This article examines the critical role of endpoints as a benchmark for data reliability in both real-world clinical practice (RWP) and traditional oncological research. We provide a contemporary classification of oncology-specific endpoints (outcomes), detailing their definitions, key characteristics, and comparative strengths and limitations. A central focus is the methodological adaptation of these endpoints for RWP applications to better capture clinical realities. For practical purposes, the article outlines the types of data (attribute composition) required for a comprehensive assessment of each outcome. The discussion encompasses commonly accepted endpoints in oncological research that involve time-to-event analysis, such as overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS). Additionally, the article thoroughly examines the potential use of complementary and alternative endpoints, including disease-specific survival (DSS), time to treatment failure, time to next treatment, and other relevant outcomes. © (2025), (Autonomous non-profit scientific and medical organization). All rights reserved.