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Purpose: Following a single seizure, or recent epilepsy diagnosis, it is difficult to balance risk of medication side effects with the potential to prevent seizure recurrence. A prediction model was developed and validated enabling risk stratification which in turn informs treatment decisions and individualises counselling., Methods: Data from a randomised controlled trial was used to develop a prediction model for risk of seizure recurrence following a first seizure or diagnosis of epilepsy. Time-to-event data was modelled via Cox's proportional hazards regression. Model validity was assessed via discrimination and calibration using the original dataset and also using three external datasets - National General Practice Survey of Epilepsy (NGPSE), Western Australian first seizure database (WA) and FIRST (Italian dataset of people with first tonic-clonic seizures)., Results: People with neurological deficit, focal seizures, abnormal EEG, not indicated for CT/MRI scan, or not immediately treated have a significantly higher risk of seizure recurrence. Discrimination was fair and consistent across the datasets (c-statistics: 0.555 (NGPSE); 0.558 (WA); 0.597 (FIRST)). Calibration plots showed good agreement between observed and predicted probabilities in NGPSE at one and three years. Plots for WA and FIRST showed poorer agreement with the model underpredicting risk in WA, and over-predicting in FIRST. This was resolved following model recalibration., Conclusion: The model performs well in independent data especially when recalibrated. It should now be used in clinical practice as it can improve the lives of people with single seizures and early epilepsy by enabling targeted treatment choices and more informed patient counselling., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Objective: To externally validate and compare the performance of the European Randomized Study of Screening for Prostate Cancer risk calculator 3/4 (ERSPC-RC3/4), the Prostate Biopsy Collaborative Group risk calculator (PBCG-RC) and the van Leeuwen model to determine which prediction model would perform the best in a contemporary Australian cohort undergoing transperineal (TP) biopsy., Materials and Methods: A retrospective review identified all patients undergoing TP biopsy across two centres. Of the 797 patients identified, 373 had the data required to test all three risk calculators. The probability of high-grade prostate cancer, defined as International Society of Urological Pathology Grade Group >1, was calculated for each patient. For each prediction model discrimination was assessed using area under the receiver-operating characteristic curve (AUC), calibration using numerical and graphical summaries, and net benefit using decision curve analysis., Results: Assessment of model discrimination for detecting high-grade prostate cancer showed AUCs of 0.79 (95% confidence interval [CI] 0.74-0.84) for the ERSPC-RC3/4, 0.81 (95% CI 0.77-0.86) for the van Leeuwen model, and 0.68 (95% CI 0.63-0.74) for the PBCG-RC, compared to 0.58 (95% CI 0.52-0.65) for prostate-specific antigen alone. The ERSPC-RC3/4 was the best calibrated in the moderate-risk range of 10-40%, whilst the van Leeuwen model was the best calibrated in the low-risk range of 0-10%. The van Leeuwen model demonstrated the greatest net benefit from 10% risk onwards, followed closely by the ERSPC-RC3/4 and then the PBCG-RC., Conclusion: The ERPSC-RC3/4 demonstrated good performance and was comparable to the van Leeuwen model with regard to discrimination, calibration and net benefit for an Australian population undergoing TP prostate biopsy. It is one of the most accessible risk calculators with an easy-to-use online platform, therefore, we recommend that Australian urologists use the ERSPC-RC3/4 to predict risk in the clinical setting., (© 2021 The Authors BJU International © 2021 BJU International Published by John Wiley & Sons Ltd.)

Introduction: The majority of pancreatic cancers present locally advanced and carry a high mortality rate. Treatment is challenging, with mixed data suggesting use of chemotherapy alone or in combination with radiotherapy. The use of radiotherapy has previously been limited due to lack of ability to deliver radiation to the tumour mass without causing significant toxicity to surrounding organs. Stereotactic body radiotherapy (SBRT) allows delivery of higher biologically equivalent dose in a shorter treatment duration. We sought to investigate the safety and application of this technique in our centre., Method: We enrolled 27 patients from 2015, identified as locally advanced unresectable with histologically confirmed, non-metastatic, pancreatic adenocarcinoma. All patients had endoscopically inserted fiducial markers and where possible concurrent chemotherapy was administered. Dose schedules ranged from 25 to 42 Gy in 5 or 3 fractions., Results: With an overall median follow up of 9 months (range, 3-32.7), the median survival was 11.6 months. Of those alive at 1 year, the local control rate was 67%. Six patients had Grade 3 toxicity, and other six had Grade 2 toxicity. None had Grade 4 or above toxicity. The most common symptom recorded was fatigue., Conclusion: SBRT for locally advanced pancreatic cancer is technically complex but feasible in a high volume centre. SBRT is unique, allowing safe delivery of high radiation dose resulting in good local control and decreases treatment time making it an attractive option for patients with unresectable pancreatic cancer., (© 2018 The Authors. Journal of Medical Radiation Sciences published by John Wiley & Sons Australia, Ltd on behalf of Australian Society of Medical Imaging and Radiation Therapy and New Zealand Institute of Medical Radiation Technology.)