Use of the diabetes risk score for opportunistic screening of undiagnosed diabetes and impaired glucose tolerance: the IGLOO (Impaired Glucose Tolerance and Long-Term Outcomes Observational) study

Application and applicability of non-invasive risk models for predicting undiagnosed prevalent diabetes in Africa: A systematic literature search

BACKGROUND AND PURPOSE

Prediction algorithms are increasingly advocated in diabetes screening strategies, particularly in developing countries. We conducted a systematic review to assess the application and applicability of existing non-invasive prevalent diabetes risk models to populations within Africa.

DESIGN

systematic review data sources A systematic search of English literatures in Medline via PubMed from 1999 until June, 2014. Study selection Included studies had to report on the development, validation or implementation of a model that was primarily constructed to predict prevalent undiagnosed diabetes using non-laboratory based predictors.

DATA EXTRACTION

Data were extracted on the type of statistical model, type and range of predictors in the model, performance measures in both internal and external validation, and whether the model was developed from, validated or implemented in an African population.

RESULTS

Twenty-three studies reporting on non-invasive prevalent diabetes models were identified. Ten from Europe (some with multiethnic populations), nine models were developed among Asian population, two from the USA and two from the Middle-East. The c-statistics for these models ranged from 0.65 to 0.88 in the development studies, and from 0.63 to 0.80 in the validation studies. Twenty models were validated, and none in Africa. Among predictors commonly included in models, parental/family history of diabetes and personal history of hypertension appear to be more prone to measurement errors in the African context.

CONCLUSION

Existing prevalent diabetes prediction models have not been applied to African populations, and issues with the measurement of key predictors make their applicability likely inaccurate.

Systematic Review and Meta-Analysis of Response Rates and Diagnostic Yield of Screening for Type 2 Diabetes and Those at High Risk of Diabetes

Background

Screening for type 2 diabetes (T2DM) and individuals at risk of diabetes has been advocated, yet information on the response rate and diagnostic yield of different screening strategies are lacking.

Methods

Studies (from 1998 to March/2015) were identified through Medline, Embase and the Cochrane library and included if they used oral glucose tolerance test (OGTT) and WHO-1998 diagnostic criteria for screening in a community setting. Studies were one-step strategy if participants were invited directly for OGTT and two, three/four step if participants were screened at one or more levels prior to invitation to OGTT. The response rate and diagnostic yield were pooled using Bayesian random-effect meta-analyses.

Findings

47 studies (422754 participants); 29 one-step, 11 two-step and seven three/four-step were identified. Pooled response rate (95% Credible Interval) for invitation to OGTT was 65.5% (53.7, 75.6), 63.1% (44.0, 76.8), and 85.4% (76.4, 93.3) in one, two and three/four-step studies respectively. T2DM yield was 6.6% (5.3, 7.8), 13.1% (4.3, 30.9) and 27.9% (8.6, 66.3) for one, two and three/four-step strategies respectively. The number needed to invite to the OGTT to detect one case of T2DM was 15, 7.6 and 3.6 in one, two, and three/four-step strategies. In two step strategies, there was no difference between the response or yield rates whether the first step was blood test or risk-score. There was evidence of substantial heterogeneity in rates across study populations but this was not explained by the method of invitation, study location (rural versus urban) and developmental index of the country in which the study was performed.

Conclusions

Irrespective of the invitation method, developmental status of the countries and or rural/urban location, using a multi-step strategy increases the initial response rate to the invitation to screening for diabetes and reduces the number needed to have the final diagnostic test (OGTT in this study) for a definite diagnosis.

The Uptake of Screening for Type 2 Diabetes and Prediabetes by Means of Glycated Hemoglobin versus the Oral Glucose Tolerance Test among 18 to 60-Year-Old People of South Asian Origin: A Comparative Study

Background

Direct comparisons of the effect of a glycated haemoglobin measurement or an oral glucose tolerance test on the uptake and yield of screening in people of South Asian origin have not been made. We evaluated this in 18 to 60-year-old South Asian Surinamese.

Materials and Methods

We invited 3173 South Asian Surinamese for an oral glucose tolerance test between June 18^th 2009- December 31^st 2009 and 2012 for a glycated hemoglobin measurement between April 19^th 2010-November 11^th, 2010. Participants were selected from 48 general practices in The Hague, The Netherlands. We used mixed models regression to analyse differences in response and participation between the groups. We described differences in characteristics of participants and calculated the yield as the percentage of all cases identified, if all invitees had been offered screening with the specified method.

Results

The response and participation in the glycated hemoglobin group was higher than in the group offered an oral glucose tolerance test (participation 23.9 vs. 19.3; OR: 1.30, 95%-confidence interval1.01–1.69). After adjustment for age and sex, characteristics of participants were similar for both groups. Overall, glycated hemoglobin identified a similar percentage of type 2 diabetes cases but a higher percentage of prediabetes cases, in the population than the oral glucose tolerance test.

Conclusion

We found that glycated hemoglobin and the oral glucose tolerance test may be equally efficient for identification of type 2 diabetes in populations of South Asian origin. However, for programs aimed at identifying people at high risk of type 2 diabetes (i.e. with prediabetes), the oral glucose tolerance test may be a less efficient choice than glycated hemoglobin.

Primary care screening for individuals with impaired glucose metabolism with focus on impaired glucose tolerance

AIM

To evaluate the utility of three short questions (the Skövde Form) combined with a random plasma glucose, and HbA1c as alternative tools for detection of individuals with impaired glucose metabolism (IGM), and particularly impaired glucose tolerance (IGT).

METHODS

Three questions concerning BMI ≥ 25 kg/m(2), heredity for type 2 diabetes, and known hypertension were asked in a random population of 573 individuals. All with two positive answers or one positive answer and a random plasma glucose > 7.2 mmol/l were invited for an oral glucose tolerance test and an HbA1c examination. FINDRISC was completed for comparison.

RESULTS

The positive predictive value (PPV) for IGM, using the Skövde Form, was 31% while sensitivity and specificity were 59% and 73%, respectively. Corresponding values for IGT were 11%, 50% and 69%. Using HbA1c ≥ 42 mmol/mol, the PPV for IGM was 64% while sensitivity and specificity were 28% and 97%, respectively. The corresponding values for IGT were 15%, 16% and 94%.

CONCLUSION

The Skövde Form combined with a random plasma glucose may be used as an alternative tool for detection of individuals with IGM and IGT in particular. HbA1c may be used to identify individuals with type 2 diabetes but fails to detect most individuals with prediabetes.

Validating prediction scales of type 2 diabetes mellitus in Spain: the SPREDIA-2 population-based prospective cohort study protocol

INTRODUCTION

The incidence of type 2 diabetes mellitus (T2DM) is increasing worldwide. When diagnosed, many patients already have organ damage or advance subclinical atherosclerosis. An early diagnosis could allow the implementation of lifestyle changes and treatment options aimed at delaying the progression of the disease and to avoid cardiovascular complications. Different scores for identifying undiagnosed diabetes have been reported, however, their performance in populations of southern Europe has not been sufficiently evaluated. The main objectives of our study are: to evaluate the screening performance and cut-off points of the main scores that identify the risk of undiagnosed T2DM and prediabetes in a Spanish population, and to develop and validate our own predictive models of undiagnosed T2DM (screening model), and future T2DM (prediction risk model) after 5-year follow-up. As a secondary objective, we will evaluate the atherosclerotic burden of the population with undiagnosed T2DM.

METHODS AND ANALYSIS

Population-based prospective cohort study with baseline screening, to evaluate the performance of the FINDRISC, DANISH, DESIR, ARIC and QDScore, against the gold standard tests: Fasting plasma glucose, oral glucose tolerance and/or HbA1c. The sample size will include 1352 participants between the ages of 45 and 74 years.

ANALYSIS

sensitivity, specificity, positive predictive value, negative predictive value, likelihood ratio positive, likelihood ratio negative and receiver operating characteristic curves and area under curve. Binary logistic regression for the first 700 individuals (derivation) and last 652 (validation) will be performed. All analyses will be calculated with their 95% CI; statistical significance will be p<0.05.

ETHICS AND DISSEMINATION

The study protocol has been approved by the Research Ethics Committee of the Carlos III Hospital (Madrid). The score performance and predictive model will be presented in medical conferences, workshops, seminars and round table discussions. Furthermore, the predictive model will be published in a peer-reviewed medical journal to further increase the exposure of the scores.

Screening for people with abnormal glucose metabolism in the European DE-PLAN project

AIMS

The aim of this report is to describe the application of the FINDRISC in clinical practice within the DE-PLAN project as a step to screen for Type 2 diabetes.

