Evidence map›Paper›PMID 29228305›Full record

ArticleJournal of the National Cancer Institute2018

Familial Cancer Clustering in Urothelial Cancer: A Population-Based Case-Control Study.

Christopher Martin, Claire L Leiser, Brock O'Neil, Sumati Gupta, William T Lowrance, Wendy Kohlmann, Samantha Greenberg, Piyush Pathak, Ken R Smith, Heidi A Hanson

Open access · bronzeAbstract read
In one paragraph

Article in Journal of the National Cancer Institute, 2018. 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
1.7field-weighted citation impact, top 15% 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, 36 citations in OpenAlex.

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  8. [Correlation between daily fluid intake behavioral habits and pathological characteristics of upper tract urothelial carcinoma].Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · 2022
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  13. Harnessing Population Pedigree Data and Machine Learning Methods to Identify Patterns of Familial Bladder Cancer Risk.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020
    Article
  14. Article
  15. Family Study Designs Informed by Tumor Heterogeneity and Multi-Cancer Pleiotropies: The Power of the Utah Population Database.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 1 country.

Christopher MartinDivision of Urology, Department of Surgery, Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT.
Claire L LeiserUniversity of Utah, Salt Lake City, UT; Population Sciences, Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT.
Brock O'NeilDivision of Urology, Department of Surgery, Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT.
Sumati GuptaUniversity of Utah, Salt Lake City, UT; Population Sciences, Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT.
William T LowranceDivision of Urology, Department of Surgery, Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT.
Wendy KohlmannUniversity of Utah, Salt Lake City, UT; Population Sciences, Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT.
Samantha GreenbergUniversity of Utah, Salt Lake City, UT; Population Sciences, Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT.
Piyush PathakDivision of Urology, Department of Surgery, Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT.
Ken R SmithDepartment of Family and Consumer Studies, Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT.
Heidi A HansonDivision of Urology, Department of Surgery, Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT.
University of Utah · USHuntsman Cancer Institute · US

Funding

UTAH REGIONAL CANCER CENTERP30CA042014 · NCI · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI KATHARINE S ULLMAN · 1986 to 2026
$72.6M
Utah Center for Clinical and Translational ScienceUL1TR002538 · NCATS · UNIVERSITY OF UTAH · PI HESS, RACHEL, MAJERSIK, JENNIFER JUHL · 2018 to 2022
$26.0M
University of Utah Center for Clinical and Translational ScienceUL1TR001067 · NCATS · UNIVERSITY OF UTAH · PI DERE, WILLARD H., HESS, RACHEL · 2013 to 2017
$19.8M
The Utah Study of Fertility, Longevity and AgingR01AG022095 · NIA · UNIVERSITY OF UTAH · PI SMITH, KEN R · 2003 to 2015
$9.4M
Utah Building Interdisciplinary Resreach Careers in Women's Health Career Development ProgramK12HD085852 · NICHD · UNIVERSITY OF UTAH · PI VARNER, MICHAEL W. · 2015 to 2019
$2.3M
Analysis of BRCA Testing Patterns Using the Utah Population DatabaseR03CA212911 · NCI · UNIVERSITY OF UTAH · PI KOHLMANN, WENDY K · 2017 to 2018
$152k
NCATS NIH HHS UL1 TR001067NCATS NIH HHS UL1 TR002538NCI NIH HHS P30 CA042014NCI NIH HHS R03 CA212911NIA NIH HHS R01 AG022095NICHD NIH HHS K12 HD085852
6 · The paper itself

Abstract

Background: Family history of bladder cancer confers an increased risk for concordant and discordant cancers in relatives. However, previous studies investigating this relationship lack any correction for smoking status of family members. We conducted a population-based study of cancer risks in relatives of bladder cancer patients and matched controls with exclusion of variant subtypes to improve the understanding of familial cancer clustering. Methods: Case subjects with urothelial carcinoma were identified using the Utah Cancer Registry and matched 1:5 to cancer-free controls from the Utah Population Database. Cox regression was used to determine the risk of cancer in first-degree relatives, second-degree relatives, first cousins, and spouses. A total of 229 251 relatives of case subjects and 1 197 552 relatives of matched control subjects were analyzed. To correct for smoking status, we performed a secondary analysis excluding families with elevated rates of smoking-related cancers. All statistical tests were two-sided. Results: First- and second-degree relatives of case subjects had an increased risk for any cancer diagnosis (hazard ratio [HR] = 1.06, 95% confidence interval [CI] = 1.03 to 1.09, P < .001; HR = 1.04, 95% CI = 1.02 to 1.07, P = .001) and urothelial cancer (HR = 1.73, 95% CI = 1.50 to 1.99, P < .001; HR = 1.35, 95% CI = 1.21 to 1.51, P < .001). Site-specific analysis found increased risk for bladder (HR = 1.69, 95% CI = 1.47 to 1.95, P < .001), kidney (HR = 1.30, 95% CI = 1.08 to 1.57, P = .006), cervical (HR = 1.25, 95% CI = 1.06 to 1.49, P = .01), and lung cancer (HR = 1.34, 95% CI = 1.19 to 1.51, P < .001) in first-degree relatives. Second-degree relatives had increased risk for bladder (HR = 1.35, 95% CI = 1.2 to 1.5, P < .001) and thyroid cancer (HR = 1.18, 95% CI = 1.03 to 1.35, P = .02). Spouses showed an increased risk for laryngeal (HR = 2.68, 95% CI = 1.02 to 7.05, P = .04) and cervical cancer (HR = 1.57, 95% CI = 1.13 to 2.17, P = .007). These results did not substantively change after correction for suspected smoking behaviors. Conclusion: Our results suggest familial urothelial cancer clustering independent of smoking, with increased risk in relatives for both concordant and discordant cancers, suggesting shared genetic or environmental roots. Identifying families with statistically significant risks for non-smoking-related urothelial cancer would be extremely informative for genetic linkage studies.

Indexed as

FamilyAdultAgedAged, 80 and overCarcinoma, Transitional CellCase-Control StudiesChildCluster AnalysisFemaleGenetic Predisposition to DiseaseHumansMaleMiddle AgedPedigreePopulationRegistries

Identifiers

PMID29228305
PMCPMC5946951
OpenAlexW2773219032

What OpenQuestion holds

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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 OpenQuestion graph.