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BACKGROUND: In the treatment of advanced urothelial (aUC) and renal cell carcinoma (aRCC), biomarkers such as PD-1 and PD-L1 are not robust prognostic markers for immunotherapy (IO) response. Previously, a significant association between IO and a change in splenic volume (SV) was described for several tumour entities. To the best of our knowledge, this study presents the first correlation of SV to IO in aUC and aRCC. METHODS: All patients with aUC (05/2017-10/2021) and aRCC (01/2012-05/2022) treated with IO at our academic centre were included. SV was measured at baseline, 3 and 9 months after initiation of IO using an in-house developed convolutional neural network-based spleen segmentation method. Uni- and multivariate Cox regression models for overall survival (OS) and progression-free survival (PFS) were used. RESULTS: In total, 35 patients with aUC and 30 patients with aRCC were included in the analysis. Lower SV at the three-month follow-up was significantly associated with improved OS in the aRCC group. CONCLUSIONS: We describe a new, innovative artificial intelligence-based approach of a radiological surrogate marker for IO response in aUC and aRCC which presents a promising new predictive imaging marker. The data presented implicate improved OS with lower follow-up SV in patients with aRCC.
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BACKGROUND: The European Association of Urology guidelines include the lutetium-177 (177Lu) PSMA-617 prostate-specific membrane antigen (PSMA) ligand as a therapy option for metastatic castration-resistant prostate cancer (mCRPC). A major challenge in clinical practice is to pursue a personalized treatment approach based on robust predictive biomarkers. OBJECTIVE: To assess the performance of 177Lu PSMA in real-world practice and to elaborate clinical biomarkers for evaluating treatment responses. DESIGN, SETTING, AND PARTICIPANTS: We conducted a retrospective observational study including 233 patients with mCRPC treated with 177Lu PSMA in eight high-volume European centers. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Baseline characteristics and clinical parameters during and after 177Lu PSMA treatment were documented. Correlations to treatment response were analyzed using χ2 and log-rank tests, with differences between groups with and without disease progression calculated using a Mann-Whitney U test. Univariate and multivariate-adjusted hazard ratios (HRs) were measured using Cox proportional hazards models. RESULTS AND LIMITATIONS: A prostate-specific antigen (PSA) decrease of ≥30% was observed in 41.7%, 63.5%, and 77.8% of patients after the first, second, and third treatment cycle, respectively. Restaging performed via PSMA positron emission tomography-computed tomography revealed that 33.7% of patients had an imaging-based response, including two patients with a complete response, while 13.4% had stable disease. The median time to progression was 5 mo and the median time until the start of a consecutive antineoplastic therapy was 8.5 mo. Of importance, a PSA decrease ≥30% after the first two cycles of 177Lu PSMA (1 cycle: p = 0.0003; 2 cycles: p = 0.004), absolute PSA after the first three cycles (1 cycle: p = 0.011; 2 cycles: p = 0.0005; 3 cycles: p = 0.002), and a PSA doubling time >6 mo (p = 0.009) were significantly correlated to treatment response. Furthermore, gamma-glutamyl transferase ≤31 U/L at the start of 177Lu PSMA therapy was correlated with 1.5 times higher risk of progression for patients without but not with visceral metastases (p = 0.046). CONCLUSIONS: 177Lu PSMA is an effective treatment option in mCRPC in the real-world setting. A PSA decrease ≥30% after the first two cycles is an early marker of response that can be easily implemented in clinical practice. PATIENT SUMMARY: 177Lu PSMA is a radioactive agent approved for treatment of advanced prostate cancer. We reviewed its use outside of clinical trials for patients treated at eight European centers. We found that 177Lu PSMA is an effective treatment option in real-world practice. A PSA (prostate-specific antigen) decrease of ≥30% after the first two therapy cycles is an early indicator of response to treatment and can be used in personalizing treatments for patients.
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PURPOSE: To investigate the epidemiology and distribution of disease characteristics of urolithiasis by data mining structured radiology reports. METHODS: The content of structured radiology reports of 2028 urolithiasis CTs was extracted from the department's structured reporting (SR) platform. The investigated cohort represented the full spectrum of a tertiary care center, including mostly symptomatic outpatients as well as inpatients. The prevalences of urolithiasis in general and of nephro- and ureterolithasis were calculated. The distributions of age, sex, calculus size, density and location, and the number of ureteral and renal calculi were calculated. For ureterolithiasis, the impact of calculus characteristics on the degree of possible obstructive uropathy was calculated. RESULTS: The prevalence of urolithiasis in the investigated cohort was 72%. Of those patients, 25% had nephrolithiasis, 40% ureterolithiasis, and 35% combined nephro- and ureterolithiasis. The sex distribution was 2.3:1 (M:F). The median patient age was 50 years (IQR 36-62). The median number of calculi per patient was 1. The median size of calculi was 4 mm, and the median density was 734 HU. Of the patients who suffered from ureterolithiasis, 81% showed obstructive uropathy, with 2nd-degree uropathy being the most common. Calculus characteristics showed no impact on the degree of obstructive uropathy. CONCLUSION: SR-based data mining is a simple method by which to obtain epidemiologic data and distributions of disease characteristics, for the investigated cohort of urolithiasis patients. The added information can be useful for multiple purposes, such as clinical quality assurance, radiation protection, and scientific or economic investigations. To benefit from these, the consistent use of SR is mandatory. However, in clinical routine SR usage can be elaborate and requires radiologists to adapt.
