Evidence map›Paper›PMID 29779672›Full record

Trial reportUrologic oncology2018

Modifiable risk factors to reduce renal cell carcinoma incidence: Insight from the PLCO trial.

Jonathan Gelfond, Osamah Al-Bayati, Aashish Kabra, Kevan Iffrig, Dharam Kaushik, Michael A Liss

Open access · greenAbstract readMulticenter StudyRandomized Controlled Trial
In one paragraph

Trial report in Urologic oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 16% 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.

  1. American Association of Clinical Endocrinology Clinical Practice Guideline: Developing a Diabetes Mellitus Comprehensive Care Plan-2022 Update.Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists · 2022
    Guideline
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  8. Association Between Diabetes and the Risk of Kidney Cancer: Systematic Review and Meta-Analysis.Clinical diabetes : a publication of the American Diabetes Association · 2022
    Article
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  11. Review
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  14. Gender-Related Approach to Kidney Cancer Management: Moving Forward.International journal of molecular sciences · 2020
    Review
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  16. 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

6 authors at 1 institution in 1 country.

Jonathan GelfondDepartment of Biostatistics, University of Texas Health Science Center San Antonio, San Antonio, TX.
Osamah Al-BayatiDepartment of Urology, University of Texas Health Science Center San Antonio, San Antonio, TX.
Aashish KabraDepartment of Urology, University of Texas Health Science Center San Antonio, San Antonio, TX.
Kevan IffrigDepartment of Urology, University of Texas Health Science Center San Antonio, San Antonio, TX.
Dharam KaushikDepartment of Urology, University of Texas Health Science Center San Antonio, San Antonio, TX.
Michael A LissDepartment of Urology, University of Texas Health Science Center San Antonio, San Antonio, TX; Department of Surgery, South Texas Veterans Healthcare System, San Antonio, TX. Electronic address: Liss@uthscsa.edu.
The University of Texas Health Science Center at San Antonio · US

Funding

TISSUE CULTURE---COREP30CA054174 · NCI · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI Robin Jean Leach · 1991 to 2026
$59.1M
San Antonio OAIC - Research Education Component (REC)P30AG044271 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI Adam Salmon · 2015 to 2026
$14.1M
NCI NIH HHS P30 CA054174NIA NIH HHS P30 AG044271
6 · The paper itself

Abstract

introductionIdentify modifiable factors contributing to renal cell carcinoma in the PCLO to target disease prevention and reduce health care costs.

methodsThe prostate, lung, colorectal, and ovarian database were queried for the primary outcome of kidney cancer. Demographics were investigated, specifically focusing on modifiable risk factors. Statistical analysis includes the Student t-test for continuous variables, chi-squared or Fisher's exact tests for dichotomous and categorical variables for bivariate analysis. The Cox proportional hazards model was used in a multivariate time-to-event analysis.

resultsWe investigate existing data relating specifically to renal cancer. After missing data were excluded, we analyzed 149,683 subjects enrolled in the prostate, lung, colorectal, and ovarian trial and noted 0.5% (n = 748) subjects developed renal cancer. Age, male gender, body mass index, diabetes, and hypertension were all significant associated with renal cancer in bivariate analysis (P<0.05). Men have a significant increased risk of kidney cancer over women (hazard ratio [HR] = 1.85; 95% CI: 1.58-2.16; P<0.0001). Nonmodifiable risk factors that are associated with kidney cancer include age (HR = 1.05; 95% CI: 1.01; 1.05, P = 0.001). Modifiable risk factors include obesity measured by body mass index (HR = 1.05; 95% CI: 1.02-1.07; P<0.0001), hypertension (HR = 1.32; 95% CI: 1.13-1.54; P = 0.0004), and smoking in pack-years (HR = 1.04; 95% CI: 1.02-1.07; P = 0.0002).

conclusionsObesity, hypertension, and smoking are the 3 modifiable risk factors that could aggressively be targeted to reduce renal cell carcinoma.

Indexed as

HypertensionObesitySmokingAgedCarcinoma, Renal CellColorectal NeoplasmsFemaleFollow-Up StudiesHumansIncidenceKidney NeoplasmsLung NeoplasmsMaleMiddle AgedOvarian NeoplasmsPrognosisBlood pressureBody mass indexHypertensionKidney cancerLifestyleModifiable risk factorsObesityPreventionRenal cancerRenal cell cancerSmoking

Identifiers

PMID29779672
PMCPMC11697291
OpenAlexW2803477113

What OpenQuestion holds

Textmetadata
LicenceTDM
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.