Arithmetic model can predict kidney damage and effectiveness of therapy
Scientists have developed a mathematical model with which they can predict the degree of kidney damage in a patient, without the need for medical intervention. They can also use the model to predict how effective a set therapy is.
The model consists of a series of mathematical formulas that can be used to determine the extent to which a patient’s kidney is damaged. In these formulas, values must mainly be entered that say something about the extent to which the immune system is activated. These values can be obtained from a urine sample that the patient has to submit. The formulas show the extent to which the kidney has been damaged. Normally, a biopsy is needed to determine the extent of damage; an invasive procedure.
The scientists also state that their model can predict the effectiveness of an established therapy. Kidney problems can be treated with medicines that reduce inflammation, among other things; based on the formulas, it can be determined whether the inflammation actually decreases.
To validate their model, a patient population diagnosed with systemic lupus erythematosus, or lupus for short, was examined. This autoimmune disease is characterized by chronic activation of the immune system, which leads to an increased presence of immune cells that secrete a variety of molecules. These can settle in the ‘filter’ of the kidney, causing damage.
According to the scientists, the model they developed can accurately predict the extent to which patients with SLE suffer from kidney damage. In the long run, they hope to prevent the need for invasive surgery to determine the extent of kidney damage. They also hope that the model can be used for the design of clinical studies. The model could provide cost savings by providing information at an early stage of development about which dose is most effective in patients with SLE. The model can probably also be used for other similar diseases, but this requires more validation. The findings of the research with SLE patients were published in the professional journal PNAS.
Several research groups are working on models that can be used to predict the disease process and the effectiveness of treatment. Biomarkers are used for this; easy to measure values that are used as a predictor. Because techniques for measuring large numbers of genes and proteins have quickly become cheaper, many new biomarkers have been discovered in recent years.