IPOscore  ‒  Predicting the risk of complications of surgical treatment and define prognosis of cancer patients through the integration of clinical and biopathological data

The performance of current risk scoring systems used to predict (post-)operative complications is limited. This weakness reduces confidence in its use to support clinical risk mitigation decisions. In the last years, IPO-Porto has been dedicated to the study of variables associated with the risk of postoperative complications, which resulted in the accumulation of large amounts of data. If used proficiently, these data will allow the extraction of relevant information for the rigorous identification of associated risk factors and the patients most susceptible to postoperative complications. These patients can then be targeted to specific preoperative optimization programs, thus contributing to the reduction of associated morbidity and mortality. However, the use and analysis of such amount of complex data remains a challenge.

This project intends to apply an innovative approach based on data-driven modeling that integrates clinical, biopathological and physiological data of patients with cancer to predict the risk of (post-)operative complications. The expected outcome is the creation of an user-friendly online platform, which includes a database to store/manage the data collected in a structured format, computational approaches and prediction models to calculate a specific risk index score (IPOscore) for the Portuguese population.