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Published in: Diabetologia 9/2011

01-09-2011 | Letter

Risk scores for predicting type 2 diabetes: using the optimal tool

Authors: M. Alssema, D. Vistisen, M. W. Heymans, G. Nijpels, C. Glümer, P. Z. Zimmet, J. E. Shaw, M. Eliasson, C. D. A. Stehouwer, A. G. Tabák, S. Colagiuri, K. Borch-Johnsen, J. M. Dekker, for the DETECT-2 collaboration

Published in: Diabetologia | Issue 9/2011

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Excerpt

To the Editor: In a recent commentary related to our paper on the performance of a risk score questionnaire for predicting future diabetes [1], Wareham and Griffin make an interesting point about the effect of real life response rates on the true performance of a risk assessment [2]. In our paper we evaluated the performance of the original Finnish diabetes risk questionnaire to predict future screen-detected and clinically diagnosed diabetes. We demonstrated that the performance of the risk score could be improved by adding information on sex, smoking and family history of diabetes [1]. In their commentary, Wareham and Griffin argue that non-response to a questionnaire should be taken into account when evaluating the performance of such a risk questionnaire. They state that when a risk questionnaire is posted out in real life, response rates may be only 50%, and the true sensitivity of the presented score would not be 76% but rather 38%. They go on to suggest that response rates can be improved to nearly 100% by using risk scores that are based on data contained in general practice databases, as has been done in the UK [3, 4], because they do not require collection of new data. They compare this with the 50% response rate for risk score questionnaires reported in the Anglo–Danish–Dutch Study of Intensive Treatment in People with Screen Detected Diabetes in Primary Care (ADDITION)–Denmark Study [5], but do not acknowledge that higher response rates have been achieved—for example 78% in the Hoorn Screening study [6]. …
Literature
1.
go back to reference Alssema M, Vistisen D, Heymans MW et al (2011) The Evaluation of Screening and Early Detection Strategies for Type 2 Diabetes and Impaired Glucose Tolerance (DETECT-2) update of the Finnish diabetes risk score for prediction of incident type 2 diabetes. Diabetologia 54:1004–1012PubMedCrossRef Alssema M, Vistisen D, Heymans MW et al (2011) The Evaluation of Screening and Early Detection Strategies for Type 2 Diabetes and Impaired Glucose Tolerance (DETECT-2) update of the Finnish diabetes risk score for prediction of incident type 2 diabetes. Diabetologia 54:1004–1012PubMedCrossRef
2.
go back to reference Wareham NJ, Griffin S (2011) Risk scores for predicting type 2 diabetes: comparing axes and spades. Diabetologia 54:994–995PubMedCrossRef Wareham NJ, Griffin S (2011) Risk scores for predicting type 2 diabetes: comparing axes and spades. Diabetologia 54:994–995PubMedCrossRef
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go back to reference Rahman M, Simmons RK, Harding AH, Wareham NJ, Griffin SJ (2008) A simple risk score identifies individuals at high risk of developing type 2 diabetes: a prospective cohort study. Fam Pract 25:191–196PubMedCrossRef Rahman M, Simmons RK, Harding AH, Wareham NJ, Griffin SJ (2008) A simple risk score identifies individuals at high risk of developing type 2 diabetes: a prospective cohort study. Fam Pract 25:191–196PubMedCrossRef
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go back to reference Hippisley-Cox J, Coupland C, Robson J, Sheikh A, Brindle P (2009) Predicting risk of type 2 diabetes in England and Wales: prospective derivation and validation of QDScore. BMJ 338:b880PubMedCrossRef Hippisley-Cox J, Coupland C, Robson J, Sheikh A, Brindle P (2009) Predicting risk of type 2 diabetes in England and Wales: prospective derivation and validation of QDScore. BMJ 338:b880PubMedCrossRef
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go back to reference Christensen JO, Sandbaek A, Lauritzen T, Borch-Johnsen K (2004) Population-based stepwise screening for unrecognised type 2 diabetes is ineffective in general practice despite reliable algorithms. Diabetologia 47:1566–1573PubMedCrossRef Christensen JO, Sandbaek A, Lauritzen T, Borch-Johnsen K (2004) Population-based stepwise screening for unrecognised type 2 diabetes is ineffective in general practice despite reliable algorithms. Diabetologia 47:1566–1573PubMedCrossRef
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go back to reference Spijkerman AM, Adriaanse MC, Dekker JM et al (2002) Diabetic patients detected by population-based stepwise screening already have a diabetic cardiovascular risk profile. Diabetes Care 25:1784–1789PubMedCrossRef Spijkerman AM, Adriaanse MC, Dekker JM et al (2002) Diabetic patients detected by population-based stepwise screening already have a diabetic cardiovascular risk profile. Diabetes Care 25:1784–1789PubMedCrossRef
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Metadata
Title
Risk scores for predicting type 2 diabetes: using the optimal tool
Authors
M. Alssema
D. Vistisen
M. W. Heymans
G. Nijpels
C. Glümer
P. Z. Zimmet
J. E. Shaw
M. Eliasson
C. D. A. Stehouwer
A. G. Tabák
S. Colagiuri
K. Borch-Johnsen
J. M. Dekker
for the DETECT-2 collaboration
Publication date
01-09-2011
Publisher
Springer-Verlag
Published in
Diabetologia / Issue 9/2011
Print ISSN: 0012-186X
Electronic ISSN: 1432-0428
DOI
https://doi.org/10.1007/s00125-011-2214-5

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