Screening for people at risk of type 2 diabetes: Current situation and

future challenges

Noël C. Barengo, MD, PhD, MPHHerbert Wertheim College of MedicineFlorida International UniversityE-mail: nbarengo@fiu.edu

https://www.facebook.com/NoelCBarengo/

mailto:nbarengo@fiu.eduhttps://www.facebook.com/NoelCBarengo/

Content

I. IntroductionII. Why to screen for people at a high risk for T2D?III. How to screen for people with type 2 diabetes?IV. Unsolved questions and challengesV. Conclusions and recommendations

I. Introduction

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IGT

IFG

Type 2 diabetes

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Modifiable type 2 diabetes risk factors• Obesity / weight gain• Central obesity• Physical inactivity• Sitting time • Smoking• Gestational Diabetes• Pre-eclamsia• Very low birth weight• Fatty liver• Depression• Anti-psychotic drugs• Poor sleep• Hypertension• Statins

• Dietary Factors (risk increase or decrease)– Carbohydrate quality– Fat quality– Glycemic index– Whole grain / cereal fibers– Low-fat dairy products– Alcohol– Coffee– Fast food intake– Sweet beverages – Magnesium

II. Why screen for people at a high risk for T2D?

Lindström et al. Lancet 2006.

Diabetes Prevention Study

Diabetes Prevention Program

W Knowler, et al. N Engl J Med 2002; 346: 393-403.

Summary of intervention trials in people with prediabetes

CDC Diabetes Prevention Recognition Program

• 1557 CDC-recognized programs across 50 states/territories.• >10,300 coaches (lay people; health professionals) trained.• Serving 156,935 eligible participants.• 65 commercial health plans providing some coverage for 3M in 11 states

Diabetes Prevention in the

RealWorld

Dunkley et al. Diabetes Care 2014

III. How to screen for people with type 2 diabetes?

Identify and treat those beyond a threshold for risk

factor

Shift the whole population distribution of risk factor lower

High riskapproach

Population approach

Risk factor distribution Risk factor distribution

Disease prevention approaches

High risk strategy

• Identification of people at high risk of type 2 diabetes (screening)

• Intervention targeting people at high risk of type 2 diabetes

Measurement of blood glucose

– OGTT– Fasting glucose– HbA1C– Capillary glucose

IDENTIFY PEOPLE AT HIGH-RISK OF DT2 LATE

Questionnaires (risk scales) of lifestyle and risk factors for diabetes

IDENTIFY PEOPLE AT HIGH-RISK OF DT2 EARLY

Strategies for detecting DT2 and hyperglycemia

Objectives of screening

• What is the probability that people with apositive test have diabetes?

• Is the test is a good predictor for futurediabetes?

• Can the test identify people at low risk?

Screening vs diagnosis

A screening test is not diagnostic

Screening tests are cheaper than diagnostic tests

A positive screening test needs confirmation through adiagnostic test

The concept is developing a screening tool that ...

... is simple, economical and reliable to identify people at high risk fortype 2 diabetes.

... can be applied easily in the general population.

... does not require blood extractions or other measures that requirespecial equipment or trained personnel.