METHODS

Nine out of 24 possible centers were included. Six centers used opportunistic screening methods for participant recruitment whereas three centers provided study participants of a random population sample. Men (n=1621) and women (n=2483) were evaluated separately. In order to assess the prevalence of abnormal glucose tolerance (AGT) disorders across different risk categories, the FINDRISC was used. Anthropometric measurements included blood pressure, height, weight, and waist circumference. Blood lipids and an oral glucose tolerance test were performed in all participants. The primary outcome was identified risk of AGT and type 2 diabetes.

RESULTS

There was no difference in the prevalence of smoking between the FINDRISC categories, people with a FINDRISC below 15 points tend to be more physically active and to eat more frequently fruits and vegetables. Men with a FINDRISC from 15 to 19 points had a prevalence of abnormal glucose tolerance of approximately 60% and women 50%. The prevalence for men and women with a FINDRISC >20 points was 80%. 30% of men and 20% of women with a FINDRISC between 15 and 19 points had Type 2 diabetes. Among people with a FINDRISC more than 20 points, 50% had previously undiagnosed Type 2 diabetes.

CONCLUSIONS

The FINDRISC may be a practical tool to be used in primary health-care systems throughout the European population.

Predictive modeling for incident and prevalent diabetes risk evaluation

With half of individuals with diabetes undiagnosed worldwide and a projected 55% increase of the population with diabetes by 2035, the identification of undiagnosed and high-risk individuals is imperative. Multivariable diabetes risk prediction models have gained popularity during the past two decades. These have been shown to predict incident or prevalent diabetes through a simple and affordable risk scoring system accurately. Their development requires cohort or cross-sectional type studies with a variable combination, number and definition of included risk factors, with their performance chiefly measured by discrimination and calibration. Models can be used in clinical and public health settings. However, the impact of their use on outcomes in real-world settings needs to be evaluated before widespread implementation.

A novel testing model for opportunistic screening of pre-diabetes and diabetes among U.S. adults

Objective

The study aim was to evaluate the performance of a novel simultaneous testing model, based on the Finnish Diabetes Risk Score (FINDRISC) and HbA1c, in detecting undiagnosed diabetes and pre-diabetes in Americans.

Research Design and Methods

This cross-sectional analysis included 3,886 men and women (≥ 20 years) without known diabetes from the U.S. National Health and Nutrition Examination Survey (NHANES) 2005-2010. The FINDRISC was developed based on eight variables (age, BMI, waist circumference, use of antihypertensive drug, history of high blood glucose, family history of diabetes, daily physical activity and fruit & vegetable intake). The sensitivity, specificity, and the receiver operating characteristic (ROC) curve of the testing model were calculated for undiagnosed diabetes and pre-diabetes, determined by oral glucose tolerance test (OGTT).

Results

The prevalence of undiagnosed diabetes was 7.0% and 43.1% for pre-diabetes (27.7% for isolated impaired fasting glucose (IFG), 5.1% for impaired glucose tolerance (IGT), and 10.3% for having both IFG and IGT). The sensitivity and specificity of using the HbA1c alone was 24.2% and 99.6% for diabetes (cutoff of ≥6.5%), and 35.2% and 86.4% for pre-diabetes (cutoff of ≥5.7%). The sensitivity and specificity of using the FINDRISC alone (cutoff of ≥9) was 79.1% and 48.6% for diabetes and 60.2% and 61.4% for pre-diabetes. Using the simultaneous testing model with a combination of FINDRISC and HbA1c improved the sensitivity to 84.2% for diabetes and 74.2% for pre-diabetes. The specificity for the simultaneous testing model was 48.4% of diabetes and 53.0% for pre-diabetes.

Conclusions

This simultaneous testing model is a practical and valid tool in diabetes screening in the general U.S. population.

Reporting and handling of missing data in predictive research for prevalent undiagnosed type 2 diabetes mellitus: a systematic review

Missing values are common in health research and omitting participants with missing data often leads to loss of statistical power, biased estimates and, consequently, inaccurate inferences. We critically reviewed the challenges posed by missing data in medical research and approaches to address them. To achieve this more efficiently, these issues were analyzed and illustrated through a systematic review on the reporting of missing data and imputation methods (prediction of missing values through relationships within and between variables) undertaken in risk prediction studies of undiagnosed diabetes. Prevalent diabetes risk models were selected based on a recent comprehensive systematic review, supplemented by an updated search of English-language studies published between 1997 and 2014. Reporting of missing data has been limited in studies of prevalent diabetes prediction. Of the 48 articles identified, 62.5% (n = 30) did not report any information on missing data or handling techniques. In 21 (43.8%) studies, researchers opted out of imputation, completing case-wise deletion of participants missing any predictor values. Although imputation methods are encouraged to handle missing data and ensure the accuracy of inferences, this has seldom been the case in studies of diabetes risk prediction. Hence, we elaborated on the various types and patterns of missing data, the limitations of case-wise deletion and state-of the-art methods of imputations and their challenges. This review highlights the inexperience or disregard of investigators of the effect of missing data in risk prediction research. Formal guidelines may enhance the reporting and appropriate handling of missing data in scientific journals.

A simple risk score for identifying individuals with impaired fasting glucose in the Southern Chinese population

This study aimed to develop and validate a simple risk score for detecting individuals with impaired fasting glucose (IFG) among the Southern Chinese population. A sample of participants aged ≥20 years and without known diabetes from the 2006-2007 Guangzhou diabetes cross-sectional survey was used to develop separate risk scores for men and women. The participants completed a self-administered structured questionnaire and underwent simple clinical measurements. The risk scores were developed by multiple logistic regression analysis. External validation was performed based on three other studies: the 2007 Zhuhai rural population-based study, the 2008-2010 Guangzhou diabetes cross-sectional study and the 2007 Tibet population-based study. Performance of the scores was measured with the Hosmer-Lemeshow goodness-of-fit test and ROC c-statistic. Age, waist circumference, body mass index and family history of diabetes were included in the risk score for both men and women, with the additional factor of hypertension for men. The ROC c-statistic was 0.70 for both men and women in the derivation samples. Risk scores of ≥28 for men and ≥18 for women showed respective sensitivity, specificity, positive predictive value and negative predictive value of 56.6%, 71.7%, 13.0% and 96.0% for men and 68.7%, 60.2%, 11% and 96.0% for women in the derivation population. The scores performed comparably with the Zhuhai rural sample and the 2008-2010 Guangzhou urban samples but poorly in the Tibet sample. The performance of pre-existing USA, Shanghai, and Chengdu risk scores was poorer in our population than in their original study populations. The results suggest that the developed simple IFG risk scores can be generalized in Guangzhou city and nearby rural regions and may help primary health care workers to identify individuals with IFG in their practice.

A home-based method for the detection of impaired glucose tolerance in hypertensive primary care patients

OBJECTIVE

The aim of this project was to compare an oral glucose tolerance test (OGTT) partly performed in the patient's home (OGTTh) with a clinic-obtained OGTT with regard to the ability of the tests to identify patients with impaired glucose tolerance (IGT) and type 2 diabetes mellitus (DM-2).

DESIGN

A method comparison.

SETTING

The study was completed at two primary health care centres.

SUBJECTS

Fifty-one patients with hypertension aged 50-79 years completed both OGTT tests.

MAIN OUTCOME MEASURES

Values for capillary P-glucose obtained two hours after a glucose load were compared between the two OGTT tests. Fasting plasma glucose (fP-glucose) and HbA1c were also measured.

RESULTS

Thirty-seven patients were classified in the same group (normal/IGT/DM-2) by the two tests. The index of validity based on the test's ability to identify normal or pathological values (≥ 8.9 mmol/l) was 0.75. The value for kappa was 0.66 with a sensitivity of 0.54 and a specificity of 0.82.

CONCLUSION

OGTTh may be a useful screening method for IGT in risk groups such as hypertensive patients.

Evaluation of Finnish Diabetes Risk Score in screening undiagnosed diabetes and prediabetes among U.S. adults by gender and race: NHANES 1999-2010

Objective

To evaluate the performance of Finnish Diabetes Risk Score (FINDRISC) in detecting undiagnosed diabetes and prediabetes among U.S. adults by gender and race.

Methods

This cross-sectional analysis included participants (aged ≥20 years) from the National Health and Nutrition Examination Survey (NHANES) 1999–2010. Sensitivity, specificity, area under the receiver operating characteristic (ROC) curve and the optimal cutoff points for identifying undiagnosed diabetes and prediabetes were calculated for FINDRISC by gender and race/ethnicity.

