Carbon footprint and staff demands of surgery and chemoradiation for muscle‐invasive bladder cancer Article Swipe
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· 2025
· Open Access
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· DOI: https://doi.org/10.1111/bju.16876
· OA: W4413957339
Objective To calculate the environmental and labour impact of two complete care pathways for patients with muscle‐invasive bladder cancer (MIBC) with similar oncological outcomes: radical cystectomy (RC) and chemoradiation (CRT), by quantifying the total carbon footprint and staff demands. Patients and Methods The RC was robot‐assisted surgery with pelvic lymph node dissection and ileal conduit. CRT included 20 fractions of 2/2.75 Gy with mitomycin C (Day 1) and capecitabine every radiation day. Waste audits identified medical products ( n = 284), for which a cradle‐to‐gate environmental impact analysis was conducted from treatment selection to first post‐treatment evaluation. Energy use was based on primary data, technical specifications or literature. Patient travel was based on the average distance, assuming petrol‐fuelled cars. Staff demands were assessed by timing clinical staff assignment. The carbon footprint was calculated in CO 2 ‐equivalents using the Ecoinvent Database 3.10. Results The carbon footprint was 208 kg CO 2 ‐equivalents for RC vs 264 kg CO 2 ‐equivalents for CRT. The larger footprint of CRT arose from travel movements and energy use: 5‐ and 1.5‐fold higher than RC, respectively. Main contributors to the total footprint were medical products for RC (49%), and patient travel for CRT (74%). A hotspot analysis identified 10 medical products with the highest impact, which accounted for 60% of the total impact of all medical products. RC averaged 93.5 staff hours per patient vs 29.0 staff hours per patient for CRT. Conclusions This is the first study to analyse the environmental impact of complete care pathways in uro‐oncology. Key strategies to reduce the carbon footprint of MIBC treatment include low‐impact patient travel, reviewing high‐impact surgical products, and using renewable energy by hospitals. Insight into staff demands per treatment assists efficient allocation of scarce personnel.