The objective of FINDRISC

FINnish DiabetesRIsk SCore

Score range 0-26 p

Lindström & TuomilehtoDiabetes Care 2003; 26: 725-731

• No laboratory tests• No specially trained

personnel needed• No special equipments• Inexpensive, easy, fast• Accurate

00.10.20.30.40.50.60.70.80.9

1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

False positive rate

Tru

e p

osit

ive r

ate

Cut off point: >10

Sensitivity = 0.73

Specificity = 0.83

Positive predictive value= 0.16

Negative predictive value= 0.99

AUC = 0.85

The ROC curve of the FINDRISC

Chart1

0.0004695938

0.0004695938

0.0009391876

0.0035219535

0.0049307349

0.0119746419

0.019018549

0.0394458793

0.066212726

0.1070673867

0.1699929561

0.2291617751

0.305001174

0.3921108241

0.4550363935

0.5393284809

0.6550833529

0.7602723644

0.843860061

0.936135243

1

False positive rate

True positive rate

0.0157894737

0.0421052632

0.0631578947

0.0947368421

0.1210526316

0.2

0.2578947368

0.3842105263

0.4684210526

0.6157894737

0.7263157895

0.7684210526

0.8473684211

0.8947368421

0.9105263158

0.9368421053

0.9631578947

0.9789473684

0.9842105263

1

1

Riskipiste_ROC_2

_PROB__POS__NEG__FALPOS__FALNEG__1MSPEC__SENSIT_SCORE GE

0.76009251883425721870.00046959380.015789473720

0.68710742438425721820.00046959380.042105263219

0.603501110812425541780.00093918760.063157894718

0.513376447184244151720.00352195350.094736842117

0.4223734873234238211670.00493073490.121052631616

0.3363520113384208511520.01197464190.215

0.2599651511494178811410.0190185490.257894736814

0.19580763577340911681170.03944587930.384210526313

0.14439430388939772821010.0662127260.468421052612

0.10472266811173803456730.10706738670.615789473711

0.0749952551383535724520.16999295610.726315789510

0.05320500581463283976440.22916177510.76842105269

0.03748942416129601299290.3050011740.84736842118

0.026286995117025891670200.39211082410.89473684217

0.018368146417323211938170.45503639350.91052631586

0.012803450717819622297120.53932848090.93684210535

0.00890929881831469279070.65508335290.96315789474CUTPOINT >=10

0.00619211871861021323840.76027236440.97894736843SENSITIVITY=0.73

0.0043000355187665359430.8438600610.98421052632SPECIFICITY=0.83

0.0029843671190272398700.93613524311POSITIVE PREDICTIVE VALUE=0.16

0.0020704125190042590110NEGATIVE PREDICTIVE VALUE=0.99

_PROB__POS__NEG__FALPOS__FALNEG__1MSPEC__SENSIT_SCORE GE

0.5580549331145112670.00044316420.014705882420

0.4604643058245094660.00088632840.029411764719

0.3658135964645058620.00177265680.088235294118

0.280503706711449815570.00332373140.161764705917

0.208546374515448825530.00553955240.220588235316

0.151169824621446251470.01130068690.308823529415

0.107436212525442390430.01994238870.367647058814

0.0752334001304344169380.03744737430.441176470613

0.0521193897404193320280.07090627080.588235294112

0.0358315604424018495260.10968313760.617647058811

0.0245022633473745768210.17017504990.691176470610

0.01669306815433921121140.24839352980.79411764719

0.0113438239593081143290.31730556170.86764705888

0.0076953143602634187980.41635275870.88235294127

0.0052140846642301221240.49013959670.94117647066

0.0035300413642019249440.55262574780.94117647065

0.0023886037651616289730.64192333260.95588235294

0.0016156512661139337420.74761799250.97058823533

0.001092552266739377420.83625083090.97058823532

0.000738691666439407420.90272545980.97058823531

0.000499383668045130110

OGTT-DM vs. RISK SCORE 1987

_PROB__POS__NEG__FALPOS__FALNEG__1MSPEC__SENSIT_

0.5959539472123233630.00128976780.015625

0.5008970016523233590.00128976780.078125

0.4057751704623215580.00214961310.09375

0.317235622812231214520.00601891660.1875

0.240205814230422500.00945829750.21875

0.177030359421227353430.02278589850.328125

0.127678285226224680380.03439380910.40625

0.09057032312165161330.06921754080.484375

0.0634626635372074252270.10834049870.578125

0.0440751086441921405200.17411865860.6875

0.0304179952481718608160.26139294930.75

0.020900152531516810110.34823731730.828125

0.0143164841571320100670.43250214960.890625

0.0097859811601094123240.52966466040.9375

0.006679456761924140230.60275150470.953125

0.004554551463770155610.66895958730.984375

0.003103520664456187000.8039552881CUTPOINT >=11

0.002113790864143218300.93852106621SENSITIVITY=0.69

0.00143923566402326011SPECIFICITY=0.83

POSITIVE PREDICTIVE VALUE=0.10

NEGATIVE PREDICTIVE VALUE=0.99

IGT (IN OGTT -87) VS. RISK SCORE (DIABETICS NOT INCLUCED)

_PROB__POS__NEG__FALPOS__FALNEG__1MSPEC__SENSIT_SCORE GE

0.52854022432204812750.00048804290.007220216620

0.44197802054204812730.00048804290.014440433218

0.39966770577204272700.00341630060.025270758117

0.3588033979112038112660.00536847240.039711191316

0.3198909094192015342580.01659346020.068592057815

0.2833337246261995542510.02635431920.093862815914

0.24942215524719351142300.0556368960.169675090313

0.21833286866518621872120.09126403120.234657039712

0.1901370629717413081800.15031722790.350180505411

0.16481474312915704791480.2337725720.465703971110

0.142272385815113906591260.32162030260.54512635389

0.12236151981841227822930.40117130310.66425992788

0.104896380520210191030750.50268423620.72924187737

0.08966940962238701179540.57540263540.80505415166

0.07646399572357281321420.6447047340.84837545135

0.06506431722534321617240.78916544660.91335740074

0.0552624701269135191480.9341142020.97111913363CUTPOINT >=8

0.0468632418277020490112SENSITIVITY=0.66

SPECIFICITY=0.40

DM-CASES %

Risk scoreY-87 follow-upY-92 follow-up

0-60.80.3

7-104.21.4

11-1416.35.4

15-1735.634.9

18-207530

GLUCOSE TOLERANCE ACCORDING TO RISK SCORE(OGTT 1987)