Results

Among the 20,633 adults (≥20 years), 49.8% were women and 53.0% were non-Hispanic White. The prevalence of undiagnosed diabetes and prediabetes was 4.1% and 35.6%, respectively. FINDRISC was positively associated with the prevalence of diabetes (OR = 1.48 for 1 unit increase, p<0.001) and prediabetes (OR = 1.15 for 1 unit increase, p<0.001). The area under ROC for detecting undiagnosed diabetes was 0.75 for total population, 0.74 for men and 0.78 for women (p = 0.04); 0.76 for White, 0.76 for Black and 0.72 for Hispanics (p = 0.03 for White vs. Hispanics). The area under ROC for detecting prediabetes was 0.67 for total population, 0.66 for men and 0.70 for women (p<0.001); 0.68 for White, 0.67 for Black and 0.65 for Hispanics (p<0.001 for White vs. Hispanics). The optimal cutoff point was 10 (sensitivity = 0.75) for men and 12 (sensitivity = 0.72) for women for detecting undiagnosed diabetes; 9 (sensitivity = 0.61) for men and 10 (sensitivity = 0.69) for women for detecting prediabetes.

Conclusions

FINDRISC is a simple and non-invasive screening tool to identify individuals at high risk for diabetes in the U.S. adults.

Evaluation of the Finnish Diabetes Risk Score (FINDRISC) as a screening tool for the metabolic syndrome

OBJECTIVES

Traditionally, the Finnish Diabetes Risk Score (FINDRISC) questionnaire is a screening tool to estimate risk of type 2 diabetes. In this study, we evaluated the ability of FINDRISC to predict the development of the metabolic syndrome (MetS) in an Iranian population without diabetes and MetS.

METHODS

A total of 1,010 first-degree relatives of consecutive patients with type 2 diabetes, 30-70 years old (274 men and 736 women), without diabetes and MetS, were examined and followed up over 8.0 ± 1.6 years (mean ± SD) for MetS incidence. The incidence of MetS was examined across quartiles of FINDRISC, and a receiver operating characteristic (ROC) curve was plotted to assess the discrimination. At baseline and through follow-ups, participants underwent a standard 75 g 2-hour oral glucose tolerance test (OGTT). Data for determining FINDRISC were available from each participant.

RESULTS

During 8,089 person-years of follow-up, 69 men and 209 women without MetS and diabetes at baseline subsequently developed MetS. The incidence of MetS was 31.4 per 1000 person-years in men and 35.5 in women. The FINDRSC at baseline was significantly associated with MetS evolution. Participants in the top quartile of FINDRISC were 4.4 times more likely to develop MetS than those in the bottom quartile (rate ratio 4.4; 95% CI 2.7-7.0). The area under the ROC curve was 65.0% (95% CI 61.3-68.7).

CONCLUSION

The results of this study suggest that FINDRISC can be applied to detect MetS in a high-risk population.

Effectiveness of Financial Incentives in a Worksite Diabetes Prevention Program

Purpose

To evaluate the effect of financial incentive in a diabetes prevention weight loss program at worksites.

Design

Group-level randomized intervention study.

Setting

Four long-term care facilities, randomly assigned to “incentive-IG” or “non incentive-NIG” groups.

Participants

Ninety-nine employees, all overweight or obese (BMI= mean 34.8±7.4 kg/m²) and at risk for type 2 diabetes.

Intervention

A 16 week weight loss program (diabetes prevention program) with a 3 month follow up. IG could either choose a "standard incentive" to receive cash award when achieving the projected weight loss or to participate in a "standard plus deposit incentive" to get additional money matched with their deposit for projected weight loss. All of the participants received a one-hour consultation for a healthy weight loss at the beginning.

Measures

Weight-loss, diabetes risk score (DRS), and cardiovascular risk outcomes.

Analyses

Linear and logistic regressions for completed cases with adjustments for clustering effect at group level.

Results

IG lost on average more pounds (p=0.027), reduced BMI (p=0.04), and reduced in DRS (p=0.011) compared to NIG at week 16. At the 12-week follow-up period, those in IG plus deposit subgroup had twice the odds (OR=2.2, p=0.042) and those in the standard IG had three times the odds of achieving weight loss goals than NIG; those in the IG plus deposit group reduced DRS by 0.4 (p=0.045).

Conclusion

Monetary incentives appear to be effective in reducing weight and diabetes risk.

Finnish Diabetes Risk Score to predict type 2 diabetes in the Isfahan diabetes prevention study

AIM

The strong association between the Finnish Diabetes Risk Score (FINDRISC) and risk of diabetes reported in European populations cannot necessarily be generalized to other populations. The aim of this study was to evaluate the ability of FINDRISC to predict progression to diabetes in an Iranian population without diabetes.

METHODS

A total of 1537 first-degree relatives (FDR) without diabetes of consecutive people with type 2 diabetes 30-70 years old (376 men and 1161 women) were examined and followed for a mean (SD) of 7.8 (1.7) years for diabetes incidence. We examined the incidence of diabetes across quartiles of FINDRISC and plotted a receiver operating characteristic (ROC) curve to assess discrimination. At baseline and through follow-up, participants underwent a standard 75-g 2-h oral glucose tolerance test. Data for the FINDRISC were available from each participant.

RESULTS

During 12,046 person-years of follow-up, 41 men and 154 women developed diabetes. The incidence of type 2 diabetes was 14.0 per 1000 person-years in men and 16.9 in women. Those in the top quartile of FINDRISC were 21.7 times more likely to develop diabetes than those in the bottom quartile (relative risk 21.7; 95% CI 9.90, 47.39). The area under the ROC was 75.1% (95% CI 71.3, 78.8).

CONCLUSIONS

The results of this study show that FINDRISC is a robust predictor of type 2 diabetes in high-risk individuals in Iran.

The performance of the Finnish Diabetes Risk Score, a modified Finnish Diabetes Risk Score and a simplified Finnish Diabetes Risk Score in community-based cross-sectional screening of undiagnosed type 2 diabetes in the Philippines

AIM

The performance of the Finnish Diabetes Risk Score (FINDRISC) and 2 modifications in community screening for undiagnosed type 2 diabetes (UDD) in the Philippines was evaluated.

METHODS

Active community-based screening for diabetes was conducted where FINDRISC assessment was done. Modified (modFINDRISC) and simplified (simpFINDRISC) versions were rendered based on Asian standards, study results, and local context. Diabetes was diagnosed through 2 separate blood glucose tests. Areas under the receiver operating characteristic curve (ROC-AUC) and statistics for diagnostic tests for FINDRISC and the modifications were analyzed.

RESULTS

Complete data was collected from 1752 people aged 20-92; 8.6% tested positive for diabetes. ROC-AUC for UDD were 0.738 (FINDRISC), 0.743 (modFINDRISC) and 0.752 (simpFINDRISC). The differences between the FINDRISC and the modifications were not statistically significant (p=0.172).

CONCLUSIONS

The performance of all 3 risk score calculators in the screening for UDD in the Philippines was good and may be useful in populations having similar characteristics. Considering the setting and resource constraints, the simpFINDRISC is preferred.

Risk-assessment score for screening diabetes mellitus among Omani adults

PURPOSE

The purpose of this study was to evaluate a self-administered risk-assessment scoring system for identifying Omani adults with type 2 diabetes mellitus (T2DM).

METHODS

An exploratory cross-sectional design was used. Simple random sampling was used to select 93 adults in Muscat. Ethical approval was obtained from the College of Nursing Research and Ethics Committee. The Finnish Diabetes Risk Score (FINDRISC) was used to collect the data in 2009. Informed consent was obtained from the participants. Data were analysed with the Pearson chi-square test.

RESULTS

A total of 9.7% of the adults had very high FINDRISC and 17.2% had slightly elevated risk of developing T2DM within 10 years. The risk assessment (family history, waist circumference, body mass index, physical activity, dietary intake, hypertension and high blood glucose) of T2DM was significant and positively related to the prediction of T2DM among Omani adults.

Prevalence and risk factors for diabetic retinopathy in a high-risk Chinese population

Background

Lifestyle plays an important role in the development of diabetic retinopathy. The lifestyle in Guangzhou is different from other cities in China as the Cantonese prefer eating rice porridge, but not spicy foods. The objectives of this study were to investigate the prevalence and determinants of diabetic retinopathy in a high-risk population of Guangzhou.

