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Purpose Magnetic resonance imaging (MRI)/ultrasound-fusion prostate biopsy (FB) comprises multiple steps each of which can cause alterations in targeted biopsy (TB) accuracy leading to false-negative results. The aim was to assess the inter-operator variability of software-based fusion TB by targeting the same MRI-lesions by different urologists. Methods In this prospective study, 142 patients eligible for analysis underwent software-based FB. TB of all lesions (n = 172) were carried out by two different urologists per patient (n = 31 urologists). We analyzed the number of mismatches [overall prostate cancer (PCa), clinically significant PCa (csPCa) and non-significant PCa (nsPCa)] between both performed TB per patient. In addition we evaluated factors contributing to inter-operator variability by uni- and multivariable analyses. Results In 11.6% of all MRI-lesions (10.6% of all patients) there was a mismatch between TB1 and TB2 in terms of overall prostate cancer (PCa detection. Regarding csPCa, patient-based mismatch occurred in 14.8% (n = 21). Overall PCa and csPCa detection rate of TB1 and TB2 did not differ significantly on a per-patient and per-lesion level. Analyses revealed a smaller lesion size as predictive for mismatches (OR 9.19, 95% CI 2.02–41.83, p Conclusion Reproducibility and precision of targeting particularly small lesions is still limited although using software-based FB. Further improvements in image-fusion, segmentation, needle-guidance, and automatization are necessary.

Purpose To validate a German translation of the convalescence and recovery evaluation (CARE) as an electronic patient-reported outcome measure (ePROM) and use it to assess recovery after major urological surgery. Methods The CARE questionnaire was provided to patients scheduled for major urological surgery preoperatively, at discharge and 6 weeks postoperatively, using an ePROM system. Cronbach’s alpha, inter-scale correlations and confirmatory factor analysis (CFA) were used to validate the translation. Mixed linear regression models were used to identify factors influencing CARE results, and a multivariable logistic regression analysis was done to determine the predictive value of CARE results on quality of life (QoL). Results A total of 283 patients undergoing prostatectomy (n = 146, 51%), partial/radical nephrectomy (n = 70, 25%) or cystectomy (n = 67, 24%) responded to the survey. Internal consistency was high (α = 0.649–0.920) and the CFA showed a factor loading > 0.5 in 17/27 items. Significant main effects were found for the time of survey and type of surgery, while a time by type interaction was only found for the gastrointestinal subscale ($$\chi_{(4)}^{2}$$ χ ( 4 ) 2 = 30.37, p 0.0001) and the total CARE score (TCS) ($$\chi_{(4)}^{2}$$ χ ( 4 ) 2 = 13.47, p = 0.009) for cystectomy patients, meaning a greater score decrease at discharge and lower level of recovery at follow-up. Complications demonstrated a significant negative effect on the TCS ($$\chi_{(2)}^{2}$$ χ ( 2 ) 2 = 8.61, p = 0.014). A high TCS at discharge was an independent predictor of a high QLQ-C30 QoL score at follow-up (OR = 5.26, 95%-CI 1.42–19.37, p = 0.013). Conclusion This German translation of the CARE can serve as a valid ePROM to measure recovery and predict QoL after major urological surgery.