Metabolic tests to determine risk for type 1 diabetes in clinical trials

DIABETES/METABOLISM RESEARCH AND REVIEWS R E S E A R C H A R T I C L EDiabetes Metab Res Rev 2011; 27: 584–589.Published online in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/dmrr.1205

Metabolic tests to determine risk for type 1diabetes in clinical trials

Carla J. Greenbaum1∗

B. Buckingham2

H. P. Chase3

J. Krischer4 for the DiabetesPrevention Trial, Type 1Diabetes (DPT-1) StudyGroup

1Diabetes Program, BenaroyaResearch Institute, Seattle, WA, USA2Department of PediatricEndocrinology,Stanford University,Palo Alto, CA, USA3Barbara Davis Center forChildhood Diabetes,University of Colorado,Denver, CO, USA4Pediatric Epidemiology,University of South Florida, Tampa,FL, USA

∗Correspondence to:Carla J. Greenbaum,Benaroya Research Institute,1201 9th Avenue, Seattle,WA 98101, USAE-mail:[email protected]

Received : 14 December 2010Revised: 4 March 2011Accepted: 22 March 2011

AbstractAims Evaluate the reproducibility and relationship of various metabolictests conducted as part of the Diabetes Prevention Trial – type 1 diabetes.

Methods Coefficients of variation, intraclass correlation coefficients, andPearson correlations between the same metabolic tests performed at differenttimes as well as the different tests were determined.

Results Fasting samples on the same day had a coefficient of variation of<10 for C-peptide, 11 for insulin, and 2 for glucose. Testing on separatedays approximately doubled the variance. Stimulated insulin values hadless variance than fasting values and there was only a moderate correlationbetween fasting and stimulated values on each test. While highly correlated,C-peptide values from mixed meal tolerance tests are significantly lowerthan that obtained during oral glucose tolerance tests (OGTTs). Neither peaknor area under the curve C-peptide on the oral glucose tolerance test wasdifferent between those with abnormal and normal glucose tolerance. Thosewith abnormal as compared with normal glucose tolerance had lower 30-minC-peptide and a longer time to peak C-peptide.

Conclusions A large, multi-centre trial, with tests performed over a decade-long period, can provide robust data. C-peptide data from oral glucosetolerance tests and mixed meal tolerance tests differ; therefore, the samestimulation test should be used to evaluate changes in beta cell functionover time. Worsening glucose tolerance is associated with lower C-peptideat 30 min and a delay in peak secretion on the oral glucose tolerance test.This Diabetes Prevention Trial – type 1 diabetes data can be used in planningparameters for future studies, including evaluation of new algorithms todetermine risk of disease. Copyright 2011 John Wiley & Sons, Ltd.

Keywords metabolic tests; type 1 diabetes; prediction and prevention

Introduction

The twin concepts that type 1 diabetes results from an immune-mediateddestruction of beta cells and that this process is far along prior to theclinical onset of disease are well established. Indeed, these concepts formedthe basis for the notion that people could be identified prior to the onsetof clinical disease, and that therapeutic strategies could be developed toprevent disease occurrence. Although therapies tested in recent large multi-centre trials were unsuccessful in preventing or delaying diabetes, thesestudies verified algorithms to identify people at risk, thereby providingimportant information for planning of future intervention trials. For example,the Diabetes Prevention Trial – type 1 diabetes (DPT-1) showed that 41%

Copyright 2011 John Wiley & Sons, Ltd.

Evaluation of Metabolic Tests in DPT-1 585

of islet cell antibody (ICA) positive relatives of peoplewith type 1 diabetes with either low first-phase insulinsecretion as determined by intravenous glucose tolerancetest (IVGTT) or impaired glucose tolerance on the oralglucose tolerance test (OGTT) developed diabetes within5 years [1]. Similarly, 26% of ICA+ relatives withoutthe above-mentioned metabolic abnormalities but withinsulin autoantibody (IAA) positive developed diabeteswithin 5 years [2]. These studies thus verified the notionthat impaired insulin secretion occurs prior to the onset ofclinical type 1 diabetes mellitus. However, the presenceof the DPT-1 large dataset also allows us to understandmore details about the course of insulin secretion prior todiabetes diagnosis. The DPT-1 not only measured insulinsecretion during IVGTT but the enrolled subjects alsounderwent the OGTT and mixed meal tolerance test(MMTT) at regular intervals, with the hypothesis thatthere may be differences between these tests with respectto their use as risk indicators or surrogate markers fortherapeutic effects or natural history. In this article, weaddress the question as to the relative strengths andweaknesses of each of these metabolic tests in the contextof a clinical trial to facilitate planning of future trialsand to enhance our understanding of the type 1 diabetesmellitus disease process.

