Estimating the potential population impact of stepwise screening strategies for identifying and treating individuals at high risk of Type 2 diabetes: a modelling study.
Diabetic medicine : a journal of the British Diabetic Association 2012 ; 29: 893-904.
PubMed ID : 22340130
PMCID : 0
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.
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.
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%).
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.