Methods

Subjects (619 totals) aged over 45 years old, without known diabetes were recruited from five randomly selected Guangzhou communities in 2009–2010. All participants were invited to complete the Finnish Diabetes Risk Score (FINDRISC) questionnaire. Subjects with FINDRISC score ≥ 9 were included in the study, and underwent an investigation of demographic data, a standardized physical examination, ocular fundus examination, and laboratory analyses. The minimum criterion for diagnosis of diabetic retinopathy was the presence of at least one microaneurysm.

Results

Of 619 subjects, 208 eligible subjects (122 women) with FINDRISC score ≥ 9 were included in the study. The mean age was 69.2 ± 8.5 years. Diabetic retinopathy was detected in 31 subjects, and the prevalence of diabetic retinopathy in subjects with high risk for diabetes was 14.9%. In binary logistic regression analysis, risk factors associated with diabetic retinopathy were history of impaired glucose regulation [odds ratio (OR), 7.194; 95% confidence interval (CI): 1.083, 47.810], higher hemoglobin A1c (HbA1c; OR, 2.912; 95% CI: 1.009, 8.402), higher two-hour postprandial plasma glucose level (OR, 1.014; 95% CI: 1.003, 1.025), and presence of microalbuminuria (OR, 5.387; 95% CI: 1.255, 23.129).

Conclusions

Diabetic retinopathy was prevalent in a high-risk Chinese population from Guangzhou. Histories of impaired glucose regulation and microalbuminuria were strong risk factors for diabetic retinopathy.

Development of a screening score for undiagnosed diabetes and its application in estimating absolute risk of future type 2 diabetes in Japan: Toranomon Hospital Health Management Center Study 10 (TOPICS 10)

OBJECTIVE

The objective of the study was to develop a screening score for undiagnosed diabetes by eliciting information on noninvasive clinical markers and to assess its effectiveness for identifying the presence of diabetes and predicting future diabetes.

DESIGN, SETTING, AND PARTICIPANTS

A screening score was cross-sectionally developed for 33 335 Japanese individuals aged 18-88 years without known diabetes who underwent a health examination. We validated its utility and compared it with existing screening tools in an independent population (n = 7477). After initial assessment of the instrument, 7332 nondiabetic individuals were followed up for a mean 4.0 years.

RESULTS

Prevalence of undiagnosed diabetes (fasting plasma glucose ≥ 7.0 mmol/L or glycated hemoglobin ≥ 6.5%) was 2.9% (n = 965). Diabetes score included age, sex, family history of diabetes, current smoking habit, body mass index, and hypertension with an area under the receiver-operating characteristics curve of 0.771. Screening with 8 or more points yielded a sensitivity of 72.7% and a specificity of 68.1%. In the validation cohort, the area under the receiver-operating characteristics curve was 0.806. The developed score with 8 or more points had better positive predictive value (9.6%) and positive likelihood ratio (2.52) compared with existing tools (positive predictive value, from 6.9% to 9.4%; positive likelihood ratio, from 1.77 to 2.46) in which each tool's highest combination of sensitivity and specificity was observed. The 4-year cumulative risk of developing diabetes gradually escalated in association with higher screening scores at the initial examination.

CONCLUSIONS

Our algorithm could serve as a self-assessment tool for undiagnosed diabetic patients needing timely medical care and as a prognostic tool for individuals without present diabetes who must be closely followed up to prevent future diabetes.

Risk scores based on self-reported or available clinical data to detect undiagnosed type 2 diabetes: a systematic review

OBJECTIVE

To systematically review published primary research on the development or validation of risk scores that require only self-reported or available clinical data to identify undiagnosed Type 2 Diabetes Mellitus (T2DM).

METHODS

A systematic literature search of Medline and EMBASE was conducted until January 2011. Studies focusing on the development or validation of risk scores to identify undiagnosed T2DM were included. Risk scores to predict future risk of T2DM were excluded.

RESULTS

Thirty-one studies were included; 17 developed a new risk score, 14 validated existing scores. Twenty-six studies were conducted in high-income countries. Age and measures of body mass/fat distribution were the most commonly used predictor variables. Studies developing new scores performed better than validation studies, with 11 reporting an AUC of >0.80 compared to one validation study. Fourteen validation studies reported sensitivities of <80%. The performance of scores did not differ by the number of variables included or the country setting.

CONCLUSIONS

There is a proliferation of newly developed risk scores using similar variables, which sometimes perform poorly upon external validation. Future research should explore the recalibration, validation and applicability of existing scores to other settings, particularly in low/middle income countries, and on the utility of scores to improve diabetes-related outcomes.

Feasibility of the FINDRISC questionnaire to identify individuals with impaired glucose tolerance in Swedish primary care. A cross-sectional population-based study

AIM

To evaluate the performance of the FINDRISC questionnaire as a tool to recruit individuals with impaired glucose tolerance for lifestyle intervention programmes.

METHODS

A cross-sectional population-based study in primary Health Care Centres in a middle-sized Swedish town. All 9734 individuals, aged 35-75 years, living within a defined area, were invited by mail to fill in and return the FINDRISC questionnaire. Participants with a risk score ≥ 15 (n = 525) were invited to perform an oral glucose tolerance test while those with known diabetes were excluded.

RESULTS

In total, 5452 questionnaires (58%) were returned and revealed a mean risk-score of 8.5 ± 4.5 (mean ± SD). We found that 525 participants had a risk-score ≥ 15 and 302 (58%) were further examined with an oral glucose tolerance testing (OGTT). Among them we detected 11% with previously undiagnosed Type 2 diabetes, 16% with impaired glucose tolerance and 29% with impaired fasting glucose. A FINDRISC score ≥ 15 was associated with a positive predictive value of 55% for impaired glucose metabolism (impaired fasting glucose + impaired glucose tolerance + Type 2 diabetes) and of 16% for impaired glucose tolerance, respectively. The positive predictive value for impaired glucose tolerance did not increase to more than 17% when choosing the cut-point 17, while there was a significant increase in the positive predictive value for impaired glucose metabolism (70%).

CONCLUSIONS

The FINDRISC questionnaire is a useful instrument for identification of individuals with impaired glucose metabolism but seems less effective for detection of individuals with impaired glucose tolerance. Strategies to find individuals with impaired glucose tolerance for implementation of lifestyle changes in primary care should therefore be developed further.

Survey of diabetes risk assessment tools: concepts, structure and performance

The objective of this study is to review the effectiveness and limitations of existing diabetes risk screening tools to assess the need for further developing of such tools. An electronic search of the EMBASE, MEDLINE, and Cochrane library supplemented by a manual search was performed from 1995-2010. The search retrieved a total of 2168 articles reporting diabetes risk assessment tools which, after culling, produced 41 tools developed in 22 countries, with the majority (n = 26) developed in North America and Europe. All are short questionnaires of 2-16 questions incorporating common variables including age, gender, waist circumference, BMI, family history of diabetes, history of hypertension or antihypertensive medications. While scoring format and cut-offs point are diverse between questionnaires, overall accuracy value range of 40-97%, 24-86% and 62-87% were reported for sensitivity, specificity and receiver operating characteristic curve respectively. In summary, there is a trend of increasing availability of diabetes prediction tools with the existing risk assessment tools being generally a short questionnaire aiming for ease of use in clinical practice. The overall performance of existing tools showed moderate to high accuracy in their predictive performance. However, further detailed comparison of existing questionnaires is needed to evaluate whether they can serve adequately as diabetes risk assessment tool in clinical practice.

Estimating the potential population impact of stepwise screening strategies for identifying and treating individuals at high risk of Type 2 diabetes: a modelling study

BACKGROUND

Diabetes risk assessment has been proposed as part of the National Health Service Health Checks programme, and HbA(1c) has recently been recommended as a diagnostic test for diabetes at a threshold of 48 mmol/mol (6.5%). We estimated the potential population impact of different stepwise screening strategies to identify individuals at high risk who might be offered preventive interventions.

METHODS

Using data from 5910 participants in the European Prospective Investigation of Cancer (EPIC)-Norfolk cohort with HbA(1c) measurements, we modelled different stepwise screening strategies for identifying and treating individuals at high risk of Type 2 diabetes using different HbA(1c) cut-off points with and without a stage of prestratification. For each strategy, we estimated the number needed to have a diagnostic test, the number needed to treat to prevent one new case of Type 2 diabetes, and the number of new cases that could be prevented in the population over 3 years. Relative risk reductions for estimated effects of intensive lifestyle intervention were derived from the US Diabetes Prevention Program.

