Abstract:Introduction: Proper planning of laparoscopic radical prostatectomy (RP) in patients with prostate cancer (PCa) is crucial to achieving good oncological results with the possibility of preserving potency and continence. Aim: The aim of this study was to identify the radiological and clinical parameters that can predict the risk of extraprostatic extension (EPE) for a specific site of the prostate. Predictive models and multiparametric magnetic resonance imaging (mpMRI) data from patients qualified for RP were … Show more
“…Twenty-two studies [ 9 , 11 , 12 , 19 – 37 ] head-to-head compared the diagnostic performance of the MRI-inclusive nomogram with that of the traditional clinical nomogram but lacked data to calculate TP, FN, TN and FP; they therefore were included in the qualitative analysis only. The remaining 26 studies (13 for MRI-inclusive nomograms [ 29 , 38 – 49 ], eight for clinical nomograms [ 50 – 57 ] and 5 for both MRI-inclusive nomograms and clinical nomograms [ 58 – 62 ]) were included in the quantitative analysis. Fig.…”
Section: Resultsmentioning
confidence: 99%
“…The forest plots of validation cohorts for MRI-inclusive and clinical nomograms are presented in Supplementary Figures S1 - S4 . In the subgroup analysis, eight external validations of the Partin table [ 50 , 51 , 53 – 55 , 59 , 61 , 62 ] showed a pooled AUC of 0.72(95% CI: 0.68, 0.76), and 5 external validations of the MSKCC nomogram [ 55 , 58 , 60 – 62 ] showed a pooled AUC of 0.79(95% CI: 0.75, 0.82).…”
Purpose
In recent decades, diverse nomograms have been proposed to predict extraprostatic extension (EPE) in prostate cancer (PCa). We aimed to systematically evaluate the accuracy of MRI-inclusive nomograms and traditional clinical nomograms in predicting EPE in PCa. The purpose of this meta-analysis is to provide baseline summative and comparative estimates for future study designs.
Materials and methods
The PubMed, Embase, and Cochrane databases were searched up to May 17, 2023, to identify studies on prediction nomograms for EPE of PCa. The risk of bias in studies was assessed by using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). Summary estimates of sensitivity and specificity were obtained with bivariate random-effects model. Heterogeneity was investigated through meta-regression and subgroup analysis.
Results
Forty-eight studies with a total of 57 contingency tables and 20,395 patients were included. No significant publication bias was observed for either the MRI-inclusive nomograms or clinical nomograms. For MRI-inclusive nomograms predicting EPE, the pooled AUC of validation cohorts was 0.80 (95% CI: 0.76, 0.83). For traditional clinical nomograms predicting EPE, the pooled AUCs of the Partin table and Memorial Sloan Kettering Cancer Center (MSKCC) nomogram were 0.72 (95% CI: 0.68, 0.76) and 0.79 (95% CI: 0.75, 0.82), respectively.
Conclusion
Preoperative risk stratification is essential for PCa patients; both MRI-inclusive nomograms and traditional clinical nomograms had moderate diagnostic performance for predicting EPE in PCa. This study provides baseline comparative values for EPE prediction for future studies which is useful for evaluating preoperative risk stratification in PCa patients.
Critical relevance statement
This meta-analysis firstly evaluated the diagnostic performance of preoperative MRI-inclusive nomograms and clinical nomograms for predicting extraprostatic extension (EPE) in prostate cancer (PCa) (moderate AUCs: 0.72–0.80). We provide baseline estimates for EPE prediction, these findings will be useful in assessing preoperative risk stratification of PCa patients.
Key points
• MRI-inclusive nomograms and traditional clinical nomograms had moderate AUCs (0.72–0.80) for predicting EPE.
• MRI combined clinical nomogram may improve diagnostic accuracy of MRI alone for EPE prediction.
• MSKCC nomogram had a higher specificity than Partin table for predicting EPE.
• This meta-analysis provided baseline and comparative estimates of nomograms for EPE prediction for future studies.
