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

Research output: Contribution to journalArticleAcademicpeer-review

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.

Original languageEnglish
JournalUrologic Oncology
Volume37
Issue number3
DOIs
Publication statusPublished - Mar 2019

Cite this

@article{6629c5605df442a196f9a3b1db2e7dbe,
title = "Adding multiparametric MRI to the MSKCC and Partin nomograms for primary prostate cancer: Improving local tumor staging?",
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.",
author = "Jansen, {Bernard H E} and Nieuwenhuijzen, {Jakko A} and Oprea-Lager, {Daniela E} and Yska, {Marit J} and Lont, {Anne P} and {van Moorselaar}, {Reindert J A} and Vis, {Andr{\'e} N}",
note = "Copyright {\circledC} 2018. Published by Elsevier Inc.",
year = "2019",
month = "3",
doi = "10.1016/j.urolonc.2018.10.026",
language = "English",
volume = "37",
journal = "Urologic Oncology",
issn = "1078-1439",
publisher = "Elsevier Inc.",
number = "3",

}

TY - JOUR

T1 - Adding multiparametric MRI to the MSKCC and Partin nomograms for primary prostate cancer

T2 - Improving local tumor staging?

AU - Jansen, Bernard H E

AU - Nieuwenhuijzen, Jakko A

AU - Oprea-Lager, Daniela E

AU - Yska, Marit J

AU - Lont, Anne P

AU - van Moorselaar, Reindert J A

AU - Vis, André N

N1 - Copyright © 2018. Published by Elsevier Inc.

PY - 2019/3

Y1 - 2019/3

N2 - 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.

AB - 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.

U2 - 10.1016/j.urolonc.2018.10.026

DO - 10.1016/j.urolonc.2018.10.026

M3 - Article

VL - 37

JO - Urologic Oncology

JF - Urologic Oncology

SN - 1078-1439

IS - 3

ER -