Important factors in selecting metabolic surrogatemarkers of the type 1 diabetes mellitus disease processinclude the reproducibility of the assay and tests in a largemulti-centre clinical trial, the relationship of each type oftest to the other, and what is the relationship of each testto glucose tolerance.

Methods

First-degree (3–45 years) and second-degree (3–20years) relatives were screened for ICA. Subjects thenunderwent ‘staging’ tests, which involved confirming thepresence of ICA, determining their human leukocyte anti-gen type, measuring IAA, and performing an IVGTT todetermine first-phase insulin release (FPIR). As previouslydescribed [1,2], FPIR was considered ‘above threshold’ ifthe 1 + 3 min insulin values from this test were >10th per-centile for siblings, offspring, and second-degree relatives(>100 µU/mL if older than 8; >60 µU/mL if younger than8 years) and >1st percentile for parents (>60 µU/mL).If the FPIR was found to be below threshold, a repeatIVGTT was performed to confirm this result. If one testwas below and the second was above threshold, a thirdIVGTT was performed. Prior to enrolment in the inter-vention phase of the study, all subjects underwent OGTT.Subjects with an OGTT consistent with the diagnosis ofdiabetes were excluded from enrolment in the interven-tion studies. Thus, relatives who were confirmed to beICA+ and either confirmed to have below-threshold FPIRor an abnormal (but not diabetic) OGTT were eligible forthe high-risk intervention protocol.

Subjects with a normal OGTT and above-threshold FPIRalong with a confirmed ICA and IAA were eligible for theintermediate risk intervention protocol.

Once in either intervention protocol, subjects under-went OGTT every 6 months as this was the primaryoutcome measure. Any time an OGTT was indicative ofdiabetes, a repeat OGTT was performed within 30 days.If this test confirmed diabetes, the subject was deemedto have reached endpoint and was no longer followedup in the study. If the test did not confirm diabetes,the subject resumed the every 6-month OGTT schedule.To mask investigators and subjects as to OGTT results,approximately 10% of OGTTs that were not indicative ofdiabetes were also repeated within 30 days.

In addition, individuals in the high-risk interventiongroup underwent other metabolic testing annually, alter-nating MMTT with IVGTT. Individuals in the intermediaterisk intervention underwent annual IVGTT assessmentsand MMTT at baseline, 36 months, and study end.

As a quality assurance measure, 5% of samples wereassigned to be ‘split duplicates’. Thus, clinical sitesreceived additional materials and labels to obtain dupli-cate blood samples during a test which was sent masked tothe laboratory. During the DPT-1, this data was among thematerial regularly available to the laboratory monitoringand data safety monitoring board committees.

Oral glucose tolerance test

As previously described [1,2], after overnight fasting, oralglucose (Sundex, Fisher) dose was consumed at 1.75 g/kg(maximum 75 g). Samples were obtained for glucose andC-peptide at −10, 0, 30, 60, 90, and 120 min.

Plasma glucose values were interpreted according tothe 1997 American Diabetes Association guidelines [3].Normal glucose tolerance (NGT) was defined as fastingplasma glucose <7.0 mmol/L (126 mg/dL) and 30-, 60-,90-, and 120-min glucose <11.1 mmol/L (200 mg/dL).Abnormal glucose tolerance (AGT) included all othercategories including diabetes, impaired fasting glucose,impaired glucose tolerance, and indeterminate glucosetolerance [3].

Intravenous glucose tolerance test

As previously described [1,2], after overnight fasting, a25% glucose solution was infused as a square-wave bolusover 3 min ±15 s with a dose of 0.5 g/kg body weight glu-cose (maximum dose 35 g) [4,5]. Samples were obtainedfor glucose, insulin, and C-peptide at −10, −4, 1, 3, 5,7, and 10 min. Insulin values at 1 and 3 min were addedto determine FPIR. FPIR was above threshold if >10thpercentile for siblings, offspring, and second-degree rel-atives (>100 µU/mL if older than 8 years; >60 µU/mLif younger than 8 years) and >1st percentile for parents(>60 µU/mL).

