Abstract
Nephroblastoma is a complex childhood cancer with a generally favorable prognosis, well-defined incidence, and demographic profile but with significant challenges in terms of recurrence and long-term health outcomes. Although the management of this pathology has evolved, leading to improved survival rates, continued research into the long-term effects of treatment and the genetic factors influencing its development is still required. The survival landscape for Wilms tumor is evolving, with emerging research focusing on therapeutic biomarkers and genetic predispositions that influence treatment efficacy and survival rates. Identifying predictors for treatment response, such as specific genetic markers and histologic features, emerges as a critical area of study that could refine future interventions. The management of Wilms tumor is complex, taking into account the stage of the disease, histological classification, and individual patient factors, including age and the presence of syndromic associations. As treatment paradigms evolve, the integration of precision medicine approaches may enhance the ability of clinicians to personalize treatment to improve long-term survival outcomes for a broader range of patients. Recent advances in technology, including machine-learning approaches, have facilitated the identification of therapeutic biomarkers that correlate with clinical outcomes. This innovative method enhances the ability to integrate clinical and genetic data to predict disease trajectory and therapeutic response.