Reasoning about bladder cancer treatment outcomes using clinical trials within a knowledge-based clinical evidence approach

Abstract

Side effects (SEs) and adverse events (AEs) of bladder cancer (BC) treatment have become more prevalent and may impact the effectiveness of the prescribed therapy. Given, the substantial combination of various treatment types and interventions, it is crucial for the urologist and the team of specialists to discern the systematic and local SEs of these treatments for more awareness and vigilance. This was shown within randomized clinical trials (RCTs) which are complex, and their management needs many efforts. RCTs generate a big amount of knowledge that can serve as evidence for future clinical decision making. Current approaches do not discuss semantic integration of different resources. In this paper we propose a knowledge-based BC treatment effects and complication infrastructure (BCTECI) approach to reason and appraise the effectiveness of BC treatments within their related SEs. This optimized treatment outcomes. Referring to ontology features, a knowledge model with semantic queries and logic rules included evidence concluded from the assessed RCTs. Hence, this supports interoperability between RCTs resources and a common treatment ontology. For this, a comprehensive literature search of relevant RCTs was performed systematically in different electronic medical databases. All pertinent RCTs covering BC treatment cases and reporting prescriptions’ effectiveness were included in BCTECI knowledge model. This study provided the required taxonomy and semanticization and evaluated the effectiveness of treatment outcomes. Furthermore, it extended the clinical evidence-based knowledge for AEs anticipation with a more efficient treatment prescription and showed whether SEs impact the effectiveness of a prescribed treatment until revocation.