Doctors have revealed that many women who have used taxane (a type of cell-suppressing drug) to treat breast cancer often suffer from side effects in the nervous system.
“Side effects in the form of nerve damage are very common after taxane breast cancer treatment, and often last for several years. For those affected, it is very stressful and has a significant impact on quality of life. It is a major clinical problem, and has received more attention in recent years, but there is no way to know which individuals are most at risk of side effects,” says Christina Engvall, who recently completed her PhD at Linköping University.
In this regard, researchers at Linköping University in southern Sweden have developed a tool that can predict the level of risk for each individual, which may help doctors adapt treatment to avoid persistent side effects in people most at risk.
Researchers began a close survey of side effects after breast cancer treatment with docetaxel or paclitaxel (the most common taxanes).
337 patients were asked to describe the severity of their nerve damage, or peripheral neuropathy as it is also called.
Women were found to have more common foot cramps, and other side effects included difficulty opening packages, numbness in the feet, and difficulty climbing stairs.
The researchers then sequenced the patients' genomes and built models that linked genetic characteristics to different side effects of taxane treatment, allowing the models to predict the risk of nerve damage.
The research team successfully modeled the risk of persistent numbness and tingling in the feet. The tool was able to separate patients into two clinically relevant groups: one with a high risk of persistent side effects, and the other corresponding to the frequency of peripheral neuropathy in the general population.
“This is the first time that a model has been developed that can predict the risk of nerve damage resulting from taxane treatment,” says Henrik Green, a professor at Linköping University who led the study. “This could be a tool for personalising treatment, and for looking at the risks to each individual patient.”
In the long term, the prediction model could be adopted as a routine procedure in healthcare.
The study was published in the journal npj Precision Oncology.
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