With help from a dozen clinical variables, researchers have been able to identify, using machine learning techniques, which of their patients with severe asthma are likely to benefit from treatment with systemic corticosteroids — and which might only suffer their side effects.
The newly identified set of variables, when processed by computer software, will yield more precise predictions of a patient’s response, said lead study authors Wei Wyu.
The study, led by Wu and Dr. Sally E. Wenzel, was recently published online by the American Journal of Respiratory and Critical Care Medicine.
Asthma causes wheezing, breathlessness, chest tightness and coughing. Predicting how people will respond to corticosteroid therapy could significantly reduce the suffering of many patients, Wenzel said.
Wenzel emphasised that the study addresses corticosteroid pills and injections, not the widely used corticosteroid inhalers, although there is likely to be some overlap in patient response to the medications in either form.
The researchers used a machine learning algorithm, developed by Wu and Seojin Bang, to sift through 100 variables for each of 346 adult patients in the federally funded Severe Asthma Research Program (SARP).
Of the original 100 variables, they identified 12 — including age of onset, weight, race and scores on a quality-of-life questionnaire — that could correctly categorise patients with high confidence if processed by a computer app.
The benefits of systemic corticosteroids can be substantial, so physicians likely will continue to try them initially in the treatment of severe asthma, Wenzel said.
But once software becomes available for practitioners to predict patient response, she said they will likely switch to alternative therapies, rather than increase corticosteroid dosages, if patients haven’t responded and fall into the subgroup of patients that don’t usually benefit from the drugs. (ANI)
