plus placebo.

The following assumptions were used

to determine the sample size goal:

~ The primary outcome is time to the con-

firmed development of diabetes by ADA

criteria (1).

~ Participants are uniformly randomized

to one of the three treatment groups dur-

ing a 2 2/3~year period, and all ran-

domized participants are followed for

an additional 3 1/3 years after the close

of randomization (Le., follow-up time

for each person is between 3 1/3 and 6


~ The type I error rate (@) is 0.05 (two-

sided) with a Bonferroni adjustment (30)

for three pairwise comparisons of the

three treatment groups.

~ In those assigned to the standard lifestyle

recommendation plus placebo, time to

the development of diabetes is exponen-

tially distributed with a diabetes devel-

opment hazard rate of 6.5 per 100


~ For participants assigned to the intensive

lifestyle or metformin intervention

groups, the diabetes development haz-

ard rate is reduced by >33%, Le., to

<4.33 per 100 person-years.

With these assumptions, the total effec-

tive sample size necessary to achieve 90%

statistical power is 2,279 participants (31).

Assuming that randomized participants

prematurely discontinue their follow-up

visits before confirmed development of dia-

betes with an exponential loss hazard rate

of < 10 per 100 person-years, the random-

ization goal of the DPP is 2,834 partici-

pants, which was increased to 3,000

participants (1,000 per group).

Assignment to treatment groups. To

ensure balance among the three treatment

groups with respect to anticipated differ-

ences in the participant populations and

possible differences in participant manage-

ment, adaptive randomization is stratified

by clinical center. An adaptive randomiza-

tion procedure provides a high probability

of balance in treatment assignments and is

unpredictable by adjusting the treatment

group allocation probabilities according to

the actual imbalance in the numbers of

participants assigned to the groups (32).

Statistical analysis plan. The principal

analyses of primary and secondary out-

comes will use the intent-to-treat approach

(33). The intent-to-treat analyses will

include all participants in their randomly

assigned treatment group regardless of a

participant’s adherence to the assigned

treatment regimen.

The principal analysis of the DPP will

be a life-table analysis of time to confirmed

development of diabetes. Separate product-

limit life-table estimated cumulative inci-

dence curves will be calculated for each

treatment group and the groups will be

compared using a log-rank test (34). For

the primary outcome analysis, participants

will be considered “administratively cen-

sored” if they complete the full duration of

the DPP without confirmed development

of diabetes. Participants who prematurely

discontinue their follow-up visits before

confirmed development of diabetes will be

censored as of their last follow-up visit.

Mortality prior to the development of

diabetes may be a competing risk event for

the primary outcome (35). To account for

mortality as a competing risk event, the

treatment groups will be compared on the

composite event, defined as confirmed

development of diabetes or all-cause mor-

tality, whichever occurs first, using the

same methods described above for the pri-

mary outcome.

Secondary time to event outcomes

(e.g., mortality, cardiovascular morbidity)

will be analyzed using the same life-table

methods described above for the primary

outcome. A proportional hazards regres-

sion model will be used to evaluate poten-

tial covariables that may modify the primary

and secondary time to event outcomes (e.g.,

risk population defined by race/ethnicity

and history of gestational diabetes, baseline

fasting and 2-h glucose, clinical site).

Graphical procedures will be used to assess
the proportionality assumption.

Some processes may involve recurrent

events, such as moving back and forth

between IGT and normal glucose toler-

ance. For these recurrent events, the family

of statistical models based on the theory of

counting processes will be applied (36).

Longitudinal data analysis techniques

will be used to analyze repeated measures

data (e.g., glycemia, fasting lipids, blood

pressure, physical activity, quality of life).

These include analyses of the point preva-

lence of a discrete characteristic (e.g.,

hypertension) at successive repeated visits

over time (37), multivariate rank analyses


of quantitative (2-h plasma glucose during

the OGTT) or ordinal (score from the

Medical Outcomes Study 36-item short

form) measures over successive visits (38),

a parametric linear random effects model

(39) to compare participant slopes over

time (e.g., rate of change in FPG) under a

linearity and normality assumption, and

techniques to compare participant slopes

under a generalized linear models frame-

work (40).

The lan-DeMets (41) spending func-

tion approach will be used to adjust the

probability of a type I error for testing the

primary outcome when interim looks of

the data are taken by the external Data

Monitoring Board. The spending function

corresponding to an O’Brien and Fleming

(42) boundary will be used. The rate at

which the type I error is spent is a function

of the fraction of total information available

at the time of the interim analysis (Le.,

information time). For an interim analysis

using the log-rank test (i.e., time to con-

firmed development of diabetes), the infor-

mation time is the fraction of the total

number of confirmed diabetes events to be

accrued in the entire DPP. Since the total

number of events to be accrued is

unknown, an estimate of the information

time will be based on the fraction of total

participant exposure (43).