RESULTS

Compared with inviting all individuals in an average primary care trust for a diagnostic test, a stepwise screening approach using simple routine data such as age and anthropometric indices could prevent a slightly lower number (lower-upper estimates) of new cases of Type 2 diabetes over 3 years (224 [130-359] and 193 [109-315] cases respectively) but would only require half the population to be invited for a diagnostic blood test. A total of 162 (88-274) cases could be prevented by inviting individuals with a Cambridge risk score of ≥ 0.15, with only 40% of the total population requiring diagnostic blood tests. Using a participant completed questionnaire for risk assessment (FINDRISC) was less effective, mainly relating to the questionnaire response rate. Providing preventive interventions to those with a lower HbA(1c) of 37-< 48 mmol/mol (5.5-< 6.5%) could prevent more cases but with a disproportionately higher workload, compared with using the recommended HbA(1c) threshold of 42-< 48 mmol/mol (6.0-< 6.5%).

CONCLUSIONS

Compared with mass screening, an approach using routine data for risk stratification followed by an HbA(1c) test with a threshold of 42-< 48 mmol/mol (6.0-< 6.5%) for identifying individuals suitable for preventive interventions might prevent slightly fewer cases of Type 2 diabetes but with potential cost-savings.

Nonpharmacological interventions for the prevention of type 2 diabetes mellitus

During the past decade, improved understanding of the pathophysiological mechanisms of diabetes development has resulted in advances in therapeutic concepts, but has also supported the potential for diabetes prevention through nonpharmacological means. At the beginning of the century, we experienced a shift in paradigm, as landmark studies have shown that diabetes mellitus is preventable with lifestyle intervention; moderate changes in diet and physical activity produce a substantial and sustained reduction in the incidence of type 2 diabetes mellitus (T2DM) for individuals with impaired glucose tolerance. This evidence must now be translated into clinical and public-health practice, but translational studies have varied in their ability to replicate the results of clinical trials. This variation reflects a number of challenging barriers for diabetes prevention in real-world clinical practice, which makes it necessary to focus on identifying efficient intervention methods and delivery mechanisms. Research is now focusing on these mechanisms, as well as on developing efficient screening and risk-identification strategies and realistic scenarios for public-health policy to implement diabetes prevention programs. In this Review, we will discuss these mechanisms and will consider the implications of diabetes prevention for public-health strategy and policy.

[Validation of the FINDRISC (FINnish Diabetes RIsk SCore) for prediction of the risk of type 2 diabetes in a population of southern Spain. Pizarra Study]

BACKGROUND AND OBJECTIVE

The aim of this study was to validate the ability of the Finnish Diabetes Risk Score (FINDRISC) to predict the risk of DM2 in a population of south-eastern Spain (Pizarra Study).

SUBJECTS AND METHODS

The Pizarra Study is a population-based prospective study developed in the town of Pizarra (Málaga). The first phase of the study was conducted in 1997-1998, including 1051 individuals aged 18-65 years randomly selected from the municipal census of the town. In 2003-2004 the subjects participating in the first study were reassessed. 824 individuals completed the second phase of the study (78.4%). All participants without known diabetes underwent an oral glucose tolerance test both at baseline and follow-up. We evaluated the ability of the FINDRISC to detect undiagnosed DM2 (first phase: cross-sectional study) and in predicting the incidence of DM2 (second phase: cohort study).

RESULTS

The test showed good results both to detect undiagnosed DM2 (ROC-AUC 0.74) and to predict incident DM2 (ROC-AUC 0.75). The best prediction of risk of incident DM2 was found in those subjects with fasting glucose >100mg/dl and a FINDRISC ≥9 (OR: 19.37; 95%IC: 8,86-42,34; P<.0001).

CONCLUSIONS

The results of our study show that FINDRISC can be a useful tool to detect subjects at high risk of diabetes in this population.

Screening for type 2 diabetes and dysglycemia

Type 2 diabetes mellitus (T2DM) and dysglycemia (impaired glucose tolerance and/or impaired fasting glucose) are increasingly contributing to the global burden of diseases. The authors reviewed the published literature to critically evaluate the evidence on screening for both conditions and to identify the gaps in current understanding. Acceptable, relatively simple, and accurate tools can be used to screen for both T2DM and dysglycemia. Lifestyle modification and/or medication (e.g., metformin) are cost-effective in reducing the incidence of T2DM. However, their application is not yet routine practice. It is unclear whether diabetes-prevention strategies, which influence cardiovascular risk favorably, will also prevent diabetic vascular complications. Cardioprotective therapies, which are cost-effective in preventing complications in conventionally diagnosed T2DM, can be used in screen-detected diabetes, but the magnitude of their effects is unknown. Economic modeling suggests that screening for both T2DM and dysglycemia may be cost-effective, although empirical data on tangible benefits in preventing complications or death are lacking. Screening for T2DM is psychologically unharmful, but the specific impact of attributing the label of dysglycemia remains uncertain. Addressing these gaps will inform the development of a screening policy for T2DM and dysglycemia within a holistic diabetes prevention and control framework combining secondary and high-risk primary prevention strategies.

A Chinese diabetes risk score for screening of undiagnosed diabetes and abnormal glucose tolerance

BACKGROUND

This study is aimed at developing and evaluating a diabetes risk score (DRS) to predict incident diabetes and screen for undiagnosed diabetes and abnormal glucose tolerance in the Chinese population.

METHODS

Three DRS instruments were respectively developed and validated based on the data collected from a 10-year longitudinal health checkup-based population of 1,851 individuals without diabetes at baseline. The efficiency on glucose abnormality screening was evaluated based on the testing of a cross-sectional sample of 699 individuals without known diabetes.

RESULTS

The DRS consisting of age, hypertension, history of high blood glucose, body mass index, fasting plasma glucose, serum triglycerides, and serum high-density lipoprotein-cholesterol had the best prediction properties (area under curve [AUC] = 0.734 [95% confidence interval 0.702-0.766] and 0.759 [0.686-0.831] in exploratory and validation cohorts, respectively). The DRS had a sensitivity of 64.5% and 72.9%, respectively, and a specificity of 71.6% and 63.9%, respectively, with an optimal cutoff of 4. AUCs were 0.828 (0.797-0.860) and 0.909 (0.884-0.933) for detecting abnormal glucose tolerance and diabetes, respectively, through cross-sectional screening. Performance of the oral glucose tolerance test (OGTT) in selected subjects with DRS ≥ 4 led to the identification of 76.2% cases of abnormal glucose tolerance and 100% cases of diabetes, while avoiding an OGTT in 52.8% of the study group.

CONCLUSIONS

The DRS instrument including age, hypertension, history of high blood glucose, body mass index, fasting plasma glucose, triglycerides, and high-density lipoprotein-cholesterol is practical and effective in predicting incident diabetes and screening glucose abnormality in the Chinese population.

Diagnosis of prediabetes

A rational approach to diagnosing prediabetes is essential to identify those who would benefit from entering diabetes prevention programs. Impaired fasting glucose and impaired glucose tolerance are similar in relation to their ability to identify those at risk of diabetes or cardiovascular disease; however, because they identify different segments of the at-risk population, there is value in undertaking glucose tolerance testing to ensure that both conditions can be diagnosed. Simple noninvasive diabetes risk scores offer a valuable entry point in the diagnosis of prediabetes, enabling the identification of those who need blood testing.

The Finnish Diabetes Risk Score (FINDRISC) as a screening tool for hepatic steatosis

INTRODUCTION. Hepatic steatosis due to non-alcoholic fatty liver disease is associated with obesity, dyslipidemia, insulin resistance, and type 2 diabetes. The Finnish Diabetes Risk Score (FINDRISC) is a prognostic screening tool to detect people at risk for type 2 diabetes without the use of any blood test. The objective of this study was to evaluate whether FINDRISC can also be used to screen for the presence of hepatic steatosis. PATIENTS AND METHODS. Steatosis was determined by ultrasound. The study sample consisted of 821 non-diabetic subjects without previous hepatic disease; 81% were men (mean age 45 ± 9 years) and 19% women (mean age 41 ± 10 years). RESULTS. Steatosis was present in 44% of men and 10% of women. The odds ratio for one unit increase in the FINDRISC associated with the risk of steatosis was 1.30 (95% CI 1.25-1.35), similar for men and women. The area under the receiver operating characteristics curve for steatosis was 0.80 (95% CI 0.77-0.83); 0.80 in men (95% CI 0.77-0.83) and 0.83 (95% CI 0.73-0.93) in women. CONCLUSIONS. Our data suggest that the FINDRISC could be a useful primary screening tool for the presence of steatosis.