Graphical Abstract
“…Twenty-two studies [ 9 , 11 , 12 , 19 – 37 ] head-to-head compared the diagnostic performance of the MRI-inclusive nomogram with that of the traditional clinical nomogram but lacked data to calculate TP, FN, TN and FP; they therefore were included in the qualitative analysis only. The remaining 26 studies (13 for MRI-inclusive nomograms [ 29 , 38 – 49 ], eight for clinical nomograms [ 50 – 57 ] and 5 for both MRI-inclusive nomograms and clinical nomograms [ 58 – 62 ]) were included in the quantitative analysis. Fig.…”
Section: Resultsmentioning
confidence: 99%
“…The forest plots of validation cohorts for MRI-inclusive and clinical nomograms are presented in Supplementary Figures S1 - S4 . In the subgroup analysis, eight external validations of the Partin table [ 50 , 51 , 53 – 55 , 59 , 61 , 62 ] showed a pooled AUC of 0.72(95% CI: 0.68, 0.76), and 5 external validations of the MSKCC nomogram [ 55 , 58 , 60 – 62 ] showed a pooled AUC of 0.79(95% CI: 0.75, 0.82).…”
Purpose
In recent decades, diverse nomograms have been proposed to predict extraprostatic extension (EPE) in prostate cancer (PCa). We aimed to systematically evaluate the accuracy of MRI-inclusive nomograms and traditional clinical nomograms in predicting EPE in PCa. The purpose of this meta-analysis is to provide baseline summative and comparative estimates for future study designs.
Materials and methods
The PubMed, Embase, and Cochrane databases were searched up to May 17, 2023, to identify studies on prediction nomograms for EPE of PCa. The risk of bias in studies was assessed by using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). Summary estimates of sensitivity and specificity were obtained with bivariate random-effects model. Heterogeneity was investigated through meta-regression and subgroup analysis.
Results
Forty-eight studies with a total of 57 contingency tables and 20,395 patients were included. No significant publication bias was observed for either the MRI-inclusive nomograms or clinical nomograms. For MRI-inclusive nomograms predicting EPE, the pooled AUC of validation cohorts was 0.80 (95% CI: 0.76, 0.83). For traditional clinical nomograms predicting EPE, the pooled AUCs of the Partin table and Memorial Sloan Kettering Cancer Center (MSKCC) nomogram were 0.72 (95% CI: 0.68, 0.76) and 0.79 (95% CI: 0.75, 0.82), respectively.
Conclusion
Preoperative risk stratification is essential for PCa patients; both MRI-inclusive nomograms and traditional clinical nomograms had moderate diagnostic performance for predicting EPE in PCa. This study provides baseline comparative values for EPE prediction for future studies which is useful for evaluating preoperative risk stratification in PCa patients.
Critical relevance statement
This meta-analysis firstly evaluated the diagnostic performance of preoperative MRI-inclusive nomograms and clinical nomograms for predicting extraprostatic extension (EPE) in prostate cancer (PCa) (moderate AUCs: 0.72–0.80). We provide baseline estimates for EPE prediction, these findings will be useful in assessing preoperative risk stratification of PCa patients.
Key points
• MRI-inclusive nomograms and traditional clinical nomograms had moderate AUCs (0.72–0.80) for predicting EPE.
• MRI combined clinical nomogram may improve diagnostic accuracy of MRI alone for EPE prediction.
• MSKCC nomogram had a higher specificity than Partin table for predicting EPE.
• This meta-analysis provided baseline and comparative estimates of nomograms for EPE prediction for future studies.
Graphical Abstract
“…Martini et al had an AUC of 0.82 in the development cohort, but external validation showed a poor fit of the calibration curve with high disagreement between predicted and observed probabilities of EPE in three separate studies[49][50][51]. A poor calibration is problematic for clinical decisionmaking because it makes predictions misleading[52].…”
The aim of this thesis is to assess and improve the outcomes of robot-assisted radical prostatectomy (RARP) for prostate cancer (PCa) patients. The hypotheses and research questions on which the studies in this thesis were based originated from a quality assurance program. This quality assurance program and a general introduction are described in the introduction. Parts one and two describe the use of magnetic resonance imaging (MRI) and prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT), respectively, for preoperative planning of RARP. Part three describes the perioperative phase and part four describes the postoperative phase.
Quality assurance programs (QAP) aim to improve patient outcomes through the continuous and cyclical process of data registration, evaluation, and process adaptation. A group of motivated clinicians identifies in which surgical step or outcome they have unsatisfactory results. After reviewing and discussing their own results and techniques, strategies are devised to overcome these shortcomings. Several studies have described a decrease in positive surgical margins (PSM) and an increase in urinary continence after RARP after implementation of a QAP. This thesis implemented a QAP for the surgical care of prostate cancer patients and evaluated clinical outcomes.
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