Evidence map›Paper›PMID 32636671›Full record

ArticleCancer management and research2019

A Novel Preoperative Nomogram for Predicting Lymph Node Invasion in Renal Cell Carcinoma Patients Without Metastasis.

Pin Li, Cheng Peng, Yongpeng Xie, Lei Wang, Liangyou Gu, Shengpan Wu, Donglai Shen, Yundong Xuan, Xin Ma, Xu Zhang

Open access · goldAbstract read
In one paragraph

Article in Cancer management and research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.5field-weighted citation impact, top 28% 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

7 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
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

10 authors at 4 institutions in 1 country.

Pin Li *Department of Urology, State Key Laboratory of Kidney Diseases, The First Medical Center of Chinese PLA General Hospital, Beijing, People's Republic of China.
Cheng Peng *Department of Urology, The Seventh Medical Center of Chinese PLA General Hospital, Beijing, People's Republic of China.
Yongpeng Xie *Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China.
Lei WangChinese PLA 534 Hospital, Luoyang, People's Republic of China.
Liangyou GuDepartment of Urology, State Key Laboratory of Kidney Diseases, The First Medical Center of Chinese PLA General Hospital, Beijing, People's Republic of China.
Shengpan WuDepartment of Urology, State Key Laboratory of Kidney Diseases, The First Medical Center of Chinese PLA General Hospital, Beijing, People's Republic of China.
Donglai ShenDepartment of Urology, State Key Laboratory of Kidney Diseases, The First Medical Center of Chinese PLA General Hospital, Beijing, People's Republic of China.
Yundong XuanDepartment of Urology, State Key Laboratory of Kidney Diseases, The First Medical Center of Chinese PLA General Hospital, Beijing, People's Republic of China.
Xin MaDepartment of Urology, State Key Laboratory of Kidney Diseases, The First Medical Center of Chinese PLA General Hospital, Beijing, People's Republic of China.
Xu ZhangDepartment of Urology, State Key Laboratory of Kidney Diseases, The First Medical Center of Chinese PLA General Hospital, Beijing, People's Republic of China.
Chinese PLA General Hospital · CNBayi Children's Hospital · CNFirst Affiliated Hospital of Chongqing Medical University · CNPeople's Liberation Army No. 150 Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo provide a preoperative predictive model to support clinical decision-making regarding the selection of in renal cell carcinoma (RCC) patients who will benefit the most from lymph node dissection.

methodsThis retrospective analysis enrolled 374 RCC patients without distant metastasis who underwent surgical treatment from January 2006 to December 2017. The relationships between lymph node invasion (LNI) and age at surgery; gender; body mass index(BMI); the presence of clinical symptoms such as flank pain, hematuria or a palpable mass; clinical T stage (cT stage); clinical N stage (cN stage); and the results of routine hematological and serum biochemical analyses were investigated. All the variables were included in univariate and multivariate logistic regression analyses, and the significant variables were then included in a novel nomogram to predict the probability of LNI. Then, we calibrated the nomogram with an internal validation set.

resultsSix of eighteen variables were significant in the univariate logistic regression analysis. After multivariate logistic regression analysis, age at surgery (OR=0.643, 95% CI: 0.421-0.975), cT stage (OR=3.034, 95% CI: 1.541-5.926), cN stage (OR=6.353, 95% CI: 3.273-12.456), lymphocyte percentage (OR=0.481, 95% CI: 0.256-0.894), and the presence of clinical symptoms (OR=2.045, 95% CI: 1.065-3.924) were independent predictors of LNI and were included in the nomogram. The C-index of this nomogram was 0.824.

conclusionPreoperative basic laboratory findings combined with the results of a physical examination and radiological examination can indicate the probability of LNI in RCC patients.

Indexed as

kidney cancerlymph node invasionpredictive nomogramrenal cell carcinoma

Identifiers

PMID32636671
PMCPMC7326626
OpenAlexW2991564461

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.