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评价解剖学和形态学列线图在小肾肿瘤患者队列中预测恶性和高级别疾病的价值。

Evaluation of anatomic and morphologic nomogram to predict malignant and high-grade disease in a cohort of patients with small renal masses.

机构信息

Department of Urology, University of Texas Southwestern Medical Center, Dallas, TX.

Department of Urology, University of Texas Southwestern Medical Center, Dallas, TX.

出版信息

Urol Oncol. 2014 Jan;32(1):37.e17-23. doi: 10.1016/j.urolonc.2013.03.003. Epub 2013 Apr 28.

Abstract

OBJECTIVE

To evaluate a nomogram using the RENAL Nephrometry Score (RENAL-NS) that was developed to characterize masses as benign vs. malignant and high vs. low grade in our patients with small renal masses treated with partial nephrectomy (PN). The nomogram was previously developed and validated in patients with widely variable tumor sizes.

MATERIALS AND METHODS

Retrospective review of PN performed between 1/2003 and 7/2011. Imaging was reviewed by a urologic surgeon for RENAL-NS. Final pathology was used to classify tumors as benign or malignant and low (I/II) or high (III/IV) Fuhrman grade. Patient age, gender, and RENAL score were entered into the nomogram described by Kutikov et al. to determine probabilities of cancer and high-grade disease. Area under the curve was determined to assess agreement between observed and expected outcomes for prediction of benign vs. malignant disease and for prediction of high- vs. low-grade or benign disease.

RESULTS

A total of 250 patients with 252 masses underwent PN during the study period; 179/250 (71.6%) had preoperative imaging available. RENAL-NS was assigned to 181 masses. Twenty-two percent of tumors were benign. Eighteen percent of tumors were high grade. Area under the curve was 0.648 for predicting benign vs. malignant disease and 0.955 for predicting low-grade or benign vs. high-grade disease.

CONCLUSIONS

The RENAL-NS score nomogram by Kutikov does not discriminate well between benign and malignant disease for small renal masses. The nomogram may potentially be useful in identifying high-grade tumors. Further validation is required where the nomogram probability and final pathologic specimen are available.

摘要

目的

评估 RENAL 评分系统(RENAL-NS)建立的列线图,该列线图用于对接受部分肾切除术(PN)治疗的小肾癌患者的肿瘤进行良性与恶性以及低级别与高级别区分。该列线图之前是在肿瘤大小差异较大的患者中开发和验证的。

材料与方法

回顾性分析 2003 年 1 月至 2011 年 7 月期间接受 PN 的患者。由泌尿外科医师对 RENAL-NS 进行影像学评估。最终病理学用于将肿瘤分类为良性或恶性以及低(I/II)或高级(III/IV)Fuhrman 分级。将患者年龄、性别和 RENAL 评分输入 Kutikov 等人描述的列线图,以确定癌症和高级别疾病的概率。曲线下面积用于评估良性与恶性疾病预测、高级别与低级别或良性疾病预测的观察结果与预期结果之间的一致性。

结果

研究期间共有 250 例患者接受了 252 个肿瘤的 PN;其中 179/250(71.6%)术前有影像学资料。181 个肿瘤被分配了 RENAL-NS。22%的肿瘤为良性,18%的肿瘤为高级别。预测良性与恶性疾病的曲线下面积为 0.648,预测低级别或良性与高级别疾病的曲线下面积为 0.955。

结论

Kutikov 的 RENAL-NS 评分列线图不能很好地区分小肾癌的良性与恶性。该列线图可能有助于识别高级别肿瘤。在有列线图概率和最终病理标本的情况下,需要进一步验证。

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