Predicting risk for pathological stage and prognostic grade in patients undergoing robotic prostatectomy: a contemporary UK based calculator
BAUS ePoster online library. Chahal R.
Jun 26, 2018; 211342
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Mr. Rohit Chahal
Mr. Rohit Chahal
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Abstract
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Introduction: Accurate risk prediction is a prerequisite for informed decision making. Current predictive models are based on American and European data.

Materials and Methods: Prospectively data from 1499 consecutive patients from the NERUS (North of England Robotic Urological Surgeons) database were used to develop a predictive calculator.

Results: The mean PSA was 8.9. 49.8% were D'Amico intermediate and 26.6% high risk. pT3a and T3b disease was noted 35.4% and 5.3% and the specimen prognostic grades ≥ 3 in 25.9%. The data was divided into training (70%) and testing (30%) to assess the performance of each model using area under the receiver operating curve (c-statistic). Age, PSA, DRE stage, biopsy prognostic grade, D'Amico risk category were co-variates assessed. Risk equations for pathological stage T2, T3a and T3b and pathological prognostic grade were developed. Discrimination (c-statistic) of 0.74 and 0.71 was noted overall for the training and testing for pathological stage and 0.73 and 0.74 for prognostic grade. The similar values in testing and training sets indicate good internal validity. Discrimination for pT3b was 0.84 and grade 5 was 0.82. A calculator was developed with 5 input data points (above) to predict pathological stage pT2, pT3a and pT3b and prognostic grades 1-5

Conclusions: We have developed a simple excel based calculator based on a large, multi-institutional cohort of contemporary patients to predict pathological stage pT2, pT3a and pT3b and prognostic grades 1-5 in patients undergoing robotic prostatectomy. There is good discrimination and internal validation making them applicable in regular clinical practice.
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