Host Metabolic Status and Biomaterial–Tissue Interactions in NMIBC Surgery

Body composition and metabolic health are increasingly recognised as important determinants of surgical and oncological outcomes. In uro-oncology, conditions such as sarcopenia, myosteatosis, obesity, and malnutrition have been associated with increased perioperative complications, impaired recovery, reduced treatment tolerance, and poorer prognosis. In non-muscle-invasive bladder cancer (NMIBC), however, these host-related factors remain insufficiently integrated into current clinical risk stratification models, which are predominantly focused on tumour characteristics. The review summarises current evidence regarding the role of body composition and metabolic status in NMIBC surgery and perioperative management. Particular emphasis is placed on computed tomography (CT)-based body composition analysis, including skeletal muscle index (SMI) and skeletal muscle density (SMD), together with nutritional and metabolic assessments such as body mass index (BMI), bioimpedance analysis (BIA), Nutritional Risk Screening 2002 (NRS-2002), and serum albumin. Alterations in skeletal muscle and adipose tissue are increasingly linked to systemic inflammation, immune dysregulation, metabolic dysfunction, and impaired tissue recovery. Evidence from surgical oncology, particularly radical cystectomy cohorts, consistently demonstrates associations between sarcopenia, myosteatosis, postoperative morbidity, prolonged hospitalisation, and reduced survival. Emerging studies further suggest that metabolic and nutritional parameters may influence recurrence and progression in NMIBC treated with transurethral resection of bladder tumour (TURBT), although available data remain limited. Overall, body composition represents a clinically relevant but underutilised component of NMIBC management. Integrating CT-derived muscle metrics and nutritional assessment into perioperative evaluation may improve risk stratification, support personalised surgical decision-making, and optimise TURBT and surveillance strategies.