Objective: To determine whether repeated [ F]fluorodeoxyglucose-positron emission tomography/computed tomography (FDG-PET-CT) scans can predict increased cancer-specific survival (CSS) after induction chemotherapy followed by radical cystectomy (RC).

Patients And Methods: Between 2007 and 2018, 86 patients with clinically lymph node (LN)-positive bladder cancer (T1-T4, N1-N3, M0-M1a) were included and underwent a repeated FDG-PET-CT during cisplatin-based induction chemotherapy. The 71 patients that had a response to chemotherapy underwent RC. Response to chemotherapy was evaluated in LNs through repeated FDG-PET-CT and stratified as partial response or complete response using three different methods: maximum standardised uptake value (SUV ), adapted Deauville criteria, and total lesion glycolysis (TLG). Progression-free survival (PFS) and CSS were analysed for all three methods by Cox regression analysis.

Results: After a median follow-up of 40 months, 15 of the 71 patients who underwent RC had died from bladder cancer. Using SUV and the adapted Deauville criteria, multivariable Cox regression analyses adjusting for age, clinical tumour stage and LN stage showed that complete response was associated with increased PFS (hazard ratio [HR] 3.42, 95% confidence interval [CI] 1.20-9.77) and CSS (HR 3.30, 95% CI 1.02-10.65). Using TLG, a complete response was also associated with increased PFS (HR 5.17, 95% CI 1.90-14.04) and CSS (HR 6.32, 95% CI 2.06-19.41).

Conclusions: Complete metabolic response with FDG-PET-CT predicts survival after induction chemotherapy followed by RC in patients with LN-positive bladder cancer and comprises a novel tool in evaluating response to chemotherapy before surgery. This strategy has the potential to tailor treatment in individual patients by identifying significant response to chemotherapy, which motivates the administration of a full course of induction chemotherapy with a higher threshold for suspending treatment due to toxicity and side-effects.

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http://dx.doi.org/10.1111/bju.15374DOI Listing

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