A new machine learning model accurately predicts whether immune checkpoint blockade (ICB), a growing class of immunotherapy drugs, will be effective in patients diagnosed with a wide variety of cancers. The forecasting tool assesses multiple patient-specific biological and clinical factors to predict the degree of response to immune checkpoint inhibitors and survival outcomes. It markedly outperforms individual biomarkers or other combinations of variables developed so far, according to new findings.

Source: Machine learning model uses clinical and genomic data to predict immunotherapy effectiveness