194P Modelling strategies to combine multiple serum tumor biomarkers for early prediction of immunotherapy non-response in non-small cell lung cancer

Despite the current success of immune checkpoint inhibitors (ICI), there is an ongoing search for new and better biomarkers to identify which non-small cell lung cancer (NSCLC) patients are likely to respond. While upfront evaluation of biomarkers might provide prognostic information, it does not provide information on the actual tumor response. Serum tumor markers (STM) are known to reflect tumor activity and might therefore be useful in early response prediction. This study aims to compare a wide range of prediction methods applied to multiple sequentially measured serum tumor markers regarding their accuracy in predicting non-response in NSCLC patients receiving ICI therapy.