Evidence map›Paper›PMID 36218146›Full record

ArticleDiagnostic and interventional radiology (Ankara, Turkey)2022

CT and clinical features for distinguishing endophytic clear cell renal cell carcinoma from urothelial carcinoma.

Xin Chen, Yidi Chen, Yiwu Lei, Fuling Huang, Cheng Tang, Liling Long

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Article in Diagnostic and interventional radiology (Ankara, Turkey), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.

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0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Xin ChenDepartment of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
Yidi ChenDepartment of Radiology, West China Hospital, Sichuan University, Sichuan, China
Yiwu LeiDepartment of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
Fuling HuangDepartment of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
Cheng TangDepartment of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
Liling LongDepartment of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PURPOSE We aimed to characterize the clinical and multiphase computed tomography (CT) features of the distinguishing endophytic clear cell renal cell carcinoma (ECCRCC) from endophytic renal urothelial carcinoma (ERUC). METHODS Data from 44 patients (35 men and 9 women) with ECCRCC and 21 patients (17 men and 4 women) with ERUC were retrospectively assessed. The mean patient age was 55 years (48.25- 59.50 years) and 68 years (63.00-73.00 years), respectively. Univariate and multivariate logistic regression analyses were performed to determine independent predictors for ECCRCC and to construct a predictive model that comprised clinical and CT characteristics for the differential diagnosis of ECCRCC and ERUC. Differential diagnostic performance was assessed using the area under the receiver operating characteristic curve (AUC). RESULTS The independent predictors of ECCRCC were heterogeneous enhancement (odds ratio [OR]=0.027, P=.005), hematuria (OR for gross hematuria=53.995, P=.003; OR for microscopic hematuria=31.126, P = .027), and an infiltrative growth pattern (OR=24.301, P = .022). The AUC of the predictive model was 0.938 (P < .001, sensitivity=84.10%, specificity=95.20%), which had a better diagnostic performance than heterogeneous enhancement (AUC=0.766, P=.001, sensitivity=81.82%, specificity=71.43%), hematuria (AUC=0.786, P < .001, sensitivity=81.82%, specificity=66.67%), and infiltrative growth pattern (AUC=0.748, P=.001, sensitivity=90.48%, specificity=59.09%). CONCLUSION The independent predictors, as well as the predictive model of CT and clinical characteristics, may assist in the differential diagnosis of ECCRCC and ERUC and provide useful information for clinical decision-making.

Indexed as

Carcinoma, Renal CellCarcinoma, Transitional CellKidney NeoplasmsUrinary Bladder NeoplasmsDiagnosis, DifferentialFemaleHematuriaHumansMaleMiddle AgedRetrospective StudiesTomography, X-Ray Computed

Identifiers

PMID36218146
PMCPMC9682587

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.