Copyright 2011 John Wiley & Sons, Ltd. Diabetes Metab Res Rev 2011; 27: 584–589.DOI: 10.1002/dmrr

586 C. J. Greenbaum et al.

Table 1. Coefficient of variation for glucose, C-peptide, and insulin values obtained on the same samples (splitduplicate samples), on two separate fasting samples obtained the same day (two baseline samples), and on fastingsamples obtained from tests performed within 30 days of each other

Split duplicate samples Two baseline samples Fasting samples 30 days apart

Glucose C-peptide Insulin Glucose C-peptide Insulin Glucose C-peptide

N 2061 2544 831 5714 7620 1981 1836 1816Coefficient of

variation ±standarddeviation %

1 ± 5 10 ± 10 11.3 ± 13 2.12 ± 4.2 9.3 ± 12.2 11.6 ± 12.9 5.9 ± 9.0 22.2 ± 20.6

Mixed meal tolerance test

As previously described [1,2], after overnight fasting, aliquid formula meal was consumed (Sustacal/Boost,Mead Johnson Nutritionals) (6 cal/kg body weight, max-imum 360 kcal). Samples were obtained for glucose andC-peptide at −10, 0, 30, 60, 90, and 120 min.

All assays were performed as previously described [1],including ICA (indirect immunofluorescence), IAA (com-petitive fluid-phase radioassay), plasma glucose (glucoseoxidase method), insulin (radioimmunoassay), C-peptide(radioimmunoassay).

Statistics

Intraclass correlations were used as a measure of within-subject correlation when a subject was tested/scored onthe same test repeatedly. Pearson correlations were usedto evaluate the correlation between test variations (assum-ing independence).

Results

Reproducibility of individual measures

Coefficients of variation (CVs) were determined for glu-cose, C-peptide, and insulin from both split duplicatesamples and from two fasting samples on the same sub-ject 5–10 min apart during the same test. Comparisonswere also made between fasting samples for glucose andC-peptide obtained up to 30 days apart (Table 1). Therewas no significant difference in the CVs of the samples forC-peptide, glucose, or insulin received from different clini-cal sites in the country or changes in split duplicate resultsover time. The intraclass correlation (r) was 0.600 [con-fidence interval (CI) 0.567–0.631] for C-peptide samplescarried out on tests 30 days apart and there was no effectof adjusting for fasting glucose or age on this relationship.The intraclass correlation coefficient for glucose was 0.107(CI 0.065–0.143), which did not change when adjustedfor age. It was hypothesized that the differences in fastingglucose on different days may contribute to the increasedCV of C-peptide measures performed on different days.However, testing the ratio of fasting C-peptide/fasting

glucose did not appreciably affect the CV (mean 21.9,standard deviation 20.1).

Reproducibility of test outcomes

Intravenous glucose tolerance testTo determine the reproducibility of measures of stimu-lated insulin secretion, we compared the results from thelast two IVGTTs performed in subjects during the stagingpart of the study. There were 249 paired tests separatedby at least 3 weeks, but performed within 26 weeks ofeach other (mean 114 days).

InsulinFirst, we explored the reproducibility of the IVGTT asassessed by categorical outcome. Of the 126 tests deter-mined to be below threshold on the first visit, 112 or 89%were confirmed in that category on the second visit. Ofthose determined to be above threshold on the initial test,82 tests (65%) were confirmed on the second visit (kappa= 0.23) (Table 2).

The intraclass correlation coefficient (r) on the 1 +3 min insulin values obtained from staging IVGTT wasr = 0.656 (CI 0.570–0.714), and that calculated fromarea under the curve (AUC) (r = 0.690, CI 0.613–0.746)and peak insulin (r = 0.637, CI 0.554–0.703) values.There was a significant decrease in the correlationbetween IVGTTs when the fasting insulin value wasused as the only measure of comparison (r = 0.471, CI0.364–0.558). Adjusting for the subject’s age, fastingglucose value, or fasting insulin value did not makea significant improvement in reproducibility betweentests.

C-peptideThe correlation coefficient of fasting C-peptide valuesobtained from two staging IVGTTs was r = 0.580 (CI0.493–0.658). The correlation was improved with usingeither the peak or AUC C-peptide values (peak r = 0.740,CI 0.678–0.791; AUC r = 0.721, CI 0.654–0.776). In allcases, adjusting for fasting C-peptide or glucose or sub-ject’s age did not significantly improve the reproducibilityof the results.



