Evidence map›Paper›PMID 33402111›Full record

ArticleBMC cancer2021

Competing risk analysis of cardiovascular/cerebrovascular death in T1/2 kidney cancer: a SEER database analysis.

Xiaofei Mo, Mingge Zhou, Hui Yan, Xueqin Chen, Yuetao Wang

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

15 citing papers in PubMed, 16 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Xiaofei MoDepartment of Nuclear Medicine, the Third Affiliated Hospital of Soochow University, Changzhou, 213003, Jiangsu, China.
Mingge ZhouDepartment of Nuclear Medicine, the Third Affiliated Hospital of Soochow University, Changzhou, 213003, Jiangsu, China.
Hui YanDepartment of Nuclear Medicine, the Third Affiliated Hospital of Soochow University, Changzhou, 213003, Jiangsu, China.
Xueqin ChenDepartment of Nuclear Medicine, the Third Affiliated Hospital of Soochow University, Changzhou, 213003, Jiangsu, China.
Yuetao WangDepartment of Nuclear Medicine, the Third Affiliated Hospital of Soochow University, Changzhou, 213003, Jiangsu, China. yuetao-w@163.com.
Soochow University · CNChangzhou University · CN

Funding

National Natural Science Foundation of China 82001858the Key Laboratory of Changzhou High-tech Research Project CM20193010Youth Talent Development Plan of Changzhou Health Commission CZQM2020053Youth Talent Science and Technology Project of Changzhou Health Commission QN201921
6 · The paper itself

Abstract

backgroundKidney cancer (KC) is associated with cardiovascular regulation disorder and easily leads to cardiovascular and cerebrovascular death (CCD), which is one of the major causes of death in patients with KC, especially those with T1/2 status. However, few studies have treated CCD as an independent outcome for analysis. We aimed to identify and evaluate the key factors associated with CCD in patients with T1/2 KC by competing risk analysis and compared these risk factors with those associated with kidney cancer-specific death (KCD) to offer some information for clinical management.

methodsA total of 45,117 patients diagnosed with first primary KC in T1/2 status were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. All patients were divided into the CCD group (n = 3087), KCD group (n = 3212), other events group (n = 6312) or alive group (n = 32,506). Patients' characteristics were estimated for their association with CCD or KCD by a competing risk model. Pearson's correlation coefficient and variance inflation factor (VIF) were used to detect collinearity between variables. Factors significantly correlated with CCD or KCD were used to create forest plots to compare their differences.

resultsThe competing risk analysis showed that age at diagnosis, race, AJCC T/N status, radiation therapy, chemotherapy and scope of lymph node represented different relationships to CCD than to KCD. In detail, age at diagnosis (over 74/1-50: HR = 9.525, 95% CI: 8.049-11.273), race (white/black: HR = 1.475, 95% CI: 1.334-1.632), AJCC T status (T2/T1: HR = 0.847, 95% CI: 0.758-0.946) and chemotherapy (received/unreceived: HR = 0.574, 95% CI: 0.347-0.949) were correlated significantly with CCD; age at diagnosis (over 74/1-50: HR = 3.205, 95% CI: 2.814-3.650), AJCC T/N status (T2/T1: HR = 2.259, 95% CI: 2.081-2.451 and N1/N0:HR = 3.347, 95% CI: 2.698-4.152), radiation therapy (received/unreceived: HR = 2.552, 95% CI: 1.946-3.346), chemotherapy (received/unreceived: HR = 2.896, 95% CI: 2.342-3.581) and scope of lymph nodes (1-3 regional lymph nodes removed/none: HR = 1.378, 95% CI: 1.206-1.575) were correlated significantly with KCD.

conclusionsWe found that age at diagnosis, race, AJCC T status and chemotherapy as the independent risk factors associated with CCD were different from those associated with KCD.

Indexed as

AdolescentAdultAgedCarcinoma, Renal CellCardiovascular DiseasesCerebrovascular DisordersChildChild, PreschoolDatabases, FactualFemaleFollow-Up StudiesHumansInfantKidney NeoplasmsMaleMiddle AgedCompeting risk analysisKidney cancer, Cardiovascular and cerebrovascular deathSEER database

Identifiers

PMID33402111
PMCPMC7786899
OpenAlexW3119634576

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.