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. 2019 Mar;37(3):181.e1-181.e6.
doi: 10.1016/j.urolonc.2018.10.026. Epub 2018 Dec 15.

Adding multiparametric MRI to the MSKCC and Partin nomograms for primary prostate cancer: Improving local tumor staging?

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Adding multiparametric MRI to the MSKCC and Partin nomograms for primary prostate cancer: Improving local tumor staging?

Bernard H E Jansen et al. Urol Oncol. 2019 Mar.

Abstract

Introduction and objectives: As a single diagnostic modality, multiparametric MRI (mpMRI) has imperfect accuracy to detect locally advanced prostate cancer (T-stages 3-4). In this study we evaluate if combining mpMRI with preoperative nomograms (Memorial Sloan Kettering Cancer Center [MSKCC] and Partin) improves the prediction of locally advanced tumors.

Materials and methods: Preoperative mpMRI results of 430 robot-assisted radical prostatectomy patients were analyzed. MSKCC and Partin nomogram scores predicting extraprostatic growth were calculated. Logistic regression analysis was performed, combining the nomogram prediction scores with mpMRI results. The diagnostic value of the combined models was evaluated by creating receiver operator characteristics curves and comparing the area under the curve (AUC).

Results: mpMRI was a significant predictor of locally advanced disease in addition to both the MSKCC and Partin nomogram, despite its low sensitivity (45.3%). However, overall predictive accuracy increased by only 1% when mpMRI was added to the MSKCC nomogram (AUC MSKCC 0.73 vs MSKCC + mpMRI 0.74). Predictive accuracy for the Partin Tables increased 4% (AUC Partin 0.62 vs Partin + mpMRI 0.66).

Conclusion: The addition of mpMRI to the preoperative MSKCC and Partin nomograms did not increase diagnostic accuracy for the prediction of locally advanced prostate cancer.

Keywords: Diagnostic accuracy; Locally advanced prostate cancer; Multiparametric MRI; Nomogram; Prostate cancer; Staging.

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