Evidence map›Paper›PMID 32420152›Full record

ArticleTranslational andrology and urology2020

A preoperative nomogram predicting the pseudocapsule status in localized renal cell carcinoma.

Jiao Hu, Jinbo Chen, Huihuang Li, Tongchen He, Hao Deng, Guanghui Gong, Yu Cui, Peihua Liu, Wenbiao Ren, Xu Zhou and 2 more

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Translational andrology and urology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 40% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 2 institutions in 1 country.

Jiao HuDepartment of Urology, Xiangya Hospital, Central South University, Changsha 410008, China.
Jinbo ChenDepartment of Urology, Xiangya Hospital, Central South University, Changsha 410008, China.
Huihuang LiDepartment of Urology, Xiangya Hospital, Central South University, Changsha 410008, China.
Tongchen HeDepartment of Urology, Xiangya Hospital, Central South University, Changsha 410008, China.
Hao DengDepartment of Urology, Xiangya Hospital, Central South University, Changsha 410008, China.
Guanghui GongDepartment of Pathology, Xiangya Hospital, Central South University, Changsha 410008, China.
Yu CuiDepartment of Urology, Xiangya Hospital, Central South University, Changsha 410008, China.
Peihua LiuDepartment of Urology, Xiangya Hospital, Central South University, Changsha 410008, China.
Wenbiao RenDepartment of Urology, Xiangya Hospital, Central South University, Changsha 410008, China.
Xu ZhouReproductive Medicine Center, Xiangya Hospital, Central South University, Changsha 410008, China.
Chao LiDepartment of Urology, Xiangya Hospital, Central South University, Changsha 410008, China.
Xiongbing ZuDepartment of Urology, Xiangya Hospital, Central South University, Changsha 410008, China.
Xiangya Hospital Central South University · CNCentral South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTumor enucleation (TE) surgery for localized renal cell carcinoma (RCC) relies on a complete peritumoral pseudocapsule (PC). Study objective was to develop a preoperative model to predict PC status.

methodsThe prediction model was developed in a cohort that consisted of 170 patients with localized RCC, and data was gathered from 2010 to 2015. Multivariable logistic regression analysis and R were used to generate this prediction model. The statistical performance was assessed with respect to the calibration, discrimination, and clinical usefulness.

resultsThe prediction model incorporated the systemic inflammatory markers [neutrophil-lymphocyte ratio (NLR); albumin-globulin ratio (AGR)], CT imaging features (tumor size and necrosis), and clinical risk factors (BMI). The model showed good discrimination, with a C-index of 0.85 (0.78-0.91), and good calibration (P=0.60). The sensitivity and specificity were 62% and 94% respectively. Decision curves and clinical impact curve demonstrated that the current model was clinically useful.

conclusionsWe constructed a model that incorporated both the systematic inflammatory markers and clinical risk factors. It can be conveniently used to preoperatively predict the individualized risk of PC invasion and identify the best candidates to receive TE surgery.

Indexed as

nomogrampseudocapsule invasionRenal cell carcinoma (RCC)

Identifiers

PMID32420152
PMCPMC7214989
OpenAlexW3009985813

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

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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.