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增强性肾肿块的解剖学特征可预测恶性和高级别病变:使用 RENAL 肾肿瘤评分的术前列线图。

Anatomic features of enhancing renal masses predict malignant and high-grade pathology: a preoperative nomogram using the RENAL Nephrometry score.

机构信息

Division of Urologic Oncology, Department of Surgical Oncology, Fox Chase Cancer Center Philadelphia, PA 19111, USA.

出版信息

Eur Urol. 2011 Aug;60(2):241-8. doi: 10.1016/j.eururo.2011.03.029. Epub 2011 Apr 1.

DOI:10.1016/j.eururo.2011.03.029
PMID:21458155
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3124570/
Abstract

BACKGROUND

Counseling patients with enhancing renal mass currently occurs in the context of significant uncertainty regarding tumor pathology.

OBJECTIVE

We evaluated whether radiographic features of renal masses could predict tumor pathology and developed a comprehensive nomogram to quantitate the likelihood of malignancy and high-grade pathology based on these features.

DESIGN, SETTING, AND PARTICIPANTS: We retrospectively queried Fox Chase Cancer Center's prospectively maintained database for consecutive renal masses where a Nephrometry score was available.

INTERVENTION

All patients in the cohort underwent either partial or radical nephrectomy.

MEASUREMENTS

The individual components of Nephrometry were compared with histology and grade of resected tumors. We used multiple logistic regression to develop nomograms predicting the malignancy of tumors and likelihood of high-grade disease among malignant tumors.

RESULTS AND LIMITATIONS

Nephrometry score was available for 525 of 1750 renal masses. Nephrometry score correlated with both tumor grade (p < 0.0001) and histology (p < 0.0001), such that small endophytic nonhilar tumors were more likely to represent benign pathology. Conversely, large interpolar and hilar tumors more often represented high-grade cancers. The resulting nomogram from these data offers a useful tool for the preoperative prediction of tumor histology (area under the curve [AUC]: 0.76) and grade (AUC: 0.73). The model was subjected to out-of-sample cross-validation; however, lack of external validation is a limitation of the study.

CONCLUSIONS

The current study is the first to objectify the relationship between tumor anatomy and pathology. Using the Nephrometry score, we developed a tool to quantitate the preoperative likelihood of malignant and high-grade pathology of an enhancing renal mass.

摘要

背景

目前,在肿瘤病理存在较大不确定性的情况下,对伴有肾占位的患者进行咨询。

目的

我们评估了肾占位的影像学特征是否可以预测肿瘤病理,并基于这些特征开发了一种全面的列线图来定量评估恶性肿瘤和高级别肿瘤的可能性。

设计、地点和参与者:我们回顾性地查询了 Fox Chase Cancer Center 前瞻性维护的数据库,以获取可获得肾肿瘤 Nephrometry 评分的连续肾占位病例。

干预措施

队列中的所有患者均接受了部分或根治性肾切除术。

测量

将肾肿瘤 Nephrometry 的各个组成部分与肿瘤的组织学和分级进行比较。我们使用多变量逻辑回归来开发预测肿瘤恶性程度和恶性肿瘤高级别疾病可能性的列线图。

结果和局限性

525 个肾占位中有 1750 个有肾肿瘤 Nephrometry 评分。肾肿瘤 Nephrometry 评分与肿瘤分级(p < 0.0001)和组织学(p < 0.0001)相关,即小的内生型非中心性肿瘤更可能代表良性病理。相反,大的极外侧和中央性肿瘤更常代表高级别癌症。这些数据得出的列线图为术前预测肿瘤组织学(曲线下面积[AUC]:0.76)和分级(AUC:0.73)提供了有用的工具。该模型经过了样本外交叉验证;然而,缺乏外部验证是该研究的一个局限性。

结论

本研究首次客观地描述了肿瘤解剖结构与病理之间的关系。使用肾肿瘤 Nephrometry 评分,我们开发了一种工具来定量评估增强型肾占位恶性和高级别肿瘤的术前可能性。

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Kidney tumor location measurement using the C index method.采用 C 指数法测量肾肿瘤位置。
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Can renal mass biopsy assessment of tumor grade be safely substituted for by a predictive model?肾脏肿块活检对肿瘤分级的评估能否安全地被预测模型所替代?
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