Developing a foot ulcer risk model: what is needed to do this in a real-world primary care setting?

Aim To determine how routinely collected data can inform a risk model to predict de novo foot ulcer presentation in the primary care setting. Methods Data were available on 15 727 individuals without foot ulcers and 1125 individuals with new foot ulcers over a 12-year follow-up in UK primary care. We examined known risk factors and added putative risk factors in our logistic model. Results People with foot ulcers were 4.2 years older (95% CI 3.1-5.2) than those without, and had higher HbA(1c) % (mean 7.9 +/- 1.9 vs 7.5 +/- 1.7) / HbA(1c) mmol/mol (63 +/- 21 vs 59 +/- 19) (p<0.0001) concentration [+0.45 (95% CI 0.33-0.56), creatinine level [+6.9 mu mol/L (95% CI 4.1-9.8)] and Townsend score [+0.055 (95% CI 0.033-0.077)]. Absence of monofilament sensation was more common in people with foot ulcers (28% vs 21%; P<0.0001), as was absence of foot pulses (6.4% vs 4.8%; P=0.017). There was no difference between people with or without foot ulcers in smoking status, gender, history of stroke or foot deformity, although foot deformity was extremely rare (0.4% in people with foot ulcers, 0.6% in people without foot ulcers). Combining risk factors in a single logistic regression model gave modest predictive power, with an area under the receiver-operating characteristic curve of 0.65 (95% CI 0.62-0.67). The prevalence of ulceration in the bottom decile of risk was 1.8% and in the top decile it was 13.4% (compared with an overall prevalence of 6.5%); thus, the presence of all six risk factors gave a relative risk of 7.4 for development of a foot ulcer over 12 years. Conclusion We have made some progress towards defining a variable set that can be used to create a foot ulcer prediction model. More accurate determination of foot deformity/pedal circulation in primary care may improve the predictive value of such a future risk model, as will identification of additional risk variables.