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Background
Available models for predicting lymph node invasion (LNI) in prostate cancer (PCa) patients undergoing radical prostatectomy (RP) might not be applicable to men diagnosed via magnetic resonance imaging (MRI)-targeted biopsies.Objective
To assess the accuracy of available tools to predict LNI and to develop a novel model for men diagnosed via MRI-targeted biopsies.Design, setting, and participants
A total of 497 patients diagnosed via MRI-targeted biopsies and treated with RP and extended pelvic lymph node dissection (ePLND) at five institutions were retrospectively identified.Outcome measurements and statistical analyses
Three available models predicting LNI were evaluated using the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analyses. A nomogram predicting LNI was developed and internally validated.Results and limitations
Overall, 62 patients (12.5%) had LNI. The median number of nodes removed was 15. The AUC for the Briganti 2012, Briganti 2017, and MSKCC nomograms was 82%, 82%, and 81%, respectively, and their calibration characteristics were suboptimal. A model including PSA, clinical stage and maximum diameter of the index lesion on multiparametric MRI (mpMRI), grade group on targeted biopsy, and the presence of clinically significant PCa on concomitant systematic biopsy had an AUC of 86% and represented the basis for a coefficient-based nomogram. This tool exhibited a higher AUC and higher net benefit compared to available models developed using standard biopsies. Using a cutoff of 7%, 244 ePLNDs (57%) would be spared and a lower number of LNIs would be missed compared to available nomograms (1.6% vs 4.6% vs 4.5% vs 4.2% for the new nomogram vs Briganti 2012 vs Briganti 2017 vs MSKCC).Conclusions
Available models predicting LNI are characterized by suboptimal accuracy and clinical net benefit for patients diagnosed via MRI-targeted biopsies. A novel nomogram including mpMRI and MRI-targeted biopsy data should be used to identify candidates for ePLND in this setting.Patient summary
We developed the first nomogram to predict lymph node invasion (LNI) in prostate cancer patients diagnosed via magnetic resonance imaging-targeted biopsy undergoing radical prostatectomy. Adoption of this model to identify candidates for extended pelvic lymph node dissection could avoid up to 60% of these procedures at the cost of missing only 1.6% patients with LNI. 相似文献Methods: A cross-sectional prospective cohort study with 7-day follow-up was conducted. Body composition, cardiorespiratory fitness and biomarkers of cardiometabolic health were measured in thirty-three participants with SCI (> 1 year post injury). Physical activity dimensions were objectively assessed over 7-days.
Results: Activity energy expenditure (r =.43), physical activity level (r =.39), and moderate-to-vigorous physical activity (MVPA) (r =.48) were significantly (P < 0.001) associated with absolute (L/min) peak oxygen uptake (?O2 peak). ?O2 peak was significantly higher in persons performing ≥150 MVPA minutes/week compared to <40 minutes/week (P?=?0.003). Individual physical activity dimensions were not significantly associated with biomarkers of cardiometabolic health. However, body composition characteristics (BMI, waist and hip circumference) showed significant (P < 0.04), moderate (r >.30) associations with parameters of metabolic regulation, lipid profiles and inflammatory biomarkers. Relative ?O2 peak (ml/kg/min) was moderately associated with only insulin sensitivity (r?=?0.37, P?=?0.03).
Conclusions: Physical activity dimensions are associated with cardiorespiratory fitness; however, stronger and more consistent associations suggest that poor cardiometabolic health is associated with higher body fat content. Given these findings, the regulation of energy balance should be an important consideration for researchers and clinicians looking to improve cardiometabolic health in persons with SCI. 相似文献