Validation of the Finnish diabetes risk score (FINDRISC) questionnaire for screening for undiagnosed type 2 diabetes, dysglycaemia and the metabolic syndrome in Greece

AIM

The present study aimed to validate the Finnish Type 2 Diabetes Risk Score (FINDRISC) questionnaire for its ability to predict the presence of any glucose homoeostasis abnormalities and the metabolic syndrome (MetS) in the Greek population.

METHODS

Validation was performed on a sample of individuals who had agreed to participate in a screening program for type 2 diabetes (T2D) prevention (the Greek part of the DE-PLAN study), using both FINDRISC and oral glucose tolerance tests (OGTT). Impaired fasting glucose (IFG) was defined as a fasting plasma glucose level of 6.1-6.9 mmol/L, and impaired glucose tolerance (IGT) as a 2-h plasma glucose of 7.8-11.0 mmol/L. The predictive value of the FINDRISC was cross-sectionally evaluated using the area under the receiver operating characteristic (AUROC) curve method.

RESULTS

A total of 869 individuals (379 men, aged 56.2 ± 10.8 years) were screened from the general population living in the city and suburbs of Athens. OGTT revealed the presence of unknown diabetes in 94 cases (10.8%), IFG in 85 (9.8%) and IGT in 109 (12.6%). The sensitivity of a FINDRISC score greater or equal to 15 (45% of the population) to predict unknown diabetes was 81.9% and its specificity was 59.7%. The AUROC curve for detecting unknown diabetes was 0.724 (95% CI: 0.677-0.770). For any dysglycaemia, the AUROC curve was 0.716 (0.680-0.752) while, for detection of the MetS, it was 0.733 (0.699-0.767).

CONCLUSION

The FINDRISC questionnaire performed well as a screening tool for the cross-sectional detection of unknown diabetes, IFG, IGT and the MetS in the Greek population.

Adiponectin gene polymorphisms and their effect on the risk of myocardial infarction and type 2 diabetes: an association study in an Italian population

OBJECTIVE

While many studies have shown an association between the gene coding for adiponectin (ADIPOQ) and adiponectin levels, much more controversy surrounds its association with metabolic traits such as insulin resistance, obesity and type 2 diabetes. Furthermore, very few studies have looked into the relations between ADIPOQ variants and risk of cardiovascular disease. The present study assessed the influence of four common ADIPOQ Single Nucleotide Polymorphisms (SNPs), rs17300539 (-11391G→A), rs266729 (-11377C→G), rs2241766 (+45T→G) and rs1501299 (+276G→T) on the risk of myocardial infarction and type 2 diabetes.

METHODS

and

RESULTS

A large genetic association case-control study was conducted in 2008 Italians, including patients with myocardial infarction, type 2 diabetes, or both, and a reference group of healthy controls. Homozygotes TT for the rs1501299 (+276) had half the risk of either myocardial infarction alone or in association with type 2 diabetes when compared to the carriers of the G allele (OR = 0.58, p =0.01, and OR = 0.55, p =0.006 respectively). SNPs rs17300539 (-11391), rs266729 (-11377) and rs2241766 (+45) showed no significant association with any of the three case groups.

CONCLUSIONS

These results suggest that homozygotes TT for the adiponectin polymorphism rs1501299 (+276) are protected from the risk of myocardial infarction.

A simple risk score to identify Southern Chinese at high risk for diabetes

AIMS

To develop a simple scoring system for identifying Southern Chinese at risk of diabetes.

METHODS

The score was derived from a risk factor matching cohort for Type 2 diabetes in Hong Kong Chinese (cohort 1, 2448 subjects without a history of diabetes; age, mean +/- sd 37.2 +/- 8.9 years, median 36.0 years; 1649 had risk factors for diabetes and 799 were age-matched control subjects from the community). Two other cohorts were used to validate the risk score (cohort 2, 3734 subjects with risk factors for diabetes; and cohort 3, 1513 participants of a community diabetes survey). All subjects had a 75 g oral glucose tolerance test (OGTT).

RESULTS

In cohort 1, 270 (11%) of the subjects were found to have diabetes on OGTT. A risk score system was derived using the beta values of the corresponding predictors in the logistic regression analysis. The area under the curve (95% confidence intervals) of the score system was 0.735 (0.705, 0.765). The application of a risk score of > or = 16 increased the detection rate 2.5-4 times in all three cohorts. A high post-test probability of diabetes of > 60% was derived from a risk score of > or = 20. Only 10-20 and approximately 5% with a score of > or = 12 and > or = 16, respectively, are indicated for OGTT. This will considerably improve the yield of OGTT screening.

CONCLUSIONS

A simple risk score identifies young-to-middle-aged Southern Chinese at high risk for diabetes. Subjects with a score of 16 or above (out of 30) should undergo OGTT for definitive diagnosis of diabetes.

An active strategy to identify individuals eligible for type 2 diabetes prevention by lifestyle intervention in Dutch primary care: the APHRODITE study

BACKGROUND

Several trials have shown the potential of lifestyle intervention programmes for prevention of type 2 diabetes. The effectiveness of implementation of these programmes into daily practice is now being studied in several countries. The 'Active Prevention in High Risk individuals of Diabetes Type 2 in Eindhoven' (APHRODITE) study investigates whether type 2 diabetes prevention by lifestyle intervention is effective in Dutch primary care. In this article we describe the process of recruiting the study participants.

OBJECTIVE

To assess the reach of an active strategy to recruit participants for a programme on type 2 diabetes prevention by lifestyle intervention in Dutch primary care.

METHODS

A diabetes risk questionnaire was sent to general practice patients aged 40-70 years. Individuals with a risk score above threshold were invited for an admission interview with the GP and an oral glucose tolerance test (OGTT). All individuals with non-diabetic glucose levels were asked to participate in the intervention study.

RESULTS

In total, 8752 (54.6%) of the individuals returned the questionnaire in time. Of all high-risk individuals (n = 1533), 73.1% contacted their practice to schedule a consultation with the GP. Response rates varied significantly among practices.

CONCLUSIONS

Using invitational letters, a substantial amount of individuals could be motivated to participate in a programme on type 2 diabetes prevention by lifestyle intervention in Dutch primary care. Further research is needed on what kind of strategy would be most effective and efficient to screen for individuals at high risk for type 2 diabetes in primary care.

Common genetic variants on chromosome 9p21 are associated with myocardial infarction and type 2 diabetes in an Italian population

Background

A genomic region on chromosome 9p21 has been identified as closely associated with increased susceptibility to coronary artery disease (CAD) and to type 2 diabetes (T2D) although the evidence suggests that the genetic variants within chromosome 9p21 that contribute to CAD are different from those that contribute to T2D.

We carried out an association case-control study in an Italian population to test the association between two single nucleotide polymorphisms (SNPs) on the 9p21 locus, rs2891168 and rs10811661, previously reported by the PROCARDIS study, and respectively myocardial infarction (MI) and T2D. Our aim was to confirm the previous findings on a larger sample and to verify the independence of their susceptibility effects: rs2891168 associated with MI but not with T2D and rs10811661 associated with T2D but not with MI.

Methods

Genomic DNA samples of 2407 Italians with T2D (602 patients), who had had a recent MI (600), or had both diseases (600) and healthy controls (605) were genotyped for the two SNPs. The genotypes were determined by allelic discrimination using a fluorescent-based TaqMan assay.

Results

SNP rs2891168 was associated with MI, but not with T2D and the G-allele odds ratio (OR) was 1.20 (95% CI 1.02-1.41); SNP rs10811661 was associated with T2D, but not with MI, and the T-allele OR was 1.27 (95% CI 1.04-1.55). ORs estimates from the present study and the PROCARDIS study were pooled and confirmed the previous findings, with greater precision.

Conclusions

Our replication study showed that rs2891168 and rs10811661 are independently associated respectively with MI and T2D in an Italian population. Pooling our results with those reported by the PROCARDIS group, we also obtained a significant result of association with diabetes for rs10811661 in the European population.

Application of support vector machine modeling for prediction of common diseases: the case of diabetes and pre-diabetes

Background

We present a potentially useful alternative approach based on support vector machine (SVM) techniques to classify persons with and without common diseases. We illustrate the method to detect persons with diabetes and pre-diabetes in a cross-sectional representative sample of the U.S. population.

