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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   
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Metabolomics may reveal novel insights into the etiology of prostate cancer, for which few risk factors are established. We investigated the association between patterns in baseline plasma metabolite profile and subsequent prostate cancer risk, using data from 3,057 matched case–control sets from the European Prospective Investigation into Cancer and Nutrition (EPIC). We measured 119 metabolite concentrations in plasma samples, collected on average 9.4 years before diagnosis, by mass spectrometry (AbsoluteIDQ p180 Kit, Biocrates Life Sciences AG). Metabolite patterns were identified using treelet transform, a statistical method for identification of groups of correlated metabolites. Associations of metabolite patterns with prostate cancer risk (OR1SD) were estimated by conditional logistic regression. Supplementary analyses were conducted for metabolite patterns derived using principal component analysis and for individual metabolites. Men with metabolite profiles characterized by higher concentrations of either phosphatidylcholines or hydroxysphingomyelins (OR1SD = 0.77, 95% confidence interval 0.66–0.89), acylcarnitines C18:1 and C18:2, glutamate, ornithine and taurine (OR1SD = 0.72, 0.57–0.90), or lysophosphatidylcholines (OR1SD = 0.81, 0.69–0.95) had lower risk of advanced stage prostate cancer at diagnosis, with no evidence of heterogeneity by follow-up time. Similar associations were observed for the two former patterns with aggressive disease risk (the more aggressive subset of advanced stage), while the latter pattern was inversely related to risk of prostate cancer death (OR1SD = 0.77, 0.61–0.96). No associations were observed for prostate cancer overall or less aggressive tumor subtypes. In conclusion, metabolite patterns may be related to lower risk of more aggressive prostate tumors and prostate cancer death, and might be relevant to etiology of advanced stage prostate cancer.  相似文献   
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This study was aimed at determining the cause for the high incidence of tuberculosis (TB) reactivation occurring in males with a low body mass index (BMI). Current thinking about pulmonary TB describes infection in the lung apex resulting in cavitation after reactivation. A different hypothesis is put forward for TB infection, suggesting that this occurs in subclinical apical cavities caused by increased pleural stress due to a low BMI body habitus. A finite element analysis (FEA) model of a lung was constructed including indentations for the first rib guided by paramedian sagittal CT reconstructions, and simulations were conducted with varying antero‐posterior (AP) diameters to mimic chests with a different thoracic index (ratio of AP to the transverse chest diameters). A Pubmed search was conducted about gender and thoracic index, and the effects of BMI on TB. FEA modeling revealed a tenfold increase in stress levels at the lung apex in low BMI chests, and a four‐fold increase with a low thoracic index, r2 = 0.9748 P < 0.001. Low thoracic index was related to BMI, P = 0.001. The mean thoracic index was statistically significantly lower in males, P = 0.001, and increased with age in both genders. This article is the first to suggest a possible mechanism linking pulmonary TB reactivation to low BMI due to the flattened thoracic wall shape of young male adults. The low thoracic index in young males may promote TB reactivation due to tissue destruction in the lung apex from high pleural stress levels. Clin. Anat. 28:614–620, 2015. © 2015 Wiley Periodicals, Inc.  相似文献   
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The COVID-19 crisis represents a global health concern, including mental health. Regarding the necessity to assess anxiety related to COVID-19, a scale was developed (Ahorsu et al., 2020). The goal of the present study was to validate the Fear of COVID-19 Scale (FCV-19S) in French (official language in 29 countries), and investigate its relationship with indicators of affective disturbances. The sample comprised 316 participants (271 females) recruited online during the French lockdown. They were from several regions of France. The FCV-19S underwent a forward-backward translation procedure. Its psychometric properties were evaluated with the confirmatory factor analysis (CFA). The French FCV-19S demonstrated a stable unidimensional structure with robust psychometric properties (strong internal consistency, good convergent and divergent validity, and good test-retest validity). With its robust psychometric properties in assessing the unidimensional construct of the fear of COVID-19, this scale will help to provide a better understanding of the relationship between emotions and psychological or psychiatric disorders during the pandemics in French-speaking countries.

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