Table 2. Intraclass correlation (r) and coefficient of variation on insulin and C-peptide values obtained during 249paired intravenous glucose tolerance tests performed within 3–26 weeks of each other

Insulin C-peptide

Fasting 1 + 3 min Area under the curve Peak Fasting Area under the curve Peak

r 0.471 0.656 0.69 0.637 0.579 0.72 0.74Coefficient of variation 24.98 23.27 22.13 21.91 27.6 18.9 18.9

Relationship between measuresobtained during the same test

Intravenous glucose tolerance testDuring the DPT-1, both insulin and C-peptide measure-ments were obtained as part of the IVGTT. While bothinsulin and C-peptide are beta cell secretory products,there are significant differences in the metabolism of thesehormones and these are reflected in the values measuredin the peripheral blood. We thus wanted to understandthe relationship of these measures within the same test.

The Pearson correlation coefficient was 0.67 whencomparing 2110 samples in which fasting insulin andC-peptide values were measured during the initial stagingIVGTT. The relationship between the peak or AUC insulinand C-peptide values was better (0.85); however, adjust-ing for fasting C-peptide or glucose did not improve thesecorrelations. Although all Pearson correlations were sig-nificant at the 0.001 level, the correlation coefficients werequite low between the fasting insulin (0.14) or C-peptidevalues (0.11) and the fasting glucose value. Indeed, thiswas also true when examined between any measure ofglucose obtained during the IVGTT and stimulated insulinor C-peptide measurements (data not shown). All Pearsoncorrelations were significant at the 0.001 level.

To better interpret this data, we also explored the rela-tionship of fasting to stimulated values during the IVGTTfor insulin and C-peptide separately. We found that fast-ing C-peptide value was reasonably correlated with eitherAUC or peak C-peptide (0.68 for both), and that therewas a strong correlation between peak and AUC C-peptidevalues (0.99). Similar data was observed for insulin inthat the fasting insulin value was moderately correlatedwith peak (0.53) and AUC (0.58), while the peak andAUC insulin values were highly correlated (0.98). Noneof these correlations were improved by adjustments forfasting insulin, C-peptide, or glucose values. All Pearsoncorrelations were significant at the 0.001 level.

Oral glucose tolerance testThe relationship between fasting and stimulated C-peptide values during the initial staging OGTT wasdetermined from 960 tests. The correlations were fast-ing and peak (0.65), fasting and AUC (0.71), and peakand AUC (0.96). These correlations were not improvedby adjustments for fasting glucose or C-peptide values. AllPearson correlations were significant at the 0.001 level.

Relationship between tests performed30 days apart

The DPT-1 used three different beta cell stimulants (intra-venous glucose, oral glucose, and oral ‘mixed meal’) toassess beta cell function after randomization. We wishedto understand the relationship of beta cell function asassessed by each of these measures.

Comparisons between MMTT and IVGTTA comparison of C-peptide values obtained up to 30 daysapart on MMTT (n = 406) and IVGTT (n = 731) wasmade. There was only a moderate correlation betweenpeak (0.53) or AUC (0.51) C-peptide values when the betacell received two different stimuli (oral mixed meal versusintravenous glucose); however, this was only slightly dif-ferent from the correlation of the fasting C-peptide valuesobtained for these tests (0.62). All Pearson correlationswere significant at the 0.001 level.

Comparisons between MMTT and OGTTThe peak and AUC C-peptide values obtained during theMMTT and OGTT obtained up to 30 days apart werecorrelated (peak 0.69; AUC 0.76), while the relationshipbetween fasting values was the same as seen above (0.66).All Pearson correlations were significant at the 0.001 level.

Notably, despite this correlation the OGTT mean C-peptide values (AUC 501.3 ng/mL +/− 198.1; peak5.36 +/− 2.2 ng/mL) and glucose values (166.6 +/−41.6 mg/dL peak) were markedly greater than that seenwith MMTT stimulation (C-peptide AUC 393.4 +/−171 ng/mL; C-peptide peak 4.49 +/− 2.00 ng/mL; glu-cose peak 122.2 +/− 23.7 mg/dL) (p < 0.001 for each)(Figure 1).

Comparisons between OGTT and IVGTTThe relationship between fasting, peak, and AUC C-peptide values obtained during the OGTT and IVGTTwere determined for studies up to 30 days apart (fasting0.70; peak 0.57; AUC 0.62). All Pearson correlations weresignificant at the 0.001 level.

In the IVGTT, C-peptide as well as insulin measure-ments were made. We thus compared the relationshipbetween the peak and AUC C-peptide values obtained onthe OGTT with peak and AUC insulin values obtainedon the IVGTT. In both instances as well as comparingfasting values, while significant at the 0.001 level, the


588 C. J. Greenbaum et al.

Figure 1. Mean C-peptide +/− standard error (ng/mL) duringmixed meal tolerance tests and oral glucose tolerance testsperformed within 30 days of each other

correlations were only moderate (fasting r = 0.43, peakr = 0.39, AUC r = 0.46) for tests separated by 30 days.

