Title: | Added Value of Multiparametric Magnetic Resonance Imaging in Men Undergoing Radical Prostatectomy |
Author: | Pohjonen, Joona |
Other contributor: |
Helsingin yliopisto, Matemaattis-luonnontieteellinen tiedekunta
University of Helsinki, Faculty of Science Helsingfors universitet, Matematisk-naturvetenskapliga fakulteten |
Publisher: | Helsingin yliopisto |
Date: | 2020 |
Language: | eng |
URI: |
http://urn.fi/URN:NBN:fi:hulib-202006012540
http://hdl.handle.net/10138/315762 |
Thesis level: | master's thesis |
Degree program: |
Life Science Informatics -maisteriohjelma
Master's Programme in Life Science Informatics Magisterprogrammet i Life Science Informatics |
Specialisation: |
Systems Biology and Medicine
Systems Biology and Medicine Systems Biology and Medicine |
Discipline: | none |
Abstract: | Prediction of the pathological T-stage (pT) in men undergoing radical prostatectomy (RP) is crucial for disease management as curative treatment is most likely when prostate cancer (PCa) is organ-confined (OC). Although multiparametric magnetic resonance imaging (MRI) has been shown to predict pT findings and the risk of biochemical recurrence (BCR), none of the currently used nomograms allow the inclusion of MRI variables. This study aims to assess the possible added benefit of MRI when compared to the Memorial Sloan Kettering, Partin table and CAPRA nomograms and a model built from available preoperative clinical variables. Logistic regression is used to assess the added benefit of MRI in the prediction of non-OC disease and Kaplan-Meier survival curves and Cox proportional hazards in the prediction of BCR. For the prediction of non-OC disease, all models with the MRI variables had significantly higher discrimination and net benefit than the models without the MRI variables. For the prediction of BCR, MRI prediction of non-OC disease separated the high-risk group of all nomograms into two groups with significantly different survival curves but in the Cox proportional hazards models the variable was not significantly associated with BCR. Based on the results, it can be concluded that MRI does offer added value to predicting non-OC disease and BCR, although the results for BCR are not as clear as for non-OC disease. |
Subject: |
Prostate cancer
magnetic resonance imaging logistic regression survival analysis imputation |
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