Clinical centers. Each of the 27 partici-

pating clinical centers has a PrincipalInves-

tigator, a Program Coordinator and

additional staff to carry out the protocol

that may include recruitment coordinators,

dietitians, behaviorists, exercise physiolo-

gists, physicians, nurses, data collectors,

and others.

Coordinating center and central resource

units. The Coordinating Center is responsi-

ble for biostatistical design, analysis, and

data storage and processing. Central

resource units include the Central Biochem-

istry Laboratory, Nutrition Coding Center,

Electrocardiogram Grading Center, Carotid

Ultrasound Reading Center, Computed

Tomography Scan Reading Center, Lifestyle

Resource Core, Medication Resource Work-

group, and a public relations firm. These

units serve as central laboratories and read-

ing centers for samples collected and studies

performed in the clinical centers, and they

provide assistance with recruitment, treat-

ment’ and retention of participants.

The Diabetes Prevention Program Research Group

NIDDK project office. The NIDDK pro-

gram officer participates in the scientific

efforts of the DPP Research Group and is

involved in the development of the proto-

col and conduct of the DPP.

Steering committee and subcommittees.

The Steering Committee is the representa-

tive body of the DPP Research Group. The

Committee consists of the Principallnvesti-

gator from each clinical center and the

Coordinating Center, and the NIDDK rep-

resentative. This committee sets policies,

makes decisions, and oversees the adminis-

trative aspects of the DPP Research Group.

Subcommittees, comprised of mem-

bers of the Research Group, develop

detailed policies and procedures and make

recommendations to the Steering Commit-

tee. The chairpersons of the subcommittees

are members of the Planning Committee,

which serves as the forum in which the

work of the subcommittees is initially

reviewed and coordinated. The following

subcommittees were active during the

planning phase to develop the protocol

and detailed study procedures: Ancillary

Studies, Concomitant Conditions, Inter-

ventions, Outcomes, Publications and

Presentations, Program Coordinators,

Recruitment and Retention, and Screening

and Eligibility.

Data monitoring board. The Data Moni-

toring Board provides external review and

advice to the NIDDK and the Steering

Committee. It consists of experts in rele-

vant biomedical fields, biostatistics, and

medical ethics who were appointed by the

director of the NIDDK. Prior to the initia-

tion of recruitment, the Data Monitoring

Board reviewed all study material to ensure

the scientific validity of the study and safety

of participants. Its principal responsibility is

to monitor the emerging results of the DPP

to assess treatment effectiveness and par-

ticipant safety. Based on these considera-

tions, the board may recommend to the

NIDDK that the protocol be modified or

that the DPP be terminated.

Data management

Clinical centers. A remote data manage-

ment system consists of a network of micro-

computers, one at each clinical center and

one at the Coordinating Center. Data col-

lected on paper forms are double-entered

into the local computer by clinical center

staff and checked for allowed ranges and

internal consistency. Electronic copies of the

newly entered and updated data are trans-

mitted weekly via telecommunications link

to the Coordinating Center, where they are

compiled into the DPP master database with

data from all clinical centers. Weekly edit

reports are sent to each clinical center with

out-of-range values, inconsistencies, and dis-

crepancies within forms. Monthly audit pro-

grams produce more detailed edits across all

forms for an individual participant.

Central resources. Data from central

resources (e.g., the central biochemistry

laboratory) are transmitted via direct

telecommunications link to the Coordinat-

ing Center, where they are compiled into

the DPP master database.

DISCUSSION ~ Treatment of diabetes

is often unsuccessful in preventing its

adverse outcomes, including vascular dis-

ease, neurological complications, and pre-

mature death. Prevention of type 2 diabetes

would, therefore, be preferable, and may be

possible through modification of risk fac-

tors (44). Despite considerable variation

among people in the relative importance of

genetic and environmental causes of type 2

diabetes, in all populations and ethnic

groups, most patients have both insulin

resistance and j3-cell dysfunction. These

appear to be the underlying metabolic

abnormalities leading to the disease

(45,46). Thus, interventions aimed at

reducing insulin resistance and preserving

j3-cell function are anticipated to be bene-

ficial in delaying or preventing most cases

of type 2 diabetes in all populations.