Methods

We used data from the 1999-2004 National Health and Nutrition Examination Survey (NHANES) to develop and validate SVM models for two classification schemes: Classification Scheme I (diagnosed or undiagnosed diabetes vs. pre-diabetes or no diabetes) and Classification Scheme II (undiagnosed diabetes or pre-diabetes vs. no diabetes). The SVM models were used to select sets of variables that would yield the best classification of individuals into these diabetes categories.

Results

For Classification Scheme I, the set of diabetes-related variables with the best classification performance included family history, age, race and ethnicity, weight, height, waist circumference, body mass index (BMI), and hypertension. For Classification Scheme II, two additional variables--sex and physical activity--were included. The discriminative abilities of the SVM models for Classification Schemes I and II, according to the area under the receiver operating characteristic (ROC) curve, were 83.5% and 73.2%, respectively. The web-based tool-Diabetes Classifier was developed to demonstrate a user-friendly application that allows for individual or group assessment with a configurable, user-defined threshold.

Conclusions

Support vector machine modeling is a promising classification approach for detecting persons with common diseases such as diabetes and pre-diabetes in the population. This approach should be further explored in other complex diseases using common variables.

Fine-tuning of prediction of isolated impaired glucose tolerance: a quantitative clinical prediction model

In this cross-sectional study, we evaluated results of oral glucose tolerance test (OGTT) from 4742 women and 3470 men, participated in the Tehran Lipid and Glucose Study, aged >or=20 years and without diabetes, to determine the diagnostic value of subjects' clinical traits with isolated impaired glucose tolerance (isolated-IGT) defined as fasting plasma glucose (FPG) <5.6 mmol/L and 2-h plasma glucose between 7.8 and 11.1 mmol/L. The overall prevalence of IGT was 13.6% (n=1120); of these subjects, 59.6% (n=668) had isolated-IGT. The adjusted odds ratios for having isolated-IGT among 7012 subjects with FPG <5.6 mmol/L were significant for age >or=40 years (2.5), hypertension (1.9), abnormal waist circumference (1.9), obesity (1.5), and family history of diabetes (1.3). Adding the lipid profiles to the clinical model increased the area under the ROC curve only slightly (73.2% vs. 72.1%, respectively; P=0.002). In summary, this study showed that in adults with FPG <5.6 mmol/L, older age, family history of diabetes, abnormal waist circumference and obesity, and hypertension were significantly associated with a higher likelihood of isolated-IGT; OGTT could hence be recommended in subjects who have most of these characteristics to find Isolated-IGT, especially if the findings are supported by appropriately designed clinical trials.

Tool to assess likelihood of fasting glucose impairment (TAG-IT)

PURPOSE

Fifty-four million people in the United States have impaired fasting glucose (IFG); if it is identified, they may benefit from prevention strategies that can minimize progression to diabetes, morbidity, and mortality. We created a tool to identify those likely to have undetected hyperglycemia.

METHODS

We undertook a cross-sectional analysis of existing data from the National Health and Nutrition Examination Survey (NHANES) 1999-2004 of 4,045 US adults aged 20 to 64 years who did not have a diagnosis of diabetes who had a measured fasting plasma glucose. Using characteristics that are self-reported or measured without laboratory data, we developed a logistic regression model predicting IFG and undiagnosed diabetes. Based on this model, we created TAG-IT (the Tool to Assess likelihood of fasting Glucose ImpairmenT), validated it using NHANES III, examined race and ethnicity subsets, and compared it with body mass index (BMI) alone.

RESULTS

Predictors in the final tool were age, sex, BMI, family history of diabetes, resting heart rate, and history of hypertension (or measured high blood pressure), which yielded an area under the curve (AUC) of 0.740, significantly better than BMI alone (AUC = 0.644).

CONCLUSIONS

The TAG-IT efficiently identifies those most likely to have abnormal fasting glucose and can be used as a decision aid for screening in clinical and population settings, or as a prescreening tool to help identify potential participants for research. The TAG-IT represents an improvement over BMI alone or a list of risk factors in both its utility in younger adult populations and its ability to provide clinicians and researchers with a strategy to assess the risks of combinations of factors.

Determinants for the effectiveness of lifestyle intervention in the Finnish Diabetes Prevention Study

OBJECTIVE

Intensive lifestyle intervention significantly reduced diabetes incidence among the participants in the Finnish Diabetes Prevention Study. We investigated whether and to what extent risk factors for type 2 diabetes and other baseline characteristics of the study participants modified the effectiveness of the lifestyle intervention.

RESEARCH DESIGN AND METHODS

Overweight, middle-aged volunteers with impaired glucose tolerance were randomly assigned to intensive lifestyle intervention (n = 265) or to a control group (n = 257) for a median of 4 years. Diabetes status was ascertained annually with repeated oral glucose tolerance testing. Incidence rates of diabetes and hazard ratios (HRs) comparing the intervention group with the control group were calculated by sex and baseline tertiles of age, BMI, waist circumference, plasma glucose concentration at fasting and 2 h after a glucose load, fasting serum insulin and insulin resistance index, and categories of composite baseline Finnish Diabetes Risk Score (FINDRISC). Interactions between the intervention assignment and baseline risk factors on diabetes risk were analyzed.

RESULTS

The intervention was most effective among the oldest individuals (HRs 0.77, 0.49, and 0.36 by increasing age tertiles, respectively; P(interaction) = 0.0130) and those with a high baseline FINDRISC (HRs 1.09, 0.84, 0.34, and 0.22 by increasing risk score category, respectively; P(interaction) = 0.0400). The effect of the intervention on diabetes risk was not modified by other baseline characteristics or risk factors.

CONCLUSIONS

The FINDRISC may be useful in identifying high-risk groups most likely to benefit from intensive lifestyle intervention to prevent type 2 diabetes.

Random plasma glucose in serendipitous screening for glucose intolerance: screening for impaired glucose tolerance study 2

BACKGROUND

With positive results from diabetes prevention studies, there is interest in convenient ways to incorporate screening for glucose intolerance into routine care and to limit the need for fasting diagnostic tests.

OBJECTIVE

The aim of this study is to determine whether random plasma glucose (RPG) could be used to screen for glucose intolerance.

DESIGN

This is a cross-sectional study.

PARTICIPANTS

The participants of this study include a voluntary sample of 990 adults not known to have diabetes.

MEASUREMENTS

RPG was measured, and each subject had a 75-g oral glucose tolerance test several weeks later. Glucose intolerance targets included diabetes, impaired glucose tolerance (IGT), and impaired fasting glucose(110) (IFG(110); fasting glucose, 110-125 mg/dl, and 2 h glucose < 140 mg/dl). Screening performance was measured by area under receiver operating characteristic curves (AROC).

RESULTS

Mean age was 48 years, and body mass index (BMI) was 30.4 kg/m(2); 66% were women, and 52% were black; 5.1% had previously unrecognized diabetes, and 24.0% had any "high-risk" glucose intolerance (diabetes or IGT or IFG(110)). The AROC was 0.80 (95% CI 0.74-0.86) for RPG to identify diabetes and 0.72 (0.68-0.75) to identify any glucose intolerance, both highly significant (p < 0.001). Screening performance was generally consistent at different times of the day, regardless of meal status, and across a range of risk factors such as age, BMI, high density lipoprotein cholesterol, triglycerides, and blood pressure.

CONCLUSIONS

RPG values should be considered by health care providers to be an opportunistic initial screening test and used to prompt further evaluation of patients at risk of glucose intolerance. Such "serendipitous screening" could help to identify unrecognized diabetes and prediabetes.

Diabetes Risk Calculator: a simple tool for detecting undiagnosed diabetes and pre-diabetes

OBJECTIVE

The objective of this study was to develop a simple tool for the U.S. population to calculate the probability that an individual has either undiagnosed diabetes or pre-diabetes.

RESEARCH DESIGN AND METHODS

We used data from the Third National Health and Nutrition Examination Survey (NHANES) and two methods (logistic regression and classification tree analysis) to build two models. We selected the classification tree model on the basis of its equivalent accuracy but greater ease of use.

RESULTS

The resulting tool, called the Diabetes Risk Calculator, includes questions on age, waist circumference, gestational diabetes, height, race/ethnicity, hypertension, family history, and exercise. Each terminal node specifies an individual's probability of pre-diabetes or of undiagnosed diabetes. Terminal nodes can also be used categorically to designate an individual as having a high risk for 1) undiagnosed diabetes or pre-diabetes, 2) pre-diabetes, or 3) neither undiagnosed diabetes or pre-diabetes. With these classifications, the sensitivity, specificity, positive and negative predictive values, and receiver operating characteristic area for detecting undiagnosed diabetes are 88%, 75%, 14%, 99.3%, and 0.85, respectively. For pre-diabetes or undiagnosed diabetes, the results are 75%, 65%, 49%, 85%, and 0.75, respectively. We validated the tool using v-fold cross-validation and performed an independent validation against NHANES 1999-2004 data.

