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Diabet Med. 2012 Jul;29(7):893-904. doi: 10.1111/j.1464-5491.2012.03609.x.

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

Author information

  • 1MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Addenbrooke's Hospital, Cambridge, UK.

Abstract

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.

© 2012 The Authors. Diabetic Medicine © 2012 Diabetes UK.

PMID:
22340130
[PubMed - indexed for MEDLINE]
PMCID:
PMC3814413
Free PMC Article
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