Target groups and goals for


A goal of diabetes prevention activities

should be to maintain or improve the health

of individuals at high risk of type 2 diabetes

by preventing or delaying the onset of the

disease and associated complications. The

primary goal of the DPP is, thus, to compare

several currently feasible strategies to pre-

vent or delay type 2 diabetes. Secondary

outcomes include the complications of type

2 diabetes, such as cardiovascular and renal

diseases and their risk factors, and all-cause

mortality rates. Because the DPP may not

have sufficient duration to test treatment

effects on late complications and mortality,

the study will also assess the effects of the

treatments on delaying or lessening the

development of cardiovascular risk factors

and surrogate measures of cardiovascular

disease. Measurements related to j3-cell

function and insulin sensitivity may help

explain the mechanism by which the pri-

mary outcome was achieved.


Diabetes Prevention Program

Although prevention of diabetes might

require modification throughout the lives of

susceptible individuals of the many predis-

posing physiologic abnormalities that are

caused by genetic factors (most of which are

currently unknown) and socioeconomic

conditions, it is impractical to design inter-

ventions addressing all these factors. The

logistic constraints of a randomized clinical

trial dictate tests of interventions in individ-

uals who are relatively close to the onset of

disease. Thus, the DPP will enroll volunteers

at high risk of developing type 2 diabetes by

vinue of having IGT and elevated FPG. IGT

is accompanied by insulin resistance with

compensatory hyperinsulinemia that main-

tains glycemia in the nondiabetic range.

When insulin secretion is no longer sufficient

to compensate for insulin resistance, hyper-

glycemia worsens to the point of diabetes

(47). Despite the high repeat test variability of

the OGTT (48), the prognostic value ofIGT

has been well established in many popula-

tion studies (23). The incidence of type 2 dia-

betes is even higher in subsets of individuals

with IGT, such as those who are obese or

who have higher FPG concentrations (4).

Thus, these additional risk factors were

included in the eligibility criteria.

Selection of the lifestyle


Individuals with greater BMI or abdominal
fat distribution and those who are less
physically active are more likely to develop
type 2 diabetes (23). Changes in diet and

an increasingly sedentary lifestyle, with
consequent increased body mass, have

been associated with the development of
type 2 diabetes in recently industrialized
populations and in migrating populations

that previously had a low prevalence of
diabetes. Thus, it is hypothesized that
lifestyle interventions aimed at reducing
weight and increasing physical activity may
help to prevent type 2 diabetes (44).

A goal of losing;::; 7% of body weight
was selected for the DPP because losses of
this magnitude have been achieved and
maintained in previous clinical trials and
appear to improve insulin sensitivity and

glycemic control in individuals with type 2

diabetes. The physical activity goal of 150
min/week of moderate activity such as
walking (equivalent to ~700 kcal/week) is

in agreement with the national physical
activity recommendations of the Centers

for Disease Control and Prevention and the

American College of Sports Medicine (49).
Modest increases in exercise improve

insulin sensitivity and promote long-term

maintenance of weight loss.

The feasibility of behavioral interven-

tions for the prevention of type 2 diabetes

has been demonstrated in Malmo, Sweden,

in a study of two groups of middle-aged

men with IGT (50). Men with IGT were

treated with an intensive diet and exercise

program for 5 years. The rate of develop-

ment of diabetes in these men was only half

that of a nonrandomized comparison group

for whom this intervention was not pro-

vided. This study is important primarily in

demonstrating the feasibility of carrying out

a diet -exercise program for 5 years. The

effect of treatment, however, remains uncer-

tain because the treatment groups were not

assigned at random and differed in their

medical conditions at baseline.

Preventive effects of diet and exercise

have been reponed in a randomized clinical

trial in adults with IGT in Da-Qing, China,

in which interventions involving diet alone,

exercise alone, or both in combination were

assigned on a clinic basis (51). The 6-year

cumulative incidence of diabetes was lower

in all three intervention groups than in the

control group receiving no interventions,

and there were no significant differences

between the three intervention groups.

Selection of the drug interventions

Drugs considered as a means to prevent the

development of type 2 diabetes belonged to

six classes: 1) biguanides, 2) thiazolidine-

diones, 3) sulfonylureas, 4) inhibitors of

carbohydrate absorption, 5) fatty acid oxi-

dase inhibitors and anti-lipolytic drugs, and

6) weight-loss agents. To be selected, drugs

had to have a proven record of efficacy in

lowering glycemia in people similar to those

to be enrolled in the DPP, have an accept-

able safety profile, and not create untoward

problems in adherence or retention.

Biguanides. Metformin, the only drug con-

sidered in this category, has beneficial effects

on glucose homeostasis by suppressing ele-

vated rates of hepatic glucose production in

type 2 diabetes (52). It may also have a mod-

est effect of delaying or inhibiting glucose

absorption from the gastrointestinal tract

(53). Finally, metforrnin may improve insulin

sensitivity (7). Any treatment that lowers

plasma glucose can also improve insulin sen-

sitivity by ameliorating the direct effect of

hyperglycemia on insulin resistance (54,55).

