The DDD score outperforms the RENAL score in predicting high‐grade renal cell carcinoma

Author:

Zhu Jun123ORCID,Pan Xi123,Xie Jun‐Yi123,Chen Yu‐Ke123,Fan Yu123,Yu Wei123,Zhou Li‐Qun123,He Zhi‐Song123,Zhang Zhong‐Yuan123

Affiliation:

1. Department of Urology Peking University First Hospital Beijing China

2. Institute of Urology, Peking University, National Urological Cancer Center Beijing China

3. Beijing Key Laboratory of Urogenital Diseases (male) Molecular Diagnosis and Treatment Center Beijing China

Abstract

ObjectivesTo explore the relationship between Fuhrman grade of renal cell carcinoma (RCC) and the DDD score.MethodsWe reviewed the records of 527 nonmetastatic RCC patients. Demographic, clinical, and pathologic characteristics were reviewed. Binary logistic regression was used to explore the independent risk factors for high‐grade RCC (HGRCC).ResultsSex, BMI (Body Mass Index), RNS, and DDD score were significantly correlated with HGRCC. Based on these independent risk factors, we constructed two predictive models integrating the RNS and DDD scores with sex and BMI to predict tumor grade. The calibration curves of the predictive model showed good agreement between the observations and predictions. The concordance indexes (C‐indexes) of the predictive models were 0.768 (95% CI, 0.713–0.824), and 0.809 (95% CI, 0.759–0.859). Receiver operating characteristic (ROC) curves were performed to compare the predictive power of the nomograms, and the prediction model including the DDD score had better prognostic ability (p = 0.01).ConclusionsThis study found that RNS, DDD score, BMI, and sex were independent predictors of HGRCC. We developed effective nomograms integrating the above risk factors to predict HGRCC. Of note, the nomogram including the DDD score achieves better prediction ability for HGRCC.

Publisher

Wiley

Subject

Urology

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3