Risk scoreDMIGTNORMAL

0-60.46.892.8

7-101.912.585.7

11-146.120.873.1

15-1723.823.852.4

18-2054.636.49.1

Riskipiste_ROC_2

PISTEET

DM %

Diabetestapausten määrä (%) riskipisteiden mukaan

PISTELUOKAT

DM %

Diabetestapausten määrä (%) riskipisteluokittain

PISTEET

DM %

Diabetestapausten määrä (%) riskipisteiden mukaan

Y-87 follow-up

Y-92 follow-up

Risk score

%

&A

Page &P

False positive rate

True positive rate

ROC-curve, Finrisk87- Prospective data

False positive rate

True positive rate

ROC-curve, Finrisk92- Prospective data

False positive rate

True positive rate

ROC-curve, OGTT-DM vs. Risk score

False positive rate

True positive rate

ROC-curve, IGT vs. Risk score

DM

IGT

NORMAL

RISK SCORE

%

Gray L.J, Khunti K, Taub NA, Hiles S, Davies MJ (2009)Oral presentation 20th World Diabetes Congress, Montreal, October 2009

1. Edad Puntaje

Menos de 45 años 0

45 a 54 años 1

55 a 64 años 2

Más de 64 años 3

4. Perímetro abdominal**Ver instrucciones de medición en cara 2

Puntaje

Hombres Mujeres

Menos de 94 cm. Menos de 90 cm. 0

94 cm. o más 90 cm. o más 2

3. Toma medicamentos para el tratamiento de la hipertensión arterial Puntaje

No 0

Si 2

2. Tiene antecedente de padres o hermanos con diagnóstico de diabetes mellitus Puntaje

No 0

Si 2

Puntos por edad

Puntos por diabetes en familiar de primer grado

Puntos por medicamentos para hipertensión arterial

Puntos por perímetro abdominal

PUNTAJE TOTAL

Sume los puntos de cada pregunta. Si el puntaje total es mayor o igual a 4, indique unaprueba de tolerancia a la glucosa dado que, la persona tiene 5 veces más posibilidades detener diabetes mellitus en comparación con aquellos sujetos con menos de 4 puntos.

ROC for original FINDRISCArea under the curve: 0.71; 95% CI 0.68-0.74

ROC for SADRISCArea under the curve: 0.76; 95% CI 0.73-0.79

Receiver operating characteristics (ROC) curves for the prevalence of abnormal glucose tolerance for the SADRISC (Saudi Arabian Diabetes Risk Score) and the original

FINDRISC.

Barengo et al. Unpublished data. 2019

Are there differences in risk factors for type 2 diabetes among different

populations?

NO!But the relative contribution (weight) may

vary between populations.

FINDRISC distributed(n=14 193)

FINDRISC ≥ 13 (n=4915)

No OGTT (n=2611) OGTT (n=2304)

Normoglycemic59% (n=1347)

IFG 11% (n=263)

IGT 9% (n=204)

IFG and IGT combined

8% (n=184)

Screen detected T2D 13% (n=306)

FINDRISC < 13 (n=9278)

Barengo et al Diabetes Metab Res Rev. 2013

IV. Unsolved questions and challenges

Which diagnostic test to use?

Which invasive diagnostic test to use after screening (fasting glucose, HbA1C, 2-hour glucose, 1-hour glucose, capillary glucose)?

Optimal time interval

What is the optimal time interval between screening activities?

Changing lifestyleAre people diagnosed as being at a high risk of T2D more likely to change their lifestyle than people who are unaware of their risk or whether a negative test may have an adverse shift in health behaviors?

Long term benefits

Information on long-term benefits of T2D screening programs?

Impact

Short or long-term impact of T2D screening programs?

Attendance

Attendance for diagnostic tests after positive screening test?

FINDRISC distributed(n=14 193)

FINDRISC ≥ 13 (n=4915)

No OGTT (n=2611) OGTT (n=2304)

Normoglycemic59% (n=1347)

IFG 11% (n=263)

IGT 9% (n=204)

IFG and IGT combined

8% (n=184)

Screen detected T2D 13% (n=306)

FINDRISC < 13 (n=9278)

Barengo et al Diabetes Metab Res Rev. 2013

V. Conclusions and recomendations

Conclusions (II)• Validated screening tests exist• Screening tests have been successfully implemented in

various countries and institutions• Main challenges include among others monitoring

attendance , short- and long term benefits, implementation of guidelines and time interval of screening tests.

Knowledge integration process

Thank you

http://www.facebook.com/NoelCBarengoE-mail: nbarengo@fiu.edu

http://www.facebook.com/NoelCBarengomailto:nbarengo@fiu.edu

Screening for people at risk of type 2 diabetes: Current situation and future challengesContentIntroductionSlide Number 4Slide Number 5Modifiable type 2 diabetes risk factorsII. Why screen for people at a high risk for T2D?Slide Number 8Diabetes Prevention ProgramSlide Number 10CDC Diabetes Prevention Recognition ProgramDiabetes Prevention in the Real�WorldIII. How to screen for people with type 2 diabetes?Slide Number 14High risk strategySlide Number 16Objectives of screeningScreening vs diagnosisSlide Number 19Slide Number 20Slide Number 21Slide Number 22Slide Number 23Slide Number 24Are there differences in risk factors for type 2 diabetes among different populations?Slide Number 26IV. Unsolved questions and challengesWhich diagnostic test to use?Optimal time intervalChanging lifestyleLong term benefitsImpactAttendanceSlide Number 34V. Conclusions and recomendationsConclusions (II)Knowledge integration processThank you