In some studies of nondiabetic insulin-

resistant individuals, metformin directly

improved insulin sensitivity, even without

concomitant weight loss (56,57). This

improvement in insulin sensitivity is accom-

panied by a lowering of plasma insulin lev-

els, and, in some cases, is also accompanied

by lowering of blood pressure and improve-

ment in lipid profiles (58). Metformin has

only a small effect on the postprandial incre-

mental glucose level, and, therefore, the

overall glycemic lowering effect is due to the

reduction in FPG. Based on its mechanism of

action plus a I-year study in France, in

which metformin improved risk factors for

type 2 diabetes (59), this drug is an excellent

intervention candidate.

Metformin has been used for many

years outside the U.S. with a very well

understood safety profile. The major seri-

ous adverse effect is lactic acidosis, which is

extremely rare, and even then occurs only

when the drug is used inappropriately in

patients with renal insufficiency or who are

undergoing surgery (60). The other major

side effect of metformin relates to gastroin-

testinal symptoms (60), which can be

minimized and usually tolerated with

appropriate titration of dosage. Based on a

large number of clinical trials, it appears

that the percentage of patients in whom the

drug must be discontinued because of gas-

trointestinal side effects is <5% (61). Based

on these considerations, metformin was

selected as a drug treatment in the DPP.

Thiazolidinediones. Drugs in this class

work exclusively by enhancing tissue

insulin sensitivity (62). Because troglita-

zone was the only agent within this class

under clinical development in the U.S., it

was considered for the DPP. Clinical stud-

ies show that in IGT, type 2 diabetes, or

polycystic ovarian syndrome, troglitazone

successfully improves insulin sensitivity,

with effects ranging from 50 to 100%

improvement, depending on the measure

of insulin sensitivity used (63~65). The

drug also lowers plasma insulin concentra-

tions and both fasting and postprandial

glycemia (63,64). In individuals with IGT

treated with troglitazone, insulin sensitivity

improves strikingly, accompanied by a low-

ering of fasting and postprandial glucose

and insulin levels (64,66). In short-term

studies of troglitazone-treated individuals

with IGT, ~80% convened from IGT to

normal glucose tolerance after 3 months of

treatment (64,66). A modest decline in

blood pressure and plasma triglycerides

has been consistently observed, along with

an increase in plasma HDL levels (65,66).

In 1997, troglitazone was approved for

treating type 2 diabetes by the Food and

Drug Administration in the US Long-term


safety data are lacking, although in pre-

marketing studies, no serious side effects

were observed, and the frequency of side

effects was comparable with that or placebo

(67). A few cases of irreversible liver failure

were reported in post marketing surveil-

lance, however, necessitating the careful

monitoring of liver function during treat-

ment. Given the acceptable sarety profile,

the need ror only one dose per day, and an

ideal mechanism or action, troglitazone was

selected as one or the drug treatments in

the DPP. Due to liver toxicity, however, its

use in the DPP was discontinued during

recruitment (see APPENDIX 1).

Other categories of drugs. The other med-

ication classes considered were not selected

because or concerns for safety, side effects,

or efficacy. Sulfonylureas were seriously

considered because of the role of deficient

insulin secretion in the pathogenesis or type

2 diabetes. They were not chosen, however,

because they can cause hypoglycemia,

which can be a serious and life-threatening

side effect. This risk was deemed unwar-

ranted in a prevention study or people with

IGT who were otherwise healthy.

CONCLUSIONS ~ Obesity and phys-

ical inactivity are potentially modifiable risk

factors for type 2 diabetes. Modirying them,

however, is very challenging, and it has not

been clearly established whether such mod-

ification reduces the incidence of diabetes.

Insulin resistance and impaired insulin

secretion, the metabolic defects predicting

type 2 diabetes, can also be treated pharma-

cologically. The hypothesis that such treat-

ment can prevent diabetes has not been

adequately tested.

Randomized clinical trials are needed

to test both behavioral and drug treat-

ments, with emphasis on measuring and

enhancing compliance. The DPP is a ran-

domized clinical trial to test three

approaches to treatment of individuals with

IGT and other high-risk characteristics for

type 2 diabetes. These treatments include

diet, exercise, and treatment or hypergly-

cemia and insulin resistance with met-

rormin. The goal is to determine the most

effective interventions in those at high risk

or type 2 diabetes, so that in the future the

tremendous burden or this disease and its

complications can be reduced.

