PO57 | A NOVEL RISK ASSESSMENT MODEL FOR CANCER DETECTION WITHIN ONE YEAR AFTER INCIDENT VENOUS THROMBOEMBOLISM

Introduction. The cumulative incidence of cancer within 1-year after incident VTE is high (5-10%) with poor prognosis. Extensive screening strategies (ESS) for cancer in incident unprovoked VTE has shown earlier cancer detection but without a clear benefit on survival. As ESS are resource-demanding and burdensome with putative adverse events for patients and health care systems, targeted screening in high‑risk VTE patients is justified. However, existing risk assessment models (RAMs) (e.g. RIETE) are not recommended in clinical guidelines due to limited discriminative power. Aim. To develop a novel RAM for prediction of cancer diagnosis within 1-year after incident VTE using readily available markers registered at the VTE event. Methods. Leveraging data from a population‑based Norwegian cohort with validated first VTE (n = 1,050), we developed a prediction model from variables routinely captured at VTE diagnosis. The candidate predictor set comprised demographics (age, sex), anthropometrics (BMI), VTE characteristics, and routine laboratory measures, including D-dimer levels. The outcome was incident cancer diagnosed between 1 and 12 months (primary, n=29) and between 1 and 24 months (secondary, n=44) after VTE. Penalized Cox regression (LASSO) was applied for variable selection given the expected low event rate, identifying six candidate predictors, which were reduced to a parsimonious three‑variable model for better clinical translation. Discrimination was assessed using the c‑index with 95% bootstrap confidence intervals. Decision curve analysis (DCA) compared the model against screen‑none and screen‑all strategies. Results. The final model included male sex, surgery