The dynamics of diabetic foot disease: new study modelling disease progression

New research from Germany studied the progression of diabetic foot disease and the influence of relevant risk factors on disease progression. They found that patients with a first ulcer and patients with reulceration but without any previous amputation had a similar probability of healing without amputation. Patients with PAD had a 10-fold increased risk of major amputation if they had undergone a minor amputation in a previous ulcer episode. Finally, the probability of death increases when the disease progresses, as well as with the development of comorbidities.

The researchers used a Markov chain model. For those who are not familiar with this method, here is a short description: a Markov chain model describes a sequence of possible events between which individuals can transit over time. This has been widely used in, for example, cost-effectiveness analyses. In the world of diabetic foot ulcers, a patient with a current ulcer can heal after one month, or develops an infection, or heals after a minor amputation. The probability of transitioning from a current ulcer state to any other possible state depends on patient characteristics and treatment received. Using a Markov chain model allows researchers to combine available short-term clinical evidence to predict patient outcomes in the long-term.

The current study upped this even further. A Markov chain model was used in this study to quantify, rather than predict, disease progression. The researchers had access to almost complete follow-up of 260 patients over a 17-year long observation period from a well-established German diabetic foot centre of expertise. With all possible transitions already observed, the researchers were able to calculate transition probabilities and mean transition time. This provided them with a unique opportunity to investigate disease progression in people with diabetic foot ulcers. For example, the calculation showed that for those with an ulcer after previous minor amputation, the probability of healing was 0.924 over the follow-up period and the mean healing time was 0.402 years. Another strength of this study was the use of survival analysis to investigate the influence of other comorbidities on the probability of healing and survival. With their model, the researchers were also able to investigate the impact of comorbidities that were not present at baseline but that developed during the observational period.

In this study, some transitions occurred rarely, which limited the reliability of estimates of transition probability and impact of risk factors. Another limitation of this study is the fact that all patients in the underlying cohort had experienced at least one active diabetic foot ulcer episode at study inclusion. Therefore, information on patients with non-ulcerated high risk feet without a previous ulcer episode is not available. A downside of the long follow-up (which is obviously a strong point), is that initial care of the first ulcer episodes took place in the end of the nineties. As major changes to healthcare have since taken place, this might not be reflective of current clinical practice.

To sum up, this article is a good source for clinicians and researchers interested in disease progression of diabetic foot ulcers and risk factors that influence this progression. The methods of developing the model and statistical analysis are thoroughly reported in the article. But don’t be scared by the complexity of the model. Once you have a second read, you will see that the model can be easily decomposed to a table of simple transitions that you observe on a daily basis in your clinic.

This “latest research” article has been written by Qinglu Cheng and Rosana Norman