Acknowledgments~ The DPP is sup-

ported by the National Institutes or Health

through the NIDDK, the Office or Research on

The Diabetes Prevention Program Research Group

Minority Health, the National Institute or Child

Health and Human Development, and the

National Institute on Aging. In addition, the

Indian Health Service, the Centers ror Disease

Control and Prevention, the American Diabetes

Association, and two pharmaceutical compa-

nies, Bristol-Myers Squibb and Parke-Davis,

contribute support. All support to the clinical

centers and the Coordinating Center is pro-

vided through the NIDDK using the mechanism

or the Cooperative Agreement, except ror the

Southwestern American Indian Center, which is

supported directly by the NIDDK and the

Indian Health Service.


This paper is dedicated to the memory or

Dr. Julio V. Santiago (1942~1997), who was

the Principal Investigator of the Clinical

Center at Washington University, St. Louis.

He made extraordinary contributions to the

planning, design, and implementation of

the DPP. His warmth and intellectual curios-

ity were inspirational to all or us.

APPENDIX 1 ~ The original study

design included four treatment arms. In

addition to the three described above, the

fourth group received the standard lifestyle

intervention combined with the drug

troglitazone given at a fixed dose of 400 mg

once daily. Because tablets for metrormin

and troglitazone are easily distinguishable,

separate placebos were prepared ror each

drug. To maintain drug masking, each per-

son assigned to medication took active

metformin plus a placebo corresponding to

troglitazone, active troglitazone plus a

placebo corresponding to metformin, or a

placebo corresponding to each drug.

One DPP participant treated with

troglitazone developed hepatic railure

requiring liver transplantation and, in the

presence of other complicating illness, sub-

sequently died. This case was immediately

reviewed by the DPP Data Monitoring

Board, which concluded that, given the

lack or established benefits or this drug in

the DPP and the inability of intensive sarety

surveillance to prevent this severe adverse

event, the risk to other participants or con-

tinuation was unacceptable. On the Boards

recommendation, therefore, the NIDDK

suspended the troglitazone treatment in

the DPP on 4 June 1998. The 585 partici-

pants randomized to this drug were

unmasked to their intervention assign-

ment, and their study medication (active

troglitazone plus metformin placebo) was

discontinued. They will be rollowed for

glycemia with semiannual visits until the

middle or 2002. To provide these partici-

pants with basic inrormation about weight

loss, healthy eating, and exercise, they are

invited to quarterly group sessions with

lessons and printed materials addressing

the principal educational components of

the lifestyle intervention. The objective or

continued follow-up is to assess differences

over time in glycemia, insulinemia, and

cardiovascular and adverse events within

the troglitazone cohort and between the

troglitazone cohort and the concurrent

control group of participants treated with

double-placebo during the DPP.

The other pharmacologic-treated par-

ticipants were told they were not taking

active troglitazone, but remained masked

as to their metformin or placebo assign-

ment. They discontinued their troglitazone

placebo but continue their active or

placebo metrormin.

Comparison of the troglitazone cohort

and the concurrent placebo control group

ror time to confirmed development or dia-

betes and other time to event outcomes

(e.g., development or cardiovascular dis-

ease) will use the same life-table methods

described for the principal analyses or the

three treatment groups. The longitudinal

data analysis techniques described for the

principal analyses will also be used to assess

differences over time in glycemia, insuline-

mia, and cardiovascular risk ractors within

the troglitazone cohort and between the
troglitazone cohort and the concurrent

placebo control group. The principal analy-

ses of primary and secondary outcomes in

the DPP will exclude the participants

assigned to troglitazone, because this treat-

ment was discontinued early.


Members of the Research Group

The rollowing individuals and institutions
constitute the Diabetes Prevention Program
Research Group (*Principal Investigator;

Program Coordinator):

Pennington Biomedical Research Cen-
ter~ G.A. Bray, MD*, I.W. Culbert, BSN,
RN, CCRC**, C.M. Champagne, PhD, RD,

L. Dawson, B. Eberhardt, RD, LDN, F.L.
Greenway, MD, F.G. Guillory, LPN, A.A.
Hebert, RD, M.L. Jeffirs, LPN, B.M.
Kennedy, MPA, J.C. Lovejoy, PhD, L.H.
Morris, BS, L.E. Melancon, BA, BS, L. Reed,

J. Pe rault, D.H. Ryan, MD, D.A. Sanford,
LPN, KG. Smith, BS, MT, L.L. Smith, BS,


Diabetes Prevention Program

].A. St.Amant, RTR, R.T. Tulley, PhD, P.C.
Vicknair, MS, RD, D. Williamson, PhD,
and ].]. Zachwieja, PhD; University of

Chicago- K.S. Polonsky, MD*, M.J. Mat-
ulik, RN, BSN**, B. Clarke, MD, C. DeSan-
dre, BA, D.A. Ehrmann, MD, R.M.

