50P Predicting onset and continuity of patient-reported symptoms in cancer patients undergoing immune checkpoint inhibitor (ICI) therapies using machine learning

ConclusionML based modeling of ePRO data on ICI treated cancer patients is feasible in predicting onset and continuation of symptoms related to ICI toxicities. The study suggest that ML based approaches could be used in early detection of toxicities. The results should be validated with a dataset collected in a prospective clinical trial.Legal entity responsible for the studyKaiku Health Oy.FundingOulu University and Finnish Cancer Society.DisclosureJ. Ekstr öm: Full / Part-time employment: Kaiku Health Oy. H. Virtanen: Full / Part-time employment: Kaiku Health Oy; Shareholder / Stockholder / Stock options: Kaiku Health Oy. J.P. Koivunen: Advisory / Consultancy: Kaiku Health Oy. All other authors have declared no conflicts of interest.
Source: Annals of Oncology - Category: Cancer & Oncology Source Type: research