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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: [email protected]
https://www.facebook.com/NoelCBarengo/
mailto:[email protected]://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: [email protected]
http://www.facebook.com/NoelCBarengomailto:[email protected]
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