Hilbrich, RD, W.L. McNabb, EdD, D. Mor-
rone, RN, BSN, A.R. Semenske, MS, RD,

K.A. Stepp, MS, and].A. Tobian, MD, PhD;
Jefferson Medical College~ P.G. Watson,
RN, ScD*,].F. Caro, MD, B.J. Goldstein,

MD, PhD, C.M. Graziani, MD, E.J. Kunkel,
MD, c.A. Laine, MD, D.Z. Louis, MS, K.A.
Smith, BSN, ]. Spandirfer, MD, and E.J.
Yuen, MBA; University of Miami~ R.B.
Goldberg, MD*, P. Rowe, MPA**,]. Calles,
MSEd, R.P. Donahue, PhD, H.]. Florez,
MD, A. Giannella, RD, MS, P. O’Hara, PhD,

and R. Prineas, MD, PhD; The University
of Texas Health Science Center~ S.M.
Haffner, MD, MPH*, M.G. Montez, RN,
MSHP, CDE**, H. Miettinen, MD, PhD,

C.M. Mobley, PhD, and L.A. Mykkanen,
MD, PhD; University of Colorado- R.F.

Hamman, MD, DrPH*, P.V. Nash, MS**,

B.N. Calonge, MD, MPH, ].0. Hill, PhD,
B.T. Jortberg, MS, RD, CDE, ].G. Regen-
steiner, PhD,]. Reusch, MD, C.M. Schiltz,
MS, RN, RD, H. Seagle, MS, RD, and B.

VanDorsten, PhD; Joslin Diabetes Cen-
ter~ E.S. Horton, MD*, K.E. Lawton,

RN* *, R.A. Arky, MD, M. Bryant, ].P.
Burke, BSN, E. Caballero, MD, K.M.
Callaphan, BA, O.P. Ganda, MD, T.

Franklin, S.D. Jackson, MS, RD, A.M.

Jacobsen, MD, L.M. Kula, RD, M. Kocal,
RN, CDE, M.A. Malloy, BS, M. Nicosia,
MS, RD, C.F. Oldmixon, RN,]. Pan, BS,

MPH, M. Quitingon, S. Rubtchinsky, BS,

E.W. Seely, MD, D. Schweizer, BSN, D.
Simonson, MD, F. Smith, MD, C.G.
Solomon, MD, MPH, and]. Warram, MD;

University of Washington~ S.E. Kahn,
MB, ChB*, B.K. Montgomery, RN, BSN**,

M. Berger, BS, E.J. Boyko, MD, W.Y. Fuji-
moto, MD, C.J. Greenbaum, MD, R.H.
Knopp, MD, B.S. McCann, PhD, E.W. lip-

kin, MD, T.T. Nguyen, BA,].P. Palmer, MD,

R.S. Schwartz, MD, C. Talbot-Lawson, RN,
and D. Wan, MS, RD; University of Ten-
nessee~ A.E. Kitabchi, PhD, MD*, M.E.
Murphy, RN, MS, CDE, MBA**, W.B.
Applegate, MD, MPH, M. Bryer-Ash, MB,
MRCp, FRCp, S.L. Frieson, RN, R. lmseis,

MD, c.L. Kennedy, PhD, H.C. Lambeth,
RN, BSN, L.c. Lichtermann, RN, BSN, H.

Oktaei, MD, M.L. O’Toole, PhD, L.M.K.
Rutledge, RN, BSN, A.R. Sherman, MS,
RD, CDE, C.M. Smith RD, MPH, ].E.

Soberman, MD, and B.J. Williams-Cleaves,

MD; Northwestern University Medical

School~ B.E. Metzger, MD*, M.K. John-
son, MS, RN**, M. Fitzgibbon, PhD, D.
Heard, MA, C.K.H. Johnson, MS, RN, D.

McPherson, MD, M.E. Molitch, MD, M.
Moore, MS, RD, T. Pius, MD, and P.A.
Schinleber, RN, MS; Massachusetts Gen-

eral Hospital~ D.M. Nathan, MD*, C.
McKitrick, BSN* *, K. Abbott, E. Anderson,
MS, RD, E. Cagliero, MD, M. Cohen, MS,
PT, S. Crowell, BSN, L. Delahanty, MS, RD,

E. Levina, BA, T. Michel, MS, PT,]. O’Keefe,
PhD, A. Poulos, BA, L. Ronan, MD, M.
Rosal, PhD, M. Salerno, BA, C. Shagensky,
BA, B. Steiner, EdM, and A. Young, MPH,

CHES; University of California, San

Diego- J.M. Olefsky, MD*, M.L. Carrion-
Petersen, RN, BSN

* *, E. Barrett -Connor,
MD, M. Beltran, RN, BSN, CDE, K.