Relationship of secretion to glucosetolerance

During staging, the OGTT was categorized as normal (n =269) or abnormal [impaired fasting glucose, impaired glu-cose tolerance, diabetic, indeterminate (n = 683)]. Wecompared the C-peptide values obtained during the initialstaging IVGTT and these categories. Fasting C-peptidewas 2.47 ng/mL in the AGT group and 3.51 ng/mL inthe NGT group (p < 0.001). The peak C-peptide valuefrom the IVGTT was 2.29 ng/mL in the AGT group and3.38 ng/mL in those with NGT (p < 0.0001). This dif-ference between groups was similar when expressed asC-peptide AUC (20.6 versus 30.4 ng/mL, p < 0.0001).There was no difference in fasting insulin values betweenthe glucose tolerance and intolerance groups (13.2 versus12.7 µU/mL, p = 0.41) even when adjusted for fastingglucose, while both the peak and AUC insulin values weremarkedly different between groups.

We also assessed whether the secretion informationobtained from the OGTT would also be different accord-ing to OGTT categories. Surprisingly, this was not thecase for peak C-peptide values in which the mean peakfor those with AGT was 4.94 ng/mL and that for thosewith NGT was 5.19 ng/mL (p = 0.15) unless an adjust-ment was made for fasting C-peptide values. However,incorporating additional C-peptide values in the calcu-lation for C-peptide AUC did demonstrate a differencebetween the glucose tolerance groups (C-peptide AUCfor AGT = 431.2 versus NGT 478.4 ng/mL; p = 0.001)Moreover, when a single time point was chosen to com-pare C-peptide values there were marked differences inglucose tolerance groups. Thus, those with AGT had

Figure 2. Mean C-peptide +/− standard error (ng/mL) duringthe oral glucose tolerance test with normal (n = 269) andabnormal glucose tolerance (n = 683) values

less C-peptide at 30 and 60 min that those with NGT(Figure 2). There was also a difference between groups atfasting and 120 min, but in this case, those with NGT hadlower C-peptide values. While this data suggested that the120-min value in those with NGT was heading towardsbaseline, when the C-peptide/glucose ratio was calculatedat 120 min there was no difference between glucose tol-erance groups. The time to peak value was significantlydifferent in the two groups. Those with AGT reached peakvalue at 99.1 ± 28 min, and those with NGT reached peakC-peptide value at 71.6 ± 29.8 min (p < 0.001).

Discussion

The DPT-1 performed multiple measures of beta cell func-tion in the subjects identified at risk for type 1 diabetes.As the pathogenesis of diabetes involves destruction ofthe beta cell, accurate and reliable assessment of beta cellfunction can serve as a surrogate marker of the diseaseprocess. The question is which tests are best to servethis purpose. Many factors would be involved in mak-ing this assessment, including standard determinations ofreproducibility, the relationship between these measuresand glucose tolerance, and practical issues of investiga-tor and subjects’ burden and cost. Thus, one purpose ofthis analysis is to assist future investigators in choosingan outcome measure. In addition, by providing the firstpublished data on the variability of these measures in thepopulation, more accurate estimation can be made of theN required to use such measures as outcome markers.

Several key points can be made from the data pre-sented. First, there was little difference in the variabilitybetween the quality control samples tested in the labora-tory for insulin, glucose, and C-peptide, and those fastingsamples drawn separately at the local clinic. In addition,the variability was not different from site to site or overthe length of the study. To assess the reproducibility of thetest itself and not variations due to progression of disease(i.e. pathophysiology), we looked at the variance whentests were performed up to 30 days apart and found that



testing on separate days approximately doubled the vari-ance. Importantly, we also found that the variances didnot differ when adjusted for age or fasting C-peptide,insulin, or glucose values.

We next determined the reproducibility of the betacell-stimulated response finding that stimulated as com-pared with fasting values are more consistent and thusbetter measures to use as outcome markers over time. Ofcourse, an alternative explanation is that the increasedvariance fasting insulin values reflect important changesin physiology over time that the stimulated values areinsensitive in detecting.

Not surprisingly, in both IVGTTs and OGTTs there wasan excellent correlation between two measures of stim-ulated secretion, indicating that either the peak or AUCcalculations could be used. However, there was only amoderate correlation between fasting insulin or C-peptidevalues and either of these stimulated measures – againindicating that these values represent different processes.

