Evidence map›Paper›PMID 41454364›Full record

ArticleBMC public health2025

Trends in kidney and renal pelvis cancer mortality and associated risk factors in the United States.

Sizhe Li, Xudan Chen, Ying Wang, Wayne R Lawrence, Yingxi Chen, Xinlei Deng, Yanji Qu, Ziqiang Lin, Yongqing Sun, Man Zhang and 6 more

Abstract read
In one paragraph

Article in BMC public health, 2025. 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
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

16 authors.

Sizhe Li *Department of Medical Statistics, School of Public Health/Sun Yat-sen Global Health Institute/Center for Health Information Research, Sun Yat-sen University, 74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, China.
Xudan Chen *Department of Medical Statistics, School of Public Health/Sun Yat-sen Global Health Institute/Center for Health Information Research, Sun Yat-sen University, 74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, China.
Ying Wang *Department of Medical Statistics, School of Public Health/Sun Yat-sen Global Health Institute/Center for Health Information Research, Sun Yat-sen University, 74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, China.
Wayne R LawrenceDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Yingxi ChenDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Xinlei DengDepartment of Epidemiology and Biostatistics, University at Albany, State University of New York, Rensselaer, NY, USA.
Yanji QuGuangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Ziqiang LinDepartment of Preventive Medicine, School of Basic Medicine and Public Health, Jinan University, Guangzhou, China.
Yongqing SunDepartment of Ultrasound, Beijing Obstetrics and Gynecology Hospital, Beijing Maternal and Child Health Care Hospital, Capital Medical University, Beijing, 100026, China.
Man ZhangDepartment of Ultrasound, Beijing Obstetrics and Gynecology Hospital, Beijing Maternal and Child Health Care Hospital, Capital Medical University, Beijing, 100026, China.
Kaili ZhuDepartment of Breast Surgery, Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Chuifei ZhongDepartment of Labor Hygiene, School of Public Health, Shanxi Medical University, Taiyuan, China.
Jie SunDepartment of Medical Statistics, School of Public Health/Sun Yat-sen Global Health Institute/Center for Health Information Research, Sun Yat-sen University, 74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, China.
Zhicheng DuDepartment of Medical Statistics, School of Public Health/Sun Yat-sen Global Health Institute/Center for Health Information Research, Sun Yat-sen University, 74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, China.
Yuantao HaoPeking university Center for Public Health and Epidemic Preparedness & Response, Peking university, Beijing, China.
Wangjian ZhangDepartment of Medical Statistics, School of Public Health/Sun Yat-sen Global Health Institute/Center for Health Information Research, Sun Yat-sen University, 74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, China. zhangwj227@mail.sysu.edu.cn.

Funding

Basic and Applied Basic Research Foundation of Guangdong Province 2023A04J207, 2022A1515010823Fundamental Research Funds for the Central Universities, Sun Yat-sen University 23qnpy108Guangdong Provincial Pearl River Talents Program 0920220207Guangzhou Municipal Science and Technology Bureau 2023A04J2072the National Natural Science Foundation of China 82204162, 82304248
6 · The paper itself

Abstract

backgroundKidney and renal pelvis cancer (KRPC) is a leading cause of cancer death in the United States, yet the mortality trends by sociodemographic characteristics are not well understood.

methodsThis serial cross-sectional analysis used National Centre for Health Statistics data (1999–2020) to examine kidney and renal pelvis cancer mortality trends among individuals aged ≥ 20, stratified by sex, age, race/ethnicity, and county-level socioeconomic status (SES) (Yost index) and rurality. County-level SES was categorized into distribution-based quintiles, where higher quintiles represented greater SES. Age-standardized mortality trends and average annual percent change were calculated, and age-adjusted multivariate quasi-Poisson regression assessed mortality relative to county-level factors.

resultsFrom 1999 to 2020, overall KRPC mortality declined (average annual percent change [AAPC]: -0.9%, 95% CI [-1.0%, -0.8%]), with decreases observed among men (-1.0%) and women (-1.2%). Black individuals had the most substantial decline (AAPC: -1.3%, 95% CI [-1.8%, -0.7%]) compared with all other racial groups. American Indian and Alaska Native individuals showed no significant changes over the study period. KRPC mortality was approximately 1.2 times higher in counties in the lowest SES quintile compared with the highest quintile. Counties with the highest degree of rurality tended to have the greatest risk of KRPC (Complete rural, < 2500 vs. Metropolitan, > 1 million, 1.0 vs. 0.6).

conclusionsThe mortality trends varied by demographics. The close association of mortality with rurality highlights the necessity for focused public health interventions to address specific demographic needs.

Indexed as

Kidney NeoplasmsKidney PelvisAdultAgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedMortalityRisk FactorsSocioeconomic Disparities in HealthUnited StatesYoung AdultEthnic groupsKidney and renal pelvis cancerMortality trendsSocioeconomic status

Identifiers

PMID41454364
PMCPMC12888682

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.