Caenepeel, S.V. Edelman, MD, R.O. Ford,].
Garcia, R.R. Henry, MD, M. Hill,]. Home,
RD, D. Leos, S. Mudaliar, MD, A. Pollard,

and]. Torio; St. Luke’s-Roosevelt Hospi-
tal~ F.X. Pi-Sunyer, MD* ,].E. Lee, MS**,

D.B. Allison, PhD, N.J. Aronoff, MS, RD,
I.M. Barreras,].P. Crandall, MD, S.T. Foo,
MD, S.J. Orlando, BA, K. Parkes, RN, E.S.

Rooney, BA, G.E.H. Van Wye, MA,

and K.A. Viscovich, ANP; Indiana Uni-
versity~ M.J. Prince, MD*, S.M. Kuk-
man, RN, CDE**, Y.F. Dotson, BS, E.S.
Fineberg, MD, ].c. Guare, PhD, ].M.

Ignaut, MA, M.A. Jackson, M.s. Kirkman,
MD, D.G. Marrero, PhD, B.D. Porter, MSN,

N.D. Rowland, BS, MS, and M.L. Wheeler,
RD; Medlantic Research Institute~ R.E.

Ramer, MD*, G. Youssef, RD, CDE**, M.
Bronsord, MS, RD, CDE, W.W. Cheatham,
MD, G. Boggs, MSN, RN, C. Evans, C. Lev-
atan, MD, T. Kellum, MS, RD, CDE, A.K.
Nair, BS, and M.D. Passaro, MD; UCLA

Medical School/University of Southern
California~ M.F. Saad, MD*, A. Khan,

MD**,A.Aziz, MD, B. Bernaba, MD, M.D.
Budgett, C. Cosenza, RD,].E. Hagar, BS, K.
lsagholian, MD, S.D. Jinagouda, MD, V.V.
Kamdar, MD, D. Kumar, MD, Q. Khawaja,
MD, B.L. Kelada, MD, G. Lui, A.R.

Marston, PhD, V. Mehta, MD, A.R. Sharma,
MD, K. Szamos, RD, A. Vargas, B. Vargas,

and N. Zambrana; Washington Univer-
sity, St. Louis- S. Dagogo-Jack, MD*,

A.E. Santiago, RN** ,].5. Brendle, MT, E.B.
Fisher Jr., PhD, D.C. Gherardini, RN, ].M.
Heins, RD, ].M. Marsala, RN, c.c. Rasp-

berry, MSW,],V. Santiago, MD, and c.L.
Stephan, RN; Johns Hopkins School of

Medicine~ C.D. Saudek, MD*, V.L.
Bradley, BA

* *, F.L. Brancati, MD, MHS, s.
Cappelli, BA, ].B. Charleston, RN, MSN,

R.R. Rubin, PhD, K.]. Stewart, EdD, and E.
Sullivan, MEd, RN; University of New
Mexico School of Medicine~ D. S.
Schade, MD*, K.S. Adams, RN, MSN**,

L.F. Atler, PhD, D.A. Bowling, P.]. Boyle,
MD, M.R. Burge, MD, ].L. Canady, RN,

CDE, L. Chai, RN, R.l. Dorin, MD, E.
Facio, M. Guillen, RD, M. Gutierrez, RD, C.

Johannes, RN, CDE, P. Katz, LPN, C. King,

R. McCalman, RD,A. Rassam, MD, W. Sen-
ter, RD, and D. Waters, PhD; Albert Ein-

stein College ofMedicine~ H. Shamoon,

MD*, ].0. Brown, RN, MPH, MSN**, L.
Cox, MS, RD, H. Duffy, MS, C-ANp, S.
Engel, MD, A. Friedler, BS, C.J. Howard-

Century, BS, MA, N. Longchamp, LPN, D.
Pompi, BA, E.A. Walker, RN, DNSc, ].

