Literature DB >> 30059288

Classification tree for the prediction of malignant disease and the prediction of non-diagnostic biopsies in patients with small renal masses.

Michael Organ1, Landan P MacDonald2, Michael A S Jewett3, Henry Ajzenberg4, Ashraf Almatar5, Mohamed Abdolell6, Matthew R Acker7, Ricardo Rendon8.   

Abstract

INTRODUCTION: Preoperative prediction of benign vs. malignant small renal masses (SRMs) remains a challenge. This study: 1) validates our previously published classification tree (CT) with an external cohort; 2) creates a new CT with the combined cohort; and 3) evaluates the RENAL and PADUA scoring systems for prediction of malignancy.
METHODS: This study includes a total of 818 patients with renal masses; 395 underwent surgical resection and 423 underwent biopsy. A CT to predict benign disease was developed using patient and tumour characteristics from the 709 eligible participants. Our CT is based on four parameters: tumour volume, symptoms, gender, and symptomatology. CART modelling was also used to determine if RENAL and PADUA scoring could predict malignancy.
RESULTS: When externally validated with the surgical cohort, the predictive accuracy of the old CT dropped. However, by combining the cohorts and creating a new CT, the predictive accuracy increased from 74% to 87% (95% confidence interval 0.84-0.89). RENAL and PADUA score alone were not predictive of malignancy. One limitation was the lack of available histological data from the biopsy series.
CONCLUSIONS: The validated old CT and new combined-cohort CT have a predictive value greater than currently published nomograms and single-biopsy cohorts. Overall, RENAL and PADUA scores were not able to predict malignancy.

Entities:  

Year:  2018        PMID: 30059288      PMCID: PMC6456341          DOI: 10.5489/cuaj.5196

Source DB:  PubMed          Journal:  Can Urol Assoc J        ISSN: 1911-6470            Impact factor:   1.862


  2 in total

1.  Identification of tumor size as the only factor associated with nondiagnostic biopsies in patients with small renal masses.

Authors:  Charlie J Gillis; Ricardo Rendon; Landan P MacDonald; Michael A S Jewett; Christopher French; Henry Ajzenberg; Ashraf Almatar; Mohammed Abdolell; Michael Organ
Journal:  Can Urol Assoc J       Date:  2019-11-29       Impact factor: 1.862

2.  Pathological diagnostic nomograms for predicting malignant histology and unfavorable pathology in patients with endophytic renal tumor.

Authors:  Xinxi Deng; Xiaoqiang Liu; Bing Hu; Ming Jiang; Ke Zhu; Jianqiang Nie; Taobin Liu; Luyao Chen; Wen Deng; Bin Fu; Situ Xiong
Journal:  Front Oncol       Date:  2022-09-21       Impact factor: 5.738

  2 in total

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