CONCLUSIONS

The Diabetes Risk Calculator is the only currently available noninvasive screening tool designed and validated to detect both pre-diabetes and undiagnosed diabetes in the U.S. population.

Relationship of elevated casual blood glucose level with coronary heart disease, cardiovascular disease and all-cause mortality in a representative sample of the Japanese population. NIPPON DATA80

AIMS/HYPOTHESIS

High fasting blood glucose is one of the well-known risk factors for CHD. However, in certain settings, patients cannot always be expected to fast. For example, community screenings for cardiovascular disease (CVD) risk factors in Japan are performed under non-fasting conditions to achieve high participation rates. Thus, we examined a representative cohort of the Japanese population (n=9,444, follow-up period 17.3 years) to clarify whether high casual blood glucose (CBG) can predict CVD mortality.

METHODS

We defined CBG groups as follows: high CBG >or= 11.1 mmol/l or participants with a history of diabetes mellitus; borderline high, 7.77 <or= CBG<11.1 mmol/l; higher normal, 5.22 <or= CBG<7.77 mmol/l); and lower normal, CBG<5.22 mmol/l. The multivariate-adjusted hazard ratios (HRs) for CHD, CVD and all-cause mortality were calculated.

RESULTS

The crude CHD mortality rate was 0.84 per 1,000 person-years. Age- and sex-adjusted HRs for CHD mortality were high among participants with CBG levels >or= 7.77 mmol/l, regardless of time since last meal. Multivariate-adjusted HRs (95% CI) of CHD mortality in high and borderline high CBG groups were 2.62 (1.46-4.67) and 2.43 (1.29-4.58), respectively. Similar results were observed for both CVD and all-cause mortality. Even within the normal blood glucose range, each 1 mmol/l increase in CBG was associated with a statistically significant increase in the HR for CVD mortality (1.12, 95% CI 1.02-1.22). Population-attributable fractions of the combined groups of high and borderline high CBG for CHD, CVD and all-cause mortality were 12.0, 4.9 and 3.5%, respectively.

CONCLUSIONS/INTERPRETATION

Increases in CBG, even within the normal range, predict CVD mortality.

Assessing risk for development of diabetes in young adults

PURPOSE

The prevalence of diabetes is increasing to epidemic levels. A multivariable risk score for the development of diabetes has been shown to be predictive for middle-aged adults; however, it is unclear how well it performs in a younger adult population. The purpose of this study was to evaluate a preexisting multivariable risk score for the development of diabetes in a young adult cohort.

METHODS

We analyzed the Coronary Artery Risk Development in Young Adults (CARDIA), a population-based observational study of participants aged 18 to 30 years recruited in 1985-1986. We observed individuals without diabetes at baseline for 10 years for the development of diabetes (n = 2,543). We computed receiver operating characteristic (ROC) curves for a diabetes risk score composed of the following 6 variables: elevated blood pressure, low high-density lipoprotein cholesterol levels, high triglyceride levels, body mass index, large waist circumference, and hyperglycemia.

RESULTS

The area under the ROC curve was .70 in this population, which was less than the .78 previously found among middle-aged adults. BMI alone (.67) was not significantly different from the risk score. Blacks (.72; 95% CI, .69-.74) and whites (.68; 95% CI, .66-.71) do not significantly differ in the area under the ROC curve for the risk score; however, the area under the ROC curve for BMI is significantly larger for blacks (.69; 95% CI, .66-.72) than for whites (.63; 95% CI, .60-.65).

CONCLUSION

An established risk score for the development of diabetes among middle-aged persons has limited utility in a younger population. Future research needs to focus on identifying novel factors that may improve the risk stratification for diabetes development among young adults.

Using common clinical data improves the prediction of abnormal glucose tolerance by the new criteria of impaired fasting glucose: Tehran lipid and glucose study

OBJECTIVE

To identify a subgroup of individuals with impaired fasting glucose (IFG) based on the new 2003 criteria that would most likely benefit from performance of oral glucose tolerance test.

METHODS

A cross-sectional study was carried out in 1999-2001 in an Iranian urban population which enrolled 8766 individuals over 20 years. Fasting and 2-h plasma glucose was measured in all subjects after exclusion of diabetic subjects. Logistic regression and receiver operation characteristic (ROC) curve analysis were used to determine the independent clinical risk factors and their optimal cut-points associated with impaired glucose tolerance (IGT) and dysglycemia (IGT or diabetes).

RESULTS

Application of the new criteria decreased positive likelihood ratio (LR+) of IFG for detecting IGT (from 6.68 to 3.86) or dysglycemia (from 9.90 to 4.46) but slightly improved their agreement (Kappa increased from 0.158 to 0.286 for IGT and 0.238 to 0.354 for dysglycemia). When the clinical data (age >45 years, BMI >28 kg/m(2) and systolic blood pressure >125 mm Hg) were added to the new criteria, the agreement of IFG with IGT and dysglycemia significantly improved (Kappa=0.470 and 0.574, respectively). This also increased the LR(+) to 14.5 and 17.4, respectively, for detecting IGT or dysglycemia.

CONCLUSION

The new IFG definition in combination with common clinical risk factors constitutes a group that most likely predicts IGT or dysglycemia and may be a target for which preventive strategies should be considered.

Diabetes risk score in Oman: a tool to identify prevalent type 2 diabetes among Arabs of the Middle East

We used Oman's 1991 National Diabetes Survey data (n=4881) to develop a simple diabetes risk score for identification of individuals at high risk of having diabetes mellitus. The logistic regression model used included age, waist circumference, body mass index, family history of diabetes and hypertension status at the time of the survey for individuals aged > or =20 years. The validity of the model was assessed in another cohort (2001 Nizwa study n=1432). On applying this model to both cohorts, the area under the receiver-operating characteristic curve was 0.83 (95% confidence interval (CI) 0.82-0.84) for the 1991 cohort and 0.76 (95%CI 0.74-0.79) for the 2001 cohort. The Risk Score of >10 was depicted as the optimal cut-point to predict diabetes diagnosed by serum glucose > or =11.1 mmol/L 2-h post 75 g oral glucose load. This score had a sensitivity of 78.6 and 62.8% and specificity of 73.4 and 78.2% in the two cohorts, respectively. Test of the Thai, Dutch, Finnish and Danish diabetes risk scores showed poor performance of these models among Omani Arabs. In comparison, the self-administered diabetes risk score of Oman could identify most individuals at high risk of having type 2 diabetes in community-based settings in Oman.

Use of survey and clinical data for screening and diagnosis

BACKGROUND

U.S. prevalence of diabetes in 2005 was 20.8 million people (6.2 million undiagnosed) (Diabetes Statistics. 2006). Recognizable preclinical stage is between 7 and 12 years. Efficient screening and early diagnosis can help: 1. avoid or delay development of diabetes. 2. treat early and avoid co-morbidities.

DESIGN

Retrospective cross-sectional study of 153 113 adults ages 24 to 83 from the Behavioural Risk Factor Surveillance Systems (BRFSS)-2003 of whom 4379 had diabetes at their current age or during the previous year and 2190 adults ages 40 to 74 from the National Health and Nutrition Examination Survey III, 211 of whom had glucose tolerance test result > or = 200 mg/dL.

OBJECTIVES

To develop statistical models for screening and diagnosis.

METHODS

Logistic and generalized linear and additive regression models, Akaike information criterion, area under the receiver operating characteristic (ROC) curve, Baye's rule.

RESULTS

Area under the 'productivity' curve using BRFSS data is 0.65 indicating an average yield of 17.3 per cent. Survey data is useful also for diagnosis. Area under the ROC curve (AUC) using only survey data is 0.68. AUC for fasting plasma glucose (FPG) alone is 0.91. Stepwise drop one method of selecting co-variates for diagnosis included pre-test probability from BRFSS. When both FPG and pre-test information are included, AUC increases to 0.93. Reduction in residual deviance and 0.02 increase in AUC are statistically significant (p = 0.0012). Clinical significance of prior odds is shown by increase in accuracy and weighted average of sensitivity and specificity. Empirically estimated regression weights for pre-test and test information vary with age and race and are not equal, as required by Baye's theorem. Overfitting index was less than 1 per cent.

CONCLUSIONS

Cross-section surveys are useful for increasing screening efficiency and diagnostic accuracy.