Evidence map›Paper›PMID 28417341›Full record

ArticleInternational urology and nephrology2017

External validation of a nomogram including the computed tomography imaging score to predict indolent renal masses.

X Chen, B Wan, D Yang, H Zhao, W Tan

Abstract readValidation Study
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In one paragraph

Article in International urology and nephrology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 43% of its field
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

0 citing papers in PubMed, 4 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

X ChenDepartment of Urology, Nanfang Hospital, Southern Medical University, Guangzhou, People's Republic of China.
B WanDepartment of Urology, Nanfang Hospital, Southern Medical University, Guangzhou, People's Republic of China.
D YangDepartment of Urology, Nanfang Hospital, Southern Medical University, Guangzhou, People's Republic of China.
H ZhaoDepartment of Urology, Nanfang Hospital, Southern Medical University, Guangzhou, People's Republic of China.
W TanDepartment of Urology, Nanfang Hospital, Southern Medical University, Guangzhou, People's Republic of China. twl@smu.edu.cn.
Nanfang Hospital · CNSouthern Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo assess a nomogram including the computed tomography (CT) score and body mass index (BMI) that was constructed to predict indolent diseases in a cohort of patients with renal masses. MATERIALS AND

methodsThe data collected from patients undergoing partial nephrectomy (PN) or radical nephrectomy (RN) between January 2012 and September 2016 were analyzed. Two urologic surgeons and a radiologist reviewed the images to determine the CT score. Postoperative pathological assessment was performed to categorize renal masses as either indolent or aggressive. The BMI and CT scores were included in the nomogram to identify the risk of indolent disease. The performance of the novel model was assessed by using discrimination, calibration plots, and decision curve analysis (DCA).

resultsTwo hundred and two participants (with 202 masses) who underwent RN or PN were included; 37% of the masses were indolent. The predictive performances of the nomogram revealed areas under the curve of 0.866 for masses of all cases and 0.808 for cT1 masses without visible fat. DCA revealed that the nomogram was moderately clinically useful. The calibration plots showed a reasonable calibration and systematic overestimation of indolent disease based on nomogram predictions.

conclusionsThe CT score nomogram discriminated well between indolent and aggressive renal masses. The model had a reasonable calibration in our cohort for discriminating indolent from aggressive lesions. Further research to validate and assess the nomogram is required.

Indexed as

Body Mass IndexNomogramsTomography, X-Ray ComputedAdolescentAdultAgedAged, 80 and overAge FactorsArea Under CurveFemaleHumansKidney NeoplasmsMaleMiddle AgedNephrectomyPredictive Value of TestsCTExternal validationNomogramRCC

Identifiers

PMID28417341
OpenAlexW2606443268

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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.