Published 17 March 2009, doi:10.1136/bmj.b880
Cite this as: BMJ 2009;338:b880

Research

Predicting risk of type 2 diabetes in England and Wales: prospective derivation and validation of QDScore

Julia Hippisley-Cox, professor of clinical epidemiology and general practice1, Carol Coupland, senior lecturer in medical statistics1, John Robson, senior lecturer in general practice2, Aziz Sheikh, professor of primary care research and development3, Peter Brindle, research and development strategy lead4

1 Division of Primary Care, Tower Building, University Park, Nottingham NG2 7RD, 2 Centre for Health Sciences, Queen Mary’s School of Medicine and Dentistry, London E1 2AT, 3 Centre for Population Health Sciences: GP Section, University of Edinburgh, Edinburgh EH8 9DX, 4 Avon Primary Care Research Collaborative, Bristol Primary Care Trust, Bristol BS2 8EE

Correspondence to: J Hippisley-Cox Julia.hippisley-cox{at}nottingham.ac.uk

Objective To develop and validate a new diabetes risk algorithm (the QDScore) for estimating 10 year risk of acquiring diagnosed type 2 diabetes over a 10 year time period in an ethnically and socioeconomically diverse population.

Design Prospective open cohort study using routinely collected data from 355 general practices in England and Wales to develop the score and from 176 separate practices to validate the score.

Participants 2 540 753 patients aged 25-79 in the derivation cohort, who contributed 16 436 135 person years of observation and of whom 78 081 had an incident diagnosis of type 2 diabetes; 1 232 832 patients (7 643 037 person years) in the validation cohort, with 37 535 incident cases of type 2 diabetes.

Outcome measures A Cox proportional hazards model was used to estimate effects of risk factors in the derivation cohort and to derive a risk equation in men and women. The predictive variables examined and included in the final model were self assigned ethnicity, age, sex, body mass index, smoking status, family history of diabetes, Townsend deprivation score, treated hypertension, cardiovascular disease, and current use of corticosteroids; the outcome of interest was incident diabetes recorded in general practice records. Measures of calibration and discrimination were calculated in the validation cohort.

Results A fourfold to fivefold variation in risk of type 2 diabetes existed between different ethnic groups. Compared with the white reference group, the adjusted hazard ratio was 4.07 (95% confidence interval 3.24 to 5.11) for Bangladeshi women, 4.53 (3.67 to 5.59) for Bangladeshi men, 2.15 (1.84 to 2.52) for Pakistani women, and 2.54 (2.20 to 2.93) for Pakistani men. Pakistani and Bangladeshi men had significantly higher hazard ratios than Indian men. Black African men and Chinese women had an increased risk compared with the corresponding white reference group. In the validation dataset, the model explained 51.53% (95% confidence interval 50.90 to 52.16) of the variation in women and 48.16% (47.52 to 48.80) of that in men. The risk score showed good discrimination, with a D statistic of 2.11 (95% confidence interval 2.08 to 2.14) in women and 1.97 (1.95 to 2.00) in men. The model was well calibrated.

Conclusions The QDScore is the first risk prediction algorithm to estimate the 10 year risk of diabetes on the basis of a prospective cohort study and including both social deprivation and ethnicity. The algorithm does not need laboratory tests and can be used in clinical settings and also by the public through a simple web calculator (www.qdscore.org).

© Hippisley et al 2009
This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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