ArticleCanadian Urological Association journal = Journal de l'Association des urologues du Canada2019
Classification tree for the prediction of malignant disease and the prediction of non-diagnostic biopsies in patients with small renal masses.
Article in Canadian Urological Association journal = Journal de l'Association des urologues du Canada, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Pathological diagnostic nomograms for predicting malignant histology and unfavorable pathology in patients with endophytic renal tumor.Frontiers in oncology · 2022Article
- Identification of tumor size as the only factor associated with nondiagnostic biopsies in patients with small renal masses.Canadian Urological Association journal = Journal de l'Association des urologues du Canada · 2020Article
- Kidney Cancer Research Network of Canada (KCRNC) consensus statement on the role of renal mass biopsy in the management of kidney cancer.Canadian Urological Association journal = Journal de l'Association des urologues du Canada · 2019Article
Corrections and comments
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Authors and funding
8 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionPreoperative 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.
methodsThis 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.
resultsWhen 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.
conclusionsThe 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.
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Registered trials
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