The key question, therefore, was the relationship offasting versus stimulated secretion measures to glu-cose tolerance status. We found that the fasting insulinvalue did not differ between those with AGT and NGTwhile IVGTT-stimulated values were markedly differ-ent between groups. This data supports the well-knownconcept of loss of FPIR resulting in AGT.

We found no differences in peak C-peptide betweenthose with NGT and AGT status. Instead, the shape of theC-peptide curve in response to the OGTT was different,those with NGT reaching peak value before those withAGT. Thus, the 30-min C-peptide value was markedly dif-ferent between the two glucose tolerance groups. Whetherthe metabolic data from an OGTT will be sufficient todetermine risk of disease progression remains to be tested.

DPT-1 also had subjects undergo MMTT to assess thebeta cell response to fats and proteins as well as glucose.We wished to understand whether this test providedadditional information. Since a given individual’s MMTTswere separated by 1–3 years, we could not comparethe reproducibility of the test per se without the con-founding problem of changes in underlying physiology.The C-peptide and glucose values were markedly greaterafter OGTT as compared to MMTT stimulation. Althoughglucagon was not measured in DPT-1, the lower C-peptideand glucose values seen in the MMTTs are likely due to theeffect of glucagon secretion in response to the protein inthe mixed meal. As there is great interest in understandinghow the beta cell function changes during the transition

period from at-risk status to clinical onset, these dataconfirm that longitudinal data will require the use of thesame stimulation test over time, i.e. it would not be validto compare the absolute C-peptide values obtained duringan OGTT in the pre-diabetes period with the C-peptidevalues obtained during an MMTT post-diagnosis.

In conclusion, the low CVs for glucose, C-peptide, andinsulin values obtained from split duplicate samples ortwo fasting samples obtained during the same test pro-vide reassurance regarding the accuracy of such data formulti-centre clinical trials conducted over a long period oftime and account for the assay, blood draw, and handlingvariability. The variance found on tests conducted within30 days is about double the values obtained the sameday. When tests are repeated over a longer period oftime (i.e. results from IVGTTs up to 26 weeks apart),the tests are less reproducible, reflecting the effect ofdisease progression. In this regard, it is of interest to notethat there was more variance in the fasting rather thanstimulated levels. Furthermore, there were only moderatecorrelations between fasting and stimulated values ofeither insulin or C-peptide. The data also indicate that,while highly correlated, the C-peptide values from anOGTT are not the same as those from the MMTTs inthis population. Finally, worsening glucose tolerance isassociated with lower C-peptide at 30 min and a delayin peak secretion on the OGTT. This DPT-1 data can beused in planning parameters for future studies, includingevaluation of new algorithms to determine risk of disease.

Acknowledgements

DPT-1 was supported through cooperative agreements by theDivision of Diabetes, Endocrinology and Metabolic Diseases,National Institute of Diabetes and Digestive and Kidney Dis-eases, the National Institutes of Health (NIH); the NationalInstitute of Allergy and Infectious Disease, NIH; the NationalInstitute of Child Health and Human Development, NIH; theNational Center for Research Resources, NIH; the AmericanDiabetes Association; the Juvenile Diabetes Research Founda-tion; and various corporate sponsors. The authors thank DavidCuthbertson for statistical support and the DPT-1 study groupmembers and participants.

Conflict of interest

The authors have no conflicts to disclose.

References

1. Diabetes Prevention Trial Study Group.Effects of insulin in relatives of patientswith type 1 diabetes mellitus. N EnglJ Med 2002; 346: 1685–1691.

2. Skyler JS, Krischer JP, Wolfsdorf J,et al. Effects of oral insulin in relativesof patients with type 1 diabetes: theDiabetes Prevention Trial – Type 1. Dia-betes Care 2005; 28: 1068–1076.

3. Expert Commitee on the Diagnosis andClassification of Diabetes Mellitus. Reportof the expert committee on the diagnosisand classification of diabetes mellitus.Diabetes Care 1997; 20: 1183–1197.

4. Bingley PJ, Colman P, Eisenbarth GS,et al. Standardization of IVGTT to pre-dict IDDM. Diabetes Care 1992; 15:1313–1316.

5. Chase HP, Cuthbertson DD, Dolan LM,et al. First-phase insulin release duringthe intravenous glucose tolerance test asa risk factor for type 1 diabetes. J Pediatr2001; 138: 244–249.


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Metabolic tests to determine risk for type 1 diabetes in clinical trials