Wylie-Rosett, EdD, RD, and]. Zonszein,
MD; University of Pittsburgh~ R.R.
Wing, PhD*, M.K. Kramer, BSN, MPH**,

S. Barr, BS, L. Clifford, BS, R. Culyba, BS,
M. Frazier, L. Harris, RN, S. Harrier, MLT,

W. Henderson, RN, BSN, S. Jeffries, RN,
MSN, G. Koenning, MS, RD, K. Maholic,
BS, M. Mullen, MPH, RD, A. Noel, BS, T.

Orchard, MBBCh, c.F. Smith, PhD, M.
Smith, RN, BSN,]. Viteri, MS, T. Wilson,
BA, K.V. Williams, MD, MPH, and]. Zgi-

bor, MPH; University of Hawaii~ R.F.
Arakaki, MD*, R.W. Latimer, BSN, MPH**,

N.K. Baker-Ladao, BS, R.M. Beddow, MD,
L.M. Dias, D.A. Dupont, L.L. Fukuhara,
BSN, RN, M.K. Mau, MD, S.K. adorn,
MPH, RD, R.U. Perry, and ].5. Tokunaga,
BS; Southwest American Indian Center

for Diabetes Prevention~ W.c. Knowler,
MD, DrPH*; Salt River/Gila River: M.A.

Hoskin, MS, RD**, V.L. Andre, RN, FNp,

K.]. Acton, MD, MPH, S. Antone, N.M.
Baptisto, P.H. Bennett, MB, FRCp, E.c. Bird,
MPH, RD, T.S. Dacawyma, PTR, R.L. Han-
son, MD, MPH, M.C. Jackson, RMA, RPT,

P.A. Jay, K.M. Kobus, RNC-ANp, ].
Roumain, MD, MPH, D.H. Rowse, MD,

R.]. Roy, and M. Yazzie, BA; Zuni: N.J.
Cooeyate* *, M. Chavez, RN, AS, B.A.
Broussard, RD, MPH, MBA, CDE, ].M.
Ghahate, G. Hughte, L.E. Ingraham, MS,
RD, LN, R.S. Kaskalla, D. Kessler, MD, Y.

Nashboo, and S. Poirier, MD; Shiprock:

c.A. Percy, RN, MS**, R. Barber, M.B. Ben-
son, RN, BSN, R. Duncan, RD, M. Glass,
MD, D. Gohdes, MD, W. Grant, MD, E.

Horse, T. Morgan, and M. Reidy, MD; Data

Coordinating Center (George Washing-
ton University Biostatistics Center)~ R.
Bain, PhD*,]. Bambad, T. Brenneman, C.
Dunegan, S.L. Edelstein, ScM, K.L. Grimes,

S.Jones, T.L.Jones, H. Klepac,].M. Lachin,
ScD, P. Mucik, R. Orlosky,]. Rochon, PhD,


e.E. Stimpson, and C. Van Aerden;
National Institute of Diabetes and Diges-
tive and Kidney Diseases Program
Office~ R. Eastman, MD, S. Garfield,
PhD, and M. Harris, PhD; National Insti-

tute on Aging~ R. Andres, MD; Centers
for Disease Control and Prevention~

M. Engelgau, MD, V. Narayan, MD, and D.
Williamson, PhD; University of Michi-
gan~ W. Herman, MD; Central Units:

Central Biochemistry Laboratory~ W.L.
Chandler, MD, S.M. Marcovina, PhD,

ScD*, and 1. McMillan, BS; Epicare
Center (Bowman Gray School of Medi-
cine)~ PM. Rautaharju, MD, PhD*, and

F.S. Razack Rautaharju, PhD; Nutrition
Coding Center (University of South Car-
olina)~ E.]. Mayer-Davis, PhD*; Central

Carotid Ultrasound Unit (New England
Medical Center)~ D.H. O’Leary, MD*,
L.R.e. Funk, MS, and K.A. O’Leary; Com-
puted Tomography~scan Reading Unit
(University of Colorado Health Sciences
Center)~ A.L. Scherzinger, PhD, and E.R.

Stamm, MD*; Lifestyle Resource Core
(University of Pittsburgh)~ B.P Gillis,
MS, RD, A.M. Kriska, PhD, e. Huffmyer, A.
Meier, MS, RD, E.M. Venditti, PhD and

R.R. Wing, PhD*; Design Committees
(Chairpersons)~ Ancillary Studies: S.M.
Haffner, MD, MPH, Concomitant Condi-

tions: R.E. Ratner, MD, Intervention: ].M.
Olefsky, MD,].V. Santiago, MD, Outcomes:

e.D. Saudek, MD, Publications and Pre-
sentations: w.e. Knowler, MD, DrPH, Pro-
gram Coordinator: M.G. Montez, RN,

MSHP, CDE, Recruitment/Retention: W.Y.
Fujimoto, MD, Screening/Eligibility: R.F.
Hamman, MD, DrPH, Steering Committee:

D.M. Nathan, MD.


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3. World Health Organization: Diabetes Melli-
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4. Edelstein SL, Knowler WC, Bain RP, Andres
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