Evidence map›Paper›PMID 33482857›Full record

ArticleJournal of translational medicine2021

Assessing the clinical utility of genetic risk scores for targeted cancer screening.

Carly A Conran, Zhuqing Shi, William Kyle Resurreccion, Rong Na, Brian T Helfand, Elena Genova, Siqun Lilly Zheng, Charles B Brendler, Jianfeng Xu

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
4.0field-weighted citation impact, top 6% 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

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Assessing a Polygenic Risk Score for Lung Cancer Susceptibility in Non-Hispanic White and Black Populations.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2023
    Article
  5. Article
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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

9 authors at 3 institutions in 2 countries.

Carly A ConranUniversity of Illinois College of Medicine, Chicago, IL, USA. carlyconran@gmail.com.ORCID 0000-0003-0282-7004
Zhuqing ShiProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, USA.
William Kyle ResurreccionProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, USA.
Rong NaFudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai, China.
Brian T HelfandProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, USA.
Elena GenovaProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, USA.
Siqun Lilly ZhengProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, USA.
Charles B BrendlerProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, USA.
Jianfeng XuProgram for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, USA.
NorthShore University HealthSystem · USFudan University · CNIllinois College · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenome-wide association studies have identified thousands of disease-associated single nucleotide polymorphisms (SNPs). A subset of these SNPs may be additively combined to generate genetic risk scores (GRSs) that confer risk for a specific disease. Although the clinical validity of GRSs to predict risk of specific diseases has been well established, there is still a great need to determine their clinical utility by applying GRSs in primary care for cancer risk assessment and targeted intervention.

methodsThis clinical study involved 281 primary care patients without a personal history of breast, prostate or colorectal cancer who were 40-70 years old. DNA was obtained from a pre-existing biobank at NorthShore University HealthSystem. GRSs for colorectal cancer and breast or prostate cancer were calculated and shared with participants through their primary care provider. Additional data was gathered using questionnaires as well as electronic medical record information. A t-test or Chi-square test was applied for comparison of demographic and key clinical variables among different groups.

resultsThe median age of the 281 participants was 58 years and the majority were female (66.6%). One hundred one (36.9%) participants received 2 low risk scores, 99 (35.2%) received 1 low risk and 1 average risk score, 37 (13.2%) received 1 low risk and 1 high risk score, 23 (8.2%) received 2 average risk scores, 21 (7.5%) received 1 average risk and 1 high risk score, and no one received 2 high risk scores. Before receiving GRSs, younger patients and women reported significantly more worry about risk of developing cancer. After receiving GRSs, those who received at least one high GRS reported significantly more worry about developing cancer. There were no significant differences found between gender, age, or GRS with regards to participants' reported optimism about their future health neither before nor after receiving GRS results.

conclusionsGenetic risk scores that quantify an individual's risk of developing breast, prostate and colorectal cancers as compared with a race-defined population average risk have potential clinical utility as a tool for risk stratification and to guide cancer screening in a primary care setting.

Indexed as

Genome-Wide Association StudyNeoplasmsAdultAgedEarly Detection of CancerFemaleGenetic Predisposition to DiseaseHumansMaleMiddle AgedPolymorphism, Single NucleotideRisk AssessmentRisk FactorsBreast cancerCancer screeningColorectal cancerGenetic risk scoreProstate cancerSingle nucleotide polymorphismTranslational genomics

Identifiers

PMID33482857
PMCPMC7821544
OpenAlexW3121830978

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.